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

Poster Session

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Poster Session 1: Combining Time Dependency and Behavioral Game: A Deep Markov Cognitive Hierarchy Model for Human-Like Discretionary Lane Changing Modeling

Title: Combining Time Dependency and Behavioral Game: A Deep Markov Cognitive Hierarchy Model for Human-Like Discretionary Lane Changing Modeling
Authors: Kehua Chen, Meixin Zhu, Lijun Sun, Hai Yang
Abstract: Human drivers take discretionary lane changes when the target lane is perceived to offer better traffic conditions. Improper discretionary lane changes, however, lead to traffic congestion or even crashes. Considering its significant impact on traffic flow efficiency and safety, accurate modeling and prediction of discretionary lane-changing (LC) b...
Keywords: Discretionary lane changing; Game theory; Hidden markov model; Cognitive hierarchy

Poster Session 1: Stability Analysis of a Departure Time Choice Problem with Atomic Vehicle Models

Title: Stability Analysis of a Departure Time Choice Problem with Atomic Vehicle Models
Authors: Koki Satsukawa, Kentaro Wada, Takamasa Iryo
Abstract: In this study, we analyse the global stability of the equilibrium in a departure time choice problem using a game-theoretic approach that deals with atomic users. We first formulate the departure time choice problem as a strategic game in which atomic users select departure times to minimise their trip cost; we call this game the ‘departure time ch...
Keywords: Convergence/stability; Departure time choice problem; Evolutionary dynamics; Epsilon-Nash equilibrium; Atomic users

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: A Topological Network Connectivity Design Problem Based on Spectral Analysis

Title: A Topological Network Connectivity Design Problem Based on Spectral Analysis
Authors: Shoichiro Nakayama, Shun-ichi Kobayashi, Hiromichi Yamaguchi
Abstract: How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue...
Keywords: Connectivity; Fiedler vector; Semidefinite programing; Convexity

Poster Session 1: Optimizing OD-Based Up-Front Discounting Strategies for Enroute Ridepooling Services

Title: Optimizing OD-Based Up-Front Discounting Strategies for Enroute Ridepooling Services
Authors: Siying Wang, Xiaolei Wang, Chen Yang, Wei Liu, Xiaoning Zhang
Abstract: The technological progress in the recent decade has greatly facilitated the large-scale implementation of dynamic enroute ridepooling services, such as Uber Pool and DiDi Pinche. To sustain a profitable dynamic ridepooling service, a well-designed pricing scheme is crucial. This paper focuses on the optimization of up-front discounting strategies f...
Keywords: enroute ridepooling; up-front pricing strategy; derivative-free optimization

Poster Session 1: Two-Step Quadratic Programming for Physically Meaningful Smoothing of Longitudinal Vehicle Trajectories

Title: Two-Step Quadratic Programming for Physically Meaningful Smoothing of Longitudinal Vehicle Trajectories
Authors: Ximeng Fan, Wen-Long Jin, Penghang Yin
Abstract: Longitudinal vehicle trajectories suffer from errors and noise due to detection and extraction techniques, challenging their applications. Existing smoothing methods either lack physical meaning or cannot ensure solution existence and uniqueness. To address this, we propose a two-step quadratic programming method that aligns smoothed speeds and hig...
Keywords: Longitudinal vehicle trajectories; discrepancy and roughness; two-step quadratic programming; existence and uniqueness; NGSIM and highD data

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

Poster Session 1: Transit Fares Integrating Alternative Modes as a Delay Insurance

Title: Transit Fares Integrating Alternative Modes as a Delay Insurance
Authors: Yihe Zhou, Wenzhe Sun, Jan-Dirk Schmöcker
Abstract: Public transport (PT) fare policy remains subject to innovations, not least evident in the Mobility as a Service discussion. Mode integration and related fare strategies can be used to increase the attractiveness of PT by compensating for potential delays. This study proposes “premium fares” as a novel pricing tool that can evaluate and improve the...
Keywords: Travel time reliability; Delay insurance; Premium fare; Integrated multimodal transport; Nonlinear and dynamic programming

Poster Session 1: Physics-Informed Machine Learning for Calibrating Macroscopic Traffic Flow Models

Title: Physics-Informed Machine Learning for Calibrating Macroscopic Traffic Flow Models
Authors: Yu Tang, Li Jin, Kaan Ozbay
Abstract: Well-calibrated traffic flow models are fundamental to understanding traffic phenomena and designing control strategies. Traditional calibration has been developed based on optimization methods. In this paper, we propose a novel physics-informed, learning-based calibration approach that achieves performances comparable to and even better than those...
Keywords: Physics-informed learning; Parameter identification; Traffic flow models

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: 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: Optimal Operation Strategies of an Urban Crowdshipping Platform in Asset-Light, Asset-Medium, or Asset-Heavy Business Format

Title: Optimal Operation Strategies of an Urban Crowdshipping Platform in Asset-Light, Asset-Medium, or Asset-Heavy Business Format
Authors: Zhuoye Zhang, Fangni Zhang
Abstract: This paper investigates the operation strategies of an urban crowdshipping platform, which utilizes the latent capacity of the traveling ‘crowd’ in the transportation system to facilitate parcel delivery. We develop an analytical model to characterize the decision-making and operation strategies of a crowdshipping operator in alternative business f...
Keywords: Crowdshipping; Two-sided market; Asset-light; Asset-medium; Asset-heavy

Poster Session 2: Modeling an On-Demand Meal Delivery System with Human Couriers and Autonomous Vehicles in a Spatial Market

Title: Modeling an On-Demand Meal Delivery System with Human Couriers and Autonomous Vehicles in a Spatial Market
Authors: Anke Ye, Kenan Zhang, Michael G.H. Bell, Xiqun (Michael) Chen, Simon Hu
Abstract: This paper investigates the impacts of introducing autonomous vehicles (AVs) into an on-demand meal delivery system at a strategic level. The proposed model consists of (i) a microscopic physical model describing the delivery process for bundled orders and (ii) a macroscopic network equilibrium model characterizing the interactions among customers,...
Keywords: On-demand meal delivery; Autonomous vehicles; Bundling delivery; Network equilibrium; Strategic management

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: Planning Service Protocols for Extra-Long Trains with Transfers

Title: Planning Service Protocols for Extra-Long Trains with Transfers
Authors: Jesus Osorio, Shiyu Shen, Yanfeng Ouyang
Abstract: This paper presents a modeling framework for optimizing operational protocols of extra-long trains (XLTs) in metro systems; i.e., trains longer than station platforms. With the rising travel demand in megacities, metro systems face challenges such as overcrowded stations, delays, and passenger anxieties. XLTs have been proposed as a promising solut...
Keywords: Metro train; Timetabling; Extra-long train; Mixed-integer program; Network design

Poster Session 2: Network Macroscopic Fundamental Diagram-Informed Graph Learning Method for Traffic State Imputation

Title: Network Macroscopic Fundamental Diagram-Informed Graph Learning Method for Traffic State Imputation
Authors: Jiawei Xue, Eunhan Ka, Yiheng Feng, Satish V. Ukkusuri
Abstract: Traffic state imputation refers to the estimation of missing values of traffic variables, such as flow rate and traffic density, using available data. It furnishes traffic context for various operation tasks such as vehicle routing, and enables us to augment existing datasets (e.g., PeMS, UTD19, Uber Movement) for diverse theoretical and practical ...
Keywords: Traffic state imputation; Physics-informed machine learning; Network macroscopic funda-mental diagram; Graph neural networks

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: Offline Planning and Online Operation of Zonal-Based Flexible Bus Service under Demand Uncertainties and Dynamic Cancellations

Title: Offline Planning and Online Operation of Zonal-Based Flexible Bus Service under Demand Uncertainties and Dynamic Cancellations
Authors: Manzi Li, Enoch Lee, Hong K. Lo
Abstract: This paper introduces a comprehensive framework for planning an operating a zonal-based flexible bus service, a public transit mode designed to accommodate uncertain demand patterns. The framework addresses both offline planning based on stochastic demand distributions and cancellations, as well as online routing considering real-time orders and ca...
Keywords: On-demand transit; Dynamic optimisation; Flexible bus; Order cancellation; Stochastic demand; Three-phase optimisation

Poster Session 2: Bridging the Gap between Micro-Economics and Micro-Mobility: A Two-Dimensional Risk-Based Microscopic Model of Pedestrians’ and Bicyclists’ Operational Behaviors

Title: Bridging the Gap between Micro-Economics and Micro-Mobility: A Two-Dimensional Risk-Based Microscopic Model of Pedestrians' and Bicyclists' Operational Behaviors
Authors: Mohaiminul Haque, Samer Hamdar, Alireza Talebpour
Abstract: Due to the inherent safety concerns associated with traffic movement in unconstrained two-dimensional settings, it is important that pedestrians’ and other modes’ movements such as bicyclists are modeled as a risk-taking stochastic dynamic process that may lead to errors and thus contacts and collisions. Among the existing models that may capture r...
Keywords: Bicycles; Pedestrians; Prospect Theory; Safety; Traffic Simulation

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

Poster Session 2: Providing Real-Time En-Route Suggestions to CAVs for Congestion Mitigation: A Two-Way Deep Reinforcement Learning Approach

Title: Providing Real-Time En-Route Suggestions to CAVs for Congestion Mitigation: A Two-Way Deep Reinforcement Learning Approach
Authors: Xiaoyu Ma, Xiaozheng (Sean) He
Abstract: This research investigates the effectiveness of information provision for congestion reduction in Connected Autonomous Vehicle (CAV) systems. The inherent advantages of CAVs, such as vehicle-to-everything communication, advanced vehicle autonomy, and reduced human involvement, make them conducive to achieving Correlated Equilibrium (CE). Leveraging...
Keywords: Information provision; Correlated Equilibrium; Reinforcement learning; Connected autonomous vehicles; Congestion mitigation

Poster Session 2: Sensor Placement Considering the Observability of Traffic Dynamics: On the Algebraic and Graphical Perspectives

Title: Sensor Placement Considering the Observability of Traffic Dynamics: On the Algebraic and Graphical Perspectives
Authors: Xinyue Hu, Yueyue Fan
Abstract: In this paper, we present a new sensor location model that aims to maximize the observability of link densities in a dynamic traffic network described using a piecewise linear ODE system. We develop an algebraic approach based on the eigenstructure to determine the sensor location for achieving full observability with a minimal number of sensors. A...
Keywords: dynamic traffic networks; sensor location problem; exact observability; structural observability

Poster Session 2: Kernel-Based Planning and Imitation Learning Control for Flow Smoothing in Mixed Autonomy Traffic

Title: Kernel-Based Planning and Imitation Learning Control for Flow Smoothing in Mixed Autonomy Traffic
Authors: Zhe Fu, Arwa Alanqary, Abdul Rahman Kreidieh, Alexandre M. Bayen
Abstract: This article presents a new architecture for managing heterogeneous fleets aimed at achieving flow harmonization in mixed-autonomy traffic, demonstrating robustness across different sensing paradigms. We develop a kernel-based planning controller capable of providing anticipative coordination over low-bandwidth or high-latency networks. Furthermore...
Keywords: Traffic Flow Harmonization; Mixed Autonomy Traffic; Kernel-based Planning; Parameter Optimization; Imitation Learning

Poster Session 2: Simulation-Based Robust and Adaptive Optimization Method for Heteroscedastic Transportation Problems

Title: Simulation-Based Robust and Adaptive Optimization Method for Heteroscedastic Transportation Problems
Authors: Ziyuan Gu, Yifan Li, Meead Saberi, Zhiyuan Liu
Abstract: Simulation-based optimization is an effective solution to complex transportation problems relying on stochastic simulations. However, existing studies generally performed a fixed number of evaluations for each decision vector across the design space, overlooking simulation heteroscedasticity and its effects on solution efficiency and robustness. In...
Keywords: Simulation-based optimization; Robust design; Computational resources allocation; Bayesian inference; Heteroscedasticity

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