2,093 results
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2. Ecological driving on multiphase trajectories and multiobjective optimization for autonomous electric vehicle platoon.
- Author
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Xiaofeng T
- Subjects
- Acceleration, Electricity, Automobile Driving
- Abstract
Autonomous electric vehicles promise to improve traffic safety, increase fuel efficiency and reduce congestion in future intelligent transportation systems. Ecological driving characteristics are first studied to concentrate on energy consumption, the ability to quickly pass its destination, etc. of autonomous electric vehicle plans (AEVPs) to maximize total energy efficiency benefits. To realize this goal, an optimal control model is developed to provide ecological driving suggestions to AEVPs. The Radau pseudospectral method (RPM) is adopted to put the optimal control model into nonlinear programs (NLP), and multiobjective optimization, including safety, economy and fast mobility, is considered, which conditions and constraints such as vehicle dynamics, traffic rules, and energy consumption. To enhance optimal model applicability, two ecological driving procedures are proposed. One procedure is that two-phase trajectory optimization and ecological driving states, such as velocity and acceleration, for the leading vehicle are developed according to RPM characteristics, while the other provides a set of targeted driving states to the following vehicles. The objective of the procedure is to minimize the total energy consumption of AEVPs, while travel comfort and safety are integrated into the schematization by optimization functions. Numerical experiments illustrate significance when ecological driving strategy for AEVPs considers energy consumption characteristics, thereby ensuring total energy consumption efficiency for AEVPs., (© 2022. The Author(s).)
- Published
- 2022
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3. Evaluation of Driver's Reaction Time Measured in Driving Simulator.
- Author
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Čulík K, Kalašová A, and Štefancová V
- Subjects
- Reaction Time, Accidents, Traffic prevention & control, Automobile Driving
- Abstract
This article evaluates the driver's reaction times in a driving simulator environment. The research focused mainly on young drivers under the age of 26, who cause many accidents. Each participating driver provided basic information later used for mathematical-statistical analysis. The main advantage of driving simulators is limitless usage. It is possible to simulate situations that would be unacceptable in real road traffic. Therefore, this study is also able to examine drunk driving. The main goal of the article is to evaluate if gender, practice, or alcohol significantly affected the reaction time of 30 drivers. We also focused on drinking before driving for a smaller number of the drivers; ten of them performed driving under the influence of alcohol. For these mathematical-statistical purposes, we used a one-sample t -test, a paired-samples t -test, an independent-sample t -test, and a correlation analysis together with the assessment of its statistical significance.
- Published
- 2022
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4. A survey of train driver schedules, sleep, wellbeing, and driving performance in Australia and New Zealand.
- Author
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Dorrian J, Chapman J, Bowditch L, Balfe N, and Naweed A
- Subjects
- Australia, Fatigue etiology, Humans, New Zealand, Sleep, Automobile Driving, Work Schedule Tolerance
- Abstract
Train drivers work long hours on 24 h schedules and many factors impact their fatigue risk at work, creating a clear imperative for good rostering practice. Adopting a systems approach, this study investigated the relationship between multiple interrelated factors (train drivers' schedule, sleep, wellbeing, and fatigue) and the perceived influence of these factors on train driving performance and safety using an online survey distributed in Australia and New Zealand. In addition to demographics and work schedule, passenger and freight train drivers (n = 751) answered questions about: (1) Sleep duration; (2) wellbeing, including physical and mental health, the extent to which shiftwork causes sleep, social, domestic, and work problems, and (3) the extent to which ten fatigue, health and wellbeing factors in the work and home environment negatively impact their driving performance. The key factor that emerged from analyses, with the largest and most consistent negative effects (and controlling for other factors) was schedule irregularity. Approved rosters were ranked as having the most important impact on day-to-day driving performance, followed by physical and mental health, and outside work factors. Results also suggested that schedule irregularity may amplify the negative impacts of the roster, impaired physical and mental health, and outside work factors on driving performance. As shift variability and schedule irregularity are often poorly represented in existing industry guidance, these results provide evidence for increased reflection on current fatigue management guidelines for train drivers and suggest a need for greater focus on schedule irregularity through the lens of a systems approach., (© 2022. The Author(s).)
- Published
- 2022
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5. Session 2515 (Paper): WELL-BEING IN OLDER ADULTS.
- Subjects
HEALTH of older people ,SELF regulation ,AUTOMOBILE driving ,COGNITION disorders ,TYPE 2 diabetes - Published
- 2021
6. Session 1485 (Paper): TRANSPORTATION ISSUES AT OLDER AGES.
- Subjects
TRANSPORTATION services for older people ,TRAFFIC accidents ,CAREGIVERS ,AUTOMOBILE driving ,PANDEMICS - Published
- 2021
7. Life and death decisions of autonomous vehicles.
- Author
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Bigman YE and Gray K
- Subjects
- Accidents, Traffic, Morals, Automobile Driving
- Published
- 2020
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8. Examining the Spatial Mode, Supply–Demand Relationship, and Driving Mechanism of Urban Park Green Space: A Case Study from China.
- Author
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Zhao, Kaixu, Chen, Chao, Wang, Jianming, Liu, Kaixi, Wu, Fengqi, and Cao, Xiaoteng
- Subjects
URBAN parks ,CITIES & towns ,SUPPLY & demand ,AUTOMOBILE driving ,SOCIAL development ,CHINA studies - Abstract
Park green space is a big part of public infrastructure in cities, and how to evaluate and optimize the mismatch of urban park green space (UPGS) has become the focus of current research in academia and industry. Taking China's 286 cities as an example, this paper used the spatial cluster and Boston Consulting Group Matrix to analyze the aggregation laws and changing modes of UPGS from 2010 to 2020, introduced the spatial mismatch model to analyze the matching of its supply and demand with GDP and population, and adopted the Geodetector to analyze the influencing factors. The findings: (1) The evolution of UPGS in China had long been characterized by a "pyramidal" pattern, i.e., limited green cities > developing green cities > steady green cities > booming green cities, exhibiting the spatial characteristics of gradient differences between the coasts and inland areas, and the aggregation of blocks in some areas. (2) The supply and demand mismatches of the UPGS were relatively stable, with negative matching being the main supply mismatch type, and positive matching being the main demand mismatch type. The contribution of supply and demand mismatches similarly showed a spatial pattern of a gradual decrease from the coast to inland and the aggregation of blocks in some areas. (3) Five types of factors played different driving roles on UPGS, with social development remaining a weak factor, and the strong factor switching from urban infrastructure to construction land scale. The interaction detection was dominated by a bilinear enhancement, with super-interaction factors changing from an output value of the tertiary industry and population urbanization rate to education expenditure in local general public budgets. (4) Based on the mismatch between the supply and demand for UPGS in China, 286 cities were classified into four types, namely a smart shrinking zone, smart growing zone, status quo zone, and overlay policy zone, and differentiated development proposals for the corresponding zoning were put forward. This paper constructed an application framework of "evolution pattern + supply demand match + driving factors + policy zoning" for UPGS at a large scale, which will effectively enhance the effective allocation of its resources across the country. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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9. Drivable Area Detection in Unstructured Environments based on Lightweight Convolutional Neural Network for Autonomous Driving Car.
- Author
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Yu, Yue, Lu, Yanhui, Wang, Pengyu, Han, Yifei, Xu, Tao, and Li, Jianhua
- Subjects
CONVOLUTIONAL neural networks ,AUTONOMOUS vehicles ,DRIVERLESS cars ,AUTOMOBILE driving - Abstract
Road detection technology is an important part of the automatic driving environment perception system. With the development of technology, the situations that automatic driving needs to consider will become broader and more complex. This paper contributes a lightweight convolutional neural network model, incorporating novel convolution and parallel pooling modules, an improved network activation function, and comprehensive training and verification with multiple datasets. The proposed model achieves high accuracy in detecting drivable areas in complex autonomous driving situations while significantly improving real-time performance. In addition, we collect data in the field and create small datasets as reference datasets for testing algorithms. This paper designs relevant experimental scenarios based on the datasets and experimental platforms and conducts simulations and real-world vehicle experiments to verify the effectiveness and stability of the algorithm models and technical solutions. The method achieves an MIoU of 90.19 and a single batch time of 340 ms with a batch size of 8, which substantially reduces the runtime relative to a typical deep network structure like ResNet50. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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10. A review of road safety evaluation methods based on driving behavior.
- Author
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Zijun Du, Min Deng, Nengchao Lyu, and Yugang Wang
- Subjects
ROAD safety measures ,AUTOMOBILE driving ,ROAD construction ,TRAFFIC engineering ,INFORMATION technology ,INFORMATION processing - Abstract
Road traffic safety should be evaluated throughout the entire life-cycle of road design, operation, maintenance, and expansion construction. However, traditional methods for evaluating road traffic safety based on traffic accidents and conflict technology are limited by their inability to account for the complex environmental factors involved. To address this issue, a new road safety evaluation method has emerged that is based on driving behavior. Because drivers' behaviors may vary depending on the driving environment and their personal characteristics, evaluating road safety from the perspective of driver behavior has become a popular research topic. This paper analyzes current research trends and mainstream journals in the field of road safety evaluation of driving behavior. Additionally, it reviews the three most commonly used driving behavior data collection methods, and compares the advantages and disadvantages of each. The paper proposes the main application scenarios of road safety evaluation methods based on driving behavior, such as road design, evaluation of the effects of road appurtenances, and intelligent highways. Furthermore, the paper summarizes a driving behavior index system based on vehicle data, driver's physiological and psychological data, and driver's subjective questionnaire data. A comprehensive evaluation method based on the fusion of each index system is presented in detail. Finally, the paper points out current research problems and the future development direction of the road safety evaluation method based on driving behavior. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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11. How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study.
- Author
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Perello-March J, Burns CG, Woodman R, Birrell S, and Elliott MT
- Subjects
- Humans, Adult, Male, Female, Automation, Young Adult, Prefrontal Cortex diagnostic imaging, Prefrontal Cortex physiology, Risk Assessment, Functional Neuroimaging, Automobile Driving, Spectroscopy, Near-Infrared
- Abstract
Objective: Using brain haemodynamic responses to measure perceived risk from traffic complexity during automated driving., Background: Although well-established during manual driving, the effects of driver risk perception during automated driving remain unknown. The use of fNIRS in this paper for assessing drivers' states posits it could become a novel method for measuring risk perception., Methods: Twenty-three volunteers participated in an empirical driving simulator experiment with automated driving capability. Driving conditions involved suburban and urban scenarios with varying levels of traffic complexity, culminating in an unexpected hazardous event. Perceived risk was measured via fNIRS within the prefrontal cortical haemoglobin oxygenation and from self-reports., Results: Prefrontal cortical haemoglobin oxygenation levels significantly increased, following self-reported perceived risk and traffic complexity, particularly during the hazardous scenario., Conclusion: This paper has demonstrated that fNIRS is a valuable research tool for measuring variations in perceived risk from traffic complexity during highly automated driving. Even though the responsibility over the driving task is delegated to the automated system and dispositional trust is high, drivers perceive moderate risk when traffic complexity builds up gradually, reflected in a corresponding significant increase in blood oxygenation levels, with both subjective (self-reports) and objective (fNIRS) increasing further during the hazardous scenario., Application: Little is known regarding the effects of drivers' risk perception with automated driving. Building upon our experimental findings, future work can use fNIRS to investigate the mental processes for risk assessment and the effects of perceived risk on driving behaviours to promote the safe adoption of automated driving technology.
- Published
- 2024
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12. Young onset dementia and driving cessation: a scoping review of lived experiences.
- Author
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Scott TL, Jaymes RWM, McCaul T, Wilton-Harding B, and Cations M
- Subjects
- Humans, Automobile Driving psychology, Dementia psychology, Age of Onset
- Abstract
Background: Driving cessation is one of the most challenging life transitions, associated with multiple negative consequences for individuals living with late-onset dementia. This paper extends the literature as to date there is no published review that details the experiences of people living with young onset dementia ("YOD")., Methods: A comprehensive search of the literature was conducted using the scoping review methodology., Results: Ten studies were included for full text review of 1634 initially identified through database searching. The results of the included articles indicated areas of concern for people living with YOD and their family members including, loss of independence; role change; threat to self-identify; feelings of isolation, grief; acceptance; predictors of driving cessation., Conclusion: There is a lack of robust evidence related to driving cessation and the experiences of people living with YOD. No published paper reported psychosocial interventions specifically targeted at supporting persons with YOD through driving cessation., (© 2024. The Author(s).)
- Published
- 2024
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13. Enhancing Driving Safety through User Experience Evaluation of the C-ITS Mobile Application: A Case Study of the DARS Traffic Plus App in a Driving Simulator Environment.
- Author
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Burger G and Guna J
- Subjects
- Humans, Adult, Male, Female, Safety, Surveys and Questionnaires, Young Adult, Middle Aged, Automobile Driving psychology, Mobile Applications, Accidents, Traffic prevention & control, Computer Simulation
- Abstract
The paper evaluates the DARS Traffic Plus mobile application within a realistic driving simulator environment to assess its impact on driving safety and user experience, particularly focusing on the Cooperative Intelligent Transport Systems (C-ITS). The study is positioned within the broader context of integrating mobile technology in vehicular environments to enhance road safety by informing drivers about potential hazards in real time. A combination of experimental methods was employed, including a standardised user experience questionnaire (meCUE 2.0), measuring quantitative driving parameters and eye-tracking data within a driving simulator, and post-experiment interviews. The results indicate that the mobile application significantly improved drivers' safety perception, particularly when notifications about hazardous locations were received. Notifications displayed at the top of the mobile screen with auditory cues were deemed most effective. The study concludes that mobile applications like DARS Traffic Plus can play a crucial role in enhancing road safety by effectively communicating hazards to drivers, thereby potentially reducing road accidents and improving overall traffic safety. Screen viewing was kept below the safety threshold, affirming the app's efficacy in delivering crucial information without distraction. These findings support the integration of C-ITS functionalities into mobile applications as a means to augment older vehicle technologies and extend the safety benefits to a broader user base.
- Published
- 2024
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14. Leveraging Wearable Sensors in Virtual Reality Driving Simulators: A Review of Techniques and Applications.
- Author
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Boboc RG, Butilă EV, and Butnariu S
- Subjects
- Humans, Computer Simulation, Wearable Electronic Devices, Virtual Reality, Automobile Driving
- Abstract
Virtual reality (VR) driving simulators are very promising tools for driver assessment since they provide a controlled and adaptable setting for behavior analysis. At the same time, wearable sensor technology provides a well-suited and valuable approach to evaluating the behavior of drivers and their physiological or psychological state. This review paper investigates the potential of wearable sensors in VR driving simulators. Methods: A literature search was performed on four databases (Scopus, Web of Science, Science Direct, and IEEE Xplore) using appropriate search terms to retrieve scientific articles from a period of eleven years, from 2013 to 2023. Results: After removing duplicates and irrelevant papers, 44 studies were selected for analysis. Some important aspects were extracted and presented: the number of publications per year, countries of publication, the source of publications, study aims, characteristics of the participants, and types of wearable sensors. Moreover, an analysis and discussion of different aspects are provided. To improve car simulators that use virtual reality technologies and boost the effectiveness of particular driver training programs, data from the studies included in this systematic review and those scheduled for the upcoming years may be of interest.
- Published
- 2024
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15. An Identification Method for Road Hypnosis Based on Human EEG Data.
- Author
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Wang B, Wang J, Wang X, Chen L, Zhang H, Jiao C, Wang G, and Feng K
- Subjects
- Humans, Accidents, Traffic, Electroencephalography methods, Hypnosis methods, Automobile Driving, Neural Networks, Computer
- Abstract
The driver in road hypnosis has not only some external characteristics, but also some internal characteristics. External features have obvious manifestations and can be directly observed. Internal features do not have obvious manifestations and cannot be directly observed. They need to be measured with specific instruments. Electroencephalography (EEG), as an internal feature of drivers, is the golden parameter for drivers' life identification. EEG is of great significance for the identification of road hypnosis. An identification method for road hypnosis based on human EEG data is proposed in this paper. EEG data on drivers in road hypnosis can be collected through vehicle driving experiments and virtual driving experiments. The collected data are preprocessed with the PSD (power spectral density) method, and EEG characteristics are extracted. The neural networks EEGNet, RNN, and LSTM are used to train the road hypnosis identification model. It is shown from the results that the model based on EEGNet has the best performance in terms of identification for road hypnosis, with an accuracy of 93.01%. The effectiveness and accuracy of the identification for road hypnosis are improved in this study. The essential characteristics for road hypnosis are also revealed. This is of great significance for improving the safety level of intelligent vehicles and reducing the number of traffic accidents caused by road hypnosis.
- Published
- 2024
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16. Driver Fatigue Detection Using Heart Rate Variability Features from 2-Minute Electrocardiogram Signals While Accounting for Sex Differences.
- Author
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Zeng C, Zhang J, Su Y, Li S, Wang Z, Li Q, and Wang W
- Subjects
- Humans, Male, Female, Young Adult, Adult, Accidents, Traffic, Sex Factors, Signal Processing, Computer-Assisted, Sex Characteristics, Heart Rate physiology, Electrocardiography methods, Automobile Driving, Fatigue physiopathology, Fatigue diagnosis
- Abstract
Traffic accidents due to fatigue account for a large proportion of road fatalities. Based on simulated driving experiments with drivers recruited from college students, this paper investigates the use of heart rate variability (HRV) features to detect driver fatigue while considering sex differences. Sex-independent and sex-specific differences in HRV features between alert and fatigued states derived from 2 min electrocardiogram (ECG) signals were determined. Then, decision trees were used for driver fatigue detection using the HRV features of either all subjects or those of only males or females. Nineteen, eighteen, and thirteen HRV features were significantly different (Mann-Whitney U test, p < 0.01) between the two mental states for all subjects, males, and females, respectively. The fatigue detection models for all subjects, males, and females achieved classification accuracies of 86.3%, 94.8%, and 92.0%, respectively. In conclusion, sex differences in HRV features between drivers' mental states were found according to both the statistical analysis and classification results. By considering sex differences, precise HRV feature-based driver fatigue detection systems can be developed. Moreover, in contrast to conventional methods using HRV features from 5 min ECG signals, our method uses HRV features from 2 min ECG signals, thus enabling more rapid driver fatigue detection.
- Published
- 2024
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17. The effects of various auditory takeover requests: A simulated driving study considering the modality of non-driving-related tasks.
- Author
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Chai C, Lei Y, Wei H, Wu C, Zhang W, Hansen P, Fan H, and Shi J
- Subjects
- Humans, Male, Female, Adult, Young Adult, Automation, Auditory Perception, Attention, Speech, Automobile Driving psychology, Task Performance and Analysis, Computer Simulation
- Abstract
With the era of automated driving approaching, designing an effective auditory takeover request (TOR) is critical to ensure automated driving safety. The present study investigated the effects of speech-based (speech and spearcon) and non-speech-based (earcon and auditory icon) TORs on takeover performance and subjective preferences. The potential impact of the non-driving-related task (NDRT) modality on auditory TORs was considered. Thirty-two participants were recruited in the present study and assigned to two groups, with one group performing the visual N-back task and another performing the auditory N-back task during automated driving. They were required to complete four simulated driving blocks corresponding to four auditory TOR types. The earcon TOR was found to be the most suitable for alerting drivers to return to the control loop because of its advantageous takeover time, lane change time, and minimum time to collision. Although participants preferred the speech TOR, it led to relatively poor takeover performance. In addition, the auditory NDRT was found to have a detrimental impact on auditory TORs. When drivers were engaged in the auditory NDRT, the takeover time and lane change time advantages of earcon TORs no longer existed. These findings highlight the importance of considering the influence of auditory NDRTs when designing an auditory takeover interface. The present study also has some practical implications for researchers and designers when designing an auditory takeover system in automated vehicles., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
- Published
- 2024
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18. Predicting Driver's mental workload using physiological signals: A functional data analysis approach.
- Author
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Lee C, Shin M, Eniyandunmo D, Anwar A, Kim E, Kim K, Yoo JK, and Lee C
- Subjects
- Data Analysis, Humans, Male, Female, Young Adult, Adult, Electrodes, Text Messaging, Radio, Acoustic Stimulation, Photic Stimulation, Mathematics, Electrocardiography, Electroencephalography, Electromyography, Galvanic Skin Response, Cognition physiology, Safety, Automobile Driving psychology, Mental Processes physiology, Workload, Psychomotor Performance physiology
- Abstract
This study investigates the impact of advanced driver-assistance systems on drivers' mental workload. Using a combination of physiological signals including ECG, EMG, EDA, EEG (af4 and fc6 channels from the theta band), and eye diameter data, this study aims to predict and categorize drivers' mental workload into low, adequate, and high levels. Data were collected from five different driving situations with varying cognitive demands. A functional linear regression model was employed for prediction, and the accuracy rate was calculated. Among the 31 tested combinations of physiological variables, 9 combinations achieved the highest accuracy result of 90%. These results highlight the potential benefits of utilizing raw physiological signal data and employing functional data analysis methods to understand and assess driver mental workload. The findings of this study have implications for the design and improvement of driver-assistance systems to optimize safety and performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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19. How to Design Human-Vehicle Cooperation for Automated Driving: A Review of Use Cases, Concepts, and Interfaces.
- Author
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Peintner, Jakob, Escher, Bengt, Detjen, Henrik, Manger, Carina, and Riener, Andreas
- Subjects
LITERATURE reviews ,COOPERATION ,COMMON sense ,AUTONOMOUS vehicles ,USER experience ,AUTOMOBILE driving - Abstract
Currently, a significant gap exists between academic and industrial research in automated driving development. Despite this, there is common sense that cooperative control approaches in automated vehicles will surpass the previously favored takeover paradigm in most driving situations due to enhanced driving performance and user experience. Yet, the application of these concepts in real driving situations remains unclear, and a holistic approach to driving cooperation is missing. Existing research has primarily focused on testing specific interaction scenarios and implementations. To address this gap and offer a contemporary perspective on designing human–vehicle cooperation in automated driving, we have developed a three-part taxonomy with the help of an extensive literature review. The taxonomy broadens the notion of driving cooperation towards a holistic and application-oriented view by encompassing (1) the "Cooperation Use Case", (2) the "Cooperation Frame", and (3) the "Human–Machine Interface". We validate the taxonomy by categorizing related literature and providing a detailed analysis of an exemplar paper. The proposed taxonomy offers designers and researchers a concise overview of the current state of driver cooperation and insights for future work. Further, the taxonomy can guide automotive HMI designers in ideation, communication, comparison, and reflection of cooperative driving interfaces. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
20. DriveLLaVA: Human-Level Behavior Decisions via Vision Language Model.
- Author
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Zhao R, Yuan Q, Li J, Fan Y, Li Y, and Gao F
- Subjects
- Humans, Algorithms, Language, Automobile Driving psychology, Decision Making physiology
- Abstract
Human-level driving is the ultimate goal of autonomous driving. As the top-level decision-making aspect of autonomous driving, behavior decision establishes short-term driving behavior strategies by evaluating road structures, adhering to traffic rules, and analyzing the intentions of other traffic participants. Existing behavior decisions are primarily implemented based on rule-based methods, exhibiting insufficient generalization capabilities when faced with new and unseen driving scenarios. In this paper, we propose a novel behavior decision method that leverages the inherent generalization and commonsense reasoning abilities of visual language models (VLMs) to learn and simulate the behavior decision process in human driving. We constructed a novel instruction-following dataset containing a large number of image-text instructions paired with corresponding driving behavior labels, to support the learning of the Drive Large Language and Vision Assistant (DriveLLaVA) and enhance the transparency and interpretability of the entire decision process. DriveLLaVA is fine-tuned on this dataset using the Low-Rank Adaptation (LoRA) approach, which efficiently optimizes the model parameter count and significantly reduces training costs. We conducted extensive experiments on a large-scale instruction-following dataset, and compared with state-of-the-art methods, DriveLLaVA demonstrated excellent behavior decision performance. DriveLLaVA is capable of handling various complex driving scenarios, showing strong robustness and generalization abilities.
- Published
- 2024
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21. A panoramic driving perception fusion algorithm based on multi-task learning.
- Author
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Wu W, Liu C, and Zheng H
- Subjects
- Humans, Task Performance and Analysis, Algorithms, Automobile Driving psychology
- Abstract
With the rapid development of intelligent connected vehicles, there is an increasing demand for hardware facilities and onboard systems of driver assistance systems. Currently, most vehicles are constrained by the hardware resources of onboard systems, which mainly process single-task and single-sensor data. This poses a significant challenge in achieving complex panoramic driving perception technology. While the panoramic driving perception algorithm YOLOP has achieved outstanding performance in multi-task processing, it suffers from poor adaptability of feature map pooling operations and loss of details during downsampling. To address these issues, this paper proposes a panoramic driving perception fusion algorithm based on multi-task learning. The model training involves the introduction of different loss functions and a series of processing steps for lidar point cloud data. Subsequently, the perception information from lidar and vision sensors is fused to achieve synchronized processing of multi-task and multi-sensor data, thereby effectively improving the performance and reliability of the panoramic driving perception system. To evaluate the performance of the proposed algorithm in multi-task processing, the BDD100K dataset is used. The results demonstrate that, compared to the YOLOP model, the multi-task learning network performs better in lane detection, drivable area detection, and vehicle detection tasks. Specifically, the lane detection accuracy improves by 11.6%, the mean Intersection over Union (mIoU) for drivable area detection increases by 2.1%, and the mean Average Precision at 50% IoU (mAP50) for vehicle detection improves by 3.7%., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2024
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22. Analyzing the factors influencing speeding behavior based on quasi-induced exposure and random parameter logit model with heterogeneity in means.
- Author
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Zhang G, Xuan Q, Cai Y, Hu X, Yin Y, and Li Y
- Subjects
- Humans, Male, Adult, Logistic Models, Female, Young Adult, Middle Aged, Adolescent, Risk-Taking, Automobile Driving statistics & numerical data, Accidents, Traffic statistics & numerical data, Accidents, Traffic prevention & control
- Abstract
Introduction: Speeding behavior is a major threat to road traffic safety, which can increase crash risks and result in severe injury outcomes. Although several studies have been conducted to analyze speeding crashes and relevant influential factors, the heterogeneity of variables has not been fully explored. Based on the traffic crash data extracted from the Crash Report Sampling System, the study aims to identify the factors that influence speeding driving with the consideration of variable heterogeneity., Method: Quasi-induced exposure technique is adopted to identify the disparities in the propensities of speeding for various driving cohorts. The random parameter logit model with heterogeneity in means is employed to examine the factors impacting speeding behavior., Results: Results indicate that: (a) driving cohorts such as young drivers, male drivers, passenger cars, and pickups appear to have higher propensities of engaging in speeding driving; (b) the propensity of speeding is higher when the driver is drinking, distracted, changing lanes, negotiating a curve, driving in lighted condition, and on curved roads; and (c) the random parameter logit model with heterogeneity in means has better performance as opposed to that without heterogeneity in means., Conclusions: Speeding behavior can be influenced by various factors in terms of driver-vehicle characteristics, physical condition, driving actions, and environmental conditions., Practical Applications: The findings could serve to develop effective countermeasures to reduce speeding behavior and improve traffic safety., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 National Safety Council and Elsevier Ltd. All rights reserved.)
- Published
- 2024
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23. Effect of eco-driving on commercial motor vehicle driver collision risk.
- Author
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D Robertson R, Delavary M, Lyon C, and Vanlaar W
- Subjects
- Humans, Adult, Male, Middle Aged, Female, Canada, Young Adult, Safety, Automobile Driving statistics & numerical data, Accidents, Traffic statistics & numerical data, Accidents, Traffic prevention & control, Motor Vehicles
- Abstract
Introduction: This study investigates the effect among commercial motor vehicle (CMV) drivers of the adoption of fuel-efficient driving techniques (commonly known as eco-driving) on the odds of being involved in safety-related events., Method: For 2,637 long-haul class 8 drivers employed by four carriers in Canada, information on driving style, total distance driven, and safety-related events like collisions, hard-braking, hard-turning, and stability control events were collected for each trip. Three carriers provided driving style-related data from the ISAAC instrument, which provides a score on a 0 to 100 scale that measures the degree to which a driver is using an appropriate amount of engine power according to driving conditions. The fourth carrier provided data on driving style characteristics, including fuel consumption, use of cruise control, and use of top gear. Depending on the carrier, information on speeding, driver age, and years of experience driving a commercial vehicle was also collected. Logit statistical models were developed to estimate the change in odds of a driver experiencing a safety-related event dependent on the measures of driving style., Results: A one-unit increase in the ISAAC score was associated with a 7%, 8%, 8%, and 4% reduction in the odds of having a hard-braking event, hard left-turn event, hard right-turn event, and collision, respectively. For the carrier not employing the ISAAC system, an increase of 10% in the time spent driving in top gear with steady speed near 100 km per hour (km/h) was associated with a substantial 34% decrease in stability control events. In addition, a year increase in the driver's age, as well as a 1% increase in the amount of time spent driving using cruise control, reduced the number of hard-braking events by 9% and 3%, respectively. Conclusion/Practical Applications: The adoption of fuel-efficient driving techniques enhances the safety of CMV drivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 National Safety Council and Elsevier Ltd. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
24. Drinking and driving: A systematic review of the impacts of alcohol consumption on manual and automated driving performance.
- Author
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Dong M, Lee YY, Cha JS, and Huang G
- Subjects
- Humans, Accidents, Traffic prevention & control, Driving Under the Influence statistics & numerical data, Driving Under the Influence prevention & control, Blood Alcohol Content, Automobiles, Automobile Driving, Alcohol Drinking, Automation
- Abstract
Introduction: Almost a third of car accidents involve driving after alcohol consumption. Autonomous vehicles (AVs) may offer accident-prevention benefits, but at current automation levels, drivers must still perform manual driving tasks when automated systems fail. Therefore, understanding how alcohol affects driving in both manual and automated contexts offers insight into the role of future vehicle design in mediating crash risks for alcohol-impaired driving., Method: This study conducted a systematic review on alcohol effects on manual and automated (takeover) driving performance. Fifty-three articles from eight databases were analyzed, with findings structured based on the information processing model, which can be extended to the AV takeover model., Results: The literature indicates that different Blood Alcohol Concentration (BAC) levels affect driving skills essential for traffic safety at various information processing stages, such as delayed reacting time, impaired cognitive abilities, and hindered execution of driving tasks. Additionally, the driver's driving experience, drinking habits, and external driving environment play important roles in influencing driving performance., Conclusions: Future work is needed to examine the effects of alcohol on driving performance, particularly in AVs and takeover situations, and to develop driver monitoring systems., Practical Applications: Findings from this review can inform future experiments, AV technology design, and the development of driver state monitoring systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 National Safety Council and Elsevier Ltd. All rights reserved.)
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- 2024
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25. Evolution of work conditions for employees driving for work in France based on data from the 2003, 2010 and 2017 SUMER surveys (Surveillance Médicale des expositions aux risques Professionnels).
- Author
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Fort E, Haddak MM, Pelissier C, and Charbotel B
- Subjects
- Humans, France epidemiology, Male, Female, Adult, Surveys and Questionnaires, Middle Aged, Occupational Health, Job Satisfaction, Accidents, Traffic statistics & numerical data, Accidents, Occupational statistics & numerical data, Accidents, Occupational prevention & control, Automobile Driving statistics & numerical data, Workplace
- Abstract
Introduction: The occupational road-accident risk on public roads and the work conditions for professional driving is still an important issue in occupational health despite lower road-accident rates. This study presents the evolution over time of the work-related constraints for these employees based on the Sumer surveys carried out in 2003, 2010 and 2017., Method: Data from the 2010 and 2017 surveys were restricted to match the scope of the 2003 survey in order to enable prevalence data to be compared in equivalent populations. The main variable of interest was "driving (car, truck, bus, and other vehicles) on public thoroughfares" for work (during the last week of work: yes/no). Work time characteristics, work rhythm, autonomy and scope for initiative, collective work group, standards and evaluations variables were completed by the occupational health physicians. A self-administered questionnaire was also provided to employees and contained the Job Content Questionnaire, which assesses decision latitude, social support and psychological demands, the reward scale of Siegrist questionnaire, the hostile behaviour with inspired questions for Leymann, sick leave and work accidents during the past 12 months and job satisfaction. Finally, prevention in the workplace was also completed by the occupational health physicians., Results: About 25% of employees in France were exposed to work-related driving in 2017, which was stable in comparison with 2003 and 2010. However, the population was older and there were more females, more often from the clerical staff/middle manager category and working in companies with fewer than 10 employees. Employees exposed to work-related driving were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks., Conclusions: The percentage of employees exposed to occupational road accident risk, i.e., exposure to work-related driving, remained stable at about 25% in 2017 compared with previous surveys. These employees were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks., Practical Applications: Prevention campaigns on work-related road accident risk should be provided to all employees in all companies since all jobs can be concerned., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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26. Resilient interactions between cyclists and drivers, and what does this mean for automated vehicles?
- Author
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Parnell KJ, Merriman SE, and Plant KL
- Subjects
- Humans, Accidents, Traffic, Autonomous Vehicles, Safety, Bicycling, Automobile Driving, Resilience, Psychological
- Abstract
The road transport system is a complex sociotechnical system that relies on a number of formal and informal rules of the road to ensure safety and resilience. Interactions between vulnerable road users and drivers often includes informal communication channels that are tightly linked to social norms, user expectations and the environmental context. Automated vehicles have a challenge in being able to communicate and respond to these informal rules of the road, therefore additional technologies are required to better support vulnerable road users. This paper presents the informal rules that cyclists and drivers employ within a cyclist overtake manoeuvre, through qualitative data collected from focus groups and interviews with road users. These informal rules are classified into the key elements of resilience (monitor, detect, anticipate, respond and learn) to understand how they guide the resilient interactions between road users. Using a human factors approach, the Perceptual Cycle Model shows how information is communicated between different road users and created by the situational context. This is then used to inform how automation will alter the communication between cyclists and drivers, and what additional feedback mechanisms will be needed to support the systems resilience. Technologies that can support these feedback mechanisms are proposed as avenues for future development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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27. Cardiac indices of driver fatigue across in-lab and on-road studies.
- Author
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Musicant O, Richmond-Hacham B, and Botzer A
- Subjects
- Humans, Fatigue diagnosis, Fatigue etiology, Accidents, Traffic prevention & control, Algorithms, Heart Rate, Automobile Driving
- Abstract
Driver fatigue is a major contributor to road accidents. Therefore, driver assistance systems (DAS) that would monitor drivers' states may contribute to road safety. Such monitoring can potentially be achieved with input from ECG indices (e.g., heart rate). We reviewed the empirical literature on responses of cardiac measures to driver fatigue and on detecting fatigue with cardiac indices and classification algorithms. We used meta-analytical methods to explore the pooled effect sizes of different cardiac indices of fatigue, their heterogeneity, and the consistency of their responses across studies. Our large pool of studies (N = 39) allowed us to stratify the results across on-road and simulator studies. We found that despite the large heterogeneity of the effect sizes between the studies, many indices had significant pooled effect sizes across the studies, and more frequently across the on-road studies. We also found that most indices showed consistent responses across both on-road and simulator studies. Regarding the detection accuracy, we found that even on-road classification could have been as accurate as 70% with only 2-min of data. However, we could only find two on-road studies that employed fatigue classification algorithms. Overall, our findings are encouraging with respect to the prospect of using cardiac measures for detecting driver fatigue. Yet, to fully explore this possibility, there is a need for additional on-road studies that would employ a similar set of cardiac indices and detection algorithms, a unified definition of fatigue, and additional levels of fatigue than the two fatigue vs alert states., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
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- 2024
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28. The impact of environmental noise on drivers' cognitive abilities: A case study on in-vehicle voice interaction interfaces.
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Jin T, Liu X, Chen C, Xia Y, Liu X, Lv M, and Li L
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- Humans, Cognition, Attention, Noise adverse effects, Reaction Time, Accidents, Traffic, Automobile Driving psychology
- Abstract
To investigate the impact of environmental noise on the cognitive abilities of drivers, this study, using in-vehicle voice interaction as an example, conducted laboratory experiments to assess the effects of road traffic noise, entertainment noise, and white noise stimuli on drivers' attention and short-term memory. The noise levels simulated to mimic acoustic conditions during car driving ranged from 35 dB(A) to 65 dB(A). The conclusions drawn were as follows: (1) Noise levels directly influenced subjective annoyance levels, with annoyance linearly increasing as noise levels escalated; (2) Both attention and short-term memory task reaction times of drivers were significantly influenced by noise types. Compared to traffic noise and white noise, drivers' cognitive efficiency was lower under entertainment noise. (3) Performance in complex cognitive tasks was more susceptible to noise levels compared to simple cognitive tasks; (4) Experimentally, it was found that drivers exhibited the highest cognitive efficiency in cognitive tasks when the environmental noise level was 55 dB(A), as opposed to noise levels of 35 dB(A), 45 dB(A), and 65 dB(A)., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tao Jin reports financial support was provided by National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
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- 2024
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29. Effects of driving style on takeover performance during automated driving: Under the influence of warning system factors.
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Zhang Y, Ma Q, Qu J, and Zhou R
- Subjects
- Humans, Automation, Reaction Time, Computer Simulation, Transtheoretical Model, Accidents, Traffic, Automobile Driving
- Abstract
Driving style has been proposed to be a critical factor in automated driving. However, the role of driving style in the process of taking over during automated driving needs further investigation. The main purpose of this study was to investigate the influence of driving style on takeover performance under the influence of warning system factors. In addition, this study also explored whether the impact of driving style on reaction time varies over time and the role of driving style on a comprehensive takeover quality indicator. Two driving simulation experiments with different takeover request (TOR) designs were conducted. In experiment 1, content warning information was provided in the TOR with different warning stage designs; in experiment 2, countdown warning information was provided in the TOR with different warning stage designs. Sixty-four participants (32 for experiment 1 and 32 for experiment 2) were classified into two groups based on their driving style (i.e., aggressive, or defensive) using the Chinese version of the Multidimensional Driving Style Inventory (the brief MDSI-C). The results suggested that drivers' driving style had significant effects on takeover performance, but the effects were influenced by warning system designs. Specifically, defensive participants performed better takeover performance, i.e., shorter reaction time and cautious vehicle control behaviors, than aggressive participants in most warning conditions. The content and countdown warning information and warning stage design affected the roles of driving style on takeover performance: 1) compared to the one-stage warning design, the two-stage warning design significantly shortened the reaction time of the participants with different driving styles, 2) compared to the countdown warning information design, the design of content warning information can shorten the reaction time of aggressive participants and lengthen the reaction time of defensive participants in the two-stage warning conditions, and 3) compared to the content warning information design, countdown warning information can improve the safe takeover performance of defensive participants. This study provides a better understanding of the role of driving style on takeover performance, and driving style should be considered when designing warning systems for autonomous vehicles., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
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- 2024
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30. "Braking bad": The influence of haptic feedback and tram driver experience on emergency braking performance.
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Callari TC, Moody L, Mortimer M, Stefan H, Horan B, and Birrell S
- Subjects
- Humans, Feedback, Haptic Technology, Motor Vehicles, Accidents, Traffic, Automobile Driving
- Abstract
Trams are experiencing a resurgence with worldwide network expansion driven by the need for sustainable and efficient cities. Trams often operate in shared or mixed-traffic environments, which raise safety concerns, particularly in hazardous situations. This paper adopts an international, mixed-methods approach, conducted through two interconnected studies in Melbourne (Australia) and Birmingham (UK). The first study involved qualitative interviews, while the second was an experimental study involving a virtual reality (VR) simulator and haptic master controller (i.e., speed lever). In tram operations, master controllers play a critical role in ensuring a smooth ride, which directly influences passenger safety and comfort. The objective was to understand how a master control system, enhanced with additional haptic feedback, could improve tram driver braking performance and perceptions in safety-critical scenarios. Interview results indicate that the use of the emergency brake is considered the final or ultimate choice by drivers, and their driving experience is a moderating factor in limiting its application. Combined with the experimental results, this paper highlights how implementing haptic feedback within a master controller can reduce the performance disparity between novice and experienced tram drivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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31. How Can the Trust-Change Direction be Measured and Identified During Takeover Transitions in Conditionally Automated Driving? Using Physiological Responses and Takeover-Related Factors.
- Author
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Yi B, Cao H, Song X, Wang J, Zhao S, Guo W, and Cao D
- Subjects
- Humans, Trust, Automation, Research Design, Heart Rate, Accidents, Traffic, Reaction Time physiology, Automobile Driving
- Abstract
Objective: This paper proposes an objective method to measure and identify trust-change directions during takeover transitions (TTs) in conditionally automated vehicles (AVs)., Background: Takeover requests (TORs) will be recurring events in conditionally automated driving that could undermine trust, and then lead to inappropriate reliance on conditionally AVs, such as misuse and disuse., Method: 34 drivers engaged in the non-driving-related task were involved in a sequence of takeover events in a driving simulator. The relationships and effects between drivers' physiological responses, takeover-related factors, and trust-change directions during TTs were explored by the combination of an unsupervised learning algorithm and statistical analyses. Furthermore, different typical machine learning methods were applied to establish recognition models of trust-change directions during TTs based on takeover-related factors and physiological parameters., Result: Combining the change values in the subjective trust rating and monitoring behavior before and after takeover can reliably measure trust-change directions during TTs. The statistical analysis results showed that physiological parameters (i.e., skin conductance and heart rate) during TTs are negatively linked with the trust-change directions. And drivers were more likely to increase trust during TTs when they were in longer TOR lead time, with more takeover frequencies, and dealing with the stationary vehicle scenario. More importantly, the F1-score of the random forest (RF) model is nearly 77.3%., Conclusion: The features investigated and the RF model developed can identify trust-change directions during TTs accurately., Application: Those findings can provide additional support for developing trust monitoring systems to mitigate both drivers' overtrust and undertrust in conditionally AVs.
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- 2024
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32. Using voice recognition to measure trust during interactions with automated vehicles.
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Deng M, Chen J, Wu Y, Ma S, Li H, Yang Z, and Shen Y
- Subjects
- Humans, Automation, Voice Recognition, Trust, Accidents, Traffic, Autonomous Vehicles, Automobile Driving
- Abstract
Trust in an automated vehicle system (AVs) can impact the experience and safety of drivers and passengers. This work investigates the effects of speech to measure drivers' trust in the AVs. Seventy-five participants were randomly assigned to high-trust (the AVs with 100% correctness, 0 crash, and 4 system messages with visual-auditory TORs) and low-trust group (the AVs with a correctness of 60%, a crash rate of 40%, 2 system messages with visual-only TORs). Voice interaction tasks were used to collect speech information during the driving process. The results revealed that our settings successfully induced trust and distrust states. The corresponding extracted speech feature data of the two trust groups were used for back-propagation neural network training and evaluated for its ability to accurately predict the trust classification. The highest classification accuracy of trust was 90.80%. This study proposes a method for accurately measuring trust in automated vehicles using voice recognition., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
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- 2024
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33. Should Steering Settings be Changed by the Driver or by the Vehicle Itself?
- Author
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Melman T, Weijerman M, de Winter J, and Abbink D
- Subjects
- Humans, Automobiles, Automation, Automobile Driving
- Abstract
Introduction: Cars are increasingly computerized, and vehicle settings such as steering gain (SG) can now be altered during driving. However, it is unknown whether transitions in SG should be adaptable (i.e., triggered by driver input) or adaptive (i.e., triggered automatically). We examined this question for road segments expected to require different SG., Objective: This paper aimed to investigate whether SG mode changes should be made by the driver or automatically., Methods: Twenty-four participants drove under four conditions in a simulator: fixed low gain (FL), fixed high gain (FH), a machine-initiated steering system, which switched between the two SG levels at predetermined locations (MI), and a driver-initiated steering system, in which the SG level could be changed by pressing a button on the steering wheel (DI)., Results: Participants showed poorer lane-keeping and reported higher effort for FH compared to FL on straights, while the opposite held true on curved roads. On curved roads, the MI condition yielded better lane-keeping and lower subjective effort than the DI condition. However, a substantial portion of the drivers gave low preference rankings to the MI system., Conclusion: Drivers prefer and benefit from a steering system with a variable rather than fixed gain. Furthermore, although automatic SG transitions reduce effort, some drivers reject this concept., Application: As the state of technology advances, MI transitions are becoming increasingly feasible, but whether drivers would want to delegate their decision-making authority to a machine remains a moot point.
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- 2024
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34. Evaluation of a 3M (mistakes, mentoring, and mastery) training program for transfer of control situations in a level 2 automated driving system.
- Author
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Roberts SC, Hanson W, Ebadi Y, Talreja N, Knodler MA Jr, and Fisher DL
- Subjects
- Humans, Awareness, Automation, Trust, Reaction Time, Accidents, Traffic, Automobile Driving, Mentoring
- Abstract
Drivers must actively supervise automation as it can only function in limited conditions. A failure to supervise the system has negative consequences in terms of missed requests to take over control and may cause crashes or jeopardize safety. The objective of this study is to determine the effect of a novel, 3M (Mistakes, Mentoring, and Mastery) training program on drivers' behavior while using level 2 driving automation systems. To achieve this, 36 participants were assigned randomly to three different training programs (3M training, User manual, and Placebo) and drove through scenarios on a fixed-based driving simulator. The results showed that drivers in the 3M training group took back control more effectively when the driving automation system reached its limits compared to drivers who received User manual or Placebo training. Drivers in the 3M training Group also had higher situation awareness and improved trust in automation. The results indicate that an interactive approach to training with regards to vehicle automation can help drivers more safely interact with automation systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
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- 2024
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35. Psychosocial factors, psychological well-being and safety incidents among long-distance bus drivers in Ghana: A cross-sectional survey.
- Author
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Amoadu M, Ansah EW, and Sarfo JO
- Subjects
- Humans, Cross-Sectional Studies, Ghana, Psychological Well-Being, Accidents, Traffic, Automobile Driving psychology, Occupational Stress
- Abstract
Background: Commercial bus drivers account for most road traffic crashes and related mortality. The psychosocial working conditions of these drivers have been found precarious. However, road safety initiatives in Ghana still focus on correcting risky driving behaviours, ignoring the conditions under which these drivers operate. Hence, the purpose of this study was to examine whether psychosocial work factors can predict the psychological well-being and risky driving behaviours of long-distance bus drivers in Ghana., Methods: This quantitative cross-sectional survey recruited 7315 long-distance bus drivers that operate from Accra to other parts of Ghana and cities in other West African countries. Hypotheses were tested using Partial Least Squares Structural Equation Modelling (PLS-SEM)., Results: We found that job demands and job resources are direct and significant predictors of psychological well-being and safety incidents among these drivers. Moreover, psychological well-being of the drivers had a significant inverse relationship with their safety incidents. Psychosocial safety climate (PSC) had a negative association with safety incidents, and a positive but non-significant association with psychological well-being. PSC had a negative and significant association with job resources contrary to the notion of the PSC theory., Conclusion: Psychosocial work factors are predictors of psychological well-being and safety incidents of long-distance bus drivers. Owners and managers of bus transport businesses in Ghana, driver unions and station masters need to highly prioritise psychological health and safety of this bus drivers by providing suitable job resources and adopting bottom-up communication that might help the drivers effectively cope with their job demands., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
- Published
- 2024
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36. Vehicle detection systems for intelligent driving using deep convolutional neural networks.
- Author
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Abiyev, Rahib and Arslan, Murat
- Subjects
CONVOLUTIONAL neural networks ,AUTOMATIC systems in automobiles ,DRIVERLESS cars ,CAMCORDERS ,SYSTEM identification ,AUTOMOBILE driving - Abstract
In the paper, a vision-based vehicle identification system is proposed for autonomous intelligent car driving. The accurate detection of obstacles (vehicles) during intelligent car driving allows avoiding crashes, preventing accidents, saving people's lives and reducing harm. The vehicle detection system, which uses low-quality images captured by a monocular video camera mounted at the front of the car, is based on convolutional neural networks (CNN). The CNN can extract global features of the images using convolutional layers and achieves more accurate, and faithful contours of vehicles. The CNN structure proposed in the paper provides high-accuracy detection of vehicle images. The experiments that have been performed using GTI dataset demonstrate that the CNN-based vehicle detection system achieves very accurate results and is more robust to different variations of images. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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37. Development of an Android-Based Self-Report Assessment for Elderly Driving Risk (SAFE-DR) App: Mixed Methods Study
- Author
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Ho Sung Hwang and Seong-Youl Choi
- Subjects
Self-assessment ,030506 rehabilitation ,Automobile Driving ,validity ,Applied psychology ,Validity ,Poison control ,Health Informatics ,Information technology ,03 medical and health sciences ,Cronbach's alpha ,driving safety ,0502 economics and business ,Republic of Korea ,driving ,Humans ,mHealth ,Reliability (statistics) ,Aged ,050210 logistics & transportation ,Original Paper ,reliability ,05 social sciences ,Reproducibility of Results ,Android driving app ,T58.5-58.64 ,self-assessment ,Mobile Applications ,Exploratory factor analysis ,Test (assessment) ,Self Report ,Public aspects of medicine ,RA1-1270 ,0305 other medical science ,Psychology - Abstract
Background Self-report assessments for elderly drivers are used in various countries for accessible, widespread self-monitoring of driving ability in the elderly population. Likewise, in South Korea, a paper-based Self-Report Assessment for Elderly Driving Risk (SAFE-DR) has been developed. Here, we implemented the SAFE-DR through an Android app, which provides the advantages of accessibility, convenience, and provision of diverse information, and verified its reliability and validity. Objective This study tested the validity and reliability of a mobile app-based version of a self-report assessment for elderly persons contextualized to the South Korean culture and compared it with a paper-based test. Methods In this mixed methods study, we recruited and interviewed 567 elderly drivers (aged 65 years and older) between August 2018 and May 2019. For participants who provided consent, the app-based test was repeated after 2 weeks and an additional paper-based test (Driver 65 Plus test) was administered. Using the collected data, we analyzed the reliability and validity of the app-based SAFE-DR. The internal consistency of provisional items in each subdomain of the SAFE-DR and the test-retest stability were analyzed to examine reliability. Exploratory factor analysis was performed to examine the validity of the subdomain configuration. To verify the appropriateness of using an app-based test for older drivers possibly unfamiliar with mobile technology, the correlation between the results of the SAFE-DR app and the paper-based offline test was also analyzed. Results In the reliability analysis, Cronbach α for all items was 0.975 and the correlation of each item with the overall score ranged from r=0.520 to r=0.823; 4 items with low correlations were removed from each of the subdomains. In the retest after 2 weeks, the mean correlation coefficient across all items was r=0.951, showing very high reliability. Exploratory factor analysis on 40 of the 44 items established 5 subdomains: on-road (8 items), coping (16 items), cognitive functions (5 items), general conditions (8 items), and medical health (3 items). A very strong negative correlation of –0.864 was observed between the total score for the app-based SAFE-DR and the paper-based Driver 65 Plus with decorrelation scales. The app-based test was found to be reliable. Conclusions In this study, we developed an app-based self-report assessment tool for elderly drivers and tested its reliability and validity. This app can help elderly individuals easily assess their own driving skills. Therefore, this assessment can be used to educate drivers and for preventive screening for elderly drivers who want to renew their driver’s licenses in South Korea. In addition, the app can contribute to safe driving among elderly drivers.
- Published
- 2020
38. Transport institutions and organisations in the formulation of policies for Australian local area traffic management: A 50-year retrospective.
- Author
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Black, John
- Subjects
TRAFFIC engineering ,AUTOMOBILE driving ,INFORMATION processing ,INFORMATION technology ,DECISION making - Abstract
A review of 115 studies on Australian local area traffic management (LATM) schemes covers network planning, computer modelling, overall design considerations, the deployment of various traffic control devices, project evaluation and numerous before and after case studies. However, no research has been published about the formulation of LATM policies and the processes involved that were formulated during the 1970s and 1980s and aimed at discouraging non-local through traffic in residential areas, improving road safety, and improving environmental amenity through physical devices. This paper develops a conceptual model of the interactions amongst institutions of government (state and local), organisations (national research institutes and universities), and civil society (the consulting industry, lobby groups and community action groups). The model is implemented through a series of unstructured interviews with key players involved with research and advocacy, capacity building, and state government policy makers that determined: who was responsible for the governance of LATM schemes? What were the respective roles of institutions and organisations in relation to the early formulation of policies and plans, especially issues of authority? Who were the key players in these institutions and organisations? To what extent did external influences of ideas by overseas agents (policy transfer) occur in decision making? A recently implemented LATM scheme (Seven Ways) by Waverley Council describes the latest approaches, including community participation. The conclusions note the importance of a society investing in road research, having universities capable of delivering high-quality professional development programs, and having a consulting industry that is willing to deliver innovative, practical advice to local governments. Suggestions are made about areas for further research [ABSTRACT FROM AUTHOR]
- Published
- 2023
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39. Predictors of Health Insurance, Life Insurance, and Retirement Savings Among NYC’s Immigrant Taxi and For-Hire Vehicle Drivers
- Author
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Alex Ocampo, Abraham Aragones, Julia Ramirez, Soo Young Kim, Francesca Gany, Jennifer Leng, Sheena Mirpuri, Bharat Narang, and Nicole Roberts-Eversley
- Subjects
Adult ,Male ,Automobile Driving ,Health (social science) ,media_common.quotation_subject ,Immigration ,Emigrants and Immigrants ,Financial plan ,Insurance Coverage ,Social determinants of health ,03 medical and health sciences ,Health insurance ,0302 clinical medicine ,Life insurance ,Humans ,030212 general & internal medicine ,Pandemics ,media_common ,Retirement ,Original Paper ,Insurance, Health ,030505 public health ,SARS-CoV-2 ,Stressor ,Public Health, Environmental and Occupational Health ,COVID-19 ,Middle Aged ,Taxi drivers ,Health equity ,Stratified sampling ,Insurance, Life ,Socioeconomic Factors ,Financial literacy ,Female ,New York City ,Demographic economics ,Business ,Health disparities ,0305 other medical science ,human activities ,Immigrant - Abstract
Taxi and for-hire vehicle (FHV) drivers are a predominantly immigrant population facing a range of occupational stressors, including lack of workplace benefits and increasing financial strain from tumultuous industry changes and now COVID-19’s devastating impact. Bilingual research staff surveyed 422 New York City taxi/FHV drivers using a stratified sampling approach in driver-frequented locations to examine drivers’ health and financial planning behaviors for the first time. Drivers lacked health insurance at double the NYC rate (20% vs. 10%). Life insurance and retirement savings rates were lower than U.S. averages (20% vs. 60%, 25% vs. 58%, respectively). Vehicle ownership was a significant predictor of health insurance, life insurance, and retirement savings. Compared to South Asian drivers, Sub-Saharan African drivers were significantly less likely to have health insurance and North African, and Middle Eastern drivers were significantly less likely to have retirement savings. Although most drivers indicated the importance of insurance and benefits
- Published
- 2020
40. Strategies to enhance the level of service and safety of rural roads: A case study.
- Author
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Ai Q, Zhang J, and Ye Y
- Subjects
- Humans, Motor Vehicles, Rural Population, Safety, Accidents, Traffic prevention & control, Automobile Driving
- Abstract
Faced with the contradiction between the increasing traffic volume and the aging road infrastructures in the rural area, this paper aims to propose feasible strategies to enhance the level of service and safety, by a case study of the rural area in the north Jintan district. In order to figure out current issues related to rural roads, a carefully designed investigation has been conducted, and the results of the two-week investigation include roads' basic information, traffic signs and protective facilities, surrounding landscape, and etc. Based on the field driving tests, specific problems including signs category, signs installation and facility maintenance have been fully analyzed. Meanwhile, the problem of roadnet connectivity has also been pointed out through the theory of complex network, and results show that the average node clustering coefficient and shortest path length perform worse than the demonstration plot of other rural districts. For the sake of rural traffic safety and management efficiency, both quantified and qualified strategies have been put forward. The quantified strategies include the regular inspection indicators, the safety sight distance at T-type crossings, as well as the risk severity of sections and the crossings. The qualified strategies involve the management of trucks and roadworks, the setting of signalized intersections, and the timely updates of traffic signs and facilities. Finally, an intelligent management system framework has been established for rural road traffic, with highly interconnected modules of data acquisition, risk identification and information publishing., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2024
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41. Knowing me, knowing you-A study on top-down requirements for compensatory scanning in drivers with homonymous visual field loss.
- Author
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Biebl B, Kuhn M, Stolle F, Xu J, Bengler K, and Bowers AR
- Subjects
- Humans, Vision Disorders, Vision, Ocular, Visual Field Tests, Accidents, Traffic, Visual Fields, Automobile Driving
- Abstract
Objective: It is currently still unknown why some drivers with visual field loss can compensate well for their visual impairment while others adopt ineffective strategies. This paper contributes to the methodological investigation of the associated top-down mechanisms and aims at validating a theoretical model on the requirements for successful compensation among drivers with homonymous visual field loss., Methods: A driving simulator study was conducted with eight participants with homonymous visual field loss and eight participants with normal vision. Participants drove through an urban surrounding and experienced a baseline scenario and scenarios with visual precursors indicating increased likelihoods of crossing hazards. Novel measures for the assessment of the mental model of their visual abilities, the mental model of the driving scene and the perceived attention demand were developed and used to investigate the top-down mechanisms behind attention allocation and hazard avoidance., Results: Participants with an overestimation of their visual field size tended to prioritize their seeing side over their blind side both in subjective and objective measures. The mental model of the driving scene showed close relations to the subjective and actual attention allocation. While participants with homonymous visual field loss were less anticipatory in their usage of the visual precursors and showed poorer performances compared to participants with normal vision, the results indicate a stronger reliance on top-down mechanism for drivers with visual impairments. A subjective focus on the seeing side or on near peripheries more frequently led to bad performances in terms of collisions with crossing cyclists., Conclusion: The study yielded promising indicators for the potential of novel measures to elucidate top-down mechanisms in drivers with homonymous visual field loss. Furthermore, the results largely support the model of requirements for successful compensatory scanning. The findings highlight the importance of individualized interventions and driver assistance systems tailored to address these mechanisms., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Biebl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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42. Improving road safety at horizontal curves using V2I speed warning messages.
- Author
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Doulabi S, Mohamed Abdu Kunnah H, and Hassan HM
- Subjects
- Humans, Male, Female, Self Report, Surveys and Questionnaires, Transportation, Accidents, Traffic prevention & control, Automobile Driving
- Abstract
Introduction: According to the Federal Highway Administration, a quarter of fatal collisions has occurred at horizontal curves. The average collision rate at horizontal curves was found to be three times higher than other types of highway segments. The lack of compliance with the speed limit and driver-related factors are among the main contributing factors to those collisions. Vehicle to Infrastructure (V2I) communications can address these limitations by providing drivers with valuable in-vehicle warning messages based on operational and safety data. There is limited effort investigating the impact of different types of V2I warning messages at horizontal curves and among different profiles of drivers. This study aims to thoroughly examine drivers' behavior and compliance with different V2I warning messages when approaching horizontal curves., Methods: A driving simulator experiment and self-reported survey were conducted. Three main hypotheses were analyzed in this study. First, whether supplying drivers with in-vehicle V2I warning messages will positively affect drivers' behavior at horizontal curves compared to the standard road signs. Second, whether there will be a significant difference in drivers' behavior when receiving text and audio V2I warning messages. Third, whether seniors and female drivers will comply more with speed limit advisory provided through V2I message than younger and male drivers., Results: The Analysis of Covariance confirmed the first two hypotheses. Two main measures of drivers' behavior found to be lower in the V2I communication scenarios compared to the base one. The audio warning message was found to be more promising in increasing drivers' compliance with speed limit advisory when approaching the curves. Analyzing the third hypothesis revealed that younger and male drivers had higher curve initiation speed compared to females and seniors., Practical Applications: The findings of this study can be used by transportation researchers, authorities, and car manufacturers to improve the effectiveness of in-vehicle V2I warning messages among different profiles of drivers., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)
- Published
- 2024
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43. Speeding behavior among teenage drivers during the learner and early independent driving stage: A case study approach.
- Author
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Chang CH, Zhu S, Chirles TJ, Weast R, Ji T, Igusa T, and Ehsani JP
- Subjects
- Adolescent, Humans, United States, Accidents, Traffic prevention & control, Longitudinal Studies, Risk-Taking, Travel, Automobile Driving
- Abstract
Introduction: Speed is a primary contributing factor in teenage driver crashes. Yet, there are significant methodological challenges in measuring real-world speeding behavior., Method: This case study approach analyzed naturalistic driving data for six teenage drivers in a longitudinal study that spanned the learner and early independent driving stages of licensure in Maryland, United States. Trip duration, travel speed and length were recorded using global position system (GPS) data. These were merged with maps of the Maryland road system, which included posted speed limit (PSL) to determine speeding events in each recorded trip. Speeding was defined as driving at the speed of 10 mph higher than the posted speed limit and lasting longer than 6 s. Using these data, two different speeding measures were developed: (1) Trips with Speeding Episodes, and (2) Verified Speeding Time. Conclusions & Practical Applications: Across both measures, speeding behavior during independent licensure was greater than during the learner period. These measures improved on previous methodologies by using PSL information and eliminating the need for mapping software. This approach can be scaled for use in larger samples and has the potential to advance understanding about the trajectory of speeding behaviors among novice teenage drivers., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)
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- 2024
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44. Interrelatedness of steering and lateral position parameters: Recommendations for the assessment of driving performance.
- Author
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Xu J, Fard M, Zhang N, Davy JL, and Robinson SR
- Subjects
- Humans, Accidents, Traffic prevention & control, Safety, Attention, Automobile Driving
- Abstract
Introduction: Loss of attention leads to less steady driving within the lane and is one of the main causes of road accidents. To improve road safety, vehicle-based parameters such as steering wheel angle and lateral position are used to objectively assess driving performance, especially in monotonous driving tasks., Method: The present driving simulator study investigated the extent to which eight commonly used parameters are independent indicators of driving performance. Fifteen participants undertook a monotonous highway driving task for 1 h. Four steering angle parameters were examined: average steering angle (ASA), standard deviation of steering angle (SDSA), steering angle range (SAR), and steering reversal rate (SRR); as well as four lateral position parameters: mean lateral position (MLP), standard deviation of lateral position (SDLP), lateral position range (LPR), and the out-of-lane duration. Measurements were averaged across 2-minute epochs. Repeated measures correlation analysis evaluated the similarity between each parameter, and the variance inflation factor test evaluated the multicollinearity of all the parameters., Results: The results demonstrated that some parameters are highly correlated and should not be used together to assess driving performance. It is recommended that the optimal combination is ASA and SAR to assess steering angle, and SDLP and out-of-lane to assess lateral position. Out-of-lane, as a factor directly contributing to road safety, is recommended because it has the least correlation with other parameters., Practical Applications: If implemented, these recommendations may improve the assessment of driving performance in future studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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45. Reported pushy driving against cyclists in Germany.
- Author
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Hagemeister C and Bertram L
- Subjects
- Humans, Bicycling, Surveys and Questionnaires, Attitude, Germany, Accidents, Traffic, Automobile Driving
- Abstract
Background: When cyclists and drivers share the road drivers sometimes try to make the cyclist give way. This study assessed which characteristics and attitudes are related to pushy driving., Methods: The sample included 695 drivers aged 18 to 85 years who answered a German online questionnaire on pushy driving. They saw a sketch with a cyclist in front of them whom they could not overtake easily. They reported how often they engage in different pushy driving behaviors and how legitimate and effective these are. They provided information about their mobility habits, goals, and attitudes., Results: Correlations between reported frequency, perceived legitimacy, and perceived effectiveness of pushy driving were between r = 0.78 and r = 0.80. Many correlations with pushy driving were of medium size: drivers with the goal to drive safe and friendly reported less pushy driving, drivers with the goal to get the cyclist out of the way reported more. The correlations between reported frequency of pushy driving and attitude toward cyclists, self-justification, victim blaming, and feeling bothered by cyclists in built-up areas were of medium size., Summary: The highest correlations with pushy driving were those with perceived legitimacy and perceived effectiveness of pushy driving. The results show that pushy drivers cannot be identified by demographic characteristics or mobility habits. General attitudes and the perception of pushy behaviors in specific situations and drivers' goals in these situations are more important., Discussion: There will always be roads that cyclists and drivers share. In order to reduce pushy driving, its legitimacy could be addressed by campaigns and its effectiveness by a lower speed limit and enforcement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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46. Does the 80 km/h speed limit save lives in France?
- Author
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Carnis L and Garcia C
- Subjects
- Humans, Safety, France, Time Factors, Accidents, Traffic prevention & control, Automobile Driving
- Abstract
Introduction: Speeding is considered to be a major contributor to road fatalities and injuries worldwide. Inappropriate speeding behavior is associated with a high casualty burden. It could be responsible for at least 30% of road accidents., Method: In 2018, the French authorities decided to introduce a new speed limit. They lowered the speed limit to 80 km/h on the unseparated interurban network. The aim was to reduce the number of fatalities and injuries and to implement some measures in line with international commitments. This paper uses different econometric models applied to time series for different groups of counties., Results: The results show a significant positive contribution of the new speed limit. The estimated number of lives saved is between 300 and 350. The overall reduction in the number of fatalities is 10%. The results also show a differentiated impact according to the local context and the different dynamics at play., Conclusions and Practical Applications: The results of this paper are in line with the scientific literature on speed limit reductions. They represent a validation of a debated public decision, while at the same time consolidating the body of knowledge on the subject, helping the decision-maker to adopt an appropriate measure to improve road safety performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)
- Published
- 2024
- Full Text
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47. The monitoring requests on young driver's fatigue and take-over performance in prolonged conditional automated driving.
- Author
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Yin J, Shao H, and Zhang X
- Subjects
- Humans, Reaction Time, Wakefulness, Automation, Fatigue prevention & control, Accidents, Traffic, Automobile Driving
- Abstract
Introduction: L3 automated vehicles can perform all dynamic driving tasks unless a take-over occurs due to operational limits. This issue is potentially important for young drivers who are vulnerable road users since they have skill deficits and easily evolve into aberrant driving. However, drivers lacking active involvement may be fatigued and drowsy. Previous research indicated that performing a voluntary non-driving-related task (NDRT) could keep drivers alert, but there was no difference in take-over performance with or without NDRT. Providing a monitoring request (MR) before a possible take-over request (TOR) exhibited better take-over performance in temporary automated driving. Therefore, the study aimed to investigate the effects of MR and voluntary NDRT on young drivers' fatigue and performance., Method: Twenty-five young drivers experienced 60 min automated driving on a highway with low traffic density and a TOR prompted due to a collision event. A within-subjects was designed that comprised three conditions: NONE, TOR-only, and MR + TOR. Drivers were allowed to perform a self-paced phone NDRT during automated driving., Results: The PERCLOS and blink frequency data showed that playing phones could keep drivers vigilant. The take-over performance on whether taking phone had no difference, but with MRs condition exhibited better take-over performance including the shorter reaction time and the longer TTC. Subjective evaluations also showed the advantages of MRs with more safety, trust, acceptance, and lower workload., Conclusions: Taking MRs had a positive effect on relieving fatigue and improving take-over performance. Furthermore, MRs could potentially improve the safety and acceptance of automated driving., Practical Applications: The MR design can be used in the automotive industry to ensure the safest interfaces between fatigue drivers and automation systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)
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- 2024
- Full Text
- View/download PDF
48. Habits, attitudes, and expectations of regular users of partial driving automation systems.
- Author
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Mueller AS, Cicchino JB, and Calvanelli JV Jr
- Subjects
- Humans, Motivation, Attention, Automation, Habits, Automobile Driving
- Abstract
Introduction: Little is known about regular users' perceptions of partial (Level 2) automation or how those perceptions affect behind-the-wheel behavior., Method: A mixed mode (phone and online) survey explored the habits, expectations, and attitudes among regular users of General Motors Super Cruise (n = 200), Nissan/Infiniti ProPILOT Assist (n = 202), and Tesla Autopilot (n = 202)., Results: All three groups reported being more likely to engage in non-driving-related activities while using their systems than while driving unassisted. Super Cruise and Autopilot users especially were more likely to report engaging in activities that involved taking their hands off the wheel or their eyes off the road. Many Super Cruise and Autopilot users also said they could perform secondary (non-driving-related) tasks better and more often while using their systems, while fewer ProPILOT Assist users shared this opinion. Super Cruise users were most likely and ProPILOT Assist users least likely to think that secondary activities were safer to perform while using their systems. While some drivers said they found user safeguards (e.g., attention reminders, lockouts) annoying and tried to circumvent them, most people said they found them helpful and felt safer with them. Large percentages of users (53% Super Cruise, 42% Autopilot and 12% ProPILOT Assist) indicated they were comfortable treating their systems as self-driving., Conclusions: Some regular users have a poor understanding of their technology's limits. System design appears to contribute to user perceptions and behavior. However, owner populations also differ, which means habits, attitudes, and expectations may not generalize. Most people value user safeguards, but some implementations may not be effective for everyone., Practical Applications: Multifaceted, proactive user-centric safeguards are needed to shape proper behavior and understanding about drivers' roles and responsibilities while using partial driving automation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)
- Published
- 2024
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49. Understanding the driving mechanisms of site contamination in China through a data-driven approach.
- Author
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Li K and Sun R
- Subjects
- Environmental Pollution analysis, China, Environmental Pollutants analysis, Automobile Driving
- Abstract
China currently faces significant environmental risks stemming from contaminated sites. The driving mechanism of site contamination, influenced by various drivers, remain obscured due to a dearth of quantitative methodologies and comprehensive data. Here, we used a data-driven causality inference approach to construct an interpretable random forest (RF) model. Results show that: (1) the trained RF model demonstrated remarkable predictive accuracy for identifying contaminated sites, with an accuracy rate of 0.89. In contrast to conventional correlation analysis, the RF model excels in discerning the key drivers through non-linear and genuine causal relationships between these drivers and site contamination. (2) Among the 25 potential drivers, we identified 18 key drivers of site contamination. These drivers encompass a broad spectrum of factors, including production and operational data, pollutant control level, site protection capability, pollutant characteristics, and physical-geographical conditions. (3) Each key driver exerts varying impacts on site pollution, with diverse directions, intensities, and underlying patterns. The partial dependence plots (PDPs) illuminate the role of each key driver, its critical value contributing to site pollution, and the interplay between these drivers. The key drivers facilitate the realization of three primary contamination processes: uncontrolled release, effective migration, and persistent accumulation. In light of our findings, environmental managers can proactively prevent site contamination by regulating single, dual, and multiple key drivers to disrupt critical pollution processes. This research offers valuable insights for devising targeted strategies and interventions aimed at mitigating environmental risks associated with contaminated sites in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)
- Published
- 2024
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50. How job stressors and economic stressors impact public transport drivers' performance and well-being under the health risk of the COVID-19 pandemic.
- Author
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Chen CF and Sih J
- Subjects
- Humans, Pandemics, Surveys and Questionnaires, Job Satisfaction, Automobile Driving, COVID-19 epidemiology
- Abstract
Introduction: During the COVID-19 pandemic, public transport (e.g., bus and taxi) drivers encountered great stress because they needed to work to maintain the operation of the transportation system. This study proposes and empirically investigates the impacts of job stressors and economic stressors of public transport drivers on emotional exhaustion, and subsequent psychological well-being and performance under the health risk of COVID-19. The moderating effects of perceived threat and death anxiety on the relationships between stressors and emotional exhaustion are also examined., Method and Results: Using two survey samples collected from bus and taxi drivers in Taiwan, the results reveal that, except for the effect of time pressure on taxi drivers' exhaustion, job stressors (job overload and time pressure) and economic stressors (job insecurity) positively relate to emotional exhaustion for both bus and taxi drivers. Drivers' emotional exhaustion has negative effects on both job satisfaction and positive effects on risky driving behaviors. Perceived pandemic threat strengthens the positive influence of job insecurity on emotional exhaustion for bus drivers, while perceived pandemic threat and death anxiety weaken the negative influence of job insecurity on emotional exhaustion for taxi drivers., Practical Applications: Effective intervention strategies and policies to mitigate perceived pandemic threat and death anxiety of drivers are recommended., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
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