Research on expressway lane management strategy in intelligent networked hybrid traffic environment

YongZhen Chen

doi:10.1117/12.2619966

22 December 2021 Research on expressway lane management strategy in intelligent networked hybrid traffic environment

YongZhen Chen

Proceedings Volume 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021); 120582L (2021) https://doi.org/10.1117/12.2619966
Event: 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 2021, Chongqing, China

Abstract

In recent years, connected and automated vehicles (CAVs) technology has attracted a lot of attention in the transportation field because CAVs have unique operational characteristics compared to human-driven vehicles (HVs) and are expected to revolutionize the current transportation landscape. The objective is to solve the traffic problems in the future intelligent network environment, and the lane management strategy research can effectively solve the traffic problems under mixed traffic flow. In mixed traffic between intelligent connected vehicles and conventional vehicles, lane management strategies are combined with intelligent connected vehicle technology to effectively utilize the advantages of both and improve traffic conditions. In this paper, we model the mixed traffic flow and lane management strategies for simulation, and the results show that lane management in a smart connected hybrid traffic environment can effectively enhance the queuing effect between CAVs and mitigate the interference between connected vehicles and conventional vehicles, thus improving highway throughput.

Citation Download Citation

YongZhen Chen "Research on expressway lane management strategy in intelligent networked hybrid traffic environment", Proc. SPIE 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 120582L (22 December 2021); https://doi.org/10.1117/12.2619966

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available