Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types

Luo, Qiang; Chen, Xinqiang; Yuan, Jie; Zang, Xiaodong; Yang, Jun; Chen, Jing

doi:10.1155/2020/7878656

Cited by 18 publications

(14 citation statements)

References 32 publications

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“…Traffic safety has become a major public health concern all around the world [1][2][3]. The traffic safety problem is multidimensional, and many risk factors, i.e., technical factors (vehicles), environmental factors (the road and infrastructures), human factors (the road users) and their interactions, contribute to causing crashes [4][5][6]. Generally, two approaches to traffic safety studies have been established so far [7,8].…”

Section: Introductionmentioning

confidence: 99%

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Boulagouas

Herrero

Chaib

et al. 2020

IJERPH

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Road traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.

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Section: Introductionmentioning

confidence: 99%

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Boulagouas

Herrero

Chaib

et al. 2020

IJERPH

View full text Add to dashboard Cite

show abstract

“…Obviously, the reaction time of the driver in the fatigue state is greater than that in the normal state. e reaction time at different ages varies, and the greatest difference in response time was in the age group 22-45 [19]. Zhang et al divided driving behavior types into five categories: conservative, cautious, conventional, radical, and adventurous [20].…”

Section: Driver Factorsmentioning

confidence: 99%

“…Our previous studies suggested that the driver reaction time is significantly positively relevant with driver fatigue magnitude, which can be quantified into the interval of [0, 10] [19]. More specifically, we consider that the driver fatigue degree is considered as a continuous parameter demonstrating the driver's travelling time on roadway.…”

Section: Driver Factorsmentioning

confidence: 99%

Research of Vehicle Rear-End Collision Model considering Multiple Factors

Luo

Zang

Yuan

et al. 2020

Mathematical Problems in Engineering

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e accuracy of the rear-end collision models is crucial for the early warning of potential traffic accident identification, and thus analyzes of the main factors influencing the rear-end collision relevant models is an active topic in the field. e previous studies have tried to determine the single factor influence on the rear-end collision model performance. Less attention was paid to exploit mutual influences on the model performance. To bridge the gap, we proposed an improved vehicle rear-end collision model by integrating varied factors which influence two parameters (i.e., response time and road adhesion coefficient). e two parameters were solved with the integrated weighting and neural network models, respectively. After that we analyzed the relationship between varied factors and the minimum car-following distance. e research findings support both the theoretical and practical guidance for transportation regulations to release more reasonable minimum headway distance to enhance the roadway traffic safety.On the basis of the traditional safety distance model, Kong et al. conducted information acquisition, distance judgment, braking, and other processes for active collision avoidance during vehicle travel. However, the judgment model used is relatively simple [5]. Jiang and Yu established a highway antitailing model based on radial basis function neural network by using traditional algorithms [6]. Nevertheless, the model is mainly applied to highways, and the influencing factors are considered to be single. Jing and Wang explored the influence of multiple vehicles on the driver and established a vehicle-following model considering the traffic state based on the full velocity difference (FVD) model [7]. Nonetheless, the model is too complicated to conduct to practical applications. Xia established a fuzzy inference system based on the characteristics (e.g., driving age, and gender) of the driver to determine the response time of different drivers and proposed an improved version of the safe model [8]. Peng and Sun derived the modified Korteweg-de Vries (mKdV) equation to describe the traffic

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“…Road traffic injuries rank sixth in the world in terms of years of life with disability, according to the World Health Organization [2]. Road safety is studied through different risk factors, such as infrastructure factors (type of road, lighting, pavements), human and behavioural factors (age, gender, actions taken) and vehicle factors (type of vehicle, speed of vehicles), and their interactions allow for a better understanding of the causes of road accidents and their impact on the injury rate of those involved [3,4].…”

Section: Introductionmentioning

confidence: 99%

Pedestrians’ Injury Severity in Traffic Accidents in Spain: A Pedestrian Actions Approach

et al. 2021

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Road traffic accidents are currently between the seventh and tenth leading cause of death in the world, with approximately 1.35 million people killed per year. Despite extensive efforts by governments, according to the World Health Organization, road accidents still cause far too many deaths, especially among pedestrians, cyclists and two-wheel motor vehicle riders, who together account for almost 50% of road traffic fatalities. In particular, Spain had 410,974 traffic accidents between 2016 and 2019, involving 722,516 vehicles and 61,177 pedestrians with varying degrees of injury. This study uses the Bayesian network method to understand how the pedestrians’ responsibility and actions at the time of the traffic accident affect the injury suffered by said pedestrian, also considering the variables of the road infrastructure and vehicles at the accident site. The results confirm that the variables linked to the unsafe behavior of pedestrians, and their responsibility in traffic accidents, increase the risk of suffering serious or fatal injuries during an accident; for example, if a pedestrian is distracted this increases his/her probability of suffering a severe injury (27.86%) with respect to not being distracted (20.73%). Conditions related to traffic in high-speed areas, areas with no or poor lighting, and areas lacking sidewalks, also record increases in pedestrian injury, as is the case in the age group of pedestrians over 60 years of age.

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Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types

Cited by 18 publications

References 32 publications

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Research of Vehicle Rear-End Collision Model considering Multiple Factors

Pedestrians’ Injury Severity in Traffic Accidents in Spain: A Pedestrian Actions Approach

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