Abstract
This study focuses on single variable optimization approaches which determine the holding time of a vehicle when it is ready to depart from a bus stop. Up to now, single variable optimization methods resort to rule-based control logics to equalize the inter-departure headways or adhere to the target headway values. One of them is the two-headway-based control logic which determines the holding time of a bus based on its headway with its preceding and following bus without addressing other implications, such as overcrowding. To rectify this, we introduce a new model for the single variable bus holding problem that considers the passenger demand and vehicle capacity limits. Then, we reformulate this problem to an easier-to-solve program with the use of slack variables and introduce an analytic solution that can determine the holding time of a vehicle at the respective bus stop. Our analytic solution does not add a computational burden to the two-headway-based control logic and can be applied in real time. The operational benefit of our bus holding approach compared to other analytic solutions that do not consider the vehicle capacity is investigated using actual data from bus line 302 in Singapore.
Highlights
Decisions regarding the operations of bus services are made at different planning stages
In contrast to periodic optimization in rolling horizons, in this study we propose an analytic solution for the bus holding problem under capacity limitations that can determine the holding time of a single bus trip upon its arrival at a bus stop
Analytic solution of bus holding considering capacity limits In Theorem Appendix 2 we proved that our reformulated program (Q) is convex and any local minimizer is a globally optimal solution
Summary
Decisions regarding the operations of bus services are made at different planning stages. If the demand and the travel times of all bus trips operating in a service line are equal and stable, bus trips will maintain their even headways at all downstream stops. This will result in a regular service where the actual passenger waiting times at stops meet the passengers’ expectations. An entirely different line of research determines the holding times of multiple bus trips, instead of only trip n, following a periodic optimization approach (Gkiotsalitis and Cats, 2019). The main findings and the limitations of this study are discussed in Sections 7 and 8
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More From: Transportation Research Part C: Emerging Technologies
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