Dynamic bus substitution strategy for bunching intervention. (September 2018)

• Record Type: Journal Article
• Authors: Petit, Antoine; Ouyang, Yanfeng; Lei, Chao
• Is Part Of: Transportation research. Volume 115(2018)
• Page Start: 1
• Page End: 16
• Publication Date: 2018-09
• Subjects: Bus bunching -- Transit operations -- Approximate dynamic programming -- Autonomous vehicles; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2018.06.001
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: Bus substitution strategy with standby fleet to control service schedule deviations. Stochastic dynamic program based on bus operation dynamics and substitution decisions. Approximate dynamic programming algorithm with offline simulations and estimation. Comparison with alternative strategies shows strong performance of the substitution strategy. Stronger performance with passenger information provision and automated vehicles. Abstract: Bus headways are typically susceptible to external disturbances (e.g., due to traffic congestion, clustered passenger arrivals, and special passenger needs), which create gaps in the system that grow eventually into bunching. Although many control strategies, such as static and dynamic holding strategies, have been implemented to mitigate the effects of unreliable bus schedules, most of them would impose longer dwell times on the passengers. In this paper, we investigate the potential of an alternative bus substitution strategy that is currently implemented by some transit agencies in an ad-hoc manner. In this strategy, the agency deploys a fleet of standby buses to take over service from any early or late buses so as to contain deviations from schedule, and the intention is to impose minimum penalties on the onboard passengers. We develop a discrete-time infinite-horizon approximate dynamic programming approach to find the optimal policy to minimize the overall agency and passenger costs. It is shown through numerical examples that schedule deviations can be controlled by regularly inserting standby buses as substitutions. In some implementation scenarios, the proposed strategy holds the potential to achieve comparable performance with some of the most advanced strategies, and to outperform the conventional slack-based schedule control scheme. In light of the emerging opportunities associated with autonomous driving, the performance of the proposed strategy can become even stronger due to the reduction in costs for keeping the fleet of standby buses.