Household-Level Use of Autonomous Vehicles: Modeling Framework, Traveler Adaptation, and Infrastructure to Mitigate Negative Effects

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With recent development in vehicle automation, the idea of sharing public roads with Autonomous Vehicles (AVs) or self-driving vehicles has been widely accepted. Adoption of AVs will drastically change the current picture of the transportation system. One of the areas that is expected to be greatly transformed is vehicle use, travel behavior, and subsequently vehicle ownership from the driverless operations. Yet, there exists no framework to forecast such behavior, demand, and systemic changes at this stage. First, this research will define a framework to simulate and evaluate potential household-level use of AVs from the fundamental notion that travel is a derived demand of individuals' activities and time allocations. Second, this research will develop an infrastructure planning framework, with a focus on parking structure planning, to reduce the potential negative external effects such as increased Vehicle-Mile-Traveled (VMT), congestion, greenhouse gas emissions, etc. The research will enhance understanding of potential issues and external effects as well as policy and infrastructure planning strategies to help reduce the social cost of AV adoption. More broadly, this research will help creating a more sustainable, economic, and efficient transportation and infrastructure system through the AV adoption. The framework of AV operations is an innovative variation of the Vehicle Routing Problem (VRP) in that (1) it integrates two scheduling and routing problems of travelers and vehicles, and (2) incorporates driverless operations. The novelty of this formulation is that it integrates two routing problems, thus providing routing flexibility for travelers and vehicles. The infrastructure planning framework is modeled through bi-level programming where AV operation decisions are at each household level. A creative modeling approach is introduced to handle the computational challenges. Lastly, a sensitivity analysis will provide insights in understanding changes and challenges in infrastructure, environment, congestion, vehicle ownership, etc. that may arise with the adoption of AVs.