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Integrated optimization of timetable, bus formation, and vehicle scheduling in autonomous modular public transport systems
School of Transportation Science and Engineering, Beihang University, Beijing 100191, China.
Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, the Netherlands.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-2141-0389
Department of Civil Engineering, Tsinghua University, Beijing 10084, China.
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2023 (English)In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 155, article id 104306Article in journal (Refereed) Published
Abstract [en]

This paper presents a joint optimization of the timetable, bus formation, and vehicle scheduling in a flexible public transport (PT) system that utilizes autonomous modular vehicles (AMVs). In this system, AMVs have the capability to detach or join with each other at intermediate stops along the route to dynamically adjust the bus formation (capacity). To increase vehicle utilization, a flexible scheduling strategy is proposed that allows AMVs to detach from one modular bus and join another modular bus in either direction of a bidirectional line. In particular, the penalty cost for each detachment or joining operation, as well as the limited number of available AMVs is explicitly considered. We formulate a unified model for the integrated optimization of the modular bus service (timetable and bus formation) and vehicle scheduling by introducing two types of decision variables. The objective is to minimize overall system costs, including passenger waiting time cost, operational costs, and detachment/joining penalty costs. The two types of decision variables are coupled by a vehicle resource consistency constraint, ensuring the conformity of the modular bus service and vehicle scheduling decisions. To tackle the complexity of our model, the Alternating Direction Method of Multipliers (ADMM) is employed to decompose it into two subproblems, which can be efficiently solved using a customized forward dynamic programming algorithm and a commercial solver. The model is validated using illustrative examples and a real-world instance from the Beijing Public Transport system, and it is compared with two benchmark models. Our results demonstrate the efficiency of the ADMM-based solution framework for solving the integrated optimization model. Furthermore, our findings indicate that the use of AMVs in PT systems can lead to reduced overall system costs and increased vehicle utilization.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 155, article id 104306
Keywords [en]
Alternating Direction Method of Multipliers, Autonomous modular vehicle, Flexible vehicle scheduling, Integrated optimization, Public transport, Timetable
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-334941DOI: 10.1016/j.trc.2023.104306ISI: 001066676300001Scopus ID: 2-s2.0-85168427216OAI: oai:DiVA.org:kth-334941DiVA, id: diva2:1792722
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QC 20230830

Available from: 2023-08-30 Created: 2023-08-30 Last updated: 2023-10-09Bibliographically approved

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Ma, Zhenliang

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