173 citations · 800 across the 20 of their papers we have counts for
20 papers
Optimal queueing-based rebalancing for one-way electric carsharing systems with stochastic demand
Tai-Yu Ma, Theodoros Pantelidis, Joseph Y. J. Chow
Viability of electric vehicle car sharing operations depends on rebalancing algorithms. Earlier methods in the literature suggest a trend toward Markovian stochastic demand with se…
Agent-based Simulation Model and Deep Learning Techniques to Evaluate and Predict Transportation Trends around COVID-19
Ding Wang, Fan Zuo, Jingqin Gao +11
The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped…
NYC Recovery at a Glance: The Rise of Buses and Micromobility
Suzana Duran Bernardes, Zilin Bian, Siva Sooryaa Muruga Thambiran +9
New York City (NYC) is entering Phase 4 of the state's reopening plan, starting July 20, 2020. This white paper updates travel trends observed during the first three reopening phas…
Toward the "New Normal": A Surge in Speeding, New Volume Patterns, and Recent Trends in Taxis/For-Hire Vehicles
Jingqin Gao, Abhinav Bhattacharyya, Ding Wang +11
Six months into the pandemic and one month after the phase four reopening in New York City (NYC), restrictions are lifting, businesses and schools are reopening, but global infecti…
A validated multi-agent simulation test bed to evaluate congestion pricing policies on population segments by time-of-day in New York City
Brian Yueshuai He, Jinkai Zhou, Ziyi Ma +5
Evaluation of the demand for emerging transportation technologies and policies can vary by time of day due to spillbacks on roadways, rescheduling of travelers' activity patterns,…
V2I Connectivity-Based Dynamic Queue-Jump Lane for Emergency Vehicles: A Deep Reinforcement Learning Approach
Haoran Su, Kejian Shi, Li Jin +1
Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion. A main reason behind EMV service delay is the lack of co…
A Real-Time Dispatching Strategy for Shared Automated Electric Vehicles with Performance Guarantees
Li Li, Theodoros Pantelidis, Joseph Y. J. Chow +1
Real-time vehicle dispatching operations in traditional car-sharing systems is an already computationally challenging scheduling problem. Electrification only exacerbates the compu…
Impact of COVID-19 behavioral inertia on reopening strategies for New York City Transit
Ding Wang, Brian Yueshuai He, Jingqin Gao +3
The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped…
A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg
Tai-Yu Ma, Joseph Y. J. Chow, Sylvain Klein +1
This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resour…
Dynamic Queue-Jump Lane for Emergency Vehicles under Partially Connected Settings: A Multi-Agent Deep Reinforcement Learning Approach
Haoran Su, Kejian Shi, Joseph. Y. J. Chow +1
Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion. The main reason behind EMV service delay is the lack of…
Online route choice modeling for Mobility-as-a-Service networks with non-separable, congestible link capacity effects
Susan Jia Xu, Joseph Y. J. Chow
With the prevalence of MaaS systems, route choice models need to consider characteristics unique to them. MaaS systems tend to involve service systems with fleets of vehicles; as a…
A user-operator assignment game with heterogeneous user groups for empirical evaluation of a microtransit service in Luxembourg
Tai-Yu Ma, Joseph Y. J. Chow, Sylvain Klein +1
We tackle the problem of evaluating the impact of different operation policies on the performance of a microtransit service. This study is the first empirical application using the…
A many-to-many assignment game and stable outcome algorithm to evaluate collaborative Mobility-as-a-Service platforms
Theodoros P. Pantelidis, Joseph Y. J. Chow, Saeid Rasulkhani
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. Ev…
Empirical validation of network learning with taxi GPS data from Wuhan, China
Susan Jia Xu, Qian Xie, Joseph Y. J. Chow +1
In prior research, a statistically cheap method was developed to monitor transportation network performance by using only a few groups of agents without having to forecast the popu…
Forecasting e-scooter substitution of direct and access trips by mode and distance
Mina Lee, Joseph Y. J. Chow, Gyugeun Yoon +1
An e-scooter trip model is estimated from four U.S. cities: Portland, Austin, Chicago and New York City. A log-log regression model is estimated for e-scooter trips based on user a…
A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers
Tai-Yu Ma, Saeid Rasulkhani, Joseph Y. J. Chow +1
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…
Online monitoring of local taxi travel momentum and congestion effects using projections of taxi GPS-based vector fields
Xintao Liu, Joseph Y. J. Chow, Songnian Li
Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel analysis. Of interest is the need to allow someone to monitor travel momentum and asso…
Route-cost-assignment with joint user and operator behavior as a many-to-one stable matching assignment game
Saeid Rasulkhani, Joseph Y. J. Chow
We propose a generalized market equilibrium model using assignment game criteria for evaluating transportation systems that consist of both operators' and users' decisions. The mod…
Dynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policy
Joseph Y. J. Chow
Given the rapid advances in unmanned aerial vehicles, or drones, and increasing need to monitor traffic at a city level, one of the current research gaps is how to systematically d…
Network learning via multi-agent inverse transportation problems
Susan Jia Xu, Mehdi Nourinejad, Xuebo Lai +1
Despite the ubiquity of transportation data, methods to infer the state parameters of a network either ignore sensitivity of route decisions, require route enumeration for paramete…