AUTHORS (177)
Ahn, Soy­oung (Sue)
Aka­mat­su, Takashi
Alan­qary, Arwa
Alisoltani, Negin
Alon­so-Mora, Javier
Ameli, Mostafa
Ban, Jeff
Bandiera, Clau­dia
Bat­ley, Richard
Bayen, Alexan­dre M.
Bell, Michael G H
Beo­jone, Caio Vitor
Bhat­tachar­jya, Jyotir­moy­ee
Bliemer, Michiel
Cao, Yumin
Cas­sidy, Michael J.
Cen, Xuekai
Chen, Zhib­in
Chen, Dan­jue
Chen, Kehua
Chen, Xiqun (Michael)
Chen, Xu
Chen, Cyn­thia
Cheng, Xi
Coif­man, Ben­jamin
Cokyasar, Tan­er
Con­nors, Richard D.
Cook, Adi­an
Dagan­zo, Car­los F.
Dantsu­ji, Takao
Di, Xuan
Doig, Jean
Engel­hardt, Roman
Fan, Ximeng
Fan, Yueyue
Feng, Liyang
Feng, Yiheng
Fiel­baum, Andrés
Fu, Zhe
Gayah, Vikash V.
Geers, Glenn
Geroli­m­in­is, Niko­las
Gu, Ziyuan
Had­dad, Jack
Ham­dar, Samer
Haque, Mohaimin­ul
Hazel­ton, Mar­tin
He, Xiaozheng (Sean)
Her­ty, Michael
Hey­deck­er, Ben­jamin
Hong, Yuan
Hu, Simon
Hu, Xinyue
Huang, Hai-Jun
Huang, Shuai
Iaco­mi­ni, Elisa
Iryo, Taka­masa
Jia, Shaocheng
Jiang, Jiwan
Jin, Li
Jin, Wen­long
Ka, Eun­han
Khan, Zaid Saeed
Kobayashi, Shun-ichi
Krei­dieh, Abdul Rahman
Krish­naku­mari, Pan­chamy
Lau­riere, Math­ieu
Laval, Jorge
Le, Dat Tien
Lebacque, Jean-Patrick
Lecler­cq, Ludovic
Lee, Enoch
Lehe, Lewis J.
Li, Zihao
Li, Shen
Li, Jiayang
Li, Manzi
Li, Yifan
Lim, Jisoon
Lin, Jane
Liu, Yuhao
Liu, Jiachao
Liu, Wei
Liu, Hao
Liu, Ronghui
Liu, Yang
Liu, Tian-Liang
Liu, Zhiyuan
Lo, Hong K.
Loder, Allis­ter
Ma, Xiaoyu
Mah­mas­sani, Hani S.
Martínez, Irene
Masoud, Neda
Menén­dez, Móni­ca
Mo, Zhaobin
Mol­nar, Tamas G.
Nakaya­ma, Shoichi­ro
Ng, Max T.M.
Nie, Yu (Mar­co)
Orosz, Gábor
Oso­rio, Jesus
Ouyang, Yan­feng
Ozbay, Kaan
Pandey, Ayush
Pee­ta, Srini­vas
Qian, Sean
Qu, Xu
Ran, Bin
Ren, Kanghui
Rock­afel­larc, R. Tyrrell
Saberi, Meead
Safa­di, Yazan
Sakai, Takara
Sat­sukawa, Koki
Schmöck­er, Jan-Dirk
Segala, Chiara
Shen, Shiyu
Si, Bingfeng
Sir­matelb, Isik Ilber
Song, Jun
Sun, Xiao­tong
Sun, Lijun
Sun, Wen­zhe
Takaya­ma, Yuki
Talebpour, Alireza
Tang, Yu
Tian, Qiong
Uğurel, Ekin
Ukkusuri, Satish V.
van Lint, Hans
Ver­bas, Ömer
Viti, Francesco
Wada, Ken­taro
Wang, Xiaolei
Wang, Xin
Wang, Siy­ing
Wang, Qian­ni
Wang, David Z.W.
Wang, Jingx­ing
Wang, Fei­long
Wang, Qiqing
Wang, Zejiang
Wang, Wen­shuo
Watling, David
Wong, S.C.
Wong, Wai
Xie, Jun
Xu, Zhengt­ian
Xu, Pu
Xue, Jiawei
Yam­aguchi, Hiromichi
Yang, Hai
Yang, Chen
Yang, Shan
Yang, Kai­di
Yao, Rui
Ye, Anke
Yin, Peng­hang
Zang, Zhao­qi
Zhang, Yun­long
Zhang, Xiaon­ing
Zhang, Yu
Zhang, Zhuoye
Zhang, Fang­ni
Zhang, Kenan
Zhang, Chengyuan
Zhao, Chaoyue
Zheng, Yuan
Zheng, Zuduo
Zhou, Yang
Zhou, Yihe
Zhou, Bo
Zhou, Anye
Zhou, Hao
Zhu, Meix­in
Zhu, Peng­bo

Podium Session 2: Economic Analysis of On-Street Parking with Urban Delivery

Title: Economic Analysis of On-Street Parking with Urban Delivery
Authors: Zhengtian Xu, Xiaotong Sun
Abstract: Problem Definition: The surge in online shopping has dramatically increased the demand for short-term curb access for package pickups and deliveries, leading to heightened competition for limited curb space. This paper addresses the problem of how the unique parking demand of deliverers, particularly their parking duration for delivery attempts lin...
Keywords: Urban logistics; “Final 50 feet” problem; On-street parking; Parking management; Delivery bay

Lightning Talk 1: Developing Platooning Systems of Connected and Automated Vehicles with Guaranteed Stability and Robustness against Degradation due to Communication Disruption

Title: Developing Platooning Systems of Connected and Automated Vehicles with Guaranteed Stability and Robustness against Degradation due to Communication Disruption
Authors: Yuan Zheng, Yu Zhang, Xu Qu, Shen Li, Bin Ran
Abstract: Connected and automated vehicle platooning systems like cooperative adaptive cruise control (CACC) have shown great potential on improving traffic performance with a shortened time gap through advanced sensing and Vehicle-to-Vehicle (V2V) communication technologies. However, V2V communication is not always reliable in realistic traffic conditions. ...
Keywords: communication disruption; cooperative adaptive cruise control; adaptive cruise control; stability analysis; delay robustness

Lightning Talk 1: A Two-Sided Equilibrium Model of Vehicle-To-Vehicle Charging Platform

Title: A Two-Sided Equilibrium Model of Vehicle-To-Vehicle Charging Platform
Authors: Xuekai Cen, Kanghui Ren, Enoch Lee, Hong K. Lo
Abstract: A novel mobile charging service utilizing vehicle-to-vehicle (V2V) charging technology has been proposed as a complement to fixed charging infrastructure (CI), enabling electric vehicles (EVs) to exchange electricity. This study develops a two-sided equilibrium model for a V2V charging platform, where the demand-side Charging Vehicles (CVs) choose ...
Keywords: Electric Vehicle; Vehicle-to-Vehicle; Charging; Non-cooperative Game; Nash Bargaining

Poster Session 1: Developing Platooning Systems of Connected and Automated Vehicles with Guaranteed Stability and Robustness against Degradation due to Communication Disruption

Title: Developing Platooning Systems of Connected and Automated Vehicles with Guaranteed Stability and Robustness against Degradation due to Communication Disruption
Authors: Yuan Zheng, Yu Zhang, Xu Qu, Shen Li, Bin Ran
Abstract: Connected and automated vehicle platooning systems like cooperative adaptive cruise control (CACC) have shown great potential on improving traffic performance with a shortened time gap through advanced sensing and Vehicle-to-Vehicle (V2V) communication technologies. However, V2V communication is not always reliable in realistic traffic conditions. ...
Keywords: communication disruption; cooperative adaptive cruise control; adaptive cruise control; stability analysis; delay robustness

Poster Session 1: A Two-Sided Equilibrium Model of Vehicle-To-Vehicle Charging Platform

Title: A Two-Sided Equilibrium Model of Vehicle-To-Vehicle Charging Platform
Authors: Xuekai Cen, Kanghui Ren, Enoch Lee, Hong K. Lo
Abstract: A novel mobile charging service utilizing vehicle-to-vehicle (V2V) charging technology has been proposed as a complement to fixed charging infrastructure (CI), enabling electric vehicles (EVs) to exchange electricity. This study develops a two-sided equilibrium model for a V2V charging platform, where the demand-side Charging Vehicles (CVs) choose ...
Keywords: Electric Vehicle; Vehicle-to-Vehicle; Charging; Non-cooperative Game; Nash Bargaining

Podium Session 5: How and When Cordon Metering Can Reduce Travel Times

Title: How and When Cordon Metering Can Reduce Travel Times
Authors: Jean Doig, Carlos F. Daganzo, Michael J. Cassidy
Abstract: The paper addresses two questions regarding cordon metering that have until now gone unanswered. The first of these pertains to how and where a metered cordon ought to be placed in a city to be of greatest benefit. A simple 3-step rule is proposed that can be readily applied in real settings, and that we call the cordon layout conjecture, or CLC. I...
Keywords: Urban congestion; Cordon metering; Traffic management

Lightning Talk 2: Distributionally Robust Origin Destination Demand Estimation

Title: Distributionally Robust Origin Destination Demand Estimation
Authors: Jingxing Wang, Jun Song, Chaoyue Zhao, Xuegang (Jeff) Ban
Abstract: Gaining a good understanding of the travel demands of a city or region is extremely important for many transportation applications. For stochastic origin-destination (OD) estimation problems, an accurate distribution assumption or observation of OD estimates or data is usually desired but not always available. In this paper, we establish a novel tw...
Keywords: OD demand estimation; distributionally robust optimization; quasi-sparsity

Lightning Talk 2: Estimation of Schedule Preference and Crowding Perception in Urban Rail Corridor Commuting: An Inverse Optimization Method

Title: Estimation of Schedule Preference and Crowding Perception in Urban Rail Corridor Commuting: An Inverse Optimization Method
Authors: Pu Xu, Tian-Liang Liu, Qiong Tian, Bingfeng Si, Wei Liu, Hai-Jun Huang
Abstract: This paper introduces an inverse optimization method to uncover commuters’ schedule preference and crowding perception based on aggregated observations from smart card data for an urban rail corridor system. The assessment of time-of-use preferences typically involves the use of econometric models of discrete choice based on detailed travel survey ...
Keywords: Travel behavior; Rail transit; Morning commute; Smart card data; Inverse optimization

Poster Session 2: Distributionally Robust Origin Destination Demand Estimation

Title: Distributionally Robust Origin Destination Demand Estimation
Authors: Jingxing Wang, Jun Song, Chaoyue Zhao, Xuegang (Jeff) Ban
Abstract: Gaining a good understanding of the travel demands of a city or region is extremely important for many transportation applications. For stochastic origin-destination (OD) estimation problems, an accurate distribution assumption or observation of OD estimates or data is usually desired but not always available. In this paper, we establish a novel tw...
Keywords: OD demand estimation; distributionally robust optimization; quasi-sparsity

Poster Session 2: Estimation of Schedule Preference and Crowding Perception in Urban Rail Corridor Commuting: An Inverse Optimization Method

Title: Estimation of Schedule Preference and Crowding Perception in Urban Rail Corridor Commuting: An Inverse Optimization Method
Authors: Pu Xu, Tian-Liang Liu, Qiong Tian, Bingfeng Si, Wei Liu, Hai-Jun Huang
Abstract: This paper introduces an inverse optimization method to uncover commuters’ schedule preference and crowding perception based on aggregated observations from smart card data for an urban rail corridor system. The assessment of time-of-use preferences typically involves the use of econometric models of discrete choice based on detailed travel survey ...
Keywords: Travel behavior; Rail transit; Morning commute; Smart card data; Inverse optimization

Podium Session 9: A Game-Theoretic Framework for Generic Second Order Traffic Flow Using Mean Field Games and Adversarial Inverse Reinforcement Learning

Title: A Game-Theoretic Framework for Generic Second Order Traffic Flow Using Mean Field Games and Adversarial Inverse Reinforcement Learning
Authors: Zhaobin Mo, Xu Chen, Xuan Di, Elisa Iacomini, Chiara Segala, Michael Herty, Mathieu Lauriere
Abstract: A traffic system can be interpreted as a multi-agent system, wherein vehicles choose the most efficient driving approaches guided by inter-connected goals or strategies. This paper aims to develop a family of mean field games (MFG) for generic second-order traffic flow models (GSOM), in which cars control individual velocity to optimize their objec...
Keywords: Mean field game (MFG); Generic second traffic flow model; Adversarial Inverse Reinforcement Learning (AIRL)

Edited by Guoyang Qin

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