Autonomous vehicle fleets for public transport: scenarios and comparisons
Journal article, 2022

Autonomous vehicles (AVs) are becoming a reality and may integrate with existing public transport systems to enable the new generation of autonomous public transport. It is vital to understand what are the alternatives for AV integration from different angles such as costs, emissions, and transport performance. With the aim to support AV integration in public transport, this paper takes a typical European city as a case study for analyzing the impacts of different AV integration alternatives. A transport planning model considering AVs is developed and implemented, with a methodology to estimate the costs of the transport network. Traffic simulations are conducted to derive key variables related to AVs. An optimization process is introduced for identifying the optimal network configuration based on a given AV integration strategy, followed by the design of different AV integration scenarios, simulation, and analyses. With the proposed method, a case study is done for the city of Uppsala with presentation of detailed cost results together with key traffic statistics such as mode share. The results show that integrating AVs into public transport does not necessarily improve the overall cost efficiency. Based on the results and considering the long transition period to fully autonomous vehicles, it is recommended that public transport should consider a gradual introduction of AVs with more detailed analysis on different combination and integration alternatives of bus services and AVs.

Autonomous vehicle

Public transport

Transport network

Author

François Poinsignon

Royal Institute of Technology (KTH)

Lei Chen

RISE Research Institutes of Sweden

Sida Jiang

WSP Sverige

Kun Gao

Transportgruppen

Hugo Badia

Polytechnic University of Catalonia

Erik Jenelius

Royal Institute of Technology (KTH)

Green Energy and Intelligent Transportation

20972512 (ISSN) 27731537 (eISSN)

Vol. 1 3 100019

Subject Categories

Transport Systems and Logistics

Vehicle Engineering

DOI

10.1016/j.geits.2022.100019

More information

Latest update

10/27/2023