AI Approaches on Urban Public Transport Routing

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Artificial intelligence (AI) is an innovative concept that can provide potentials to overcome the challenges of operation in public transport (PT) systems. The AI applications in the PT operation offer the opportunities to alleviate traffic congestion and enhance the accessibility, mobility, and reliability of services with a more efficient and effective PT system. One of the key areas that AI is beneficial is in optimization of network route design. Examples of AI approaches that are finding their way under fuel and electric vehicle conditions include genetic algorithm (GA), simulated annealing (SA), etc. The more promising application of AI techniques requires a well-understood knowledge of multiple data sets and features of different PT services, including conventional buses and demand-responsive transit systems, especially when dealing with travel demands fluctuating in time and space. Moreover, the emerging development in connected and autonomous vehicles (CAVs) is leading a rapid improvement in flexibility, punctuality, vehicle safety, and transit priority. The purpose of this chapter is to review AI approaches applied on public transport operation, especially on routing. The overview concludes by addressing the issues and challenges of AI applications in PT operation.
Original languageEnglish
Title of host publicationDeception in Autonomous Transport Systems
Subtitle of host publicationThreats, Impacts and Mitigation Policies
EditorsSimon Parkinson, Alexandros Nikitas, Mauro Vallati
PublisherSpringer, Cham
Chapter8
Pages111-130
Number of pages20
ISBN (Electronic)9783031550447
ISBN (Print)9783031550430, 9783031550461
DOIs
Publication statusPublished - 16 May 2024

Publication series

NameWireless Networks
PublisherSpringer
ISSN (Print)2366-1186
ISSN (Electronic)2366-1445

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