Abstract
AbstractThe maturing of autonomous driving technology in recent years has led to several pilot projects and the initial integration of autonomous pods and buses into the public transport (PT) system. An emerging field of interest is the design of public transport networks operating autonomous buses and the potential to attract higher levels of travel demand. In this work a multi-objective optimization and multi-agent simulation framework is developed to study potential changes in the network design and frequency settings compared to conventional PT systems when autonomous vehicles (AV) systems are deployed on fixed-route networks. During the optimization process multiple deployment scenarios (network configurations and service frequency) are evaluated and optimized considering the operator cost, user cost and infrastructure preparation costs of the system. User-focused network design and operator-focused network design are studied for a real-world urban area in Sweden. The results provide insights into the network design and level of service implications brought about by the deployment of autonomous bus (AB) when those are integrated in route-based PT systems. We show that the deployment of autonomous buses result with a network design that increases service ridership. In the context of our case study this increase is likely to primarily substitute walking.
Funder
VINNOVA
Royal Institute of Technology
Publisher
Springer Science and Business Media LLC
Subject
Transportation,Development,Civil and Structural Engineering
Reference60 articles.
1. Anderson, S.D., Molenaar, K.R., Schexnayder, C.J.: Independent cost estimates for design and construction of transit facilities in rural and small urban areas. Vol. 397 of Research results digest/National Cooperative Highway Research Program. Transportation Research Board, Washington, D.C (2015)
2. Auger, A., Bader, J., Brockhoff, D., Zitzler, E.: Hypervolume-based multiobjective optimization: theoretical foundations and practical implications. Theor. Comput. Sci. 425, 75–103 (2012)
3. Baaj, M.H., Mahmassani, H.S.: An AI-based approach for transit route system planning and design. J. Adv. Transp. 25(2), 187–209 (1991)
4. Barabasi, A.: Emergence of scaling in random networks. Science (New York, N.Y.) 286 (5439), 509–512 (1999)
5. Börjesson, M., Eliasson, J.: Experiences from the swedish value of time study. Transp. Res. Part A Policy Practice 59, 144–158 (2014)
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