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 1: Alleviating Bus Bunching via Modular Vehicles

Title: Alleviating Bus Bunching via Modular Vehicles
Authors: Yuhao Liu, Zhibin Chen, Xiaolei Wang
Abstract: The notorious phenomenon of bus bunching prevailing in uncontrolled bus systems produces irregular headways and downgrades the level of service by increasing passengers’ expected waiting time. Modular autonomous vehicles (MAVs), due to their ability to split and merge enroute, have the potential to help both late and early buses recover from schedu...
Keywords: Bus bunching; Modular vehicle; Dynamic system; Deep reinforcement learning

Lightning Talk 1: Modeling Residual-Vehicle Effects in Undersaturation Conditions on Uncertainty Estimation of the Connected Vehicle Penetration Rate

Title: Modeling Residual-Vehicle Effects in Undersaturation Conditions on Uncertainty Estimation of the Connected Vehicle Penetration Rate
Authors: Shaocheng Jia, S.C. Wong, Wai Wong
Abstract: In the transition to full deployment of connected vehicles (CVs), the CV penetration rate plays a key role in bridging the gap between partial and complete traffic information. Several innovative methods have been proposed to estimate the CV penetration rate using only CV data. However, these methods, as point estimators, may lead to biased estimat...
Keywords: Connected vehicle penetration rate uncertainty; probabilistic penetration rate model; residual vehicle estimation; Markov-constrained queue; length model; signal control with uncertainty

Lightning Talk 1: Data Driven Origin-Destination Matrix Estimation on Large Networks – A Joint Origin-Destination-Path-Choice Formulation

Title: Data Driven Origin-Destination Matrix Estimation on Large Networks - A Joint Origin-Destination-Path-Choice Formulation
Authors: Yumin Cao, Hans van Lint, Panchamy Krishnakumari, Michiel Bliemer
Abstract: This paper presents a novel approach to data-driven time-dependent origin-destination (OD) estimation using a joint origin-destination-path choice formulation, inspired by the well-known equivalence of doubly constraint gravity models and multinomial logit models for joint O-D choice. This new formulation provides a theoretical basis and generalize...
Keywords: Dynamic OD matrix estimation; Gravity model; Joint origin-destination-path choice; Principal component analysis

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

Poster Session 1: Modeling Residual-Vehicle Effects in Undersaturation Conditions on Uncertainty Estimation of the Connected Vehicle Penetration Rate

Title: Modeling Residual-Vehicle Effects in Undersaturation Conditions on Uncertainty Estimation of the Connected Vehicle Penetration Rate
Authors: Shaocheng Jia, S.C. Wong, Wai Wong
Abstract: In the transition to full deployment of connected vehicles (CVs), the CV penetration rate plays a key role in bridging the gap between partial and complete traffic information. Several innovative methods have been proposed to estimate the CV penetration rate using only CV data. However, these methods, as point estimators, may lead to biased estimat...
Keywords: Connected vehicle penetration rate uncertainty; probabilistic penetration rate model; residual vehicle estimation; Markov-constrained queue; length model; signal control with uncertainty

Poster Session 1: Data Driven Origin-Destination Matrix Estimation on Large Networks – A Joint Origin-Destination-Path-Choice Formulation

Title: Data Driven Origin-Destination Matrix Estimation on Large Networks - A Joint Origin-Destination-Path-Choice Formulation
Authors: Yumin Cao, Hans van Lint, Panchamy Krishnakumari, Michiel Bliemer
Abstract: This paper presents a novel approach to data-driven time-dependent origin-destination (OD) estimation using a joint origin-destination-path choice formulation, inspired by the well-known equivalence of doubly constraint gravity models and multinomial logit models for joint O-D choice. This new formulation provides a theoretical basis and generalize...
Keywords: Dynamic OD matrix estimation; Gravity model; Joint origin-destination-path choice; Principal component analysis

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

Podium Session 4: Design of Mixed Fixed-Flexible Bus Public Transport Networks by Tracking the Paths of On-Demand Vehicles

Title: Design of Mixed Fixed-Flexible Bus Public Transport Networks by Tracking the Paths of On-Demand Vehicles
Authors: Andrés Fielbaum, Javier Alonso-Mora
Abstract: On-demand ridepooling (ODRP) vehicles follow routes that are fully flexible. However, when the system does not provide door-to-door service and users can be asked to walk, their paths tend to concentrate, particularly along main streets that connect highly demanded areas of the city. These frequently travelled segments are hence useful to multiple ...
Keywords: Public transport design; On-demand mobility; Ridepooling; Walking legs; Fixed routes

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

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 7: A Paradox of Telecommuting and Staggered Work Hours in the Bottleneck Model

Title: A Paradox of Telecommuting and Staggered Work Hours in the Bottleneck Model
Authors: Takara Sakai, Takashi Akamatsu, Koki Satsukawa
Abstract: We study the long- and short-term effects of telecommuting (TLC), staggered work hours (SWH), and their combined scheme on peak-period congestion and location patterns. In order to enable a unified comparison of the schemes’ long- and short-term effects, we develop a novel equilibrium analysis approach that consistently synthesizes the long-term eq...
Keywords: Bottleneck model; Corridor network; Telecommuting; Staggered work hours; Departure time choice; Location choice

Lightning Talk 2: Mobility Service Providers’ Interacting Strategies under Multi-Modal Equilibrium

Title: Mobility Service Providers' Interacting Strategies under Multi-Modal Equilibrium
Authors: Claudia Bandiera, Richard D. Connors, Francesco Viti
Abstract: In this paper, we analyse the interactions between Mobility Service Providers (MSP) strategies in a multi-modal system. We formulate the problem using a bi-level structure extending Multi-modal Network Design (MND) principles. The upper level models the profit maximisation objectives of multiple MSPs operating and offering different services to the...
Keywords: Mobility-as-a-Service; Mobility Service Providers; Multi-modal Equilibrium; Variational Inequality; EPEC

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: Mobility Service Providers’ Interacting Strategies under Multi-Modal Equilibrium

Title: Mobility Service Providers' Interacting Strategies under Multi-Modal Equilibrium
Authors: Claudia Bandiera, Richard D. Connors, Francesco Viti
Abstract: In this paper, we analyse the interactions between Mobility Service Providers (MSP) strategies in a multi-modal system. We formulate the problem using a bi-level structure extending Multi-modal Network Design (MND) principles. The upper level models the profit maximisation objectives of multiple MSPs operating and offering different services to the...
Keywords: Mobility-as-a-Service; Mobility Service Providers; Multi-modal Equilibrium; Variational Inequality; EPEC

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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