Cooperative merging strategy between connected autonomous vehicles in mixed traffic
Journal article, 2022

In this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy. The new cooperation strategy considers a pair of vehicles approaching an on-ramp. The strategy then makes decisions on the target speeds/accelerations of both vehicles, possible lane changing, and a dynamic decision-making approach in order to reduce the risk during the cut-in manoeuvre. In this work, the CRI was first used to assess the risk during the merging manoeuvre. For this purpose, scenarios with penetration rates of autonomous vehicles from 20% to 100%, with step of 10%, both connected and non-connected autonomous vehicles were evaluated. As a result, on average a 35% reduction of the cut-in risk manoeuvres in connected autonomous vehicles compared to non-connected autonomous vehicles is obtained. It is shown through the analysis of probability density functions characterising the CRI distribution that the reduction is not homogeneous across all indicator values, but depends on the penetration rate and the severity of the manoeuvre.

mixed-traffic

on-ramp merging

traffic simulations

cooperative merging strategy

cut-in risk indicator

Author

Eleonora Andreotti

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

CINECA

Selpi Selpi

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Maytheewat Aramrattana

The Swedish National Road and Transport Research Institute (VTI)

IEEE Open Journal of Intelligent Transportation Systems

26877813 (eISSN)

Vol. 3 825-837

Driving styles of autonomous vehicles in mixed traffic (DS-Auto)

Chalmers, 2019-04-01 -- 2021-03-31.

Heterogeneous Traffic Groups Cooperative Driving Behaviours Research under Mixed Traffic Condition

VINNOVA (2018-02891), 2019-04-01 -- 2021-03-31.

Areas of Advance

Information and Communication Technology

Transport

Driving Forces

Sustainable development

Subject Categories

Computer and Information Science

Transport Systems and Logistics

Infrastructure Engineering

DOI

10.1109/OJITS.2022.3179125

More information

Latest update

4/21/2023