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Traffic Accident Control and Prevention

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

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 77992

Special Issue Editor

Prof. Dr. Marcel Kuhlmey

E-Mail Website
Guest Editor
University of Economics and Law Berlin, Old Friedrichsfelde 60, 10315 Berlin, Germany
Interests: Risiko groups in traffic; traffic accident statistics; causes of accidents

Special Issue Information

Dear Colleagues,

We host a Special Issue in the International Journal of Environmental Research and Public Health called “Traffic Accident Control and Prevention”. The venue is an expert peer-reviewed scientific journal that publishes articles and communications in the interdisciplinary field of transportation sciences. Detailed information about the journal can be found at https://0-www-mdpi-com.brum.beds.ac.uk/journal/ijerph.

Increasing traffic safety is an important political and social goal. Road safety comprises the three pillars of “Engineering, Enforcement, and Education”.

The integrative approach has already contributed to increasing road safety over the last thirty years. The number of traffic fatalities has been reduced worldwide. Thanks to new technologies, it has also been possible to increase the efficiency of traffic, despite increasing traffic volumes.

An essential aspect, however, is the environmental impact of transport. A promising development is autonomous driving.

Improving road transport and its future challenges is an important target for legislation, police, city planners, and policymakers.

Research makes a significant contribution to achieving these goals.

Prof. Dr. Marcel Kuhlmey
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • Education
  • Enforcement
  • Engineering
  • Causes of accidents
  • Traffic accident recording
  • Traffic accident research
  • Traffic control

Published Papers (19 papers)

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15 pages, 1521 KiB  
Article
Identifying the Factors Contributing to the Severity of Truck-Involved Crashes in Shanghai River-Crossing Tunnel
by Shengdi Chen, Shiwen Zhang, Yingying Xing and Jian Lu
Int. J. Environ. Res. Public Health 2020, 17(9), 3155; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17093155 - 01 May 2020
Cited by 25 | Viewed by 2848
Abstract
The impact that trucks have on crash severity has long been a concern in crash analysis literature. Furthermore, if a truck crash happens in a tunnel, this would result in more serious casualties due to closure and the complexity of the tunnel. However, [...] Read more.
The impact that trucks have on crash severity has long been a concern in crash analysis literature. Furthermore, if a truck crash happens in a tunnel, this would result in more serious casualties due to closure and the complexity of the tunnel. However, no studies have been reported to analyze traffic crashes that happened in tunnels and develop crash databases and statistical models to explore the influence of contributing factors on tunnel truck crashes. This paper summarizes a study that aims to examine the impact of risk factors such as driver factor, environmental factor, vehicle factor, and tunnel factor on truck crashes injury propensity based on tunnel crashes data obtained from Shanghai, China. An ordered logit model was developed to analyze injury crashes and property damage only crashes. The driver factor, environmental factor, vehicle factor, and tunnel factor were explored to identify the relationship between these factors and crashes and the severity of crashes. Results show that increased injury severity is associated with driver factors, such as male drivers, older drivers, fatigue driving, drunkenness, safety belt used improperly, and unfamiliarity with vehicles. Late night (00:00–06:59) and afternoon rushing hours (16:30–18:59), weekdays, snow or icy road conditions, combination truck, overload, and single vehicle were also found to significantly increase the probability of injury severity. In addition, tunnel factors including two lanes, high speed limits (≥80 km/h), zone 3, extra-long tunnels (over 3000 m) are also significantly associated with a higher risk of severe injury. So, the gender, age of driver, mid-night to dawn and afternoon peak hours, weekdays, snowy or icy road conditions, the interior zone of a tunnel, the combination truck, overloaded trucks, and extra-long tunnels are associated with higher crash severity. Identification of these contributing factors for tunnel truck crashes can provide valuable information to help with new and improved tunnel safety control measures. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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15 pages, 499 KiB  
Article
Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis
by Qiang Zeng, Wei Hao, Jaeyoung Lee and Feng Chen
Int. J. Environ. Res. Public Health 2020, 17(8), 2768; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17082768 - 17 Apr 2020
Cited by 63 | Viewed by 3711
Abstract
This study presents an empirical investigation of the impacts of real-time weather conditions on the freeway crash severity. A Bayesian spatial generalized ordered logit model was developed for modeling the crash severity using the hourly wind speed, air temperature, precipitation, visibility, and humidity, [...] Read more.
This study presents an empirical investigation of the impacts of real-time weather conditions on the freeway crash severity. A Bayesian spatial generalized ordered logit model was developed for modeling the crash severity using the hourly wind speed, air temperature, precipitation, visibility, and humidity, as well as other observed factors. A total of 1424 crash records from Kaiyang Freeway, China in 2014 and 2015 were collected for the investigation. The proposed model can simultaneously accommodate the ordered nature in severity levels and spatial correlation across adjacent crashes. Its strength is demonstrated by the existence of significant spatial correlation and its better model fit and more reasonable estimation results than the counterparts of a generalized ordered logit model. The estimation results show that an increase in the precipitation is associated with decreases in the probabilities of light and severe crashes, and an increase in the probability of medium crashes. Additionally, driver type, vehicle type, vehicle registered province, crash time, crash type, response time of emergency medical service, and horizontal curvature and vertical grade of the crash location, were also found to have significant effects on the crash severity. To alleviate the severity levels of crashes on rainy days, some engineering countermeasures are suggested, in addition to the implemented strategies. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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16 pages, 526 KiB  
Article
Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management
by Soumendra Nath Sanyal, Izabela Nielsen and Subrata Saha
Int. J. Environ. Res. Public Health 2020, 17(7), 2470; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17072470 - 04 Apr 2020
Cited by 5 | Viewed by 2779
Abstract
Efficient human resource deployment is one of the key aspects of road traffic management for maintaining the lifelines of any metropolitan city. The problem becomes relevant when collaboration between human resources with different skills in day-to-day operations is necessary to maintain public and [...] Read more.
Efficient human resource deployment is one of the key aspects of road traffic management for maintaining the lifelines of any metropolitan city. The problem becomes relevant when collaboration between human resources with different skills in day-to-day operations is necessary to maintain public and commercial transport, manage various social events and emergency situations, and hence reduce congestion, injuries, emissions, etc. This study proposes a two-phase fuzzy multi-objective binary programming model for optimal allocation of five different categories of human resources to minimize the overall operational cost, maximize the allocation to accident-prone road segments, minimize the number of volunteer personnel and maximize the direct contact to reduce emissions and road traffic violations, simultaneously. A binary programming model is formulated to provide an efficient individual manpower allocation schedule for multiple road segments at different shifts. A case study is proposed for model evaluation and to derive managerial implications. The proposed model can be used to draw insights into human resource allocation planning in traffic management to reduce road traffic congestion, injuries and vehicular emissions. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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17 pages, 1539 KiB  
Article
Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting
by Ke Wang, Qingwen Xue, Yingying Xing and Chongyi Li
Int. J. Environ. Res. Public Health 2020, 17(7), 2375; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17072375 - 31 Mar 2020
Cited by 20 | Viewed by 2698
Abstract
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggressive drivers in real traffic is infrequent, most [...] Read more.
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggressive drivers in real traffic is infrequent, most machine learning algorithms treat each sample equally and prone to better predict normal drivers rather than aggressive drivers, which is our real interest. This paper aims to test the advantage of imbalanced class boosting algorithms in aggressive driver recognition using vehicle trajectory data. First, a surrogate measurement of collision risk, called Average Crash Risk (ACR), is proposed to calculate a vehicle’s crash risk. Second, the driver’s driving aggressiveness is determined by his/her ACR with three anomaly detection methods. Third, we train classification models to identify aggressive drivers using partial trajectory data. Three imbalanced class boosting algorithms, SMOTEBoost, RUSBoost, and CUSBoost, are compared with cost-sensitive AdaBoost and cost-sensitive XGBoost. Additionally, we try two resampling techniques with AdaBoost and XGBoost. Among all algorithms tested, CUSBoost achieves the highest or the second-highest Area Under Precision-Recall Curve (AUPRC) in most datasets. We find the discrete Fourier coefficients of gap as the key feature to identify aggressive drivers. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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16 pages, 5334 KiB  
Article
Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea
by Seung-Hoon Park and Min-Kyung Bae
Int. J. Environ. Res. Public Health 2020, 17(7), 2358; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17072358 - 31 Mar 2020
Cited by 16 | Viewed by 3281
Abstract
Pedestrian-vehicle crashes can result in serious injury to pedestrians, who are exposed to danger when in close proximity to moving vehicles. Furthermore, these injuries can be considerably serious and even lead to death in a manner that varies depending on the pedestrian’s age. [...] Read more.
Pedestrian-vehicle crashes can result in serious injury to pedestrians, who are exposed to danger when in close proximity to moving vehicles. Furthermore, these injuries can be considerably serious and even lead to death in a manner that varies depending on the pedestrian’s age. This is because the pedestrian’s physical characteristics and behaviors, particularly in relation to roads with moving vehicles, differ depending on the pedestrian’s age. This study examines the determinants of pedestrian injury severity by pedestrian age using binary logistic regression. Factors in the built environment, such as road characteristics and land use of the places where pedestrian crashes occurred, were considered, as were the accident characteristics of the pedestrians and drivers. The analysis determined that the accident characteristics of drivers and pedestrians are more influential in pedestrian-vehicle crashes than the factors of the built environmental characteristics. However, there are substantial differences in injury severity relative to the pedestrian’s age. Young pedestrians (aged under 20 years old) are more likely to suffer serious injury in school zones; however, no association between silver zones and injury severity is found for elderly pedestrians. For people in the age range of 20–39 years old, the severity of pedestrian injuries is lower in areas with more crosswalks and speed cameras. People in the age range of 40–64 years old are more likely to be injured in areas with more neighborhood streets and industrial land use. Elderly pedestrians are likely to suffer fatal injuries in areas with more traffic signals. This study finds that there are differences in the factors of pedestrian injury severity according to the age of pedestrians. Therefore, it is suggested that concrete and efficient policies related to pedestrian age are required to improve pedestrian safety and reduce pedestrian-vehicle crashes. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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16 pages, 912 KiB  
Article
Health Care and Productivity Costs of Non-Fatal Traffic Injuries: A Comparison of Road User Types
by Marjolein van der Vlegel, Juanita A. Haagsma, Leonie de Munter, Mariska A. C. de Jongh and Suzanne Polinder
Int. J. Environ. Res. Public Health 2020, 17(7), 2217; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17072217 - 26 Mar 2020
Cited by 12 | Viewed by 2507
Abstract
This study aimed to provide a detailed overview of the health care and productivity costs of non-fatal road traffic injuries by road user type. In a cohort study in the Netherlands, adult injury patients admitted to a hospital as a result of a [...] Read more.
This study aimed to provide a detailed overview of the health care and productivity costs of non-fatal road traffic injuries by road user type. In a cohort study in the Netherlands, adult injury patients admitted to a hospital as a result of a traffic accident completed questionnaires 1 week and 1, 3, 6, 12 and 24 months after injury, including the iMTA Medical Consumption and Productivity Cost Questionnaire. In-hospital, post-hospital medical costs and productivity costs were calculated up to two years after traffic injury. In total, 1024 patients were included in this study. The mean health care costs per patient were € 8200. The mean productivity costs were € 5900. Being female, older age, with higher injury severity and having multiple comorbidities were associated with higher health care costs. Higher injury severity and being male were associated with higher productivity costs. Pedestrians aged ≥ 65 years had the highest mean health care costs (€ 18,800) and motorcyclists the highest mean productivity costs (€ 9000). Bicycle injuries occurred most often in our sample (n = 554, 54.1%) and accounted for the highest total health care and productivity costs. Considering the high proportion of total costs incurred by bicycle injuries, this is an important area for the prevention of traffic injuries. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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22 pages, 6066 KiB  
Article
Relationship Between Traffic Volume and Accident Frequency at Intersections
by Angus Eugene Retallack and Bertram Ostendorf
Int. J. Environ. Res. Public Health 2020, 17(4), 1393; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17041393 - 21 Feb 2020
Cited by 35 | Viewed by 6070
Abstract
Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic [...] Read more.
Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic accidents. This paper aims to improve our understanding of this relationship by analysing accidents at 120 intersections in Adelaide, Australia. Data comprised of 1629 motor vehicle accidents with traffic volumes from a dataset of more than five million hourly measurements. The effect of rainfall was also examined. Results showed an approximately linear relationship between traffic volume and accident frequency at lower traffic volumes. In the highest traffic volumes, poisson and negative binomial models showed a significant quadratic explanatory term as accident frequency increases at a higher rate. This implies that focusing management efforts on avoiding these conditions would be most effective in reducing accident frequency. The relative risk of rainfall on accident frequency decreases with increasing congestion index. Accident risk is five times greater during rain at low congestion levels, successively decreasing to no elevated risk at the highest congestion level. No significant effect of congestion index on accident severity was detected. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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19 pages, 2887 KiB  
Article
Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China
by Yingying Xing, Shengdi Chen, Shengxue Zhu, Yi Zhang and Jian Lu
Int. J. Environ. Res. Public Health 2020, 17(4), 1344; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17041344 - 19 Feb 2020
Cited by 26 | Viewed by 3297
Abstract
With the increasing demand of hazardous material (Hazmat), traffic accidents occurred frequently during Hazmat transportation, which had caused widespread concern in communities. Therefore, a good understanding of Hazmat transportation accident characteristics and contributing factors is of practical importance. In this study, 1721 Hazmat [...] Read more.
With the increasing demand of hazardous material (Hazmat), traffic accidents occurred frequently during Hazmat transportation, which had caused widespread concern in communities. Therefore, a good understanding of Hazmat transportation accident characteristics and contributing factors is of practical importance. In this study, 1721 Hazmat accidents that have occurred during road transportation for the period 2014–2017 in China were examined, and a random-parameters ordered probit model was established to explore the influence of contributing factors on the severity of accidents by accounting for unobserved heterogeneity in the data. Both the injuries and the number of people evacuated were considered as the indicator of accident severity and investigated, respectively. Results show that higher injury severity is likely to be associated with type of Hazmat (compressed gas, explosive, and poison), misoperation, driver fatigue, speeding, tunnel, slope, county road, dry road surface, winter, dark, more than two vehicles, rear end crash, and explosion. As for the correlation between risk factors and the severity of evacuation, type of Hazmat (compressed gas, explosive, and poison), quantity of Hazmat (10–39 t), misoperation, county road, dry road surface, weekdays, dusk, explosion significantly contribute to increasing the severity of evacuation of Hazmat accidents. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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17 pages, 2062 KiB  
Article
Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver’s Rear-End Risk Compensation Behavior via a Driving Simulator Study
by Yunxing Chen, Rui Fu, Qingjin Xu and Wei Yuan
Int. J. Environ. Res. Public Health 2020, 17(4), 1328; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17041328 - 19 Feb 2020
Cited by 18 | Viewed by 3118
Abstract
Mobile phone use while driving has become one of the leading causes of traffic accidents and poses a significant threat to public health. This study investigated the impact of speech-based texting and handheld texting (two difficulty levels in each task) on car-following performance [...] Read more.
Mobile phone use while driving has become one of the leading causes of traffic accidents and poses a significant threat to public health. This study investigated the impact of speech-based texting and handheld texting (two difficulty levels in each task) on car-following performance in terms of time headway and collision avoidance capability; and further examined the relationship between time headway increase strategy and the corresponding accident frequency. Fifty-three participants completed the car-following experiment in a driving simulator. A Generalized Estimating Equation method was applied to develop the linear regression model for time headway and the binary logistic regression model for accident probability. The results of the model for time headway indicated that drivers adopted compensation behavior to offset the increased workload by increasing their time headway by 0.41 and 0.59 s while conducting speech-based texting and handheld texting, respectively. The model results for the rear-end accident probability showed that the accident probability increased by 2.34 and 3.56 times, respectively, during the use of speech-based texting and handheld texting tasks. Additionally, the greater the deceleration of the lead vehicle, the higher the probability of a rear-end accident. Further, the relationship between time headway increase patterns and the corresponding accident frequencies showed that all drivers’ compensation behaviors were different, and only a few drivers increased their time headway by 60% or more, which could completely offset the increased accident risk associated with mobile phone distraction. The findings provide a theoretical reference for the formulation of traffic regulations related to mobile phone use, driver safety education programs, and road safety public awareness campaigns. Moreover, the developed accident risk models may contribute to the development of a driving safety warning system. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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15 pages, 17639 KiB  
Article
Using Vehicle-to-Vehicle Communication to Improve Traffic Safety in Sand-dust Environment
by Jinhua Tan, Xuqian Qin and Li Gong
Int. J. Environ. Res. Public Health 2020, 17(4), 1165; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17041165 - 12 Feb 2020
Cited by 4 | Viewed by 2445
Abstract
Sand-dust environment affects drivers’ perceptions of surrounding traffic conditions, resulting in unsafe operations. From an ergonomics perspective, such adverse effects could be alleviated by environment control as well as the assistance of machines. Vehicle-to-vehicle (V2V) communication appears to be an important component of [...] Read more.
Sand-dust environment affects drivers’ perceptions of surrounding traffic conditions, resulting in unsafe operations. From an ergonomics perspective, such adverse effects could be alleviated by environment control as well as the assistance of machines. Vehicle-to-vehicle (V2V) communication appears to be an important component of machines in future traffic systems, which could support the driving task. In order to explore what influences V2V communication would generate on traffic systems, this paper proposes a car-following model accounting for V2V communication in a sand-dust environment. The results indicate that V2V communication helps to reduce the fluctuations of acceleration, headway, and velocity, when a small perturbation is added to the traffic flow in sand-dust environment. If a vehicle in the traffic flow stops suddenly, the number of crumped vehicles decreases with V2V communication taken into account. Furthermore, the residual velocities of the crumped vehicles decrease, which means the severity of collision is suppressed. It is concluded that V2V communication can play an active role in the improvement of traffic safety in a sand-dust environment. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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13 pages, 3189 KiB  
Article
Automatic Emergency Braking (AEB) System Impact on Fatality and Injury Reduction in China
by Hong Tan, Fuquan Zhao, Han Hao, Zongwei Liu, Amer Ahmad Amer and Hassan Babiker
Int. J. Environ. Res. Public Health 2020, 17(3), 917; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17030917 - 02 Feb 2020
Cited by 27 | Viewed by 6732
Abstract
The automatic emergency braking (AEB) system is an effective intelligent vehicle active safety system for avoiding certain types of collisions. This study develops a national-level safety impact evaluation model for this intelligent vehicle function, including the potential maximum impact and realistic impact. The [...] Read more.
The automatic emergency braking (AEB) system is an effective intelligent vehicle active safety system for avoiding certain types of collisions. This study develops a national-level safety impact evaluation model for this intelligent vehicle function, including the potential maximum impact and realistic impact. The evaluation model was firstly applied in China to provide insights into Chinese policymaking. Road traffic fatality and severe injury trends, the proportion of different collision types, the effectiveness of collision avoidance, and the AEB market penetration rates are considered in the potential maximum impact scenario. Furthermore, the AEB activation rate and the technology’s technical limitations, including its effectiveness in different weather, light, and speed conditions, are discussed in the realistic scenario. With a 100% market penetration rate, fatalities could be reduced by 13.2%, and injuries could be reduced by 9.1%. Based on China’s policy, the market penetration rate of intelligent vehicles with AEB is predicted to be 34.0% in 2025 and 60.3% in 2030. With this large market penetration rate increase of AEB, the reductions in fatalities and severe injuries are 903–2309 and 2025–5055 in 2025; and 1483–3789 and 3895–7835 in 2030, respectively. Considering AEB’s activation rate and its three main limitations, the adjusted realistic result is approximately 2/5 of the potential maximum result. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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17 pages, 4518 KiB  
Article
Analysis of Driving Behavior Based on Dynamic Changes of Personality States
by Fanyu Wang, Junyou Zhang, Shufeng Wang, Sixian Li and Wenlan Hou
Int. J. Environ. Res. Public Health 2020, 17(2), 430; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17020430 - 08 Jan 2020
Cited by 14 | Viewed by 3597
Abstract
This study investigated the relationship between personality states and driving behavior from a dynamic perspective. A personality baseline was introduced to reflect the driver’s trait level and can be used as a basic reference for the dynamic change of personality states. Three kinds [...] Read more.
This study investigated the relationship between personality states and driving behavior from a dynamic perspective. A personality baseline was introduced to reflect the driver’s trait level and can be used as a basic reference for the dynamic change of personality states. Three kinds of simulated scenarios triggered by pedestrian crossing the street were established using a virtual reality driving simulator. Fifty licensed drivers completed the driving experiments and filled in the Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) questionnaire to measure the drivers’ personality baselines. Key indicators were quantified to characterize the five types of personality states by K-means clustering algorithm. The results indicated that the high-risk situation had a greater impact on the drivers, especially for drivers with openness and extroversion. Furthermore, for the drivers of extroverted personality, the fluctuation of personality states in the high-risk scenario was more pronounced. This paper put forward a novel idea for the analysis of driving behavior, and the research results provide a personalized personality database for the selection of different driving modes. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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23 pages, 2895 KiB  
Article
The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies
by Arshad Jamal, Muhammad Tauhidur Rahman, Hassan M. Al-Ahmadi and Umer Mansoor
Int. J. Environ. Res. Public Health 2020, 17(1), 157; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010157 - 24 Dec 2019
Cited by 53 | Viewed by 8834
Abstract
Road traffic crashes (RTCs) are one of the most critical public health problems worldwide. The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per 100,000 people) due to RTCs in the Kingdom of Saudi Arabia (KSA) has increased [...] Read more.
Road traffic crashes (RTCs) are one of the most critical public health problems worldwide. The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per 100,000 people) due to RTCs in the Kingdom of Saudi Arabia (KSA) has increased from 17.4 to 27.4 over the last decade, which is an alarming situation. This paper presents an overview of RTCs in the Eastern Province, KSA, from 2009 to 2016. Key descriptive statistics for spatial and temporal distribution of crashes are presented. Statistics from the present study suggest that the year 2012 witnessed the highest number of crashes, and that the region Al-Ahsa had a significantly higher proportion of total crashes. It was concluded that the fatality rate for the province was 25.6, and the mean accident to injury ratio was 8:4. These numbers are substantially higher compared to developed countries and the neighboring Gulf states. Spatial distribution of crashes indicated that a large proportion of severe crashes occurred outside the city centers along urban highways. Logistic regression models were developed to predict crash severity. Model estimation analysis revealed that crash severity can be attributed to several significant factors including driver attributes (such as sleep, distraction, overspeeding), crash characteristics (such as sudden deviation from the lane, or collisions with other moving vehicles, road fences, pedestrians, or motorcyclists), and rainy weather conditions. After critical analysis of existing safety and infrastructure situations, various suitable crash prevention and mitigation strategies, for example, traffic enforcement, traffic calming measures, safety education programs, and coordination of key stakeholders, have been proposed. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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16 pages, 657 KiB  
Article
Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment
by Rachel Aldred, Susana García-Herrero, Esther Anaya, Sixto Herrera and Miguel Ángel Mariscal
Int. J. Environ. Res. Public Health 2020, 17(1), 96; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010096 - 21 Dec 2019
Cited by 14 | Viewed by 4532
Abstract
This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least [...] Read more.
This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least one injured cyclist, of whom 7230 were injured cyclists. Bayesian methods were used to model relationships between cyclist injury severity and circumstances related to the crash, with the outcome variable being whether a cyclist was killed or seriously injured (KSI) rather than slightly injured. Factors in the model included those relating to the injured cyclist, the route environment, and involved motorists. Injury severity among cyclists was likely to be higher where an Heavy Goods Vehicle (HGV) was involved, and certain route conditions (bicycle infrastructure, 30 kph zones, and urban zones) were associated with lower injury severity. Interactions exist between the two: collisions involving large vehicles in lower-risk environments are less likely to lead to KSIs than collisions involving large vehicles in higher-risk environments. Finally, motorists involved in a collision were more likely than the injured cyclists to have committed an error or infraction. The study supports the creation of infrastructure that separates cyclists from motor traffic. Also, action needs to be taken to address motorist behaviour, given the imbalance between responsibility and risk. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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15 pages, 2714 KiB  
Article
Effect of Imitation Phenomenon on Two-Lane Traffic Safety in Fog Weather
by Jinhua Tan, Li Gong and Xuqian Qin
Int. J. Environ. Res. Public Health 2019, 16(19), 3709; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph16193709 - 01 Oct 2019
Cited by 7 | Viewed by 2299
Abstract
A neighboring lane’s vehicles are potentially important influence factors of traffic safety. In fog weather, drivers will automatically imitate the behaviors demonstrated by other vehicles in the neighboring lane. To illustrate the effect of the imitation phenomenon on traffic safety, this paper develops [...] Read more.
A neighboring lane’s vehicles are potentially important influence factors of traffic safety. In fog weather, drivers will automatically imitate the behaviors demonstrated by other vehicles in the neighboring lane. To illustrate the effect of the imitation phenomenon on traffic safety, this paper develops an extended two-lane car-following model in fog weather. Numerical simulations are carried out to study the effect of imitation on multiple-vehicle collision induced by a sudden stop, as well as perturbation propagation when a small perturbation is added to the uniform traffic flow. The results indicate that the number of collisions depends on the influence coefficient of neighboring lane’s vehicles, sensitivity, headway and initial velocity. Furthermore, the number of crumpled vehicles decreases when the imitation phenomenon is taken into account. In addition, lower vehicular velocity in the neighboring lane can reduce the magnitude of acceleration and fluctuation of headway. The perturbation can be absorbed under certain given conditions regarding the imitation phenomenon. Therefore, traffic safety can be improved by considering the effect of the imitation phenomenon on two-lane traffic flow in fog weather. The findings in this study can provide a theoretical reference for the development of multi-lane intermittent release measures in fog weather. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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14 pages, 1315 KiB  
Article
Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS
by Mingyu Kang, Anne Vernez Moudon, Haena Kim and Linda Ng Boyle
Int. J. Environ. Res. Public Health 2019, 16(19), 3565; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph16193565 - 24 Sep 2019
Cited by 4 | Viewed by 3205
Abstract
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a [...] Read more.
Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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11 pages, 567 KiB  
Article
The Association between Mobile Phone Use and Severe Traffic Injuries: A Case-Control Study from Saudi Arabia
by Suliman Alghnam, Jawaher Towhari, Mohamed Alkelya, Ahmad Alsaif, Mohamed Alrowaily, Fawaz Alrabeeah and Ibrahim Albabtain
Int. J. Environ. Res. Public Health 2019, 16(15), 2706; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph16152706 - 29 Jul 2019
Cited by 25 | Viewed by 4650
Abstract
Road traffic injury (RTI) is the third leading cause of death in Saudi Arabia. Using a mobile phone when driving is associated with distracted driving, which may result in RTIs. Because of limited empirical data, we investigated the association between mobile phone use [...] Read more.
Road traffic injury (RTI) is the third leading cause of death in Saudi Arabia. Using a mobile phone when driving is associated with distracted driving, which may result in RTIs. Because of limited empirical data, we investigated the association between mobile phone use and RTI in injured patients and community controls in Riyadh. Cases were patients admitted to King Abdulaziz Medical City (KAMC) between October 2016 and March 2018 due to RTIs. During admission, mobile phone use at the time of the accident was investigated. The controls were drivers observed at various locations citywide. A logistic regression model was constructed to estimate the association between mobile phone use while driving and sustaining RTIs. We included 318 cases and 1700 controls. For the cases, using a mobile phone was associated with higher severity and prevalence of disability. In addition, using a mobile phone while driving is associated with 44% higher odds of incurring a severe RTI (p = 0.04). Mobile phone use while driving is prevalent in Riyadh and pose a significant threat of disability. In addition, the low prevalence of seatbelt use is alarming and requires significant improvement. Prevention programs may use these findings to educate the public and policymakers and to advocate for increased visibility of enforcement to reduce RTIs and improve population health. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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20 pages, 2038 KiB  
Article
Optimal Evacuation Strategy for Parking Lots Considering the Dynamic Background Traffic Flows
by Xinhua Mao, Changwei Yuan, Jiahua Gan and Jibiao Zhou
Int. J. Environ. Res. Public Health 2019, 16(12), 2194; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph16122194 - 21 Jun 2019
Cited by 6 | Viewed by 3181
Abstract
An optimal evacuation strategy for parking lots can shorten evacuation times and reduce casualties and economic loss. However, the impact of dynamic background traffic flows in a road network on the evacuation plan is rarely taken into account in existing approaches. This research [...] Read more.
An optimal evacuation strategy for parking lots can shorten evacuation times and reduce casualties and economic loss. However, the impact of dynamic background traffic flows in a road network on the evacuation plan is rarely taken into account in existing approaches. This research develops an optimal evacuation model with total evacuation time minimization by dividing the evacuation process in a parking lot into two periods. In the first period, a queuing theory is used to estimate the queuing time, and in the second period, a traffic flow equilibrium model and an intersection delay model are employed to simulate vehicles’ route choice. To deal with these models, a modified ant colony algorithm is developed. The results of a numerical example prove that the proposed method has an advantage in improving evacuation efficiency. The results also show that background traffic flows affect not only vehicles’ average queuing time in parking lots but also optimal evacuation route choice. Additionally, a sensitivity analysis indicates that the minimum threshold of headway time that allows vehicles out of a parking lot to merge into the background traffic flows on the roads connecting the exits has a great impact on average queuing time, average travel time, and total evacuation time. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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Jump to: Research

24 pages, 12539 KiB  
Technical Note
Digital Reconstitution of Road Traffic Accidents: A Flexible Methodology Relying on UAV Surveying and Complementary Strategies to Support Multiple Scenarios
by Luís Pádua, José Sousa, Jakub Vanko, Jonáš Hruška, Telmo Adão, Emanuel Peres, António Sousa and Joaquim J. Sousa
Int. J. Environ. Res. Public Health 2020, 17(6), 1868; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17061868 - 13 Mar 2020
Cited by 16 | Viewed by 4591
Abstract
The reconstitution of road traffic accidents scenes is a contemporary and important issue, addressed both by private and public entities in different countries around the world. However, the task of collecting data on site is not generally focused on with the same orientation [...] Read more.
The reconstitution of road traffic accidents scenes is a contemporary and important issue, addressed both by private and public entities in different countries around the world. However, the task of collecting data on site is not generally focused on with the same orientation and relevance. Addressing this type of accident scenario requires a balance between two fundamental yet competing concerns: (1) information collecting, which is a thorough and lengthy process and (2) the need to allow traffic to flow again as quickly as possible. This technical note proposes a novel methodology that aims to support road traffic authorities/professionals in activities involving the collection of data/evidences of motor vehicle collision scenarios by exploring the potential of using low-cost, small-sized and light-weight unmanned aerial vehicles (UAV). A high number of experimental tests and evaluations were conducted in various working conditions and in cooperation with the Portuguese law enforcement authorities responsible for investigating road traffic accidents. The tests allowed for concluding that the proposed method gathers all the conditions to be adopted as a near future approach for reconstituting road traffic accidents and proved to be: faster, more rigorous and safer than the current manual methodologies used not only in Portugal but also in many countries worldwide. Full article
(This article belongs to the Special Issue Traffic Accident Control and Prevention)
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