详情

Automated Vehicle Impacts on Underserved Populations

项目名称：	Automated Vehicle Impacts on Underserved Populations
摘要：	Only four of the 25 Texas Metropolitan Planning Organizations’ (Bryan-College Station, Austin, Dallas-Fort Worth (North Central Texas Council of Governments), and San Antonio (Alamo MPO)) current Metropolitan Transportation Plans (MTPs) explicitly include automated vehicles (AVs) in their goals and objectives. Another eight MPOs briefly discuss the potential for AVs to address congestion within their transportation management plan. MPOs and other agencies face significant challenges related to AVs because AV development and deployment as well as their ownership/use models remain uncertain. These uncertainties compound when translating these to a transportation system where travel behavior, latent demand, and changes in land use appear more uncertain than anytime in the past seventy-five years. With the uncertainty about potential impacts of AVs many times not really known until the technology is actually deployed to the public, traditional transportation modeling methods remain inherently inadequate. This project develops a scenario-based approach to overcome this shortcoming. The scenario planning framework relies on previous research, investment and patent patterns, and expert feedback to create a range of plausible AV development, deployment, adoption, and service scenarios. The scenarios may include different responses from the public in terms of travel behavior and land use decisions, too. Previous efforts of the research team show that patent and investment patterns provide better insight into the emergence of new technologies than research investments. This study will develop an AV scenario development and impact analysis framework. The framework will consist of three modules: (i) scenario development, (ii) scenario factor flow chart, and (iii) GIS methodology for evaluating community level AV impacts. The first module uses existing national level AV scenarios, local contexts with the Region 6 states, previous research, patent applications, and AV investments to develop metropolitan and rural Region 6 AV scenarios. After developing the scenarios, the research team uses the Delphi method to assess the probability of the different scenarios. The second module will identify the factors that may cause the AV development, deployment, adoption, and services to move towards a particular scenario or change scenario paths. These factors will be incorporated into a flow chart to create guidance on the key factors that agencies must monitor to track their possible scenario pathways. The third module develops a GIS-based framework for evaluating AV impacts using a sustainable framework that captures, access and affordability at a community level as well as other traditional transportation performance measures like vehicle miles traveled, crash rates, and travel times. This study formulates AV development, deployment, services, and adoption scenarios. While these scenarios capture the infrastructure requirements and impacts on the general population and overall communities, this study focuses on the spatio-temporal patterns of impacts and behaviors of vulnerable transportation disadvantaged communities, which are typically overlooked due to a lack of data, lesser impact on peak hour travel, and inflexible housing location choices. At this planning stage, agencies must develop policies, strategies, and infrastructure investments that do not perpetuate past transportation inequalities and seek to address these inequalities directly when possible. Based on existing gaps and barriers experienced by transportation disadvantaged populations, agencies can develop transportation services and infrastructure investments using and supporting AVs that seek to eliminate these obstructions and create an efficient and resilient transportation system for all residents and communities.
状态：	Active
资金：	106000
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	Transportation Consortium of South-Central States (Tran-SET)
项目负责人：	Dhasmana, Heena
执行机构：	University of Texas at Arlington
主要研究人员：	Mattingly, Stephen
开始时间：	20220401
主题领域：	Economics；Highways；Operations and Traffic Management；Planning and Forecasting；Society；Vehicles and Equipment