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Traffic calming devices (TCD) like speed bumps are effective measures in reducing speed on residential roads but in a limited section of the road. Previous studies found that if the entrance speed of the traffic calming road (TCR) is higher than the posted speed limit (30 kmph), it will affect speed reduction by TCD. Little research has been undertaken on predicting speed at the entrance of a TCR. Thus, the purpose of this study is to predict the variables of interest in the context of the study area by applying a methodological approach described in this study; a combination of multiple linear regression, and artificial neural networking (ANN) models. Seventeen variables derived from four categories including road design, roadside environment, traffic, and speed were considered in the proposed model. Two approaching criterion was defined in this study: a minor (speed limit 30 km/h) and a major approach (speed limit 40/50 km/h). Over 1000 vehicle speeds were collected from almost 20 different urban roads in Japan. Entrance characteristics, lane width, barrier types, posted speed limit, etc. have found as significant predictors in the regression output. Furthermore, the ANN technique was employed where the input variables were the significant predictors of regression models, and variable importance was also calculated using sensitivity analysis. Although the results of sensitivity and regression are different, sensitivity plays a role in illuminating the relationship between road factors and speed. By comparing the prediction performance between the two models this study reveals that developing an ANN model followed by regression output could be a consistent method for analyzing the entry speed of TCR for varying approaches. Additionally, the findings can be used to effectively predict the entry speed of TCR without installing a gateway design and help to achieve a safer speed through modifications to the road features. [ABSTRACT FROM AUTHOR]

The impacts of raising speed limits on traffic safety is an area that has generated much research, although a strong consensus has not emerged on the relationship between speed and safety. The Ohio legislature raised speed limits from 65 mi/h to 70 mi/h on 570 miles of rural freeways in Ohio on July 1, 2013 and an additional 398 miles of rural freeways starting on September 29, 2013. The primary goal of the current study was to investigate the safety impacts of this new speed limit using available crash, roadway, and traffic characteristics data. Statewide crash data from January 1, 2010 to December 31, 2015 were obtained from the Highway Safety Information System (HSIS). The study utilized the empirical Bayes (EB) before-after study in the evaluation of the safety effectiveness of the raised speed limit. The intent of the before-after study was to estimate the performance (in terms of crash frequency and severity levels) following the speed limit increase and what the safety performance would have been if there was no increase in speed limit. Safety performance functions (SPFs) were developed for both total crashes and fatal and injury (FI) crashes combined using the negative binomial regression and the SPFs were used to predict the average crash frequency of each of the segments in the observed period. The EB analysis showed that total crashes went down by 24.6% and FI crashes went down by 8.8% for the two years after the speed limit was changed. Therefore, caution should be taken in drawing conclusion from this study because the after period did not meet the minimum of three years recommended by the HSM since the data available for the after period were only for two years. We have received additional 2 years of data and the updated analysis is ongoing. [ABSTRACT FROM AUTHOR]

This paper presents a traffic volume prediction method for global vehicle path planning at freeway entrances and exits. Firstly, a "point-line" vehicle path planning model was established, and the vehicle driving data was obtained by combining CCD sensor camera. Secondly, the weight of holidays in traffic volume prediction is analyzed from time Angle. The weight and speed in traffic volume prediction are analyzed from the perspective of space, and the weight of vehicle state index is calculated by using adaptive weighted data fusion algorithm. Finally, the traffic volume prediction algorithm is designed to realize the traffic volume prediction of vehicle global path planning. The results show that in the long-term traffic volume forecast results through this method, the Japanese and RMSE are stable at 5.44 and 9.06 respectively and the difference between the daily traffic volume forecast results and the actual results is in 10, which is obviously higher than the comparison method with high accuracy. [ABSTRACT FROM AUTHOR]

Due to the traditional method in the analysis of traffic flow stability, there is no analysis of the influence factors, resulting in the analysis results are not reliable, and cannot accurately analyze the traffic flow in different periods. Therefore, this paper proposes a new type of intelligent network connected vehicle hybrid traffic flow progressive stability analysis method. This method establishes a basic graph model of mixed traffic flow, and analyzes the relationship between traffic flow density, flow and speed through this model. Establish a car-following model to reflect the relationship between the traffic flow and the speed difference, vehicle speed, and headway distance of hybrid intelligent networked vehicles and manually driven vehicles. According to the analysis results, the vehicle collision index, vehicle collision time and vehicle speed dispersion are selected as indicators to analyze the factors affecting the stability of traffic flow, and complete the progressive stability analysis of the mixed traffic flow of intelligent networked vehicles. The results show that the analysis results of this method are highly reliable and can accurately analyze the traffic flow in different periods. [ABSTRACT FROM AUTHOR]

Traffic speed prediction plays a vital role in the intelligent monitoring and scheduling of urban traffic. The urban traffic status is affected by a variety of complex factors, considering multiple features to improve the performance of speed prediction model is an urgent problem to be solved. This paper establishes a multisource feature bidirectional long short-term memory (MF-BiLSTM) framework, which considers the influence of weather, air quality and temporal attribute on the traffic state. The bidirectional network structure captures the characteristics in both forward and backward periods, thus effectively capturing the influence of meteorological factors, environmental changes and time-related characteristics on the operation state of urban traffic. On the above model, experiments are conducted on a time-series dataset of the road speed in Chengdu, which is computed based on the DidiChuxing open-source algorithm. Five baselines of the recurrent neural network (RNN), autoregressive integrated moving average (ARIMA), convolutional neural network (CNN), stacked long short-term memory (LSTM) model and single LSTM model are executed for validation. The results indicate that MF-BiLSTM outperforms the above baselines with MAPE improving by 2.94%, 1.02%, 2.45%, 1.10%, 1.67%, respectively, and exhibiting a higher stability under different road grades. In addition, at different weather and air quality levels, MF-BiLSTM exhibits a more accurate and smoother prediction performance. An intelligent traffic prediction system was developed and open source based on MF-BiLSTM, which facilitates the visualization of prediction results. [ABSTRACT FROM AUTHOR]

Road traffic is an important factor restricting economic development. With the rapid growth of the number of motor vehicles, traffic accidents, traffic congestion and traffic pollution have become the persistent diseases of contemporary society, and become more and more serious. The existing traffic accident analysis is difficult to comprehensively and objectively reflect the process of traffic accidents. In order to improve the effectiveness of traffic accident prevention and measures, it is particularly important to carry out road traffic accident analysis. The paper proposes a new method for modeling the relationship between vehicle speed dispersion and traffic accidents in mixed traffic flow. Simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Highway traffic safety management is an essential part of the highway operation management system. It plays a vital role in ensuring highway traffic safety and clear roads. In this paper, an accurate real-time positioning and monitoring algorithm based on RFID vehicle flow speeding automatic monitoring. The highway speed measurement system is used to collect the data on the traffic flow and speed of vehicles passing Shanfen highway monitoring point. Through statistical analysis of sample data in the traffic database, the changes in the average speed, speeding volume and rate in this section before and after the enforcement of illegal speeding vehicles were compared and analyzed by the speed measurement system. The positioning and real-time monitoring were completed by extracting the feature information of the visual perception images in the positioning and real-time monitoring range based on the visual perception technology. The inertial information is combined to perform unscented Kalman filtering to improve the accuracy further. Based on the simulation results, the impact of the detection line setting on the detection accuracy is analyzed, the detection and discrimination process of the detection algorithm is described, the theoretical calculation of the maximum detection speed is conducted, and the rapid recovery technology research on the false detection is performed. [ABSTRACT FROM AUTHOR]

In order to overcome the problems of large total vehicle delay and high average absolute error in the process of travel path dynamic planning, this paper proposes a new dynamic planning method of transportation travel path based on Internet of vehicles technology. This method is based on the RFID technology of Internet of vehicles, which makes the electronic tag on the vehicle connect with the traffic network platform to determine the specific position, speed and driving status of the vehicle, so as to identify the behavior track of the vehicle. The vehicle target image is enhanced to estimate the real-time average traffic flow speed of the vehicle driving section. The shortest path of the vehicle driving process is taken as the value function, and the related road path distance is used to complete the dynamic planning of the traffic travel path. The experimental results show that the average total delay of fixed cycle vehicles is 4.604s, which can improve the control effect of traffic lights. The average absolute error value is far less than the existing three methods, and the minimum value can reach 8.13. The predicted value of traffic flow is close to the actual value. [ABSTRACT FROM AUTHOR]

Interchanges are constructed in urban and suburban areas to ease traffic operation. Outer connection ramps constitute a major part of interchanges planning and design. The objective of this study was to estimate interchange ramp capacity and investigate the impacts of ramp geometry on the obtained capacity. To achieve this objective, 20 ramps were selected, including 10 circular ramps and 10 curve-straight-curve ramps. Capacity of ramp proper and ramp exit were investigated in the study. At ramp proper, data on traffic speed and traffic flow were collected at 1 -minute intervals using video camera. Also, traffic data for ramp exit and mainline traffic were obtained under queued traffic condition on the ramp exit. An empirical approach using regression analysis was adopted to estimate capacity of the selected ramps and explore the impact of geometric design and traffic variables that might affect the estimated capacity. For ramp proper, the analyses revealed that the relationship between traffic speed and density is linear and between speed and traffic flow is parabolic irrespective of ramp configuration. For circular ramps, the capacity was found to vary from 1470 to about 2100 pc/hr./lane, and it was found that ramp radius is the most influencing factor in capacity estimation. For curve-straight-curve ramps, the results indicated that the obtained capacity varied from 1490 to 2200 pc/hr./lane, and both the straight segment length and the radius of the first curve are the most influencing factors. Also, it was found that ramp exit capacity is affected by flow and speed of traffic in the mainline street and degree of curvature of ramp exit curve. Finally, it was concluded that the use of curves with large radii at ramp proper and exit would increase ramp capacity, and customization of capacity values to reflect local conditions would provide more realistic estimates. [ABSTRACT FROM AUTHOR]

Measures of traffic organization and traffic management in school zones, key protection areas for traffic safety, have been increasingly discussed by government administrations at all levels and researchers as well. Juveniles' trips occur frequently near school areas, especially in primary and secondary school zones. The sensitive topic of these vulnerable road users encountering traffic accidents tends to draw the whole society's attention. In this regard, the paper analyzed different traffic characteristics of 20 primary school zones in Beijing. With the starting point of traffic safety in the area, the paper divided these school zones by type, which was then verified preliminarily reliable and proper, by means of field measurement and driving simulation test, with speed characteristics as the major basis for judgment. By doing this, the authors look forward to providing a theoretical basis for carrying out measures of traffic organization and traffic management. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency and safety of urban expressway, the macroscopic dynamic traffic flow model is extended using speed guidance control. Speed guidance as control variable was introduced into the urban expressway control system, and the macroscopic dynamic traffic flow model was established. Model predictive control is presented to calculate the optimal speed guidance under the objective function of total travel time and changes of speed guidance. Speed guidance control of urban expressway was designed and optimized. Simulation analysis is carried out in simulation platform based on the case of mutations traffic in the downstream. The results show that the speed guidance under safety constraints has a good control effect to smooth traffic flow, alleviate traffic congestion and improve traffic safety which can be applied in practice to provide a theoretical basis for active traffic management [ABSTRACT FROM AUTHOR]

To improve design consistency of existing and new roads, several studies developed operating speed prediction models and investigated drivers' speed behaviour. Most of the existing models are based on spot speed data assuming constant operating speed throughout the horizontal curves and occurrence of acceleration and deceleration only on tangents. To overcome limitations associated with these hypotheses, this study investigated continuous speed profiles of individual drivers by a driving simulator experiment carried out on a two-lane rural highway using the VERA high-fidelity dynamic-driving simulator, operating at the Road Safety Laboratory of University of Naples Federico II (Italy). The experimental route consisted of the succession of 20 tangents with length equal to 1,000 m and curves with radius equal to 400 m. The tangent-to-curve transition was carried out by spiral curves with parameter equal to 150 m and length equal to 55 m. Study results show that speed is not constant along the curve and deceleration rates are considerably higher than acceleration rates. These findings question the traditional hypotheses used to develop operating speed profiles. The analysis of individual drivers' behaviour showed that: (a) 85th percentile of the speed reduction experienced by individual drivers is more than twice as the operating speed difference in the tangent-to-curve transition, and (b) deceleration and acceleration rates experienced by the individual drivers are approximately double than deceleration and acceleration rates used to draw the operating speed profiles. Study results emphasize that the analysis of the individual speed profiles adds important information to the analysis of the operating speed profile and has the potential to identify supplementary design inconsistencies and safety issues. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to examine the influence of road alignment on vehicle operating speed. The authors propose and validate a new operating speed model in which the geometric features of an alignment and the lengths of its elements (curve, tangent) are considered. The results demonstrate that grade, radius, and length affect driver perception and operating speeds and are relevant to safety analysis methods. In contrast, the geometric features of previous and oncoming elements, although essential for an accurate analysis of the single locations and sections, had a negligible statistical influence on operating speed. The paper provides a set of analytical tools for predicting driver behaviour and speed in a given section based on the alignment features (previous and oncoming elements included). Furthermore, a framework for ranking and screening the factors that affect speed profiles is presented. Finally, the model can be used in safety evaluation of horizontal curves and tangents on rural undivided roads. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine how comparable driving performance on a 'Low-Cost Desktop' single screen driving simulator and a 'Mid-level' fixed-base driving simulator (STISIM, Systems Technology Inc.) is. Fifty-two participants completed a 12 km virtual driving course on each simulator with at least 14 days separating both sessions. Driving performance was assessed using overall driving errors recorded by the simulator and through an observer-based demerit point scoring system. Speed and lane deviation parameters were used as local indicators of driving responses. Moderate to high correlations between the two platforms indicated that participants reacted similarly on both platforms. Our findings suggest that the two platforms yielded comparable data and that the 'Low-Cost Desktop' simulators could be used as a reliable replacement option to 'Mid-Level' driving simulators. [ABSTRACT FROM AUTHOR]

Actively commuting to school gives children the opportunity to explore nature, get exercise, and develop cognitive skills. Today though, few children in the United States (US) are able or given the opportunity to travel to and from school by their own power. Although walking or biking to school was customary 30 years ago, many of today's children are driven to school regardless of the distance. Understanding the barriers that prevent parents from allowing their children to commute to school actively is the first step in encouraging more children to travel by their own power. This study looked at the barriers parents of school children in Illinois, US, reported in the National Safe Routes to School Parent Surveys. The findings indicated that the top barriers for urban and suburban children both included intersection safety and traffic speed/volume, however; distance from school affected suburban students more than urban students. Analysis of parent responses revealed the strongest correlation between speed and volume barriers (r=0.48). With these barriers identified, the Safe Routes to School Programs in Illinois can target their resources effectively to encourage children and their parents to consider walking and biking alternatives for trips to and from school. [ABSTRACT FROM AUTHOR]