All (106)
Podi­um (36)
Poster (24)
Light­ning Talk (24)
Spe­cial Ses­sion (3)
Sun­day, July 14 (3)
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)
Emerg­ing Mobil­i­ty Sys­tems: II (3)
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

AI and Machine Learning Innovations in Traffic and Mobility Analysis

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Podium Session 10: Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach

Title: Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach
Authors: Qiqing Wang, Kaidi Yang
Abstract: This paper proposes a privacy-preserving data fusion method for traffic state estimation (TSE). Unlike existing works that assume all data sources to be accessible by a single trusted party, we explicitly address data privacy concerns that arise in the collaboration and data sharing between multiple data owners, such as municipal authorities (MAs) ...
Keywords: Data Fusion; Federated Learning; Data Privacy; Traffic State Estimation; Traffic Flow Theory

Podium Session 10: Implications of Stop-and-Go Traffic on Training Learning-Based Car-Following Control

Title: Implications of Stop-and-Go Traffic on Training Learning-Based Car-Following Control
Authors: Anye Zhou, Srinivas Peeta, Hao Zhou, Jorge Laval, Zejiang Wang, Adian Cook
Abstract: Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving t...
Keywords: Car-following control; System identification; Behavior cloning; Deep reinforcement learning; Generalizability

Podium Session 10: Uncovering Physics-Regularized Data Generation Processes for Individual Human Mobility: A Multi-Task Gaussian Process Approach Based on Multiple Kernel Learning

Title: Uncovering Physics-Regularized Data Generation Processes for Individual Human Mobility: A Multi-Task Gaussian Process Approach Based on Multiple Kernel Learning
Authors: Ekin Uğurel, Shuai Huang, Cynthia Chen
Abstract: Passively-generated mobile data has grown increasingly popular in the travel behavior (or human mobility) literature. A relatively untapped potential for passively-generated mobile data is synthetic population generation, which is the basis for any large-scale simulations for purposes ranging from state monitoring, policy evaluation, and digital tw...
Keywords: Synthetic mobile data; Gaussian process; Multiple kernel Learning; Physics-regularization; Travel behavior

Podium Session 10: Calibrating Car-Following Models via Bayesian Dynamic Regression

Title: Calibrating Car-Following Models via Bayesian Dynamic Regression
Authors: Chengyuan Zhang, Wenshuo Wang, Lijun Sun
Abstract: Car-following behavior modeling is critical for understanding traffic flow dynamics and developing high-fidelity microscopic simulation models. Most existing impulse-response car-following models prioritize computational efficiency and interpretability by using a parsimonious nonlinear function based on immediate preceding state observations. Howev...
Keywords: car-following models; dynamic regression; Bayesian inference; microscopic traffic simulation

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