activity
20242026
collaborators

15 papers

eess.SY2026

Semi-on-Demand Hybrid Transit Route Design with Shared Autonomous Mobility Services

Max T. M. Ng, Florian Dandl, Hani S. Mahmassani +1

Shared Autonomous Vehicles (SAVs) enable transit agencies to design more agile and responsive services at lower operating costs. This study designs and evaluates a semi-on-demand h…

eess.SY2026

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Max T. M. Ng, Hani S. Mahmassani, Draco Tong +2

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service effici…

eess.SY2026

Joint Optimization of Pattern, Headway, and Fleet Size of Multiple Urban Transit Lines with Perceived Headway Consideration and Passenger Flow Allocation

Max T. M. Ng, Draco Tong, Hani S. Mahmassani +2

This study addresses the urban transit pattern design problem, optimizing stop sequences, headways, and fleet sizes across multiple routes and periods simultaneously to minimize us…

cs.RO2026

Can the Waymo Open Motion Dataset Support Realistic Behavioral Modeling? A Validation Study with Naturalistic Trajectories

Yanlin Zhang, Sungyong Chung, Nachuan Li +4

The Waymo Open Motion Dataset (WOMD) has become a popular resource for data-driven modeling of autonomous vehicles (AVs) behavior. However, its validity for behavioral analysis rem…

stat.AP2025

Using Drift Diffusion Model to Analyze Cars' Lane Change Decisions behind Heavy Vehicles

Nachuan Li, Hani S. Mahmassani, Soyoung Ahn +1

Heavy vehicles (HVs) pose a significant challenge to maintaining a smooth traffic flow on the freeway because they are slower moving and create large blind spots. It is therefore d…

cs.LG2025

Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Control

Max T. M. Ng, Roman Engelhardt, Florian Dandl +2

This paper develops a semi-on-demand transit feeder service using shared autonomous vehicles (SAVs) and zonal dispatching control based on reinforcement learning (RL). This service…