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The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 86571

Special Issue Editors

Dr. Feng Chen

E-Mail Website
Guest Editor
Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC, College of Transportation Engineering, Tongji University, Shanghai 1239, China
Interests: transportation safety, aviation meteorology; civil aviation safety; statistical modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Kun Xie

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Old Dominion University, Norfolk, VA 23529, USA
Interests: transportation safety; connected and autonomous vehicles; big data analytics, statistics and machine learning; resilience in multimodal transportation systems
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaoxiang Ma

E-Mail Website
Guest Editor
School of Transportation and Logistics, Southwest University, 611756 Chengdu, China
Interests: accident data mining and modeling; human factors and driving behavior

Special Issue Information

Dear Colleagues,

Metropolitan areas face serious traffic-related problems. Road traffic accidents cause a large number of deaths and disabilities every day. Moreover, traffic congestion has been increasingly severe around the world, causing enormous pollutant emissions to degrade air quality. Both traffic accidents and vehicle pollutions have become major public health issues. The recent development of new technologies such as big data, automated driving, and connected vehicle and cooperative vehicle infrastructure systems show great potential to enhance traffic safety and mitigate traffic congestion. By harnessing the power of these emerging technologies, a better understanding of data-driven traffic systems can be achieved, which is of practical importance to traffic safety and traffic operation.

This Special Issue aims to report on recent advances in interdisciplinary research related to understanding associated risks and the improvement of traffic safety and environment problems in transportation networks around the world. It is open to any subject area of the related theme, and research articles encompassing multiple fields, such as big data, ITS, automated driving, connected vehicle, cooperative vehicle infrastructure systems, etc., are particularly welcome. The International Journal of Environmental Research and Public Health is indexed by SCI-E, PubMed, and other databases.

Fourteen papers were published in the first edition of this Special Issue, which have attracted a lot of interest since their publication, including some that were ESI hot papers or highly cited papers. The website of the 1st edition is https://www.mdpi.com/journal/ijerph/special_issues/Traffic_Safety.

Dr. Feng Chen
Dr. Kun Xie
Dr. Xiaoxiang Ma
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data and traffic safety
  • big data and traffic environment
  • intelligent transportation and traffic safety
  • intelligent transportation and traffic environment
  • automatic driving
  • cooperative vehicle infrastructure system
  • connected car

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Related Special Issue

Published Papers (33 papers)

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Research

13 pages, 2447 KiB  
Article
A Recognition Method of Truck Drivers’ Braking Patterns Based on FCM-LDA2vec
by Jianfeng Xi, Yunhe Zhao, Zhiqiang Li, Yizhou Jiang, Wenwen Feng and Tongqiang Ding
Int. J. Environ. Res. Public Health 2022, 19(23), 15959; https://doi.org/10.3390/ijerph192315959 - 30 Nov 2022
Cited by 1 | Viewed by 1391
Abstract
Taking truck drivers’ braking patterns as the research objects, this study used a large amount of truck running data. A recognition method of truck drivers’ braking patterns was proposed to determine the distribution of braking patterns during the operation of trucks. First, the [...] Read more.
Taking truck drivers’ braking patterns as the research objects, this study used a large amount of truck running data. A recognition method of truck drivers’ braking patterns was proposed to determine the distribution of braking patterns during the operation of trucks. First, the segmented data of braking behaviors were collected in order to extract 25 characteristic parameters. Additionally, seven main correlation factors were obtained by dimensionality reduction. The FCM clustering algorithm and CH scores were used to identify nine categories of truck drivers’ braking behaviors. Then the LDA2vec model was used to identify the distribution of different braking behavior words in braking patterns, and three categories of truck drivers’ braking patterns were identified. The test results showed that the accuracy of the truck drivers’ braking pattern recognition model based on LDA2vec was higher than 85%, and braking patterns of drivers in the daily operation process could be mined from vehicle operation data. Furthermore, through the monitoring and pre-warning of the braking patterns and targeted training of drivers, traffic accidents could be avoided. At the same time, this paper’s results can be used to protect human life and health and reduce environmental pollution caused by traffic congestion or traffic accidents. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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17 pages, 3341 KiB  
Article
Examining the Effects of Visibility and Time Headway on the Takeover Risk during Conditionally Automated Driving
by Haorong Peng, Feng Chen and Peiyan Chen
Int. J. Environ. Res. Public Health 2022, 19(21), 13904; https://doi.org/10.3390/ijerph192113904 - 26 Oct 2022
Cited by 2 | Viewed by 1527
Abstract
The objective of this study is to examine the effects of visibility and time headway on the takeover performance in L3 automated driving. Both non-critical and critical driving scenarios were considered by changing the acceleration value of the leading vehicle. A driving simulator [...] Read more.
The objective of this study is to examine the effects of visibility and time headway on the takeover performance in L3 automated driving. Both non-critical and critical driving scenarios were considered by changing the acceleration value of the leading vehicle. A driving simulator experiment with 18 driving scenarios was conducted and 30 participants complete the experiment. Based on the data obtained from the experiment, the takeover reaction time, takeover control time, and takeover responses were analyzed. The minimum Time-To-Collision (Min TTC) was used to measure the takeover risk level and a binary logit model for takeover risk levels was estimated. The results indicate that the visibility distance (VD) has no significant effects on the takeover control time, while the time headway (THW) and the acceleration of the leading vehicle (ALV) could affect the takeover control time significantly; most of the participants would push the gas pedal to accelerate the ego vehicle as the takeover response under non-critical scenarios, while braking was the dominant takeover response for participants in critical driving scenarios; decreasing the TCT and taking the appropriate takeover response would reduce the takeover risk significantly, so it is suggested that the automation system should provide the driver with the urgency of the situation ahead and the tips for takeover responses by audio prompts or the head-up display. This study is expected to facilitate the overall understanding of the effects of visibility and time headway on the takeover performance in conditionally automated driving. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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21 pages, 7492 KiB  
Article
Analysis of Car-Following Behaviors under Different Conditions on the Entrance Section of Cross-River and Cross-Sea Tunnels: A Case Study of Shanghai Yangtze River Tunnel
by Ting Zhang, Feng Chen, Yadi Huang, Mingtao Song and Xiao Hu
Int. J. Environ. Res. Public Health 2022, 19(19), 11975; https://doi.org/10.3390/ijerph191911975 - 22 Sep 2022
Cited by 4 | Viewed by 1549
Abstract
Compared to highway road tunnels, the entrance section of cross-river and cross-sea tunnels feature long and steep slopes. Along with a complicated traffic environment and harmful weather conditions, traffic congestion and rear-end crashes occur frequently during car-following in cross-river and cross-sea tunnels. It [...] Read more.
Compared to highway road tunnels, the entrance section of cross-river and cross-sea tunnels feature long and steep slopes. Along with a complicated traffic environment and harmful weather conditions, traffic congestion and rear-end crashes occur frequently during car-following in cross-river and cross-sea tunnels. It is necessary to examine the impact of traffic flow and weather conditions on car-following behavior at the entrance section of cross-river and cross-sea tunnels. To this end, this paper first extracted the vehicle speed data based surveillance video at the entrance of the Shanghai Yangtze River Tunnel. Moreover, the actual average speed under different traffic flow conditions was obtained through the clustering algorithm, which was used as the basis for setting the experimental parameters. Then, in the driving simulation experiment, three traffic flow conditions (free flow, congested flow, and jam flow) were set up in three weather conditions (sunny, rainy, and snowy), and a risk situation was set up in each condition. Distance headway, time headway, acceleration, lateral offset, and driver’s emergency response time were collected. Moreover, seven slopes of 2% to 5% were set, and the relationship of slope on longitudinal speed and lateral offset was analyzed. ANOVA and post-hoc analyses were applied. The result indicates that traffic flow conditions have a significant effect on the car-following behavior, while weather conditions mainly influence the time headway. Moreover, drivers tend to adopt more cautious driving behavior as the distance between the vehicle and the tunnel entrance decreases. The results also show that the slope of the cross-river and cross-sea tunnel entrance section has a major influence on vehicle speed. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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23 pages, 12137 KiB  
Article
Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety
by Lei Han, Zhigang Du, Shoushuo Wang and Ying Chen
Int. J. Environ. Res. Public Health 2022, 19(16), 10349; https://doi.org/10.3390/ijerph191610349 - 19 Aug 2022
Cited by 17 | Viewed by 2393
Abstract
To study the influence of traffic signs information volume (TSIV) on drivers’ visual characteristics and driving safety, the simulation scenarios of different levels of TSIV were established, and 30 participants were recruited for simulated driving tests. The eye tracker was used to collect [...] Read more.
To study the influence of traffic signs information volume (TSIV) on drivers’ visual characteristics and driving safety, the simulation scenarios of different levels of TSIV were established, and 30 participants were recruited for simulated driving tests. The eye tracker was used to collect eye movement data under three-speed conditions (60 km/h, 80 km/h, and 100 km/h) and different levels of TSIV (0 bits/km, 10 bits/km, 20 bits/km, 30 bits/km, 40 bits/km, and 50 bits/km). Principal component analysis (PCA) was used to select indicators sensitive to the influence of TSIV on the drivers’ visual behavior and to analyze the influence of TSIV on the drivers’ visual characteristics and visual workload intensity under different speed conditions. The results show that the fixation duration, saccade duration, and saccade amplitude are the three eye movement indicators that are most responsive to changes in the TSIV. The driver’s visual characteristics perform best at the S3 TSIV level (30 bits/km), with the lowest visual workload intensity, indicating that drivers have the lowest psychological stress and lower driving workload when driving under this TSIV condition. Therefore, a density of 30 bits/km is suggested for the TSIV, in order to ensure the security and comfort of the drivers. The theoretical underpinnings for placing and optimizing traffic signs will be provided by this work. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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19 pages, 3674 KiB  
Article
The Analysis of Classification and Spatiotemporal Distribution Characteristics of Ride-Hailing Driver’s Driving Style: A Case Study in China
by Runkun Liu, Haiyang Yu, Yilong Ren and Shuai Liu
Int. J. Environ. Res. Public Health 2022, 19(15), 9734; https://doi.org/10.3390/ijerph19159734 - 7 Aug 2022
Cited by 1 | Viewed by 2039
Abstract
Monitoring the driving styles of ride-hailing drivers is helpful for providing targeted training for drivers and improving the safety of the service. However, previous studies have lacked analyses of the temporal variation as well as spatial variation characteristics of driving styles. Understanding the [...] Read more.
Monitoring the driving styles of ride-hailing drivers is helpful for providing targeted training for drivers and improving the safety of the service. However, previous studies have lacked analyses of the temporal variation as well as spatial variation characteristics of driving styles. Understanding the variations can also help authorities formulate driver management policies. In this study, trajectory data are used to analyze driving styles in various temporal and spatial scenarios involving 34,167 drivers. The k-means method is used to cluster sample drivers. In terms of driving style time-varying, we found that only 31.79% of drivers could maintain a stable driving style throughout the day. Spatially, we divided the research area into two parts, namely, road segments and intersections, to analyze the spatial driving characteristics of drivers with different styles. The speed distribution, the acceleration and deceleration distributions are analyzed, results indicated that aggressive drivers display more aggressive driving styles in road segments, and conservative drivers exhibit more conservative driving styles at intersections. The findings of this study provide an understanding of temporal and spatial driving behavior factors for ride-hailing drivers and offer valuable contributions to ride-hailing driver training and road safety management. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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14 pages, 2318 KiB  
Article
Characterization of Pedestrian Crossing Spatial Violations and Safety Impact Analysis in Advance Right-Turn Lane
by Ziyu Chen, Xiufeng Chen, Ruicong Wang and Mengyuan Gao
Int. J. Environ. Res. Public Health 2022, 19(15), 9134; https://doi.org/10.3390/ijerph19159134 - 26 Jul 2022
Cited by 2 | Viewed by 1983
Abstract
In view of the pedestrian space violation in an advance right-turn lane, the pedestrian crossing paths are divided by collecting the temporal and spatial information of pedestrians and motor vehicles, and the characteristics of different pedestrian crossing behaviors are studied. Combined with the [...] Read more.
In view of the pedestrian space violation in an advance right-turn lane, the pedestrian crossing paths are divided by collecting the temporal and spatial information of pedestrians and motor vehicles, and the characteristics of different pedestrian crossing behaviors are studied. Combined with the time and speed indicators of conflict severity, the K-means method is used to divide the level of conflict severity. A multivariate ordered logistic regression model of the severity of pedestrian–vehicle conflict was constructed to quantify the effects of different factors on the severity of the pedestrian–vehicle conflict. The study of 1388 pedestrians and the resulting pedestrian–vehicle conflicts found that the type of spatial violation has a significant impact on pedestrian crossing behavior and safety. The average crossing speed and acceleration variation values of spatially violated pedestrians were significantly higher than those of other pedestrians; there is a significant increase in the severity of pedestrian–vehicle conflicts in areas close to the oncoming traffic; the average percentage of pedestrian–vehicle conflicts due to spatial violations increased by 12%, and the percentage of serious conflicts due to each type of spatial violation increased from 18% to 87%, 74%, 30%, and 63%, respectively, compared with those of non-violated pedestrians. In addition, the decrease in the number of lanes and the increase in speed and vehicle reach all lead to an increase in the severity of pedestrian–vehicle conflicts. The results of the study will help traffic authorities to take measures to ensure pedestrian crossing safety. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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11 pages, 357 KiB  
Article
Exploring Influential Factors Affecting the Severity of Urban Expressway Collisions: A Study Based on Collision Data
by Kun Wang, Xiaoyuan Feng, Hongbo Li and Yilong Ren
Int. J. Environ. Res. Public Health 2022, 19(14), 8362; https://doi.org/10.3390/ijerph19148362 - 8 Jul 2022
Cited by 6 | Viewed by 1919
Abstract
When traffic collisions occur on urban expressways, the consequences, including injuries, the loss of lives, and damage to properties, are more serious. However, the existing research on the severity of expressway traffic collisions has not been deeply explored. The purpose of this research [...] Read more.
When traffic collisions occur on urban expressways, the consequences, including injuries, the loss of lives, and damage to properties, are more serious. However, the existing research on the severity of expressway traffic collisions has not been deeply explored. The purpose of this research was to investigate how various factors affect the severity of urban expressway collisions. The severity of urban expressway collisions was set as the dependent variable, which could be divided into three categories: slight collisions, severe collisions, and fatal collisions. Ten variables, including individual characteristics, collision characteristics, and road environment conditions, were selected as independent factors. Based on 975 valid urban expressway collisions, an ordered logistic regression model was established to evaluate the impacts of influence factors on the severity of these crashes. The results show that gender, collision modality, road pavement conditions, road surface conditions, and visibility are significant factors that affect the severity of urban expressway collisions. Females were more likely to be involved in more severe urban expressway collisions than males. For collisions involving pedestrians and non-motorized vehicles, the risk of more severe injury was 7.508 times higher than that associated with vehicle–vehicle collisions. The probability of more severe collisions on urban expressways with poor pavement conditions and wet surface conditions is greater than that on urban expressways with good pavement conditions and dry surface conditions. In addition, as visibility increases, the probability of more severe collisions on urban expressways gradually decreases. These results provide more effective strategies to reduce casualties as a result of urban expressway collisions. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
17 pages, 37593 KiB  
Article
How Effective Is a Traffic Control Policy in Blocking the Spread of COVID-19? A Case Study of Changsha, China
by Wang Xiang, Li Chen, Qunjie Peng, Bing Wang and Xiaobing Liu
Int. J. Environ. Res. Public Health 2022, 19(13), 7884; https://doi.org/10.3390/ijerph19137884 - 27 Jun 2022
Cited by 6 | Viewed by 1774
Abstract
(1) Background: COVID-19 is still affecting people’s daily lives. In the past two years of epidemic control, a traffic control policy has been an important way to block the spread of the epidemic. (2) Objectives: To delve into the blocking effects of different [...] Read more.
(1) Background: COVID-19 is still affecting people’s daily lives. In the past two years of epidemic control, a traffic control policy has been an important way to block the spread of the epidemic. (2) Objectives: To delve into the blocking effects of different traffic control policies on COVID-19 transmission. (3) Methods: Based on the classical SIR model, this paper designs and improves the coefficient of the infectious rate, and it builds a quantitative SEIR model that considers the infectivity of the exposed for traffic control policies. Taking Changsha, a typical city of epidemic prevention and control, as a study case, this paper simulates the epidemic trends under three traffic control policies adopted in Changsha: home quarantine, road traffic control, and public transport suspension. Meanwhile, to explore the time sensitivity of all traffic control policies, this paper sets four distinct scenarios where the traffic control policies were implemented at the first medical case, delayed by 3, 5, and 7 days, respectively. (4) Results: The implementation of the traffic control policies has decreased the peak value of the population of the infective in Changsha by 66.03%, and it has delayed the peak period by 58 days; with the home-quarantine policy, the road traffic control policy, and the public transport suspension policy decreasing the peak value of the population of the infective by 56.81%, 39.72%, and 45.31% and delaying the peak period by 31, 18, and 21 days, respectively; in the four scenarios where the traffic control policies had been implemented at the first medical case, delayed by 3, 5, and 7 days, respectively, the variations of both the peak value and the peak period timespan of confirmed cases under the home-quarantine policy would have been greater than under the road traffic control and the public transport suspension policies. (5) Conclusions: The implementation of traffic control policies is significantly effective in blocking the epidemic across the city of Changsha. The home-quarantine policy has the highest time sensitivity: the earlier this policy is implemented, the more significant its blocking effect on the spread of the epidemic. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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25 pages, 8557 KiB  
Article
School Surrounding Region Traffic Commuting Analysis Based on Simulation
by Huasheng Liu, Haoran Deng, Yu Li, Yuqi Zhao and Xiaowen Li
Int. J. Environ. Res. Public Health 2022, 19(11), 6566; https://doi.org/10.3390/ijerph19116566 - 27 May 2022
Cited by 1 | Viewed by 1949
Abstract
Student commuting is an important part of urban travel demand and private car commuting plays an important role in urban traffic, especially in areas near schools. Since parents, especially the parents of elementary and junior high school students, prefer to drive rather than [...] Read more.
Student commuting is an important part of urban travel demand and private car commuting plays an important role in urban traffic, especially in areas near schools. Since parents, especially the parents of elementary and junior high school students, prefer to drive rather than take public transport, there will be a negative effect on traffic management. To address the challenge, a simulation model is established based on schools’ surrounding regions to analyze traffic status. Specifically, the model focuses on urban construction and transportation near the entrance of schools and neighborhoods. In addition, four variable parameters consisting of the directional hourly volume, the parking demand of delivery vehicles, the distance between the school and intersection, and the average parking time for pick-up vehicles are set as influence factors, while traffic efficiency, energy consumption, and pollutant emissions are considered as the evaluation criteria of our model. Extensive simulated experiments show that comparing different scenarios, the traffic state of schools’ surrounding areas can achieve much better performance when the distance between entrances and intersections is 400 m under the 1000 pcu/h condition. This research can provide a scientific basis for school regional traffic management and organization optimization. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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25 pages, 5051 KiB  
Article
A Two-Phase, Joint-Commuting Model for Primary and Secondary Schools Considering Parking Sharing
by Huasheng Liu, Yuqi Zhao, Jin Li, Yu Li, Xiaowen Li and Sha Yang
Int. J. Environ. Res. Public Health 2022, 19(11), 6435; https://doi.org/10.3390/ijerph19116435 - 25 May 2022
Viewed by 2024
Abstract
In light of the traffic congestion and traffic environment problems around schools that are caused by students commuting by car, this paper explores an efficient and feasible student commuting travel plan. Based on the ideas of “public–private cooperation” and “parking sharing”, combined with [...] Read more.
In light of the traffic congestion and traffic environment problems around schools that are caused by students commuting by car, this paper explores an efficient and feasible student commuting travel plan. Based on the ideas of “public–private cooperation” and “parking sharing”, combined with the characteristics of the family travel chain during the commuting period, a joint-commuting model of “private car and school bus” is creatively proposed. On the basis of considering the travel cost of parents and the operating cost of school bus, a two-phase commuting travel model for primary and secondary schools is proposed, and an algorithm is designed. The validity of the model is verified by an example and sensitivity analysis. The results show that the total time cost can be reduced by 23.33% when the private-car commuting mode is converted to the joint-commuting model. Among the results, we found that the driving time of a private car in the school commuting phase can be reduced by 23.36%, the dwell time can be reduced by 92.29%, and the driving time in the work and home phase can be reduced by 7.44%. Compared with the school-bus commuting mode, the school-bus time cost of joint commuting can be reduced by 54.88%. In addition, by analyzing the impact of various factors on the objective function and vehicle emissions, it can be seen that staggered commuting to school, regulating regional traffic volume, increasing parking spaces, and improving the utilization of parking spaces can effectively reduce the operating time cost of vehicles and exhaust emissions. The joint-commuting model proposed in this paper considers the balance between service level and resource consumption. While meeting the door-to-door travel needs of students, it can effectively reduce the travel costs of parents and school-bus operation costs, and it can alleviate traffic congestion around schools and reduce the impact on the environment. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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17 pages, 2400 KiB  
Article
Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network
by Lining Liu, Xiaofei Ye, Tao Wang, Xingchen Yan, Jun Chen and Bin Ran
Int. J. Environ. Res. Public Health 2022, 19(10), 6013; https://doi.org/10.3390/ijerph19106013 - 15 May 2022
Cited by 10 | Viewed by 2406
Abstract
The purpose of this paper is to analyze the complex coupling relationships among accident factors contributing to the automobile and two-wheeler traffic accidents by establishing the Bayesian network (BN) model of the severity of traffic accidents, so as to minimize the negative impact [...] Read more.
The purpose of this paper is to analyze the complex coupling relationships among accident factors contributing to the automobile and two-wheeler traffic accidents by establishing the Bayesian network (BN) model of the severity of traffic accidents, so as to minimize the negative impact of automobile to two-wheeler traffic accidents. According to the attribution of primary responsibility, traffic accidents were divided to two categories: the automobile and two-wheeler traffic as the primary responsible party. Two BN accident severity analysis models for different primary responsible parties were proposed by innovatively combining the Kendall correlation analysis method with the BN model. A database of 1560 accidents involving an automobile and two-wheeler in Guilin, Guangxi province, were applied to calibrate the model parameters and validate the effectiveness of the models. The result shows that the BN models could reflect the real relationships among the influential factors of the two types of traffic accidents. For traffic accidents of automobiles and two-wheelers as the primary responsible party, respectively, the biggest influential factors leading to fatality were weather and visibility, and the corresponding fluctuations in the probability of occurrence were 32.20% and 27.23%, respectively. Moreover, based on multi-factor cross-over analysis, the most influential factors leading to fatality were: {Off-Peak Period → Driver of Two-Wheeler: The elderly → Driving Behavior of Two-Wheeler: Parking} and {Drunk Driving Two-Wheeler → Having a License of Automobiles → Visibility: 50 m~100 m}, respectively. The results provide a theoretical basis for reducing the severity of automobile to two-wheeler traffic accidents. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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21 pages, 4139 KiB  
Article
Spatio-Temporal Variation-Induced Group Disparity of Intra-Urban NO2 Exposure
by Huizi Wang, Xiao Luo, Chao Liu, Qingyan Fu and Min Yi
Int. J. Environ. Res. Public Health 2022, 19(10), 5872; https://doi.org/10.3390/ijerph19105872 - 12 May 2022
Viewed by 2005
Abstract
Previous studies on exposure disparity have focused more on spatial variation but ignored the temporal variation of air pollution; thus, it is necessary to explore group disparity in terms of spatio-temporal variation to assist policy-making regarding public health. This study employed the dynamic [...] Read more.
Previous studies on exposure disparity have focused more on spatial variation but ignored the temporal variation of air pollution; thus, it is necessary to explore group disparity in terms of spatio-temporal variation to assist policy-making regarding public health. This study employed the dynamic land use regression (LUR) model and mobile phone signal data to illustrate the variation features of group disparity in Shanghai. The results showed that NO2 exposure followed a bimodal, diurnal variation pattern and remained at a high level on weekdays but decreased on weekends. The most critical at-risk areas were within the central city in areas with a high population density. Moreover, women and the elderly proved to be more exposed to NO2 pollution in Shanghai. Furthermore, the results of this study showed that it is vital to focus on land-use planning, transportation improvement programs, and population agglomeration to attenuate exposure inequality. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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17 pages, 3115 KiB  
Article
Investigating the Daytime Visibility Requirements of Pavement Marking Considering the Influence of CCT and Illuminance of Natural Light
by Jiangbi Hu, Yanyan Guan, Ronghua Wang, Qingyun Cao, Yunpeng Guo and Qingxin Hu
Int. J. Environ. Res. Public Health 2022, 19(5), 3051; https://doi.org/10.3390/ijerph19053051 - 5 Mar 2022
Cited by 3 | Viewed by 2047
Abstract
Pavement marking in daylight with poor quality cannot provide a reference for drivers to specify their own position relative to nearby vehicles. Luminance and Correlated color temperature (CCT) of sunlight is of importance for daytime visibility of in-service pavement markings, which lacks detailed [...] Read more.
Pavement marking in daylight with poor quality cannot provide a reference for drivers to specify their own position relative to nearby vehicles. Luminance and Correlated color temperature (CCT) of sunlight is of importance for daytime visibility of in-service pavement markings, which lacks detailed consideration. This paper aims to explore the daytime visibility requirements of in-service pavement markings considering the influence of natural light characteristics. Based on analyzing the mechanism and impact factors of daytime visibility of pavement markings, a subjective scale of pavement markings state in the drivers’ field of view was proposed and a short and bold line was recommended as the standard state. Thirty-six tested drivers were randomly selected to detect white and yellow markings of both 15 cm and 20 cm width under 2000 to 23,000 lx and 5500 to 8500 K for outdoor natural light environment. The luminance contrast of the pavement marking to the surrounding road surface ranged from 0 to 10. The result indicated that the natural light with 2000 to 3000 lx and 7500 to 8500 K is the most unfavorable light environment for drivers to recognize pavement markings during daytime. The detection distance is becoming longer with the increase of luminance contrast. The detection distance does not increase with the increase of luminance contrast when the luminance contrast of white markings is greater than 4 and that of yellow markings is greater than 3. The model was established expressing the relationship between luminance contrast and Qd contrast. The preview time 3.65 s was selected to calculate the minimum requirements of Qd at speeds of 60, 80, 100 km/h, respectively, for different types of markings. The results can provide scientific evidence for quality evaluation and maintenance management of pavement markings in service for daytime visibility. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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23 pages, 3359 KiB  
Article
Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations
by Sheng Dong, Afaq Khattak, Irfan Ullah, Jibiao Zhou and Arshad Hussain
Int. J. Environ. Res. Public Health 2022, 19(5), 2925; https://doi.org/10.3390/ijerph19052925 - 2 Mar 2022
Cited by 49 | Viewed by 5808
Abstract
Road traffic accidents are one of the world’s most serious problems, as they result in numerous fatalities and injuries, as well as economic losses each year. Assessing the factors that contribute to the severity of road traffic injuries has proven to be insightful. [...] Read more.
Road traffic accidents are one of the world’s most serious problems, as they result in numerous fatalities and injuries, as well as economic losses each year. Assessing the factors that contribute to the severity of road traffic injuries has proven to be insightful. The findings may contribute to a better understanding of and potential mitigation of the risk of serious injuries associated with crashes. While ensemble learning approaches are capable of establishing complex and non-linear relationships between input risk variables and outcomes for the purpose of injury severity prediction and classification, most of them share a critical limitation: their “black-box” nature. To develop interpretable predictive models for road traffic injury severity, this paper proposes four boosting-based ensemble learning models, namely a novel Natural Gradient Boosting, Adaptive Gradient Boosting, Categorical Gradient Boosting, and Light Gradient Boosting Machine, and uses a recently developed SHapley Additive exPlanations analysis to rank the risk variables and explain the optimal model. Among four models, LightGBM achieved the highest classification accuracy (73.63%), precision (72.61%), and recall (70.09%), F1-scores (70.81%), and AUC (0.71) when tested on 2015–2019 Pakistan’s National Highway N-5 (Peshawar to Rahim Yar Khan Section) accident data. By incorporating the SHapley Additive exPlanations approach, we were able to interpret the model’s estimation results from both global and local perspectives. Following interpretation, it was determined that the Month_of_Year, Cause_of_Accident, Driver_Age and Collision_Type all played a significant role in the estimation process. According to the analysis, young drivers and pedestrians struck by a trailer have a higher risk of suffering fatal injuries. The combination of trailers and passenger vehicles, as well as driver at-fault, hitting pedestrians and rear-end collisions, significantly increases the risk of fatal injuries. This study suggests that combining LightGBM and SHAP has the potential to develop an interpretable model for predicting road traffic injury severity. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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21 pages, 6351 KiB  
Article
Impact of Helmet-Wearing Policy on E-Bike Safety Riding Behavior: A Bivariate Ordered Probit Analysis in Ningbo, China
by Jibiao Zhou, Tao Zheng, Sheng Dong, Xinhua Mao and Changxi Ma
Int. J. Environ. Res. Public Health 2022, 19(5), 2830; https://doi.org/10.3390/ijerph19052830 - 28 Feb 2022
Cited by 13 | Viewed by 5209
Abstract
At present, Chinese authorities are launching a campaign to convince riders of electric bicycles (e-bikes) and scooters to wear helmets. To explore the effectiveness of this new helmet policy on e-bike cycling behavior and improve existing e-bike management, this study investigates the related [...] Read more.
At present, Chinese authorities are launching a campaign to convince riders of electric bicycles (e-bikes) and scooters to wear helmets. To explore the effectiveness of this new helmet policy on e-bike cycling behavior and improve existing e-bike management, this study investigates the related statistical distribution characteristics, such as demographic information, travel information, cycling behavior information and riders’ subjective attitude information. The behavioral data of 1048 e-bike riders related to helmet policy were collected by a questionnaire survey in Ningbo, China. A bivariate ordered probit (BOP) model was employed to account for the unobserved heterogeneity. The marginal effects of contributory factors were calculated to quantify their impacts, and the results show that the BOP model can explain the common unobserved features in the helmet policy and cycling behavior of e-bike riders, and that good safety habits stem from long-term safety education and training. The BOP model results show that whether wearing a helmet, using an e-bike after 19:00, and sunny days are factors that affect the helmet wearing rate. Helmet wearing, evenings during rush hour, and picking up children are some of the factors that affect e-bike accident rates. Furthermore, there is a remarkable negative correlation between the helmet wearing rate and e-bike accident rate. Based on these results, some interventions are discussed to increase the helmet usage of e-bike riders in Ningbo, China. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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18 pages, 5886 KiB  
Article
Study on the Influence of Opposing Glare from Vehicle High-Beam Headlights Based on Drivers’ Visual Requirements
by Jiangbi Hu, Yunpeng Guo, Ronghua Wang, Sen Ma and Aolin Yu
Int. J. Environ. Res. Public Health 2022, 19(5), 2766; https://doi.org/10.3390/ijerph19052766 - 27 Feb 2022
Cited by 7 | Viewed by 3595
Abstract
The anti-glare facilities in median strips are designed to block opposing headlights in order to avoid disability glare, but a large amount of headlight leakage results in uncomfortable glare, to the point that drivers can barely detect dangerous obstacles or road conditions. This [...] Read more.
The anti-glare facilities in median strips are designed to block opposing headlights in order to avoid disability glare, but a large amount of headlight leakage results in uncomfortable glare, to the point that drivers can barely detect dangerous obstacles or road conditions. This paper aims to explore the glare range under high-beam headlights on drivers’ visual requirements. Based on an analysis of the mechanism of headlight glare, this paper proposes a subjective headlight glare scale, and classifies glare discomfort into two categories: interference glare, and acceptability glare. Combining the scales, 24 drivers and a standard light-emitting diode automotive headlamp were used to conduct glare effect tests. The size of the laboratory that closes to scotopic vision is 12 m × 6 m. The illuminance thresholds of disability glare–interference glare (DGIG) and interference glare–acceptability glare (IGAG), along with the spatial distribution of each glare level, were collected at the longitudinal distances of 3 m, 5 m, 7 m, 10 m, and 12 m. Meanwhile, the illuminance threshold and the spatial distribution of each glare level up to a longitudinal distance of 120 m were calculated. The results indicate that disability glare is distributed in the central area, while interference glare and acceptability glare are distributed from the center to the margins. At the same longitudinal distance, the vertical illuminance of the driver’s eye under the same glare level is almost equal. In the range of a longitudinal distance of 120 m, the spatial distribution of each glare level enlarges with each increase in longitudinal distance. The results can provide scientific evidence for calculating the reasonable heights of anti-glare facilities for expressways with different alignments. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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19 pages, 1356 KiB  
Article
Underestimated Risk Perception Characteristics of Drivers Based on Extended Theory of Planned Behavior
by Yunteng Chen, Xianyong Liu, Jinliang Xu and Huan Liu
Int. J. Environ. Res. Public Health 2022, 19(5), 2744; https://doi.org/10.3390/ijerph19052744 - 26 Feb 2022
Cited by 8 | Viewed by 3529
Abstract
Aggressive driving behaviors due to drivers’ underestimation of risks are one of the major causes of traffic accidents. Due to the complexity of factors influencing risk perception, the mechanism of risk underestimation remains unclear. In this study, the theory of planned behavior (TPB) [...] Read more.
Aggressive driving behaviors due to drivers’ underestimation of risks are one of the major causes of traffic accidents. Due to the complexity of factors influencing risk perception, the mechanism of risk underestimation remains unclear. In this study, the theory of planned behavior (TPB) was extended by adding a new variable, namely drivers’ normlessness, forming an extended TPB (ETPB) framework to analyze the factors influencing risk underestimation and the extent of their influence. A total of 376 drivers’ perceived characteristics of risk underestimation were collected through an online survey, and a structural equation model was applied to investigate the effects of normlessness, behavioral attitudes, subjective norm, and perceived behavioral control on the tendency to underestimate the risk. The results showed that the ETPB model can explain the variance in the underestimation risk behavior by 69%; perceptual behavior control, attitude, and subjective norm (in descending order) had significant positive effects on driver’s tendency to underestimate risk; the normlessness variable can directly promote attitude and underestimated risk behavior; drivers with low annual mileage, complete insurance coverage, and no prior accident experience were more likely to underestimate driving risk. The study contributes to understanding of risk perception characteristics and provide theoretical basis for reducing underestimated risk behavior. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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23 pages, 6478 KiB  
Article
Study on the Maximum Safe Instantaneous Input of the Steering Wheel against Rollover for Trucks on Horizontal Curves
by Jinliang Xu, Tian Xin, Chao Gao and Zhenhua Sun
Int. J. Environ. Res. Public Health 2022, 19(4), 2025; https://doi.org/10.3390/ijerph19042025 - 11 Feb 2022
Cited by 7 | Viewed by 2353
Abstract
Truck rollover crashes on horizontal curves have been recognized as one of the most serious types of crashes. Driver’s instantaneous emergency steering maneuvers (DIESM) play an important role in truck rollover crashes, but have not received much attention. In the present study, the [...] Read more.
Truck rollover crashes on horizontal curves have been recognized as one of the most serious types of crashes. Driver’s instantaneous emergency steering maneuvers (DIESM) play an important role in truck rollover crashes, but have not received much attention. In the present study, the radius of curvature of the actual vehicle travel path (AVTP) under DIESM was calculated based on the transient bicycle model. Rollover margins were used to evaluate the truck-rollover potential under DIESM. To calculate rollover margins, the lateral acceleration under DIESM was calculated based on the radius of the curvature of the AVTP. A rollover threshold formula was introduced to calculate vehicle’s rollover thresholds by distinguishing two turning conditions. According to rollover margins, the maximum safe instantaneous input of the steering wheel against rollover for trucks was obtained. Moreover, theoretical results were verified by computer simulation. Results showed: (1) The maximum safe instantaneous inputs of the steering wheel were 259°, 212°, 182°, 162°and 147°, respectively, at speeds of 60 km/h, 70 km/h, 80 km, 90 km and 100 km when the superelevation rate was 0, and (2) superelevation significantly affected truck-rollover potential; the worst turning condition was turning from the inside to the outside of the curve. Due to the consideration of the wheelbase, the centroid position, the tire’s cornering stiffness and the suspension roll gain, the prediction results were more accurate. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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14 pages, 25140 KiB  
Article
The Effects of Dynamic Complexity on Drivers’ Secondary Task Scanning Behavior under a Car-Following Scenario
by Linhong Wang, Hongtao Li, Mengzhu Guo and Yixin Chen
Int. J. Environ. Res. Public Health 2022, 19(3), 1881; https://doi.org/10.3390/ijerph19031881 - 8 Feb 2022
Cited by 9 | Viewed by 2271
Abstract
The user interface of vehicle interaction systems has become increasingly complex in recent years, which makes these devices important factors that contribute to accidents. Therefore, it is necessary to study the impact of dynamic complexity on the carrying capacity of secondary tasks under [...] Read more.
The user interface of vehicle interaction systems has become increasingly complex in recent years, which makes these devices important factors that contribute to accidents. Therefore, it is necessary to study the impact of dynamic complexity on the carrying capacity of secondary tasks under different traffic scenarios. First, we selected vehicle speed and vehicle spacing as influencing factors in carrying out secondary tasks. Then, the average single scanning time, total scanning time, and scanning times were selected as evaluation criteria, based on the theories of cognitive psychology. Lastly, we used a driving simulator to conduct an experiment under a car-following scenario and collect data on scanning behavior by an eye tracker, to evaluate the performance of the secondary task. The results show that the relationship between the total scanning time, scanning times, and the vehicle speed can be expressed by an exponential model, the relationship between the above two indicators and the vehicle spacing can be expressed by a logarithmic model, and the relationship with the total number of icons can be expressed by a linear model. Combined with the above relationships and the evaluation criteria for driving secondary tasks, the maximum number of icons at different vehicle speeds and vehicle spacings can be calculated to reduce the likelihood of accidents caused by attention overload. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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22 pages, 5309 KiB  
Article
Analyzing the Influencing Factors and Workload Variation of Takeover Behavior in Semi-Autonomous Vehicles
by Hui Zhang, Yijun Zhang, Yiying Xiao and Chaozhong Wu
Int. J. Environ. Res. Public Health 2022, 19(3), 1834; https://doi.org/10.3390/ijerph19031834 - 6 Feb 2022
Cited by 8 | Viewed by 2940
Abstract
There are many factors that will influence the workload of drivers during autonomous driving. To examine the correlation between different factors and the workload of drivers, the influence of different factors on the workload variations is investigated from subjective and objective viewpoints. Thirty-seven [...] Read more.
There are many factors that will influence the workload of drivers during autonomous driving. To examine the correlation between different factors and the workload of drivers, the influence of different factors on the workload variations is investigated from subjective and objective viewpoints. Thirty-seven drivers were recruited to participant the semi-autonomous driving experiments, and the drivers were required to complete different NDRTs (Non-Driving-Related Tasks): mistake finding, chatting, texting, and monitoring when the vehicle is in autonomous mode. Then, we introduced collision warning to signal there is risk ahead, and the warning signal was triggered at different TB (Time Budget)s before the risk, at which time the driver had to take over the driving task. During driving, the NASA-TLX-scale data were obtained to analyze the variation of the driver’s subjective workload. The driver’s pupil-diameter data acquired by the eye tracker from 100 s before the TOR (Take-Over Request) to 19 s after the takeover were obtained as well. The sliding time window was set to process the pupil-diameter data, and the 119-s normalized average pupil-diameter data under different NDRTs were fitted and modeled to analyze the variation of the driver’s objective workload. The results show that the total subjective workload score under the influence of different factors is as follows: obstacle-avoidance scene > lane-keeping scene; TB = 7 s and TB = 3 s have no significant difference; and mistake finding > chatting > texting > monitoring. The results of pupil-diameter data under different factors are as follows: obstacle-avoidance scene > lane-keeping scene; TB = 7 s > TB = 3 s; and monitoring type (chatting and monitoring) > texting type (mistake finding and texting). The research results can provide a reference for takeover safety prediction modeling based on workload. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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13 pages, 24829 KiB  
Article
A Field Study on Safety Performance of Apron Controllers at a Large-Scale Airport Based on Digital Tower
by Jianping Zhang, Xiaoqiang Tian, Jian Pan, Zhenling Chen and Xiang Zou
Int. J. Environ. Res. Public Health 2022, 19(3), 1623; https://doi.org/10.3390/ijerph19031623 - 31 Jan 2022
Cited by 2 | Viewed by 2985
Abstract
The innovative concept of digital tower provides a new solution for reducing the construction and operation costs of airports with adverse natural environments, poor intervisibility conditions, or sparse traffic. However, it leads to changes in the situational awareness of air traffic controllers and [...] Read more.
The innovative concept of digital tower provides a new solution for reducing the construction and operation costs of airports with adverse natural environments, poor intervisibility conditions, or sparse traffic. However, it leads to changes in the situational awareness of air traffic controllers and to challenges in safety performance. To research the safety performance of apron controllers at a large-scale airport applying a digital tower, a field study was conducted at Baiyun International Airport in Guangzhou, China. In this study, we established a comprehensive index system from the perspective of situational awareness, which provided measurements on the areas of interests, gaze and physiological features, and vigilance of controllers. Three modules were compared: a physical tower module, a digital tower module with a large panoramic screen, and a digital tower module with a small panoramic screen. The differences in the safety performances of apron controllers are discussed in two aspects: adaptability and reliability. The results indicated that the apron controllers at the three modules performed different cognition patterns, but similar cognition effort was paid toward maintaining performance. Furthermore, the significant vigilance decrement of controllers exists between after-duty and before-duty, but with no significant difference among the three modules. In conclusion, apron controllers at a large-scale airport could obtain effective safety performances based on a digital tower that were no less than those from a physical tower. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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22 pages, 4356 KiB  
Article
Drivers’ Decelerating Behaviors in Expressway Accident Segments under Different Speed Limit Schemes
by Wenhui Zhang, Jing Yi, Ge Zhou and Tuo Liu
Int. J. Environ. Res. Public Health 2022, 19(3), 1590; https://doi.org/10.3390/ijerph19031590 - 30 Jan 2022
Viewed by 2465
Abstract
Traffic accidents occurring on expressways tend to give rise to traffic bottlenecks. To ensure the vehicles safely and smoothly pass through the accident segments, speed limits are generally taken to regulate the vehicles’ movements. This study aims to explore the decelerating behaviors of [...] Read more.
Traffic accidents occurring on expressways tend to give rise to traffic bottlenecks. To ensure the vehicles safely and smoothly pass through the accident segments, speed limits are generally taken to regulate the vehicles’ movements. This study aims to explore the decelerating behaviors of drivers under different speed limit schemes. We designed traffic accident scenarios under four speed limit schemes using the driving simulator. A total of 60 subjects drove the simulator passing the accident segments according to their habits. The vehicles’ kinematic data and the subjects’ operating data were recorded. To further analyze the drivers’ decelerating behaviors in different speed limit scenarios, driving experience was also taken into account. The results show that the speed limit schemes have significant effects on drivers’ decelerating behaviors. The more speed limit signs there are, the smoother the decelerating process will be. Driving experience significantly affects some of the decelerating parameters, including the location of deceleration starting point, average deceleration, and locations of decelerating to the initial and final speed limits. These results provide a theoretical basis for traffic safety and driving behavior management. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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13 pages, 2261 KiB  
Article
Driving Performance Evaluation of Shuttle Buses: A Case Study of Hong Kong–Zhuhai–Macau Bridge
by Ming Lv, Xiaojun Shao, Chimou Li and Feng Chen
Int. J. Environ. Res. Public Health 2022, 19(3), 1408; https://doi.org/10.3390/ijerph19031408 - 27 Jan 2022
Cited by 1 | Viewed by 2389
Abstract
The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors [...] Read more.
The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors to risky performance. To achieve this, 1648 records of GPS trajectory data and 8281 records of advance warning message data from Hong Kong–Zhuhai–Macau Bridge shuttle buses were obtained. The temporal and spatial distribution of risky behaviours was analysed. A random parameters negative binomial model was developed to further investigate the relationship between speed-related factors and risky behaviours. The results indicated that the warning of safety distance, lane departure, forward collision, and distraction were more likely to occur on weekdays. The period between 14 and 16 o’clock obtained the highest frequency of safety distance and lane departure warnings. Regarding the model estimation results, indicators reflecting average speed, acceleration, and number of trips per day showed a statistically significant impact on safety distance and lane departure warnings. Also, the acceleration of bus drivers showed a mixed impact on lane departure warnings. Corresponding implications were discussed according to the findings to reduce the frequency of risky behaviours in shuttle bus operations. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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12 pages, 5284 KiB  
Article
Adaptive Aging Safety of Guidance Marks in Rail Transit Connection Systems Based on Eye Movement Data
by Yong Fang, Wenli Zhang, Hua Hu, Jiayi Zhou, Dianliang Xiao and Shaojie Li
Int. J. Environ. Res. Public Health 2022, 19(2), 725; https://doi.org/10.3390/ijerph19020725 - 10 Jan 2022
Cited by 2 | Viewed by 1943
Abstract
The aim of this study was to meet the visual cognition needs of the elderly population for the guidance marks and safety guidance marks of the rail transit connection system. Based on the visual characteristics of the elderly population, this paper firstly determined [...] Read more.
The aim of this study was to meet the visual cognition needs of the elderly population for the guidance marks and safety guidance marks of the rail transit connection system. Based on the visual characteristics of the elderly population, this paper firstly determined the visual field and sight range of the marks of the elderly population from three aspects—visual angle, visual distance, and height of the elderly population—and constructed the visual recognition space of the elderly population. Then, from the perspective of the setting position, the setting height, and the deflection angle, an adaptive aging safety design method for the guidance marks in the rail transit connection system is proposed. Then, based on the eye movement data of fixation duration, initial fixation duration, and the number of visits, a visual behavior index model is constructed to iteratively optimize the adaptive aging safety design of guidance marks in a rail transit connection system. A radar map is used to calculate the comprehensive index of visual behavior to determine the optimal scheme. Finally, taking the traffic connection system of Shanghai Songjiang University Town Station as an example, the eye movement data of 37 participants were collected, according to the principle that each connection path should only be taken once per person; the above method was used to design 7 connection path guidance marks for an adaptive aging safety design. The results showed that the comprehensive index of visual behavior of different paths had different degrees of improvement of up to 14.00%, which verified the effectiveness of the design method. The research results have certain theoretical significance and application value for the adaptive aging safety design and retrofit of guidance marks of rail transit connection systems. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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20 pages, 6116 KiB  
Article
How Does Approaching a Lead Vehicle and Monitoring Request Affect Drivers’ Takeover Performance? A Simulated Driving Study with Functional MRI
by Chimou Li, Xiaonan Li, Ming Lv, Feng Chen, Xiaoxiang Ma and Lin Zhang
Int. J. Environ. Res. Public Health 2022, 19(1), 412; https://doi.org/10.3390/ijerph19010412 - 31 Dec 2021
Cited by 8 | Viewed by 1964
Abstract
With the popularization and application of conditionally automated driving systems, takeover requirements are becoming more and more frequent, and the subsequent takeover safety problems have attracted attention. The present study used functional magnetic resonance imaging (fMRI) technology, combined with driving simulation experiments, to [...] Read more.
With the popularization and application of conditionally automated driving systems, takeover requirements are becoming more and more frequent, and the subsequent takeover safety problems have attracted attention. The present study used functional magnetic resonance imaging (fMRI) technology, combined with driving simulation experiments, to study in depth the effects of critical degree and monitor request (MR) 30 s in advance on drivers’ visual behavior, takeover performance and brain activation. Results showed that MR can effectively improve the driver’s visual and takeover performance, including visual reaction times, fixation frequency and duration, takeover time, and takeover mode. The length of the reserved safety distance can significantly affect the distribution of longitudinal acceleration. Critical or non-critical takeover has a significant impact on the change of pupil diameter and the standard deviation of lateral displacement. Five brain regions, including the middle occipital gyrus (MOG), fusiform gyrus (FG), middle temporal gyrus (MTG), precuneus and precentral, are activated under the stimulation of a critical takeover scenario, and are related to cognitive behaviors such as visual cognition, distance perception, memory search and movement association. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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14 pages, 3844 KiB  
Article
Real-Time Driving Behavior Identification Based on Multi-Source Data Fusion
by Yongfeng Ma, Zhuopeng Xie, Shuyan Chen, Ying Wu and Fengxiang Qiao
Int. J. Environ. Res. Public Health 2022, 19(1), 348; https://doi.org/10.3390/ijerph19010348 - 29 Dec 2021
Cited by 9 | Viewed by 2956
Abstract
Real-time driving behavior identification has a wide range of applications in monitoring driver states and predicting driving risks. In contrast to the traditional approaches that were mostly based on a single data source with poor identification capabilities, this paper innovatively integrates driver expression [...] Read more.
Real-time driving behavior identification has a wide range of applications in monitoring driver states and predicting driving risks. In contrast to the traditional approaches that were mostly based on a single data source with poor identification capabilities, this paper innovatively integrates driver expression into driving behavior identification. First, 12-day online car-hailing driving data were collected in a non-intrusive manner. Then, with vehicle kinematic data and driver expression data as inputs, a stacked Long Short-Term Memory (S-LSTM) network was constructed to identify five kinds of driving behaviors, namely, lane keeping, acceleration, deceleration, turning, and lane changing. The Artificial Neural Network (ANN) and XGBoost algorithms were also employed as a comparison. Additionally, ten sliding time windows of different lengths were introduced to generate driving behavior identification samples. The results show that, using all sources of data yields better results than using the kinematic data only, with the average F1 value improved by 0.041, while the S-LSTM algorithm is better than the ANN and XGBoost algorithms. Furthermore, the optimal time window length is 3.5 s, with an average F1 of 0.877. This study provides an effective method for real-time driving behavior identification, and thereby supports the driving pattern analysis and Advanced Driving Assistance System. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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17 pages, 5375 KiB  
Article
Cascading Failure Analysis on Shanghai Metro Networks: An Improved Coupled Map Lattices Model Based on Graph Attention Networks
by Haonan Ye and Xiao Luo
Int. J. Environ. Res. Public Health 2022, 19(1), 204; https://doi.org/10.3390/ijerph19010204 - 25 Dec 2021
Cited by 10 | Viewed by 3085
Abstract
Analysis of the robustness and vulnerability of metro networks has great implications for public transport planning and emergency management, particularly considering passengers’ dynamic behaviors. This paper presents an improved coupled map lattices (CMLs) model based on graph attention networks (GAT) to study the [...] Read more.
Analysis of the robustness and vulnerability of metro networks has great implications for public transport planning and emergency management, particularly considering passengers’ dynamic behaviors. This paper presents an improved coupled map lattices (CMLs) model based on graph attention networks (GAT) to study the cascading failure process of metro networks. The proposed model is applied to the Shanghai metro network using the automated fare collection (AFC) data, and the passengers’ dynamic behaviors are simulated by GAT. The quantitative cascading failure analysis shows that Shanghai metro network is robust to random attacks, but fragile to intentional attacks. Moreover, there is an approximately normal distribution between instant cascading failure speed and time step and the perturbation in a station which leads to steady state is approximately a constant. The result shows that a station surrounded by other densely distributed stations can trigger cascading failure faster and the cascading failure triggered by low-level accidents will spread in a short time and disappear quickly. This study provides an effective reference for dynamic safety evaluation and emergency management in metro networks. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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20 pages, 2438 KiB  
Article
Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach
by Shuaiming Chen, Haipeng Shao and Ximing Ji
Int. J. Environ. Res. Public Health 2021, 18(23), 12725; https://doi.org/10.3390/ijerph182312725 - 2 Dec 2021
Cited by 4 | Viewed by 2993
Abstract
Traffic accidents have significant financial and social impacts. Reducing the losses caused by traffic accidents has always been one of the most important issues. This paper presents an effort to investigate the factors affecting the accident severity of drivers with different driving experience. [...] Read more.
Traffic accidents have significant financial and social impacts. Reducing the losses caused by traffic accidents has always been one of the most important issues. This paper presents an effort to investigate the factors affecting the accident severity of drivers with different driving experience. Special focus was placed on the combined effect of driving experience and age. Based on our dataset (traffic accidents that occurred between 2005 and 2021 in Shaanxi, China), CatBoost model was applied to deal with categorical feature, and SHAP (Shapley Additive exPlanations) model was used to interpret the output. Results show that accident cause, age, visibility, light condition, season, road alignment, and terrain are the key factors affecting accident severity for both novice and experienced drivers. Age has the opposite impact on fatal accident for novice and experienced drivers. Novice drivers younger than 30 or older than 55 are prone to suffer fatal accident, but for experienced drivers, the risk of fatal accident decreases when they are young and increases when they are old. These findings fill the research gap of the combined effect of driving experience and age on accident severity. Meanwhile, it can provide useful insights for practitioners to improve traffic safety for novice and experienced drivers. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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23 pages, 5269 KiB  
Article
Social Force Model-Based Safety Evaluation of Intersections in Arterials Considering the Pedestrian Yield Rule
by Jiao Yao, Yuhang Li and Jiaping He
Int. J. Environ. Res. Public Health 2021, 18(23), 12461; https://doi.org/10.3390/ijerph182312461 - 26 Nov 2021
Cited by 1 | Viewed by 2104
Abstract
To enhance the safety of pedestrians crossing the street, a series of new regulations regarding pedestrian yield has been proposed and widely implemented across cities. In this study, we first made some improvements to the social force model, in which pedestrian crossing at [...] Read more.
To enhance the safety of pedestrians crossing the street, a series of new regulations regarding pedestrian yield has been proposed and widely implemented across cities. In this study, we first made some improvements to the social force model, in which pedestrian crossing at the intersection, drivers’ psychology of giving way, vehicle yield to pedestrians, vehicle yield in different directions, the influence of pedestrians crossing boundaries, and signal lamp groups on pedestrian behavior were considered. Furthermore, pedestrian crossing and vehicle yield safety models were established, based on which the comprehensive safety evaluation model of intersections in arterials was established, in which two indices—(1) the safety degree of pedestrian crossings and (2) vehicle acceleration interference—were combined with the entropy weight method. Finally, four types of intersections in arterials were studied using a simulation: the intersections between different levels of arterials, and intersections with one-time and two-times pedestrian crossings. Moreover, safety evaluation and analysis of those intersections, considering the rule of pedestrian yield, were conducted combined with the trajectory data from the VISSIM simulation. The relevant results showed that for pedestrians crossing the street, the pedestrian safety of two-time crossing is significantly higher than that of one-time crossing, and compared with the arterial, the pedestrian crossing distance of the sub-arterial is shorter, and the pedestrian perception is safer. Moreover, due to the herd psychology effect, the increase in pedestrian flow volume improves the safety perception of pedestrians at the intersection. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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17 pages, 1993 KiB  
Article
A Field Study of Work Type Influence on Air Traffic Controllers’ Fatigue Based on Data-Driven PERCLOS Detection
by Jianping Zhang, Zhenling Chen, Weidong Liu, Pengxin Ding and Qinggang Wu
Int. J. Environ. Res. Public Health 2021, 18(22), 11937; https://doi.org/10.3390/ijerph182211937 - 13 Nov 2021
Cited by 11 | Viewed by 2593
Abstract
The fatigue of air traffic controllers (ATCOs) on duty seriously threatens air traffic safety and needs to be managed. ATCOs perform several different types of work, with each type of work having different characteristics. Nonetheless, the influence of work type on an ATCO’s [...] Read more.
The fatigue of air traffic controllers (ATCOs) on duty seriously threatens air traffic safety and needs to be managed. ATCOs perform several different types of work, with each type of work having different characteristics. Nonetheless, the influence of work type on an ATCO’s fatigue has yet to be demonstrated. Here, we present a field study in which the fatigue of ATCOs working in two types of work was compared based on an optimized data-driven method that was employed to detect the percentage of eyelid closure over the pupil over time (PERCLOS). Sixty-seven ATCOs working within two typical jobs (i.e., from the terminal control unit (TCU) and area control unit (ACU)) were recruited, and their fatigue was detected immediately before and after shift work using PERCLOS. Using a Spearman correlation test analysis, the results showed that the influence of work type on an ATCO’s fatigue had interesting trends. Specifically, the ATCOs at the TCU who handle departures and arrivals, which include converging with and maneuvering around conflicts, retain normal circadian rhythms. Their fatigue was significantly influenced by the various demands from tasks focusing on sequencing and conflict resolution and by the time phase of a normal circadian rhythm. At the ACU, ATCOs manage flights that are mainly on route, causing monotonous monitoring and routine reporting tasks, and the ATCOs generally have frequent night shifts to handle overflights. Their fatigue was significantly influenced by the demand characteristics from tasks, but changes in fatigue rule were not consistent with a normal circadian rhythm, revealing that the ATCOs’ circadian rhythms may have already been slightly disturbed. Furthermore, the interactions between task demand and circadian rhythm with an ATCO’s fatigue were significantly observed in ATCOs working in the TCU but not in those in the ACU. This study provides first evidence that an ATCO’s work type influences his or her fatigue. This discovery may incite stakeholders to consider work type in the management of employee fatigue, not only in the civil aviation industry but also in other transport industries. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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16 pages, 828 KiB  
Article
Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
by Zhongxiang Feng, Jingyu Li, Xiaoqin Xu, Amy Guo, Congjun Huang and Xu Jiang
Int. J. Environ. Res. Public Health 2021, 18(21), 11076; https://doi.org/10.3390/ijerph182111076 - 21 Oct 2021
Cited by 3 | Viewed by 2397
Abstract
Drivers’ take-over intention is important for the design of the automated driving systems and affects the safety of automated driving. This study explored the influence factors on drivers’ take-over intention during conditionally automated driving, examined the correlations among factors through path analysis, and [...] Read more.
Drivers’ take-over intention is important for the design of the automated driving systems and affects the safety of automated driving. This study explored the influence factors on drivers’ take-over intention during conditionally automated driving, examined the correlations among factors through path analysis, and established a take-over intention model. A questionnaire survey was conducted in Hefei, China, and a sample of 277 drivers was obtained. Our study shows that the average take-over intention of those aged under 20 is lower than that of the older age groups. In the positive emotions (PE) scenarios, the take-over intention of aged 31–40 is significantly higher than that of the other age groups. Education and occupation have a significant influence on the take-over intention. The perceived ease of use (PEofU) and perceived usefulness (PU) of automated driving are significantly negatively correlated with drivers’ take-over intention in the road conditions (RC) and climate conditions (CC) scenarios. In addition, through path model analysis, our study shows that trust in the safety of autonomous vehicles (AVs) plays an important role in drivers’ take-over intention. Technology acceptance, risk perception and self-efficacy has indirectly correlated with take-over intention through trust in the safety of AVs. In general, drivers with lower technology acceptance, lower self-efficacy and higher risk perception are less likely to trust automated driving technology and have shown stronger intention to take-over the control of the vehicles. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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20 pages, 7832 KiB  
Article
Effects of the Spatial Structure Conditions of Urban Underpass Tunnels’ Longitudinal Section on Drivers’ Physiological and Behavioral Comfort
by Zhongxiang Feng, Miaomiao Yang, Yingjie Du, Jin Xu, Congjun Huang and Xu Jiang
Int. J. Environ. Res. Public Health 2021, 18(20), 10992; https://doi.org/10.3390/ijerph182010992 - 19 Oct 2021
Cited by 3 | Viewed by 2296
Abstract
To investigate the physiological and behavioral comfort of drivers traversing urban underpass tunnels with various spatial structure conditions, a driving simulator experiment was conducted using 3DMAX and SCANeRTM studio software. Three parameters, including the slope, slope length, and height of a tunnel, were [...] Read more.
To investigate the physiological and behavioral comfort of drivers traversing urban underpass tunnels with various spatial structure conditions, a driving simulator experiment was conducted using 3DMAX and SCANeRTM studio software. Three parameters, including the slope, slope length, and height of a tunnel, were selected as research objects to explore the optimal combination of structural parameters in urban underpass tunnels. The heart rate (HR), interbeat (RR) interval, speed, and lane centerline offset value were collected for 30 drivers. Then, a measurement model of the relationship among HR, RR interval, speed, lane centerline offset value, and structural parameters was established by using partial correlation analyses and the stepwise regression method. On this basis, a structural constraint model based on the drivers’ physiological and behavioral comfort thresholds was also constructed. The results show that the driver’s HR, RR interval, speed, and lane centerline offsets are significantly related to the tunnel height, slope, and slope length. More importantly, this paper not only analyzed the effects of various structural parameters on drivers’ physiology and behavior but also proposed an optimized combination of structural parameters based on drivers’ physiological and behavioral comfort. It can reasonably improve tunnel design in China, ensure tunnel traffic safety, and seek the maximum comfort of the driver in the driving process. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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14 pages, 5747 KiB  
Article
The Relationship of the Information Quantity of Urban Roadside Traffic Signs and Drivers’ Visibility Based on Information Transmission
by Kun Liu and Hongxing Deng
Int. J. Environ. Res. Public Health 2021, 18(20), 10976; https://doi.org/10.3390/ijerph182010976 - 19 Oct 2021
Cited by 11 | Viewed by 2614
Abstract
For the lack of quantitative basis of traffic sign combination information, this paper established a model of information quantity of urban road traffic signs by analyzing the driver’s information processing and the visual recognition of traffic signs combined with theories of informatics. It [...] Read more.
For the lack of quantitative basis of traffic sign combination information, this paper established a model of information quantity of urban road traffic signs by analyzing the driver’s information processing and the visual recognition of traffic signs combined with theories of informatics. It used various analytical methods to build a model of the relationship between the traffic sign information quantity (TSIQ) and the driver’s visual recognition. Based on factors, the relationship between the TSIQ and the driver’s visual recognition was studied and analyzed to provide a reference for the design of urban traffic sign layout information. The results show that the TSIQ can explain 61% of the driver’s recognition time (DRT). The more information the road traffic sign conveys, the longer DRT will be. The TSIQ’s threshold is 642 bits, and exceeding this value will cause information overload. Different influence factors have a certain impact on drivers’ visual recognition distance (VRD). The male VRD is shorter than the female. The VRD of the young driver is larger than the old driver. The VRD of a novice driver is longer than an experienced driver, while the visual recognition sign of an experienced driver is shorter. Full article
(This article belongs to the Special Issue The 2nd Edition: Promotion of Big Data and Intelligent Transportation to Traffic Safety and the Environment)
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