Risk perception and the warning strategy based on microscopic driving state

The paper aimed to explore the relationship between risks and individuals’ driving states and then design an efficient method to help drivers avoid high risks. The relationship between risks and individuals’ driving states was deeply studied first. Microscopic driving states were categorized into different clusters, and it was found that the risks are distinct in different clusters and a specific driver might experience different risks in car-following process. Then, according to these findings, a risk warning strategy was designed to help drivers avoid high risks. The risk warning is active when the risk is higher than its threshold. The Helly models were used to mimic the drivers’ reaction to study the influence of the warning strategy. Simulation results showed that with the consideration of the risk warning, the spacing obviously increases, and the oscillations of velocity and acceleration are significantly shrunk, and risks in the driving process dampen down. Because drivers can perceive high risks during the driving process, and then appropriately change their car-following decisions to avoid high risks. These findings are helpful to improve driving behaviors and promote traffic safety.

• Record URL:
  https://doi.org/10.1016/j.aap.2018.02.012
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0001457518300630
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhao, Xiaomei
  • Li, Qian
  • Xie, Dongfan
  • Bi, Jun
  • Lu, Rongqin
  • Li, Chao
• Publication Date: 2018-9

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 154-165
• Serial:
  • Accident Analysis & Prevention
  • Volume: 118
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Drivers; Microscopic traffic flow; Risk assessment; Traffic safety; Warning systems
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01677044
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 30 2018 2:32PM