Research on the characteristics of mixed traffic flow in an intelligent connected environment

Yicong Liu; Lunhui Xu

doi:10.1117/12.3024823

14 February 2024 Research on the characteristics of mixed traffic flow in an intelligent connected environment

Yicong Liu, Lunhui Xu

Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130180T (2024) https://doi.org/10.1117/12.3024823
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China

Abstract

To study the characteristics of the mixed traffic flow composed of manually driven vehicles and connected automated vehicles in the intelligent connected environment, mainly exploring the relationship between flow, density, and speed, this paper constructs a basic graphical model of the mixed traffic flow in the intelligent connected environment. First, four different car-following models in the mixed traffic flow are analyzed, as well as the corresponding percentage of following modes under different penetration rates of connected automated vehicles. Based on this, the different following models, and the corresponding model parameters, are applied to derive the fundamental diagram model of mixed traffic flow in the intelligent connected environment. Finally, the simulation is verified by designing SUMO simulation experiments. The simulation results show that the flow-density data scatters obtained under different connected automated vehicle occupancy ratios are in high agreement with the theoretical curves, which verifies the feasibility of the model.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yicong Liu and Lunhui Xu "Research on the characteristics of mixed traffic flow in an intelligent connected environment", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130180T (14 February 2024); https://doi.org/10.1117/12.3024823

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