International Journal of Environmental Research and Public Health

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Dear Colleagues,

With the continuous improvement of transportation infrastructure and intelligent connected vehicles, the intelligence of the transportation system is gradually improving. Intelligent transportation systems are showing new trends and characteristics, such as vehicle telematics, cooperative vehicle infrastructure system, autonomous driving. Different from the traditional road traffic environment, the perception, cognition, and decision-making behaviors of drivers in the intelligent and connected environment fundamentally change. Intelligent transportation systems present potential opportunities for improved traffic safety, efficiency and energy savings; while the gradual penetration of intelligent connected vehicles also makes the traffic operation characteristics more complicated. Facing the changes in Intelligent Transportation Systems, it urgently needs to research the following issues in this field: analyzing characteristics of travel and driving behavior under the background of intelligent transportation systems, exploring the characteristics of traffic flow and the risk evolution under intelligent transportation system, modeling the impact of intelligent transportation technology on transportation systems; proposing driving behavior intervention and risk control method in the intelligent transportation system. Papers addressing these topics are invited for this Special Issue.

Dr. Nengchao Lyu
Prof. Dr. Adriana Tapus
Dr. Quan Yuan
Guest Editors

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Keywords

intelligent transportation systems
traffic safety
driving behaviors
accident analysis
intelligent and connected vehicles
human factors
traffic control

Published Papers (2 papers)

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Research

15 pages, 3135 KiB

Open AccessArticle

Quantifying the Impact of Deployments of Autonomous Vehicles and Intelligent Roads on Road Safety in China: A Country-Level Modeling Study

by Hong Tan, Fuquan Zhao, Haokun Song and Zongwei Liu

Int. J. Environ. Res. Public Health 2023, 20(5), 4069; https://doi.org/10.3390/ijerph20054069 - 24 Feb 2023

Cited by 3 | Viewed by 1557

Abstract

Approximately 1.35 million people lose their lives due to road traffic collisions worldwide per year. However, the variation of road safety depending on the deployment of Autonomous Vehicles (AV), Intelligent Roads (IR), and Vehicle-to-Vehicle technology (V2V) is largely unknown. In this analysis, a bottom-up analytical framework was developed to evaluate the safety benefits of avoiding road injuries and reducing crash-related economic costs from the deployment of AVs, IRs, and V2Vs in China in 26 deployment scenarios from 2020 to 2050. The results indicate that compared with only deploying AVs, increasing the availability of IRs and V2V while reducing the deployment of fully AVs can achieve larger safety benefits in China. Increasing the deployment of V2V while reducing the deployment of IRs can sometimes achieve similar safety benefits. The deployment of AVs, IRs, and V2V plays different roles in achieving safety benefits. The large-scale deployment of AVs is the foundation of reducing traffic collisions; the construction of IRs would determine the upper limit of reducing traffic collisions, and the readiness of connected vehicles would influence the pace of reducing traffic collisions, which should be designed in a coordinated manner. Only six synergetic scenarios with full equipment of V2V can meet the SDG 3.6 target for reducing casualties by 50% in 2030 compared to 2020. In general, our results highlight the importance and the potential of the deployment of AVs, IRs, and V2V to reduce road fatalities and injuries. To achieve greater and faster safety benefits, the government should prioritize to the deployment of IRs and V2V. The framework developed in this study can provide practical support for decision-makers to design strategies and policies on the deployment of AVs and IRs, which can also be applied in other countries. Full article

(This article belongs to the Special Issue Intelligent Transportation System Influences on Driving Behavior and Traffic Safety)

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20 pages, 7912 KiB

Open AccessArticle

An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field

by Yuning Wang, Shuocheng Yang, Jinhao Li, Shaobing Xu and Jianqiang Wang

Int. J. Environ. Res. Public Health 2023, 20(3), 2278; https://doi.org/10.3390/ijerph20032278 - 27 Jan 2023

Cited by 2 | Viewed by 1442

Abstract

Driver disability has become an increasing factor leading to traffic accidents, especially for commercial vehicle drivers who endure high mental and physical pressure because of long periods of work. Once driver disability occurs, e.g., heart disease or heat stroke, the loss of driving control may lead to serious traffic incidents and public damage. This paper proposes a novel driving intervention system for autonomous danger avoidance under driver disability conditions, including a quantitative risk assessment module named the Emergency Safety Field (ESF) and a motion-planning module. The ESF considers three factors affecting hedging behavior: road boundaries, obstacles, and target position. In the field-based framework, each factor is modeled as an individual risk source generating repulsive or attractive force fields. Individual risk distributions are regionally weighted and merged into one unified emergency safety field denoting the level of danger to the ego vehicle. With risk evaluation, a path–velocity-coupled motion planning module was designed to generate a safe and smooth trajectory to pull the vehicle over. The results of our experiments show that the proposed algorithms have obvious advantages in success rate, efficiency, stability, and safety compared with the traditional method. Validation on multiple simulation and real-world platforms proves the feasibility and adaptivity of the module in traffic scenarios. Full article

(This article belongs to the Special Issue Intelligent Transportation System Influences on Driving Behavior and Traffic Safety)

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