Assessing the introduction of regional driverless demand-responsive transit services through agent-based modeling and simulation

Anne S. Patricio (), Gonçalo Gonçalves Duarte Santos and António Pais Antunes
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Anne S. Patricio: CITTA, Department of Civil Engineering
Gonçalo Gonçalves Duarte Santos: CITTA, Department of Civil Engineering
António Pais Antunes: CITTA, Department of Civil Engineering

Transportation, 2025, vol. 52, issue 3, No 14, 1118 pages

Abstract: Abstract Demand-responsive transit systems are seen as a solution to improve the level of service and decrease the costs of providing transit to rural or low-demand areas. There are great expectations on the impact that driverless demand-responsive transit (DDRT) systems can have on a regional setting. Nevertheless, the application of DDRT in such type of setting has not been widely studied, in particular for scenarios where the system is an addition to the existing alternatives (as characteristic of the early diffusion stage of an innovation). This study provides an assessment of the early-stage operation of a regional DDRT system used by a small portion of the entire potential adopters. A methodological approach is built upon an agent-based model through which the daily operation of a DDRT system is simulated in detail. This approach is applied to a case study in Portugal considering scenarios varying in terms of several operational parameters, adoption rates (from 1 to 20%), and types of services (private versus shared rides). Results show that each vehicle in the DDRT system with shared rides could replace up to 13 private vehicles with a decrease in the vehicle-kilometers traveled of 1%. The DDRT system operation is profitable even with low adoption rates (starting from 2% for the system with shared rides). When considering the adoption rate of 5%, the system with shared rides is 54% more profitable than the one with private rides, but, from the perspective of travelers, shared rides lead to longer waiting times and detours.

Keywords: Regional transport; Low-demand areas; Demand-responsive transit; Driverless vehicles; Agent-based modeling and simulation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11116-023-10450-9

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