Abstract

The paper develops a simulation model and evaluates fixed versus on-demand operational designs of a station-based automated feeder service. The evaluation considers the operational cost and average passenger level-of-service trade-offs as well as distributional differences in waiting times. Two case studies are used to evaluate such trade-offs under different fleet compositions; (1) a simple circular network feeder service; (2) a case based on a real-world coordinated branched service in Stockholm, combining fixed-line services on the trunk portion with a flexible feeder service on the branches. Results for the circular network indicate that there are benefits in utilizing an on-demand operational policy for the lowest and highest demand levels tested. When fixed service capacity is exceeded, it is found that there are potential benefits in on-demand operations with respect to average level-of-service, as well as delivering a more even distribution of passenger waiting times. Results for the real-world case show that combining DRT on branches with fixed services on the trunk improves the overall median waiting times for all DRT scenarios and provides substantial improvements for passengers on the trunk, at the cost of more variable, and less equitable waiting times on the branches. For larger fleet sizes, generalized travel costs are reduced with and without rebalancing and level-of-service provided to branch-to-branch passengers is improved considerably by rebalancing idling vehicles to branch end-stops. The case studies demonstrate the usefulness of the simulation framework in evaluating trade-offs between fixed and on-demand service design variables and their effects on disaggregate level-of-service provided for stop-based feeder services.

Highlights

  • Demand-responsive transit (DRT) is a form of user-oriented public transport characterized by flexible routing and scheduling depending on passenger needs

  • This paper presents a simulation framework encompassing essential components for modeling demand-responsive transit services designed for prototyping a wide variety of demand-responsive operational policies

  • This framework is embedded within an existing public transit simulation model that has previously been utilized in evaluating fixed transit services and that includes a detailed representation of adaptive passenger behavior

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Summary

Introduction

Demand-responsive transit (DRT) is a form of user-oriented public transport characterized by flexible routing and scheduling depending on passenger needs. There is a widely held view that DRT systems are expensive solutions that come at a much higher cost to operators, and must be heavily subsidized if provided as a public service (Ferreira et al, 2007; Davison et al, 2014). This is often a result of an inability to spread the cost of a given trip over a greater number of passengers. With reductions of on-board crew costs (which is often estimated to constitute roughly 50% of the operational cost of bus transit in developed countries (Australian Transport Council, 2006; Davison et al, 2012)), an automated DRT service could potentially be offered at a lower per-vehicle operational cost (Bösch et al, 2018)

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