A Novel Potential Line Strategy for Autonomous Vehicle Control in Lane-Free Traffic

Hanwen Zhang, Majid Rostami-Shahrbabaki, Dimitrios Troullinos, Klaus Bogenberger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent developments in vehicular traffic have brought about the concept of lane-free traffic, challenging the traditional notion of parallel lanes, allowing vehicles to potentially drive at any arbitrary lateral location of the road. In this paper, we investigate the potential lines strategy proposed in our previous study for an efficient lateral distribution of vehicles in automated lane-free freeways. Potential lines allow for structured lane-free traffic where each vehicle receives a desired lateral location based on its desired speed. To this end, we mimic the behavior of conventional driving by assigning the right side of the road to slower vehicles while faster vehicles are led toward the left. As a result, the road surface effectively forms a speed-based hierarchy, with vehicles flowing smoothly from right to left in a monotonic increase of speed. We utilize the Probability Integral Transform approach to have a uniform lateral distribution of potential lines despite different distributions of desired speed. In addition, we show that the potential lines are efficient means of handling different maneuvers such as merge, diverge, and emergency vehicle preemption on a freeway. The simulation results for a relatively long freeway demonstrate that potential lines can minimize unnecessary lateral movement during overtaking, creating a more structured and efficient driving environment. Furthermore, results show that potential lines can smoothly guide vehicles to take off-ramps or merge from on-ramps in high-density traffic conditions.

Original languageEnglish
Title of host publication2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4173-4180
Number of pages8
ISBN (Electronic)9798350399462
DOIs
StatePublished - 2023
Event26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Bilbao, Spain
Duration: 24 Sep 202328 Sep 2023

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)2153-0009
ISSN (Electronic)2153-0017

Conference

Conference26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Country/TerritorySpain
CityBilbao
Period24/09/2328/09/23

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