173 citations · 800 across the 20 of their papers we have counts for
9 papers · 1 filter
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…