AI for Smart Transportation
Public transportation systems worldwide face persistent challenges of efficiency, reliability, and sustainability. In this chapter, we explore how AI-powered approaches can …
Michael Wilbur
Michael Wilbur
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Artificial Intelligence and Society, 2026
SmartTransit.AI: A Dynamic Paratransit and Microtransit Application
New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing …
Sophie Pavia
Deploying Mobility-On-Demand for All by Optimizing Paratransit Services
While on-demand ride-sharing services have become popular in recent years, traditional on-demand transit services cannot be used by everyone, e.g., wheelchair-bound people. …
Sophie Pavia
Impact of COVID-19 on Public Transit Accessibility and Ridership
COVID-19 has radically transformed urban travel behavior throughout the world. Agencies have had to provide adequate service while navigating a rapidly changing environment with …
Michael Wilbur
Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows
The offline pickup and delivery problem with time windows (PDPTW) is a classical combinatorial optimization problem in the transportation community, which has proven to be very …
Youngseo Kim
Decentralized Computation Market for Stream Processing Applications
While cloud computing is the current standard for outsourcing computation, it can be prohibitively expensive for cities and infrastructure operators to deploy services. At the same …
Scott Eisele
An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services
Many transit agencies operating paratransit and microtransit ser-vices have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and …
Michael Wilbur
Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles
Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal-combustion and electric vehicles. Optimizing the operation …
Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-Task and Inductive Transfer Learning
Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and hybrid (HV) vehicles to their fleets. However, …
Michael Wilbur
Efficient Data Management for Intelligent Urban Mobility Systems
Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data …
Michael Wilbur