dc.contributor.author | Hegde, Bharathkumar Shripad | en |
dc.contributor.author | Bouroche, Melanie | en |
dc.date.accessioned | 2023-01-26T09:07:39Z | |
dc.date.available | 2023-01-26T09:07:39Z | |
dc.date.created | 25/07/2022 | en |
dc.date.issued | 2022 | en |
dc.date.submitted | 2022 | en |
dc.identifier.citation | Bharathkumar Hegde and M?lanie Bouroche, Design of AI-based lane changing modules in connected and autonomous vehicles: a survey, Twelfth International Workshop on Agents in Traffic and Transportation, ATT 2022, Vienna, 25/07/2022, 3137, 2022 | en |
dc.identifier.other | Y | en |
dc.description | PUBLISHED | en |
dc.description | Vienna | en |
dc.description.abstract | Lane changing is one of the complex driving tasks as it requires the vehicle to be aware of its highlydynamic surrounding environment, make decisions, and enact them in a timely manner. By exploiting both sensors and inter-vehicle communication, Connected and Autonomous Vehicles (CAVs) have the potential to significantly improve lane changing safety and efficiency. The complexity of the task and the real-time requirements make lane-changing a problem particularly suited to Artificial Intelligence (AI) approaches. In this paper, we survey the design of AI-based Lane-Changing(LC) modules for CAVs. First, we identify the key factors that can influence the design of an LC module. Next, we survey recent developments in AI-based lane changing. Finally, we analyse these approaches along the dimensions of the key influencing factors and summarise the challenges that are yet to be addressed and opportunities that can guide the future developments in AI-based LC modules. | en |
dc.description.sponsorship | SFI Centre for Research Training in Advanced Networks for Sustainable Societies (ADVANCE
CRT), Ireland under the Grant number 18/CRT/6222 | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | 3137 | en |
dc.rights | Y | en |
dc.subject | Artificial Intelligence | en |
dc.subject | Multi-agent systems | en |
dc.subject | Connected and autonomous vehicle (CAV) | en |
dc.subject | Autonomous lane change | en |
dc.subject | Deep learning | en |
dc.subject | Intelligent transportation system | en |
dc.subject.lcsh | Transportation | en |
dc.subject.lcsh | Artificial Intelligence | en |
dc.subject.lcsh | Computer Science | en |
dc.title | Design of AI-based lane changing modules in connected and autonomous vehicles: a survey | en |
dc.title.alternative | Twelfth International Workshop on Agents in Traffic and Transportation | en |
dc.title.alternative | ATT 2022 | en |
dc.type | Conference Paper | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/hegdeb | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/bourocm | en |
dc.identifier.rssinternalid | 250378 | en |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTheme | Smart & Sustainable Planet | en |
dc.subject.TCDTheme | Telecommunications | en |
dc.subject.TCDTag | ARTIFICIAL INTELLIGENCE | en |
dc.subject.TCDTag | Autonomous lane change | en |
dc.subject.TCDTag | Connected and autonomous vehicles | en |
dc.subject.TCDTag | Distributed Systems | en |
dc.subject.TCDTag | Multi-agent systems | en |
dc.subject.TCDTag | deep learning | en |
dc.identifier.rssuri | https://ceur-ws.org/Vol-3173/7.pdf | en |
dc.identifier.orcid_id | 0000-0002-2085-7867 | en |
dc.subject.darat_thematic | Accessibility | en |
dc.subject.darat_thematic | Transport | en |
dc.status.accessible | N | en |
dc.contributor.sponsor | Science Foundation Ireland (SFI) | en |
dc.contributor.sponsorGrantNumber | 18/CRT/6222 | en |
dc.identifier.uri | http://hdl.handle.net/2262/102027 | |