Abstract
We propose a ridesharing strategy with integrated transit in which a private on-demand mobility service operator may drop off a passenger directly door-to-door, commit to dropping them at a transit station or picking up from a transit station, or to both pickup and drop off at two different stations with different vehicles. We study the effectiveness of online solution algorithms for this proposed strategy. Queueing-theoretic vehicle dispatch and idle vehicle relocation algorithms are customized for the problem. Several experiments are conducted first with a synthetic instance to design and test the effectiveness of this integrated solution method, the influence of different model parameters, and measure the benefit of such cooperation. Results suggest that rideshare vehicle travel time can drop by 40–60% consistently while passenger journey times can be reduced by 50–60% when demand is high. A case study of Long Island commuters to New York City (NYC) suggests having the proposed operating strategy can substantially cut user journey times and operating costs by up to 54% and 60% each for a range of 10–30 taxis initiated per zone. This result shows that there are settings where such service is highly warranted.
Highlights
There is huge potential for collaborations between public transport agencies and private transport operators to leverage mobility-on-demand (MoD) services (Murphy and Feigon, 2016)
The share of people taking the ridesharing as a last mile (WTR) is small compared to RTW because the morning time period studied has most trips coming from Long Island to New York City (NYC) and not the other way around
The nonmyopic relocation algorithm for rideshare-only option does not make any significant improvements in the Long Island Railroad (LIRR) case study
Summary
There is huge potential for collaborations between public transport agencies and private transport operators to leverage mobility-on-demand (MoD) services (Murphy and Feigon, 2016). The basic form of collaboration is for MoD services to cover the first and last mile segments of a passenger trip. There is no integrated optimization of vehicle dispatch and repositioning of idle vehicles with transit stations to provide an integrated, multimodal trip. Computational experiments are conducted in synthetic instances as well as in a largescale case study of the Long Island Railroad (LIRR) accessing New York City (NYC) to provide insights on how to select algorithm parameters to obtain effective results
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More From: Transportation Research Part E: Logistics and Transportation Review
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