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Previous studies showed that the use of haptic feedback can improve user's experience. However, quantitative data on driver performance are missing. This paper examines potential benefits of various feedbacks on driving performance and user's preference: Visual feedback M, Visual and Auditory feedback (VA), and Visual, Auditory and Haptic feedback (VAH). 24 participants completed a dual-task approach, using the Lane Change Test (LCT) as a driving task and two use cases of touchscreen tasks (Slide or Push task). Moreover, in a given condition participants had to performed a third task to increase mental workload. Results showed that the presence of the trimodal feedback VAH significantly improved driving performances compared to other feedbacks. This was observed through a decrease in standard deviations of lateral. Haptic feedbacks reduce error rates in the dual-task, and that participants significantly preferred this trimodal haptic feedback Therefore, haptic feedback use have an objective positive effect on driver performance and on subjective user's experience while interacting with a touchscreen interface for both Slide and Push tasks conditions. [ABSTRACT FROM AUTHOR]

When we drive a car in the high luminance environment, to comply with drivers and passengers' requests for better visibility, the display should be low reflection. In this report, the Advanced Reflection Invisible technology with Embedded System (ARIES) will be introduced for automotive wide‐view LCD with CTP to get super low reflection and improve ambient contrast ratio. It makes excellent sunlight readability without increasing the backlight luminance [ABSTRACT FROM AUTHOR]

The article reports that the periodical has announced public release of position papers as part of the work of its National Practice and Standards Reference Group related to occupational therapy and driver assessment and support of allied health assistants towards occupational therapy practice.

In urban railway systems, the timetable guides the section operation of the single train and the arrangement of the train group to meet the dual needs of cost and passengers. This paper proposes a two‐objective train operation optimization based on eco‐driving and timetabling to restore a more realistic scene, including a method level and an objective level. For the method level, the speed curve optimization of the single train and the timetable optimization of the train group are adopted jointly. For the objective level, both the total energy consumption of the train group and the consuming time of passengers are considered. A hybrid solution strategy based on quadratic programming and improved artificial bee colony algorithm is proposed. A hardware‐in‐the‐loop platform is built to carry out validation experiments. Both the cases in general hours and special hours are verified based on the actual data from Beijing Metro Line 15. The results show that both the energy consumption and the passenger consuming time are reduced simultaneously. Correspondingly, the speed curve and the time distribution of the timetable are individually optimized based on the fluctuating passenger flow. [ABSTRACT FROM AUTHOR]

The Austroads Fitness to Drive Guidelines were updated in 2022. Most of the focus to date has been on Part 2 of the Guidelines, which provide guidance as to specific medical conditions. Less attention has been paid to Part 1 of the Guidelines, which cover a medical practitioner's ethical and legal obligations. This paper addresses the imbalance by considering and amplifying the obligations discussed in Part 1 of the Guidelines. [ABSTRACT FROM AUTHOR]

The primary aim of this systematic review was to examine the efficacy of driving interventions with regard to a reduction in motor vehicle crashes and improvements in driving skills among older people. The secondary aim was to identify the optimal type (on‐road or off‐road) and dosage (period, sessions, and duration) of driving interventions for improving driving skills in older people. We searched MEDLINE, EMBASE, PsycINFO, and Scopus of Systematic Reviews for papers published from their inception to December 1, 2020, as well as the reference lists of the included papers. The selected studies were randomized controlled trials examining the effects of driving interventions among community‐dwelling older drivers aged 65 years and over. A meta‐analysis of two studies (n = 960) showed that driving interventions significantly reduced the number of motor vehicle crashes per person‐years. Ten studies (n = 575) were included in the meta‐analysis showing that the interventions significantly improved the driving skill scores. Driving skill scores significantly improved after on‐road training, and in interventions of at least 3 h, 3 sessions, and 3 weeks. Driving interventions significantly improve driving skills and reduce motor vehicle crashes among older drivers aged 65 years and over. On‐road training is more efficacious than off‐road training and driving interventions of at least 3 h taking place in 3 sessions over a period of 3 weeks may be required to improve driving skills in older drivers. Geriatr Gerontol Int 2023; 23: 771–778. [ABSTRACT FROM AUTHOR]

This paper investigates the potential impacts of dynamic wireless power transfer (DWPT) systems on the urban road network with a particular focus on charging and energy consumption implications. The paper is motivated by the recent advancement of connected and autonomous vehicle (CAV) technology and innovations on smart transportation infrastructure. An eco‐driving model aiming at energy consumption reduction is developed and a DWPT system layout suitable for charging eco‐driving CAVs at a signalised intersection is proposed. The idea is demonstrated in a simulated environment with different market penetration rate (MPR) of CAVs travelling through a signalized intersection equipped with the proposed DWPT system. The results suggest that as MPR of CAV increases, the energy savings for both CAVs and human‐driven vehicles (HVs) will increase significantly. At full MPR of CAVs, the reduction of average energy consumption of all types of vehicles can reach up to 62%. The average energy transferred and stored per battery electric vehicle can increase by up to 5% and 10%, respectively. These promising results indicate that a well‐designed DWPT system layout together with the eco‐driving behaviour of CAVs can have a positive impact on the urban transportation system in terms of resulting energy consumption and emissions. [ABSTRACT FROM AUTHOR]

Motion planning, decision making, and control are vital functions in autonomous driving for accomplishing the desired driving task while considering passenger comfort, road infrastructure, and surrounding traffic participants. Model predictive control (MPC) is a promising method for simultaneously realizing these functions. However, formulating a single MPC that can run through all driving scenarios is difficult, and previous research has often been conducted to design an MPC for a specific driving task. To extend the availability of MPC for all driving tasks, smooth switching between different MPCs designed for each driving task must be addressed. One of the difficulties in switching between MPCs is guiding the state to a feasible set of optimization problems after switching. In this paper, we present a new framework to realize the smooth connection of MPCs, that is, to reduce the optimization infeasibility at the time of MPC switching. In our proposed method, two general nonlinear MPCs with different state spaces, cost functions, constraints, and formulations can be systematically switched via automatically generated intermediate‐MPCs without requiring any particular alterations. This can help reduce the system complexity of the hybrid MPC system. [ABSTRACT FROM AUTHOR]

With the continuous development of automated driving, the path planning algorithm of unmanned vehicles has been continuously innovated. First, some basic concepts of path planning are briefly introduced. Secondly, starting with the classification idea of path planning algorithm based on graph structure and sampling, the paper introduces four typical basic algorithms: Dijkstra algorithm, A* algorithm, PRM algorithm and RRT algorithm. In addition, the Apollo algorithm, which has been studied most at present, is also introduced. The principle and application scenario of each algorithm are summarized. Finally, several new algorithms and their development prospects are introduced. [ABSTRACT FROM AUTHOR]

Policy PointsThe health care sector is increasingly investing in social conditions, including availability of safe, reliable, and adequate transportation, that contribute to improving health.In this paper, we suggest ways to advance the impact of transportation interventions and highlight the limitations of how health services researchers and practitioners currently conceptualize and use transportation.Incorporating a transportation justice framework offers an opportunity to address transportation and mobility needs more comprehensively and equitably within health care research, delivery, and policy. [ABSTRACT FROM AUTHOR]

As human society continues to progress and develop, people's means of transport are becoming more and more advanced and road conditions more and more complex. In the case of complex traffic conditions, the amount of information available to people driving cars in a short period of time is relatively small for the overall traffic system. Based on the development of the Internet of vehicles technology, this paper proposes a method based on the Internet of vehicles system to present the out‐of‐line‐of‐sight traffic information to vehicle drivers by receiving the out‐of‐line‐of‐sight vehicle information from the roadside unit and obtaining the roadside pedestrian information combined with visual perception. Firstly, the roadside unit receives information on all traffic participants in the traffic node, where vehicle information is obtained by connecting the vehicle unit to the roadside unit, and pedestrian and non‐motorised vehicle information is obtained by using an improved target detection algorithm to convert pedestrian and non‐motorised vehicle coordinates into world coordinates using the principle of camera imaging, thus obtaining the location information of pedestrians and non‐motorised vehicles. Then, after obtaining the information of each traffic participant, the vehicle is informed by the roadside unit, and after the position conversion between the roadside unit and the vehicle, the information of the position of each traffic participant in the view of that vehicle is obtained and the road condition is displayed through the display system. [ABSTRACT FROM AUTHOR]

Highly automated vehicles (HAVs) are expected to fundamentally change the on‐road transportation field by increasing traffic flow efficiency, reducing road crashes caused by human errors, and increasing comfort and driving productivity. With the help of recent developments in cognitive management techniques and machine learning analysis, intelligent on‐board computing services are gaining acceptance. The main goal of the present paper is to introduce and develop a novel on‐board cognitive decision‐making functionality that dynamically and automatically enables HAVs to operate each time in the best available level of driving automation (LoDA). The proposed functionality utilizes several attributes associated with the driving environment and the driver's personality characteristics and personal preferences. The cognitive nature of the proposed functionality is based on previous knowledge, turned into experience, by implementing the Naive Bayes classifier supervised machine learning method. The effectiveness of the proposed cognitive functionality, in terms of accuracy and speed of convergence, in proactively identifying the optimal LoDA, is illustrated by modelling and analysing three scenarios with regards to drivers with different profile data and to driving scenes with different environment characteristics. Therefore, it can operate as an in‐car intelligent personal assistant for the drivers. [ABSTRACT FROM AUTHOR]

This paper explores the importance of two forms of interactions, namely marketer–traveler interaction and traveler–traveler interaction in driving destination brand engagement (DBE) dimensions, and their effect on travelers' short‐term and long‐term behavioral intentions based on impulse buying and external search behavior. Using multi‐group analysis, the impact of DBE dimensions on external search behavior and impulse buying across Generation‐Z travelers (aged between 18 and 25) and Generation‐Y travelers (aged between 26 and 40) was also explored. The results provide meaningful implications for tourism marketers to drive relationships between travelers and destinations on digital tourism platforms. [ABSTRACT FROM AUTHOR]

When errors of automated vehicles (AVs) occur, drivers' trust can easily be destroyed, resulting in the reduction of the use of AVs. This study aims to examine how error of AVs declines driver's trust by impacting their subjective perceptions. A driving simulator experiment is conducted, in which 104 participants (male = 58; female = 46) experienced automated driving with automation errors and rated their trust. The results indicate that automation error will affect the driver's perceived predictability, perceived reliability, and perceived safety, which will lead to the decline of trust and abandonment of automated driving. With the occurrence of automation error of AVs, perceived safety plays a more critical role in drivers' trust. In addition, when automation errors occur in specific tasks with low risk, the trust of drivers will drop faster than that in high‐risk tasks. This paper has explored the internal effects of the decline of driver's trust after automation errors of AVs, and further considers the influence of different external risks on these perception factors and trust. This study can help AVs manufacturers to formulate different degrees of trust repair strategies according to different driving tasks and accident severity. [ABSTRACT FROM AUTHOR]

Background The on-the-road driving test in normal traffic is used to examine the impact of drugs on driving performance. This paper compares the sensitivity of standard deviation of lateral position (SDLP) and SD speed in detecting driving impairment. Methods A literature search was conducted to identify studies applying the on-the-road driving test, examining the effects of anxiolytics, antidepressants, antihistamines, and hypnotics. The proportion of comparisons (treatment versus placebo) where a significant impairment was detected with SDLP and SD speed was compared. Results About 40% of 53 relevant papers did not report data on SD speed and/or SDLP. After placebo administration, the correlation between SDLP and SD speed was significant but did not explain much variance ( r = 0.253, p = 0.0001). A significant correlation was found between ΔSDLP and ΔSD speed (treatment-placebo), explaining 48% of variance. When using SDLP as outcome measure, 67 significant treatment-placebo comparisons were found. Only 17 (25.4%) were significant when SD speed was used as outcome measure. Alternatively, for five treatment-placebo comparisons, a significant difference was found for SD speed but not for SDLP. Conclusions Standard deviation of lateral position is a more sensitive outcome measure to detect driving impairment than speed variability. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The high incidence of traffic accidents brings immeasurable losses to life. In order to avoid such crises, researchers and automakers have used many methods to solve this problem. Among them, technology based on visual features is widely used in driver fatigue detection. As fatigue detection plays a vital role in the driving process, the high accuracy of fatigue monitoring is very important. This paper focuses on the method based on convolutional neural network to detect driver fatigue. First, in the face detection part, the Single‐Shot Multi‐Box Detector algorithm is used to improve the speed and accuracy of face detection to extract the eye and mouth regions; second, the VGG16 network is used to learn fatigue features, which is performed on the NTHU‐Drowsy Driver Detection (NTHU‐DDD) data set and the other two modified data sets Training test. The main result of this work is that the accuracy of fatigue monitoring is higher than other methods including the original method, with an accuracy rate of over 90%. And it has better generalization ability than the multi‐physical feature fusion detection method. At the same time, we propose the fatigue detection method based on convolutional neural network to improve the advanced driver assistance system (ADAS) to make it more robust and reliable decision making. [ABSTRACT FROM AUTHOR]

We propose a new digital driving technique using pulse‐density modulation (PDM) with a random dither matrix for evenness of luminance uniformity and higher motion image quality. As a digital driving technique, pulse‐width modulation (PWM) is conventionally used for active‐matrix organic light‐emitting diode (AMOLED) displays in order to improve luminance uniformity. However, in PWM driving, it is difficult to realize high‐frame‐rate driving for improving motion image quality. On the other hand, it is considered that PDM driving method is effective to obtain high motion image quality because of non‐frame‐refreshing property. In the present paper, we proposed a PDM driving technique using a random dither matrix and evaluated the relationship between the display image quality and the driving frequency in the proposed method through simulations. As a result, it is confirmed that good image quality can be obtained by using a blue‐noise mask as a random dither matrix at a practical driving frequency. Moreover, we demonstrated the proposed technique using an actual AMOLED panel. [ABSTRACT FROM AUTHOR]

Background/aim: The assessment of executive functions is an integral component in determining fitness to drive. A structured review was conducted to identify assessment tools used to measure executive function in relation to driving and to describe these tools according to: (i) specific executive function components assessed; (ii) the tool's validity in predicting safe driving; and (iii) clinical utility. Methods: Sixty-nine articles were reviewed, identifying 53 executive function tools/assessments used in driving research. Each tool was critically appraised and the findings were compiled in a Driving Executive Function Tool Guide. Results: Among the 53 tools, there were 27 general assessments of cognition, 19 driving-specific and seven activities of daily living/instrumental activities of daily living assessments. No single tool measured all executive function components: working memory was the most common ( n = 20/53). Several tools demonstrated strong predictive validity and clinical utility. For example, tools, such as the Trail Making Test and the Maze Task, have the shortest administration time (i.e. often less than 10 minutes) and the most easily accessible method of administration (i.e. pen and paper or verbal). Driving-specific tools range from short questionnaires, such as the 10-minute Manchester Driving Behaviour Questionnaire, to more complex tools requiring about 45 minutes to administer. Conclusions and significance of the study: The appropriateness of a tool depends on the individual being assessed and on practical constraints of the clinical context. The Driving Executive Function Tool Guide provides useful information that should facilitate decision-making and selection of appropriate executive function tools in relation to driving. [ABSTRACT FROM AUTHOR]

The control scheme for an electric motor drive is generally implemented by involving proportional‐integral (PI) controllers in current and speed feedback control loops. A good design of PI controller parameters has always been a challenging task for control system design engineers. This paper describes the D‐decomposition method for the design of the parameters of involved DC‐link current and speed PI controllers in closed‐loop scheme of a pulse width‐modulated, current source inverter (CSI)‐fed squirrel‐cage induction motor drive. The PI controllers ensure the stable operation of CSI‐fed induction motor in natural unstable operating region of its torque‐slip characteristic. In order to achieve smoother speed tracking performance with minimum overshoot/undershoot, the damping ratio has been pre‐specified while designing the PI controller parameters using the D‐decomposition method. Simulation results have been presented to confirm the design and have been compared with the results already published. [ABSTRACT FROM AUTHOR]

Autonomous driving decision is a critical component of automatic driving system, which informs and updates the unmanned vehicle of object movements. However, end‐to‐end autonomous driving decision is still a great challenge due to the different scales of traffic target in the wild dynamic traffic scenes. To solve these problems, this paper proposes a novel model with attention mechanism and spatiotemporal features extraction. Specifically, for the important spatial information of traffic targets with scale differences, the spatial dimensions of height H, width W and channel C are independent of each other to build sparse spatial attention map. Moreover, different sparse masks are trained for spatial network by pruning elements of feature maps at the end of each block of backbone, which improves the accuracy of the two subnetworks of spatial network by 2.3% and 3.9%, respectively. Then the extracted spatial information is introduced jointly to the time sequence network with previous speed as input to obtain the vehicle steering angle and speed. Experiments on public virtual datasets show that the prediction accuracy of the model reaches 85.8%. Compared with other state‐of‐the‐art models, our model increased by 4.8% and 2.2%, respectively. [ABSTRACT FROM AUTHOR]

In the field of automatic driving, identifying vehicles and pedestrians is the starting point of other automatic driving techniques. Using the information collected by the camera to detect traffic targets is particularly important. The main bottleneck of traffic object detection is due to the same category of targets, which may have different scales. For example, the pixel‐level of cars may range from 30 to 300 px, which will cause instability of positioning and classification. In this paper, a multi‐dimension feature pyramid is constructed in order to solve the multi‐scale problem. The feature pyramid is built by developing a U‐shaped module and using a cascade‐method. In order to verify the effectiveness of the U‐shaped module, we also designed a new one‐shot detector U‐FPNDet. The model first extracts the basic feature map by using the basic network and constructs the multi‐dimension feature pyramid. Next, a pyramid pooling module is used to get more context information from the scene. Finally, the detection network is run on each level of the pyramid to obtain the final result by NMS. By using this method, a state‐of‐the‐art performance is achieved on both detection and classification on commonly used benchmarks. [ABSTRACT FROM AUTHOR]

Few if any sanctions have been imposed on doctors for inappropriate certification of fitness to drive. This paper reviews a recent Tribunal decision on inappropriate certification of fitness to drive. This paper reviews the facts of the case of Medical Board of Australia v Andrew and discusses the legal implications for doctors who certify patients as fit to drive. The paper offers a necessary and timely warning that the Medical Board sought harsh sanctions, more severe than were imposed by the Tribunal, but that the Tribunal also felt compelled to impose 'general deterrence' to prevent inappropriate certification. The paper emphasises the need for scrupulous attention to detail and an absolute need for circumspection when assessing patients who claim to be seizure free, or who minimise impairment from a range of other conditions, insisting on clearance to be able to drive [ABSTRACT FROM AUTHOR]

Personal transport choices are under increased government scrutiny as private cars are attributed with exacerbating carbon emissions. This paper appraises the value of mobile methodologies for researching transport choices through paying closer attention to life-on-the-move. Drawing on key debates within geography regarding the 'new' mobilities paradigm that challenge ideas which render drivers as lifeless, this paper illustrates the merits and challenges of designing a project that embraced mobile methodologies to explore the unwilled and unforeseen aspects of driving. Examples are drawn from a project conducted in Wollongong, New South Wales, Australia. [ABSTRACT FROM AUTHOR]

In this paper, the literature on aggressive driving tendencies as a consumption experience is reviewed. Two studies test a comprehensive model that includes personality, attitudinal, and value antecedents to such behavior. The research supports the role of most of the antecedents. However, personality and attitudinal constructs were found to be stronger predictors of aggressive driving than values. Furthermore, the paper demonstrates that aggressive driving tendencies increase incidences of law breaking. Suggestions for future research and practical implications are discussed. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

This paper presents a novel switching controller incorporated with backlash and friction compensations, which is utilized to achieve speed synchronization among multi-motor and load position tracking. The proposed controller consists of two parts: synchronization and tracking control in contact mode and robust control in backlash mode, where a function characterizing whether backlash occurs is used for switching between two modes. Using the proposed switching controller, several control objectives are achieved. Firstly, the coupling problem of speed synchronization and load tracking in contact mode is addressed by introducing a switching plane. Secondly, based on the switching plane, an improved prescribed performance function is introduced to attain load tracking with prescribed performances, and L ∞ performance of speed synchronization is guaranteed by initialization method, maintaining the transient performance of synchronization behavior. Thirdly, the lumped uncertain nonlinearity including friction and other uncertain functions is compensated by Chebyshev neural network in contact mode. Furthermore, a robust control is adopted in backlash mode to make system traverse backlash at an exponential rate and simultaneously eliminate low-speed crawling phenomenon of LuGre friction. Finally, comparative simulations on four-motor driving servo system are provided to verify the effectiveness and reliability. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Population ageing will lead to an increase in the number of older drivers. The ageing process can affect older adults' driving ability. Nurses can play a major role in identifying potentially at‐risk drivers and providing guidance about driving safety and cessation, but their role remains somewhat unknown. Objective: This scoping review aims to present the scientific literature in relation to the nursing profession in the field of road safety. Design: CINAHL and PubMed databases were used to identify quantitative, qualitative, mixed methods or clinical practice guideline articles that referred to the role of nurses in older people's road safety and were published in English or French languages between January 1990 and August 2020. Ten (10) articles met the inclusion criteria and were analysed. Results: Analysis of included articles revealed one main theme: Nurses' and NPs' roles in the mobility continuum. Results showed that nurses and nurse practitioners (NPs) often see older drivers in their clinical practice and that they have the competencies to screen and assess their fitness to drive. They are well positioned to discuss age‐related changes, fitness to drive and a driving retirement plan with their older patients, but they are not confident when addressing this issue. Few older adults have discussed their driving abilities with healthcare professionals, but they would be willing to discuss this if the subject were brought up. Conclusions: This scoping review highlighted the paucity of research addressing the role of the nurse in road safety. More research is needed to adequately document this role. [ABSTRACT FROM AUTHOR]

Abstract: Assessing fitness to drive in applicants with a historical or current substance use disorder presents a specific clinical challenge. The Australian guidelines require evidence of remission and absence of cognitive change when considering applications for re‐licensing driver or individuals applying to reengage in safety‐sensitive work. This paper reviews some of the clinical and biochemical indicators that determine whether a particular person is in ‘remission’ and meets the criteria for return to driving or other safety‐sensitive occupation. It provides an overview of the challenges in establishing an evidence‐based approach to determining fitness for safety critical activities. There is no internationally accepted definition of ‘remission’. Review of the literature and examination of assessment protocols from other national jurisdictions are available for alcohol and the more important drugs of interest in road safety. Assessing fitness to drive when there is a history of substance misuse and/or substance use disorders is a complex issue that requires assessment of biomarkers, clinical findings and clinical assessment before the person returns to driving. We propose that hair testing provides a reliable and reproducible way to demonstrate remission and provide cost‐effective monitoring. Standardised psychological tests could provide a reproducible assessment of the cognitive effects of drug use and suitability to resume driving. We recommend that AustRoads amend the national guidelines to reflect an evidence‐based approach to assessing fitness to drive after conviction for offences related to alcohol and drug use. [ABSTRACT FROM AUTHOR]

The paper deals with instructions in a specific instructional setting, in which a driver learns to drive on a race circuit, assisted by a coach helping him to improve his performance and speed. This setting opens up both original issues for the study of learning to drive a car and general issues concerning the praxeological, multimodal, and sequential analysis of instructions in an ethnomethodological and conversation analytic (EMCA) perspective. On the basis of a systematic analysis of the coach's instructions and the driver's responses, the paper reveals the situated methodic production and understanding of these instructions and their organization in sequences and series of sequences. Training to drive at high speed appears as a perspicuous setting for investigating the ecology and the indexicality of instructed action, its temporal features, and the way these feature affect sequentiality—in particular action formation and sequence organization. [ABSTRACT FROM AUTHOR]

Currently, traffic sign recognition techniques have been brought into the assistive driving of automobiles. However, small traffic sign recognition in real scenes is still a challenging task due to the class imbalance issue and the size limit of the traffic signs. To address the above issues, a feature‐enhanced hybrid attention network is proposed based on YOLOv5s for a small, fast, and accurate traffic sign detector. First, a series of online data augmentation strategies are designed in the preprocessing module for the model training. Second, the hybrid channel and spatial attention module CSAM are integrated into the backbone for a better feature extraction ability. Third, the channel attention module CAM is used in the detection head for a more efficient feature fusion ability. To validate the approach, extensive experiments are conducted based on the Tsinghua‐Tencent 100K dataset. It is found that the novel method achieves state‐of‐the‐art performance with only negligible increases in the model parameter and computational overhead. Specifically, the mAP@0.5$mAP@0.5$, parameters, and FLOPs are 85.8%, 7.13 M, and 16.1 G, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a collision warning system that gives a warning to a driver by detecting a hazard during driving. This system has a configuration based on the fail-safe concept that gives a warning to the driver by determining the state of danger when a path that the vehicle cannot safely drive on cannot be found within a certain processing time. Furthermore, it proposes a road extraction VLSI processor for a highly safe vehicle based on the logic-in-memory architecture, which eliminates transfer bottlenecks by integrating the memory and the functional units. This VLSI processor uses a VLSI-oriented algorithm based on regular repetitions of local parallel processing of external three-dimensional coordinate information. A memory system that allows parallel accessing with a minimal amount of hardware is desirable in designing a VLSI processor. For this purpose, optimal memory allocation for parallel accessing designed for minimal memory capacity is important. In order to resolve the problem of increased search space for obtaining optimal allocation in global search, a method of limiting the search space by focusing on the periodicity of the three-dimensional coordinates of the memory module and the data stored in it is proposed. Evaluation of this VLSI processor reveals a significant reduction of the chip area under identical performance conditions. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 87(6): 49–57, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20094 [ABSTRACT FROM AUTHOR]

This paper proposes a personalized output‐feedback path‐following control strategy for automated vehicles. A personalized path generation approach is created to obtain the expected paths of drivers with different driving styles. Historical driving data and road features are used to calculate the waypoints that characterize driving styles. Then, a robust H∞ output‐feedback controller is designed to follow the generated paths. A solution based on matrix partition is provided to compute the output‐feedback control gains without using the vehicle lateral velocity signal, which facilitates the practical implementation of the designed controller. The proposed driving strategy is validated in CarSim® simulations and scaled car experiments. The results show the personalized paths can match with drivers' driving styles and can be tracked by the designed output‐feedback path‐following controller. [ABSTRACT FROM AUTHOR]

There are continuing concerns about the experiences offered to older adolescents being looked after (‘in care’) in the UK and, especially, to care leavers. Questions are asked about the limitations of State care compared with normal family life. This paper reports on an initiative to provide driving lessons to a group of six young men living in residential homes in one city. It links with resilience theory – how individuals can have relatively good outcomes despite early adversity. A qualitative study was undertaken to explore the effects of the initiative, including individual interviews with young men, heads of homes in which they lived and children's services managers. The overall results indicated that the initiative was very worthwhile. The lessons were a significant part of young people's lives. Possible effects on young people were divided into personal, instrumental and social. Benefits were reported from all parties concerning young people's self‐esteem and self‐confidence, as well as in forging close relationships with supportive adults. Driving would not be seen as a panacea for complex personal histories and structural problems, yet this small experiment suggests that driving lessons could be of disproportionate benefit and there is a moral obligation to provide them in any case. [ABSTRACT FROM AUTHOR]

Background: Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low‐ and middle‐income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high‐income countries have successfully reduced RTI by using a public health approach and implementing evidence‐based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high‐income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge. Objectives: The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels. Search Methods: The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019. Selection Criteria: The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post‐crash pre‐hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non‐fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes. Data Collection and Analysis: The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case‐control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2. Main Results: The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post‐crash pre‐hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non‐fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety‐six percent of the studies were reported from high‐income countries (HIC), 4.5% from upper‐middle‐income countries, and only 1.4% from lower‐middle and low‐income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality. Authors' Conclusions: The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence‐synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions. [ABSTRACT FROM AUTHOR]

The significance of occupational choice, in particular those that involve driving, has not yet been studied or investigated in relation to serial murder. This paper, which adopts a case study approach, attempts to shed light on how driving as an occupation may instrumentally influence the offending behaviour of one North American serial murderer-Dennis Rader. Attention is given towards how spending such significant amounts of time driving may have held deep psychological importance for Rader, with regard to the development of his offending-oriented fantasies. In particular, the 'offending space model' is used to examine the relationship between 'thinking and doing'. In providing this micro-level analysis, we suggest that transient oriented occupations provide a rich array of practical advantages that may aid serial murderers in avoiding detection, whilst also holding deep psychological influence in the nurturing and development of their fantasies. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ETRI's Co-Pilot project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the Co-Pilot system; the block is named "Co- Pilot agent" and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive multimodal in-vehicle information system (AMiVIS) for safe driving. The proposed system first filters input information based on the priority and driving situation, to effectively manage input information and then intelligently provide the information to the driver, and then interacts with the driver using an adaptive multimodal interface by considering both driving workload and the driver's cognitive reaction. This system consists of four stages: information-priority determination, driving-situation awareness, optimized-workload based modality selection, and driver's cognitive-reaction based modality-level control. It was shown experimentally that the proposed system can promote driver safety and enhance information understanding by filtering the input information. Also the system can reduce the driving workload by selecting the proper modality and its level. In addition, an analysis of subjective questionnaires regarding the proposed system shows that more than 85% of the respondents were satisfied with it. The proposed system is expected to provide prioritized information through a modality that is very easy to understand. [ABSTRACT FROM AUTHOR]

Numerous scientific studies show that risk factors can interact to synergistically increase the likelihood of certain adverse and life-threatening outcomes. Yet, the extent to which individuals know that specific risk factor combinations present 'synergistic risks' is unclear and little is known about the determinants of such knowledge. This is largely because epistemological progress concerning this topic has been frustrated by a reliance on metrics that have latterly been judged to be of questionable validity. To address this issue, this paper presents two studies that assess an alternative approach (i.e., risk model judgements) which requires respondents to judge the risk for a factor combination relative to, rather than in isolation from, the risk attributable to each constituent factor. Results from both studies indicate that risk model judgements overcome the drawbacks of traditional metrics. More importantly, the results provide epistemological insights into what can determine whether an individual understands that a factor combination presents a synergistic risk; these determinants include experiential and intuitive insights into the effects of combining specific risk factors, domain-specific judgemental experience and exposure to effective learning opportunities. These findings can be utilized in interventions aimed at helping individuals to make better decisions concerning multiple risk factors. [ABSTRACT FROM AUTHOR]

Background The traditional outcome measure of the Dutch on-the-road driving test is the standard deviation of lateral position (SDLP), the weaving of the car. This paper explores whether excursions out-of-lane are a suitable additional outcome measure to index driving impairment. Methods A literature search was conducted to search for driving tests that used both SDLP and excursions out-of-lane as outcome measures. The analyses were limited to studies examining hypnotic drugs because several of these drugs have been shown to produce next-morning sedation. Results Standard deviation of lateral position was more sensitive in demonstrating driving impairment. In fact, solely relying on excursions out-of-lane as outcome measure incorrectly classifies approximately half of impaired drives as unimpaired. The frequency of excursions out-of-lane is determined by the mean lateral position within the right traffic lane. Defining driving impairment as having a ΔSDLP > 2.4 cm, half of the impaired driving tests (51.2%, 43/84) failed to produce excursions out-of-lane. Alternatively, 20.9% of driving tests with ΔSDLP < 2.4 cm (27/129) had at least one excursion out-of-lane. Conclusions Excursions out-of-lane are neither a suitable measure to demonstrate driving impairment nor is this measure sufficiently sensitive to differentiate adequately between differences in magnitude of driving impairment. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

After 9 years, Austroads has published new guidelines for fitness to drive. The guidelines have a preamble, which includes a legal disclaimer denying any culpability for those who designed the guidelines. They also warn of the legal responsibility for health professionals to satisfy their obligations, the need to be current with both relevant medical and legal expectations and if in doubt to seek guidance from Medical Defence Organisations. The guidelines are divided into Parts A and B, with A providing broad overview and background information while B deals with specific entities, such as blackouts, epilepsy or sleep disorders. This paper examines the guidelines and offers an appraisal of their content, their relevance to health practitioners and an assessment of their role in assisting to improve road safety. [ABSTRACT FROM AUTHOR]

Older Australians are increasingly reliant on automobiles as their sole form of transport. As our population is ageing and the prevalence of dementia is increasing, it is anticipated that the number of drivers with dementia will rise over time. Much of the literature relating to driving and dementia focuses on safety rather than mobility. The objective of this paper is to highlight several topical ethical issues that pertain to Australian drivers with dementia. It is recommended that future research, policy and practice should centre on the crucial mobility and transport needs of our senior citizens. [ABSTRACT FROM AUTHOR]

Young novice drivers are significantly more likely to be killed or injured in car crashes than older, experienced drivers. Graduated driver licensing (GDL), which allows the novice to gain driving experience under less-risky circumstances, has resulted in reduced crash incidence; however, the driver's psychological traits are ignored. This paper explores the relationships between gender, age, anxiety, depression, sensitivity to reward and punishment, sensation-seeking propensity, and risky driving. Participants were 761 young drivers aged 17-24 ( M= 19.00, SD= 1.56) with a Provisional (intermediate) driver's licence who completed an online survey comprising socio-demographic questions, the Impulsive Sensation Seeking Scale, Kessler's Psychological Distress Scale, the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, and the Behaviour of Young Novice Drivers Scale. Path analysis revealed depression, reward sensitivity, and sensation-seeking propensity predicted the self-reported risky behaviour of the young novice drivers. Gender was a moderator; and the anxiety level of female drivers also influenced their risky driving. Interventions do not directly consider the role of rewards and sensation seeking, or the young person's mental health. An approach that does take these variables into account may contribute to improved road safety outcomes for both young and older road users. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles (HEVs) provide a promising alternative to conventional engine-powered vehicles, with less emission and better fuel economy. This study proposes a hierarchical control for a power-split HEV over a driving cycle, featuring pre-trip optimisation and en-route speed adaption. Constraints including vehicle powertrain boundaries, road gradients, and speed limits, are taken into consideration. In the first stage, the HEV operating conditions, including the optimal vehicle SOC, speed profiles, and total driving time, are generated for the entire trip before departure. Based on the pre-trip results, the second stage adapts the vehicle speed for a short horizon when driving, while taking the safety spacing to the preceding vehicle into consideration, which acts as an indicator of actual traffic conditions and guarantees safe driving. Both optimisations are conducted under the distance domain for realising localisation in the optimal speed profile due to frequent changes in traffic conditions. An estimation of distribution algorithm is used to run the simulation so that the feasibility, robustness, and effectiveness of the proposed hierarchical control can be demonstrated. [ABSTRACT FROM AUTHOR]

BSTRACT [ABSTRACT FROM AUTHOR]

Issues. Road crashes contribute significantly to the total burden of injury in Australia, with the risk of injury being associated with the presence of drugs and/or alcohol in the driver's blood. Increasingly, some of the most commonly detected drugs include prescription medicines, the most notable of these being benzodiazepines and opioids. However, there is a paucity of experimental research into the effects of prescribed psychoactive drugs on driving behaviours. Approach. This paper provides an overview of experimental studies investigating the effects of prescribed doses of benzodiazepines and opioids on driving ability, and points to future directions for research. Key Findings. There is growing epidemiological evidence linking the therapeutic use of benzodiazepines and opioids to an increased crash risk. However, the current experimental literature remains unclear. Limitations to study methodologies have resulted in inconsistent findings. Implications. Limited experimental evidence exists to inform policy and guidelines regarding fitness-to-drive for patients taking prescribed benzodiazepines and opioids. Conclusion. Further experimental research is required to elucidate the effects of these medications on driving, under varying conditions and in different medical contexts. This will ensure that doctors prescribing benzodiazepines and opioids are well informed, and can appropriately advise patients of the risks associated with driving whilst taking these medications. [Leung SY. Benzodiazepines, opioids and driving: An overview of the experimental research. Drug Alcohol Rev 2011;30:281-286] [ABSTRACT FROM AUTHOR]

This paper presents the development, validation, and deployment of the visual target tracking capability onto the Mars Exploration Rover (MER) mission. Visual target tracking enables targeted driving, in which the rover approaches a designated target in a closed visual feedback loop, increasing the target position accuracy by an order of magnitude and resulting in fewer ground-in-the-loop cycles. As a result of an extensive validation, we developed a reliable normalized cross-correlation visual tracker. To enable tracking with the limited computational resources of a planetary rover, the tracker uses the vehicle motion estimation to scale and roll the template image, compensating for large image changes between rover steps. The validation showed that a designated target can be reliably tracked within several pixels or a few centimeters of accuracy over a 10-m traverse using a rover step size of 10% of the target distance in any direction. It also showed that the target is not required to have conspicuous features and can be selected anywhere on natural rock surfaces excluding rock boundary and shadowed regions. The tracker was successfully executed on the Opportunity rover near Victoria Crater on four distinct runs, including a single-sol instrument placement. We present the flight experiment data of the tracking performance and execution time. © 2009 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The paper assumes that damages in the form of deaths and traumatic injuries caused by alcohol-related road accidents constitute a significant part of the negative externalities associated with alcohol consumption. It then compares the conventional Pigouvian solution with the impact that a sufficiently high penalty on drunken driving and better law enforcement may have. It is hypothesised that these measures may cause heavy drinkers either to cut back on their consumption of alcohol on occasions when they have to drive a vehicle or to maintain their consumption levels but refrain from driving. The welfare losses are much lower for each of these scenarios and are also carried specifically by those responsible for the negative externality. An attempt is also made to consider how individuals may respond to higher penalties and/or a more effective law enforcement system. [ABSTRACT FROM AUTHOR]

As many of the harms associated with drug use may be due to intoxication, particularly where the individual is driving, operating machinery or involved in other tasks requiring high level psycho-motor functioning, it follows that having a valid, reliable convenient measure of recent drug use and, if possible, intoxication, will be important in reducing drug-related harm. Oral fluid testing is the latest technology offering promise in this area. As with any such technology, it has advantages and disadvantages. In this Harm Reduction Digest, Dyer and Wilkinson describe the technology, its strengths and limitations and provide examples of where it is currently being employed in practice. This is a must read paper for those of us interested in reducing drug-related harm. Simon Lenton Editor, Harm Reduction Digest [ABSTRACT FROM AUTHOR]

Introduction: Austroads Guidelines for fitness to drive were promulgated in 2003. Epilepsy was one of the conditions included and this paper reports results of a survey of Australian neurologists regarding opinions and practices relevant to the guidelines. Methods: The survey was developed, piloted and Human Research Ethics Committee approved. Members of the Australian Association of Neurologists received three mailings and results were analysed. Results: Almost 70% of 236 surveyed indicated assessment of epilepsy and driving with <9% not doing so – establishing ∼77% response for eligible neurologists. Most questions achieved 90% response. Almost 90% respondents assessed epilepsy and 70% found the guidelines helpful. Seventy-seven per cent endorsed doctor assessors although half discounted General Practitioners as insufficiently knowledgeable and half advocated that only neurologists evaluate potential drivers with epilepsy. Most respondents supported reporting recalcitrant patients; yet only <30% did so. Three-quarters favoured licences carrying a warning to self-report and two-thirds felt that product information should identify driving implications. Although many questions attracted expected responses, the surprise was the large undecided numbers, which were greater than expected. Neurologists were more lenient than prescribed by the guidelines with neither consensus for controlled epilepsy nor mandatory driving restrictions. Conclusion: Respondents supplied predictable answers regarding ideal circumstances; yet most did not report recalcitrant patients. Most claimed to adhere to the guidelines and yet advocated more lenient driving restrictions that may allow preventable accidents. There was agreement between neurologists and guidelines for more rigourous restrictions for commercial drivers although again neurologists were more lenient. There is need for prospective research on epilepsy and driving. [ABSTRACT FROM AUTHOR]

This paper introduces an experimental multitechnique method which was developed to establish a basis for a task performance-based mesopic photometry. This approach considers night-time driving by dividing visual performance into three visual tasks, of which achromatic threshold and reaction time are presented. The performance of both visual tasks decreased with decreasing luminance level from 1 to 0.01 cd m−2, showing the strong effect of light level on visual performance in driving. The behaviour of the achromatic contrast threshold and reaction time for low-contrast targets was similar in terms of spectral effects, the strongest effects occurring at the lower mesopic levels. Both measures showed the Purkinje shift with decreasing luminance levels. The experimental data were used to calculate mesopic performance measures with the new mesopic model. The results imply that compared with V( λ), spectral sensitivity in night-time driving can be better described with a mesopic model based on visual performance measures. [ABSTRACT FROM AUTHOR]

In ITS, there has recently been emphasis on the importance of developing a driving assistance system which can detect pedestrians with a car-mounted camera and warn of their presence in order to assure pedestrian safety. In particular, the ability to detect multiple pedestrians in real time (at a video rate of 30 fps) is indispensable from the practical point of view. Consequently, this study proposes a method of recognizing multiple moving objects (pedestrians) in real time using dynamic scene input from a car-mounted camera, as a basic technology for the driving assistance system. The presence of a pedestrian is evaluated on the basis of hue information in the HSI color representation system and model-based matching using a circular approximation model. Thus, in terms of the evaluation function, the problem of recognition of multiple pedestrians is replaced by the problem of search for multiple local maxima. However, it is difficult to realize the process in real time if the evaluation value is calculated for the whole image. This paper considers the “attention,” which is a function that reduces the burden of human visual information processing, and proposes a method in which a pseudo-attention function is realized by using a hybrid GA, allowing multiple local maxima to be retrieved efficiently in real time. A real-time experiment on the recognition of multiple pedestrians in dynamic images obtained from a car-mounted camera was used to verify the effectiveness of the proposed method. In addition, the practical performance of the system was investigated by an experiment on the recognition of suddenly appearing pedestrians. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(4): 21–33, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20181 [ABSTRACT FROM AUTHOR]