Journal of Advanced Transportation

Safety, Behavior, and Sustainability under the Mixed Traffic Flow Environment


Publishing date
01 May 2020
Status
Closed
Submission deadline
03 Jan 2020

Lead Editor

1Tongji University, Shanghai, China

2University of Central Florida, Orlando, USA

3Khalifa University of Science and Technology, Abu Dhabi, UAE

4South China University of Technology, Guangzhou, China

This issue is now closed for submissions.
More articles will be published in the near future.

Safety, Behavior, and Sustainability under the Mixed Traffic Flow Environment

This issue is now closed for submissions.
More articles will be published in the near future.

Description

In complex urban areas mixed traffic consists of various users, including motor vehicles, motorcycles, scooters, bicycles, and pedestrians, which causes numerous problems not only in traffic operation but also in traffic safety. Combined with roadways with complex features and/or inclement weather, this kind of mixed traffic flow environment can cause difficulty for drivers in making the right choices and decisions within a given time. These problems have attracted more and more attention in the transportation research field.

Furthermore, with the rapid development of autonomous driving, an emerging type of mixed traffic flow with manual driving and connected/autonomous vehicles has also arisen. In such an environment, more studies are needed to tackle the questions of traffic safety, drivers’ behavior, and facility sustainability for this different traffic environment. Intelligent transportation systems and driving assistance systems could potential solutions to improve safety, behavior, and sustainability under this mixed traffic flow environment.

The proposed special issue aims to compile recent studies particularly related to three topics—traffic safety, driving behavior, and sustainability—under the mixed traffic flow environment. Original research and review articles related to the influence of a mixed traffic flow environment will be considered. All aspects of statistical analyses, machine learning, driving simulator experiments, and naturalistic driving experiments are of interest. We also welcome submissions with a focus on field tests or surveys, to better understand the interactions between the mixed traffic flow environment and driver behavior considering traffic safety and sustainability.

Potential topics include but are not limited to the following:

  • Crash risk assessment under the mixed traffic flow environment
  • Drivers’ behavior under the mixed traffic flow environment
  • Facility sustainability and optimal design under the mixed traffic flow environment
  • Data analysis, modeling, and simulation studies on the mixed traffic flow environment
  • Driver simulators and naturalistic driving experiments under the mixed traffic flow environment
  • The effect of intelligent and connected vehicle (ICV) on the mixed traffic flow environment
  • Evaluation of driving assistance systems in the mixed traffic flow environment
  • Analysis of traffic safety and/or operation under the mixed traffic flow environment with complex features or under inclement weather
  • Investigation of safety of vulnerable road users (e.g., motorcyclists, scooters, bicycles, and pedestrians) in the mixed traffic flow environment
  • Novel urban planning strategies for maintaining sustainability under the mixed traffic flow environment of the future

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 1269415
  • - Research Article

A Proportional-Switch Adjustment Model towards Mixed Equilibrium with Multiroute Choice Behaviour Criterion

Zhongxiang Huang | Xiangjun Jiang | Wei Hao
  • Special Issue
  • - Volume 2020
  • - Article ID 4795830
  • - Research Article

Discovering the Graph-Based Flow Patterns of Car Tourists Using License Plate Data: A Case Study in Shenzhen, China

He Bing | Kong Bo | ... | Ma Zhanwu
  • Special Issue
  • - Volume 2020
  • - Article ID 9401062
  • - Research Article

Deployment Optimization of Connected and Automated Vehicle Lanes with the Safety Benefits on Roadway Networks

Zhibo Gao | Zhizhou Wu | ... | Kejun Long
  • Special Issue
  • - Volume 2020
  • - Article ID 3754062
  • - Research Article

Research on Mandatory Lane-Changing Behavior in Highway Weaving Sections

Wei Hao | Zhaolei Zhang | ... | Jie Wang
  • Special Issue
  • - Volume 2020
  • - Article ID 1528028
  • - Research Article

Sectional Information-Based Collision Warning System Using Roadside Unit Aggregated Connected-Vehicle Information for a Cooperative Intelligent Transport System

Sehyun Tak | Jinsu Yoon | ... | Hwasoo Yeo
  • Special Issue
  • - Volume 2020
  • - Article ID 4219562
  • - Research Article

Fatigue Driving Prediction on Commercial Dangerous Goods Truck Using Location Data: The Relationship between Fatigue Driving and Driving Environment

Shifeng Niu | Guiqiang Li
  • Special Issue
  • - Volume 2020
  • - Article ID 7475682
  • - Research Article

Risk Modeling and Quantification of a Platoon in Mixed Traffic Based on the Mass-Spring-Damper Model

Luo Jiang | Jie Ji | ... | Yanjun Huang
  • Special Issue
  • - Volume 2020
  • - Article ID 2793150
  • - Research Article

Risk Analysis of Vehicle Rear-End Collisions at Intersections

Sheng Dong | Minjie Zhang | Zhenjiang Li
  • Special Issue
  • - Volume 2020
  • - Article ID 8573232
  • - Research Article

Exploring Factors Affecting the Yellow-Light Running Behavior of Electric Bike Riders at Urban Intersections in China

Jing Cai | Jianyou Zhao | ... | Yuntao Ye
  • Special Issue
  • - Volume 2020
  • - Article ID 1250827
  • - Research Article

A Comparative Study on Drivers’ Stop/Go Behavior at Signalized Intersections Based on Decision Tree Classification Model

Sheng Dong | Jibiao Zhou
Journal of Advanced Transportation
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
Acceptance rate36%
Submission to final decision106 days
Acceptance to publication75 days
CiteScore3.000
Impact Factor1.670
 Submit