Modeling the Impact of Emerging Mobility Services Using Big Data Analytics

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The transportation market is undergoing a paradigm shift in response to new mobility trends and technologies. Today's market benefits from more wide-ranging and flexible, on-demand, and responsive emerging mobility services, varying from micro-mobility (e.g., scooter) to ride-hailing (e.g., UberX) and on-demand transit services. These services promise to bring substantial economic, environmental, and social benefits to society. On the other hand, if not properly introduced, emerging mobility services might induce more demand for travel, a shift away from public transit, and possibly urban sprawl, thereby leading to unsustainable travel practices among their users. There is also a question of whether the benefits and costs of emerging mobility services on various population groups are distributed equitably. There is thus a pressing need to model the impacts of these emerging mobility services to provide transportation planners and mobility providers with a more informed decision-making process to capitalize on their potential benefits. The long-term vision of the research program is to advance our ability to model emerging mobility services and analyze their multifaceted impacts to proactively plan their introduction, management, and operation while meeting the sustainability goals of our cities. To help achieve the short-term objectives of this vision, this research program will: (1) Develop a multimodal database to collect, store, fuse, and process data from different emerging mobility services; (2) Develop models to estimate and predict the demand for emerging mobility services, and (3) Develop a unified framework to assess the equity performance of emerging mobility services. This innovative research will develop a generic data-driven demand prediction modeling framework that accommodates many emerging mobility services and their continuously evolving features. This research will thus capitalize on multimodal data collection and integration, data mining and fusion algorithms, visualization, big data analytics, machine learning, and advanced econometric modeling. Further innovation will result from a new unified equity analysis framework that can adequately adjust to the complexity of the service provision processes of emerging mobility services, ensuring optimal and equitable use of these services by Canadians from all walks of life. Despite the rapid influx of emerging mobility services in Canadian cities, research is lacking in modeling the impacts of these services compared to the USA and Europe. The proposed program will enhance Canada's international standing and allow HQP to gain high-demand skills and understand the broader implications of emerging mobility services on the Canadian transportation systems and society at large. Moreover, the developed models will provide insights into policy development, allowing transportation planners and decision-makers to apply these models for evidence-based policy implementation.