All (106)
Podi­um (36)
Poster (24)
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Mon­day, July 15 (43)
Tues­day, July 16 (42)
Wednes­day, July 17 (17)
Advanced Traf­fic Con­trol (4)
AI and Machine Learn­ing Inno­va­tions in Traf­fic and Mobil­i­ty Analy­sis (4)
Curb­side Space Man­age­ment (3)
Dynam­ics and Safe­ty Impli­ca­tions in Auto­mat­ed Vehi­cle Sys­tems (3)
Emerg­ing Mobil­i­ty Sys­tems: I (3)
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Inno­va­tions in Tran­sit Design and Opti­miza­tion (3)
Inno­va­tions in Trans­porta­tion Mod­el­ing (4)
Rout­ing and Equi­lib­ri­um in Traf­fic Net­works (4)
Traf­fic Flow The­o­ry (4)

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

Routing and Equilibrium in Traffic Networks

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Podium Session 6: A Generalized Rationally Inattentive Route Choice Model with Non-uniform Marginal Information Costs

Title: A Generalized Rationally Inattentive Route Choice Model with Non-uniform Marginal Information Costs
Authors: Bo Zhou, Ronghui Liu
Abstract: Information consumes attention. In the information-rich society, a wealth of information can support decision-making, but it can also create poverty of attention to and inability to make the best use of information. This study applies the theory of rational inattention in modelling traveller’s route choice behaviour, where the attention (costs) to ...
Keywords: Route choice; Rational inattention; Non-uniform marginal information costs; Closed-form expression

Podium Session 6: Markov Game for CV Joint Adaptive Routing in Stochastic Traffic Networks: A Scalable Learning Approach

Title: Markov Game for CV Joint Adaptive Routing in Stochastic Traffic Networks: A Scalable Learning Approach
Authors: Shan Yang, Yang Liu
Abstract: This study proposes a learning-based approach to tackle the challenge of joint adaptive routing in stochastic traffic networks with Connected Vehicles (CVs). We introduce a Markov Routing Game (MRG) to model the adaptive routing behavior of all vehicles in such networks, thereby incorporating both competitive route choices and real-time decision-ma...
Keywords: Markov routing game; Connected vehicles; Joint adaptive routing; Mean-field multi-agent reinforcement learning; Stochastic traffic network

Podium Session 6: Estimating Markov Chain Mixing Times: Convergence Rate Towards Equilibrium of a Stochastic Process Traffic Assignment Model

Title: Estimating Markov Chain Mixing Times: Convergence Rate Towards Equilibrium of a Stochastic Process Traffic Assignment Model
Authors: Takamasa Iryo, David Watling, Martin Hazelton
Abstract: Network equilibrium models have been extensively used for decades. The rationale for using equilibrium as a predictor is essentially that (i) a unique and globally stable equilibrium point is guaranteed to exist, and (ii) the transient period over which a system adapts to a change is sufficiently short in time that it can be neglected. However, we ...
Keywords: Markov chain mixing time; Day-to-day dynamics; Stochastic traffic assignment process

Podium Session 6: A Day-to-Day Dynamical Approach to the Most Likely User Equilibrium Problem

Title: A Day-to-Day Dynamical Approach to the Most Likely User Equilibrium Problem
Authors: Jiayang Li, Qianni Wang, Liyang Feng, Jun Xie, Yu (Marco) Nie
Abstract: The lack of a unique user equilibrium (UE) route flow in traffic assignment has posed a significant challenge to many transportation applications. The maximum-entropy principle, which advocates for the consistent selection of the most likely solution, is often used to address the challenge. Built on a recently proposed day-to-day (DTD) discrete-tim...
Keywords: Maximum entropy; Traffic assignment; Cumulative logit; Day-to-day dynamical model; Proportionality condition

Edited by Guoyang Qin

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