Abstract
One of the pivotal challenges presented to urban road traffic controllers is the effective utilisation of transport infrastructure, as a result of growing urbanisation, the finite network capacity, and of the increasing number of road vehicles. In this context, the arrival of connected vehicles present a unique opportunity for a fundamental change in urban traffic control. Urban traffic control approaches should then take an active role in integrating connected vehicles into the mobility ecosystem in order to maximise benefits. To support such integration, in this work we propose to leverage automated planning, a well-studied branch of artificial intelligence, to perform real-time traffic routing in urban areas. We describe the proposed approach, and we demonstrate its effectiveness using real-world historical data of a UK town.
Original language | English |
---|---|
Title of host publication | Proceedings of the 7th International IEEE Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS 2021) |
Publisher | IEEE Computer Society |
Number of pages | 6 |
ISBN (Electronic) | 9781728189956 |
ISBN (Print) | 9781728189963 |
DOIs | |
Publication status | Published - 7 Sep 2021 |
Event | 7th International IEEE Conference on Models and Technologies for Intelligent Transportation Systems - Aquila Atlantis Hotel, Heraklion, Crete, Greece Duration: 16 Jun 2021 → 17 Jun 2021 Conference number: 7 https://www.mt-its2021.tse.bgu.tum.de/ |
Conference
Conference | 7th International IEEE Conference on Models and Technologies for Intelligent Transportation Systems |
---|---|
Abbreviated title | MT-ITS 2021 |
Country/Territory | Greece |
City | Heraklion, Crete |
Period | 16/06/21 → 17/06/21 |
Internet address |