no code implementations • 22 Sep 2023 • Xiyuan Ren, Joseph Y. J. Chow
We propose a group-level agent-based mixed (GLAM) logit approach that is estimated with inverse optimization (IO) and group-level market share.
no code implementations • 16 May 2023 • Gyugeun Yoon, Joseph Y. J. Chow
Prior knowledge is reproduced from the regional household travel survey data.
no code implementations • 30 Dec 2022 • Srushti Rath, Joseph Y. J. Chow
The goal is to determine the optimal selection and timing of a set of zones to include in a service region.
no code implementations • 27 Jun 2022 • Haoran Su, Yaofeng D. Zhong, Joseph Y. J. Chow, Biswadip Dey, Li Jin
Emergency vehicles (EMVs) play a crucial role in responding to time-critical calls such as medical emergencies and fire outbreaks in urban areas.
Multi-agent Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 29 Mar 2022 • Srushti Rath, Joseph Y. J. Chow
Despite the value of understanding a city's typology, labeled data (city and it's typology) is scarce, and spans at most a few hundred cities in the current transportation literature.
1 code implementation • 11 Feb 2021 • Bingqing Liu, Theodoros P. Pantelidis, Stephanie Tam, Joseph Y. J. Chow
The model is then applied to compare charging station investment policies of DCFCs to Level 2 charging stations based on two alternative criteria.
Computers and Society
no code implementations • 23 Sep 2020 • Ding Wang, Fan Zuo, Jingqin Gao, Yueshuai He, Zilin Bian, Suzana Duran Bernardes, Chaekuk Na, Jingxing Wang, John Petinos, Kaan Ozbay, Joseph Y. J. Chow, Shri Iyer, Hani Nassif, Xuegang Jeff Ban
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 by social distancing.
no code implementations • 1 Aug 2020 • Haoran Su, Kejian Shi, Li Jin, Joseph Y. J. Chow
Emergency vehicle (EMV) service is a key function of cities and is exceedingly challenging due to urban traffic congestion.
no code implementations • 28 Jun 2020 • Li Li, Theodoros Pantelidis, Joseph Y. J. Chow, Saif Eddin Jabari
To overcome this complexity, we employ an online minimum drift plus penalty (MDPP) approach for SAEV systems that (i) does not require a priori knowledge of customer arrival rates to the different parts of the system (i. e. it is practical from a real-world deployment perspective), (ii) ensures the stability of customer waiting times, (iii) ensures that the deviation of dispatch costs from a desirable dispatch cost can be controlled, and (iv) has a computational time-complexity that allows for real-time implementation.
no code implementations • 9 Nov 2019 • Susan Jia Xu, Qian Xie, Joseph Y. J. Chow, Xintao Liu
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 population flows.
no code implementations • 21 Aug 2019 • Mina Lee, Joseph Y. J. Chow, Gyugeun Yoon, Brian Yueshuai He
An e-scooter trip model is estimated from four U. S. cities: Portland, Austin, Chicago and New York City.
no code implementations • 1 Apr 2019 • Srushti Rath, Joseph Y. J. Chow
Witnessing the rapid progress and accelerated commercialization made in recent years for the introduction of air taxi services in near future across metropolitan cities, our research focuses on one of the most important consideration for such services, i. e., infrastructure planning (also known as skyports).
1 code implementation • 14 Sep 2016 • Susan Jia Xu, Mehdi Nourinejad, Xuebo Lai, Joseph Y. J. Chow
New inverse optimization models and supporting algorithms are proposed to learn the parameters of heterogeneous travelers' route behavior to infer shared network state parameters (e. g. link capacity dual prices).