Design and Operation of Bi-Modal Urban Networks: System-Optimum Strategies to Accommodate People's Day-Long Decisions

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The research explores how buses and cars can serve a city's travel needs more effectively. To this end, the research (i) reexamines how people make their travel choices, recognizing that a day has two peak travel periods and that commuters make decisions by jointly considering both peaks; (ii) evaluates city-wide policies in regard to bus fares, parking prices, etc, to induce system-optimum travel patterns; and (iii) develops adaptive operating strategies (such as metering and turning bans) to ensure that the city's optimum ratio of bus and car traffic is accommodated with the least possible congestion, both when buses enjoy priority treatment and when they don't. The tasks are feasible because of recent advances at Berkeley with respect to city-scale modeling. The models are tested, both, with simulations and real-world experiments. If successful, this work will be the first generic analysis to recognize that commuters schedule their trips and select their travel modes, accounting for conditions that occur over the course of an entire day. With the insights that result from this, the work will unveil how these commuter decisions impact both travel peaks together, and how these impacts can best be managed by a city's transportation agency. The research is expected to explore new issues in transportation network design and management, and provide more realistic blueprints for greener, more sustainable urban transport systems. By considering day-long decisions, the research challenges current thinking and may influence future research directions. The research results are integrated into the curriculum at U.C. Berkeley. This will benefit women and under-represented minorities because roughly half of the graduate students in Berkeley's transportation engineering program belong to these demographic groups. Course notes that are developed will be used at other schools by Berkeley graduates and will magnify the long-term benefits of the research.