Journal of Advanced Transportation

Traffic Efficiency and Safety in Mixed Traffic Flow Environments 2020


Publishing date
01 Mar 2021
Status
Published
Submission deadline
16 Oct 2020

Lead Editor

1Beijing Jiaotong University, Beijing, China

2University of Tennessee, Tennessee, USA

3Traffic Engineers, Inc., Texas, USA

4The Hong Kong Polytechnic University, Hong Kong

5University of Bath, London, UK


Traffic Efficiency and Safety in Mixed Traffic Flow Environments 2020

Description

The roadways are used simultaneously by passenger cars, trucks, buses, cyclists, pedestrians, etc. This creates a mixed traffic flow environment in which all the traffic participants share the available infrastructure. In addition, there is an increasing number of automated vehicles (AVs) appearing on roadways that are interacting with conventional traffic, which is forming a new type of mixed traffic flow environment.

There is a need for investigating the resulting effects of mixed traffic, and advanced research should be conducted to explore the traffic efficiency and safety in mixed traffic flow environment. Developing better traffic efficiency and safety methodologies, technologies, and policies are critical importance to reduce the traffic congestion, crashes, traffic-related air pollution, and improve the operation reliability of the mixed traffic flow. Enabled by emerging sensing technologies, big data analytics, and recent advances in driving experiments, traffic efficiency and safety research will greatly enhance our scientific understanding of the new interactions and phenomena in a mixed traffic flow environment.

The aim of this Special Issue is to collate original research and review articles with a focus on addressing the crucial aspects of traffic efficiency and safety issues in a mixed traffic flow environment, with particular emphasis on the interactions between motorized vehicles and non-motorized vehicles, passenger cars and trucks, conventional vehicles, and AVs. The Special Issue also welcomes scientific research that develops and refines methodologies and technologies using new sources of data, such as data from GPS, naturalistic driving, connected vehicles, social media, and smart phones.

Potential topics include but are not limited to the following:

  • Safety and efficiency performance assessment of mixed traffic flow
  • Safety and efficiency modelling of mixed traffic flow
  • The resulting effects of mixed traffic flow environment
  • Prediction of mixed traffic flow
  • Data-driven traffic efficiency and safety monitoring, assessment, and improvement
  • Methodological advancement in mixed traffic flow theory
  • Mixed traffic flow simulation
  • Innovative traffic efficiency and safety data collection, analyzing, and molding using advanced technologies
  • Advanced traffic safety and traffic flow efficiency management strategies and policies
  • Travel behaviors and activities modelling

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 6624452
  • - Research Article

A Multifeatures Spatial-Temporal-Based Neural Network Model for Truck Flow Prediction

Shengyou Wang | Chunfu Shao | ... | Yan Zheng
  • Special Issue
  • - Volume 2021
  • - Article ID 8849234
  • - Research Article

The Impact of Pedestrian and Nonmotorized Vehicle Violations on Vehicle Emissions at Signalized Intersections in the Real World: A Case Study in Beijing

Jianchang Huang | Guohua Song | ... | Lei Yu
  • Special Issue
  • - Volume 2021
  • - Article ID 6652278
  • - Research Article

Determining the Operator for the Public Toll Road

Bin Shang | Qiang Sun | ... | Jiancong Chang
  • Special Issue
  • - Volume 2021
  • - Article ID 8816540
  • - Research Article

Traffic Flow Characteristics and Lane Use Strategies for Connected and Automated Vehicles in Mixed Traffic Conditions

Zijia Zhong | Joyoung Lee | Liuhui Zhao
  • Special Issue
  • - Volume 2020
  • - Article ID 8897325
  • - Research Article

Traffic Speed Forecast in Adjacent Region between Highway and Urban Expressway: Based on MFD and GRU Model

Yuan Gao | Jiandong Zhao | ... | Bin Jia
  • Special Issue
  • - Volume 2020
  • - Article ID 8818496
  • - Research Article

Modeling Drivers’ Stopping Behaviors during Yellow Intervals at Intersections considering Group Heterogeneity

Juan Li | Hui Zhang | ... | Xuan Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 8878346
  • - Research Article

Expansion of the Fundamental Diagram from a Microscopic Multilane Modeling Framework of Mixed Traffic

Mudasser Seraj | Jiangchen Li | Tony Z. Qiu
  • Special Issue
  • - Volume 2020
  • - Article ID 8892693
  • - Research Article

A Discretionary Lane-Changing Decision-Making Mechanism Incorporating Drivers’ Heterogeneity: A Signalling Game-Based Approach

Haipeng Shao | Miaoran Zhang | ... | Yifan Dong
  • Special Issue
  • - Volume 2020
  • - Article ID 8850591
  • - Research Article

An Approach for Handling Uncertainties Related to Behaviour and Vehicle Mixes in Traffic Simulation Experiments with Automated Vehicles

Johan Olstam | Fredrik Johansson | ... | Markus Friedrich
  • Special Issue
  • - Volume 2020
  • - Article ID 8830731
  • - Research Article

Data-Driven Analysis of the Chaotic Characteristics of Air Traffic Flow

Zhaoyue Zhang | An Zhang | ... | Shanmei Li
Journal of Advanced Transportation
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Acceptance rate22%
Submission to final decision126 days
Acceptance to publication18 days
CiteScore3.900
Journal Citation Indicator0.480
Impact Factor2.3
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