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Future Urban Mobility: Long-Term Decision-Making Under Uncertainty
11: Urban Studies and Planning
February 2, 2020
We are witnessing revolutionary and exciting changes in the mobility landscape involving infrastructure, technology, and policy. Of particular relevance are emerging modes like autonomous vehicles (AVs) and micro-mobility (like e-scooters), and services like mobility-on-demand (Uber, Lyft, etc.). While their impact on transportation infrastructure and use has received significant attention, we are more interested in understanding how these technologies will shape (or, rather, re-shape) our cities. This particular project is based on our in-house land use-transport interaction (LUTI) simulator named SimMobility, which has three different components. We will focus specifically on the Long-Term (LT) component that models residential location choice, vehicle ownership choice, and job location choice at the individual and household level. Optimizing mathematical operations in large-scale agent-based simulations: Popular data science libraries in the computation and big data realms, e.g. numpy, scikit-learn, TensorFlow, utilize matrix algebra formulations that improve computational efficiency. This UROP will assist the software programmers in the LT team to implement matrix algebra-based model computations, and evaluate the performance against the current implementation. Our agent-based simulator (SimMobility) uses multiple threads for day-to-day simulation of various decision-making processes, which can be another area the UROP could work on for improving latency. We expect this UROP applicant to have had prior experience with software programming (C++ is a plus, pun intended) in a large-scale multi-membered project setting. An undergraduate majoring in 6-3, with a goal of working in the software industry after graduation, would be an appropriate fit.
1) Experience in programming using C++ 2) Must have taken at least one class in software programming or algorithm design 3) Interest in transportation, urban planning and policy 4) The undergraduate applicant must be in their sophomore, junior, or senior year