Cyber-Physical Systems

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. Paratransit services, operated by public transit agencies, are a critical …

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 users to share rides in high-capacity vehicles and vans. Most transit …

Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing

An emergency responder management (ERM) system dispatches responders, such as ambulances, when it receives requests for medical aid. ERM systems can also proactively reposition responders between predesignated waiting locations to cover any gaps that …

An Online Approach to Solving Public Transit Stationing and Dispatch Problem

Public bus transit systems provide critical transportation services for large sections of modern communities. On-time performance and maintaining the reliable quality of service is therefore very important. Unfortunately, disruptions caused by …

Forecasting and Mitigating Disruptions in Public Bus Transit Services

Public transportation systems often suffer from unexpected fluctuations in demand and disruptions, such as mechanical failures and medical emergencies. These fluctuations and disruptions lead to delays and overcrowding, which are detrimental to the …

Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks

The increasing reliance of drivers on navigation applications has made transportation networks more susceptible to data-manipulation attacks by malicious actors. Adversaries may exploit vulnerabilities in the data collection or processing of …

Grid Resilience Against Wildfire with Machine Learning: Machine Learning based Detection, Localization and Mitigation of the Impact of Forest Fires on Power Grids

Decision-making by human operators, using system data obtained from bulk transmission systems, under adverse dynamic events should be supplemented by intelligent proactive control based on state-of-the-art machine learning (ML) algorithms. This …

Reinforcement Learning based Proactive Control for Enabling Power Grid Resilience to Wildfire

Industrial electric power grid operation subject to an extreme event requires decision making by human operators under stressful conditions. Decision making using system data informatics under adverse dynamic events, especially if forecasted, should …

PhobosBC: A Blockchain-based Crowdsourced Post-disaster Mapping System and its Agent-based Simulation

After a major natural disaster strikes a region, emergency response often lacks information about the post-disaster state of the road network. Conflicting information about the region from multiple sources creates confusion. Thus, it is imperative to …

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 reduced revenue. As COVID-19-related restrictions are lifted, transit …