Urban Transit System Diagnosis, Monitoring, and Management Using Mobility Sensing Data

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The adoption of emerging technologies in transportation such as autonomous vehicles (AV) and shared mobility services are poised to create a revolutionary future for urban mobility. However, this trend may create existential threat to public transportation systems and to social values, such as equity, accessibility, affordability, and environmental sustainability, that public transit services protect in our society. Despite this threat, public transportation system operations and planning are being transformed from a once data-starved arena into one of the most data-rich areas in transportation planning and management. With the emergence and availability of mobility sensing data and automated data sources in public transportation systems, there is an opportunity to perform better system diagnoses, enhance operational solutions, and create actionable intelligence to improve the quality and efficiency of public transport services. The long--term goal of the proposed research is to develop a framework for system diagnostics for public transit systems to monitor, control, and manage services and operations. A set of rigorous data analysis techniques and innovative methods will be utilized to develop empirical models, network simulations, and optimization models. The proposed framework has the following models as building blocks: 1) Performance (system supply); 2) Behaviour (system demand); and 3) Decision Support. Important short--term objectives are defined in this research proposal. Each objective contributes to one building block of the proposed framework (performance, behaviour, and decision support) and toward the long--term objective: Objective 1: Study seasonal and temporal effects on public transit system performance by conducting a cross-comparison study among public transit systems. Objective 2: Modeling of passenger experience for the future design of public transportation network structure in an integrated public transportation and (autonomous) shared mobility system. Objective 3: Macroscopic modeling of rail transit operations considering the effect of operational practices and passenger crowding in the system. This research proposal is aligned with Environment Canada's sustainable development strategies and the federal government policy on investing in public transit. The output of this research will be useful for transit agencies and authorities in providing decision support tools for efficient urban public transport systems. This research program can shape policies on transportation toward more sustainable and environment friendly principles. The research will directly contribute to social values such as equity, inclusion, and sustainability in our society.