Safety and Efficiency of Intersections With Mix of Connected and Non-Connected Vehicles

Connected and autonomous vehicles have been significantly studied. They are connected to a network and communicate by exchanging information with each other, so they can detect blind spots that cannot be recognized by non-connected (conventional) vehicles. Therefore, they are expected to contribute to traffic efficiency and safety. However, even if connected vehicles are put to practical use in the future, it will take time to spread to the market, so it is considered that connected vehicles and non-connected vehicles will be mixed on the road. The authors proposed a method of enabling connected vehicles to share the information gathered from their sensors on surrounding vehicles near intersection in the mixed situation. They then examined the safety and efficiency of passing through an intersection through simulation. They found that efficiency improved and safety could be ensured compared to using conventional methods such as stopping before the intersection without using communication and using traffic lights.

• Record URL:
  http://dx.doi.org/10.1109/OJITS.2020.2991464
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/26877813
• Supplemental Notes:
  • © 2020 Koki Higashiyama et al.
• Authors:
  • Higashiyama, Koki
  • Kimura, Kenta
  • Babakarkhail, Habibullah
  • Sato, Kenya
• Publication Date: 2020

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 29-34
• Serial:
  • IEEE Open Journal of Intelligent Transportation Systems
  • Volume: 1
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 2687-7813
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Connected vehicles; Highway safety; Intersections; Traffic calming; Vehicle to vehicle communications
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01787344
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 5 2021 11:54AM