arXiv subjects

Saeid Rasulkhani

Publications and source records attributed to Saeid Rasulkhani.

3 recordsLinked to original sources

arXiv2020

A many-to-many assignment game and stable outcome algorithm to evaluate collaborative Mobility-as-a-Service platforms

As Mobility as a Service (MaaS) systems become increasingly popular, travel is changing from unimodal trips to personalized services offered by a platform of mobility operators. Evaluation of MaaS platforms depends on modeling both user route decisions as well as operator service and pricing decisions. We adopt a new paradigm for traffic assignment in a MaaS network of multiple operators using the concept of stable matching to allocate costs and determine prices offered by operators corresponding to user route choices and operator service choices without resorting to nonconvex bilevel programming formulations. Unlike our prior work, the proposed model allows travelers to make multimodal, multi-operator trips, resulting in stable cost allocations between competing network operators to provide MaaS for users. An algorithm is proposed to efficiently generate stability conditions for the stable outcome model. Extensive computational experiments demonstrate the use of the model to handling pricing responses of MaaS operators in technological and capacity changes, government acquisition, consolidation, and firm entry, using the classic Sioux Falls network. The proposed algorithm replicates the same stability conditions as explicit path enumeration while taking only 17 seconds compared to explicit path enumeration timing out over 2 hours.

cs.CY↗

arXiv2019

A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers

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.

cs.CY↗

arXiv2019

Route-cost-assignment with joint user and operator behavior as a many-to-one stable matching assignment game

We propose a generalized market equilibrium model using assignment game criteria for evaluating transportation systems that consist of both operators' and users' decisions. The model finds stable pricing, in terms of generalized costs, and matches between user populations in a network to set of routes with line capacities. The proposed model gives a set of stable outcomes instead of single point pricing that allows operators to design ticket pricing, routes/schedules that impact access/egress, shared policies that impact wait/transfer costs, etc., based on a desired mechanism or policy. The set of stable outcomes is proven to be convex from which assignment-dependent unique user-optimal and operator-optimal outcomes can be obtained. Different user groups can benefit from using this model in a prescriptive manner or within a sequential design process. We look at several different examples to test our model: small examples of fixed transit routes and a case study using a small subset of taxi data in NYC. The case study illustrates how one can use the model to evaluate a policy that can require passengers to walk up to 1 block away to meet with a shared taxi without turning away passengers.

cs.CE↗