Cooperative merging strategy between connected autonomous vehicles in mixed traffic
Artikel i vetenskaplig tidskrift, 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

Författare

Eleonora Andreotti

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

CINECA

Selpi Selpi

Chalmers, Data- och informationsteknik, Data Science och AI

Maytheewat Aramrattana

Statens Väg- och Transportforskningsinstitut (VTI)

IEEE Open Journal of Intelligent Transportation Systems

26877813 (eISSN)

Vol. 3 825-837

Körstilar av autonoma fordon i blandad trafik

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.

Styrkeområden

Informations- och kommunikationsteknik

Transport

Drivkrafter

Hållbar utveckling

Ämneskategorier

Data- och informationsvetenskap

Transportteknik och logistik

Infrastrukturteknik

DOI

10.1109/OJITS.2022.3179125

Mer information

Senast uppdaterat

2023-04-21