Enhanced Methodology for Exploring Autonomy-Enabled Multi-Mode Regional Transportation

Enhanced Methodology for Exploring Autonomy-Enabled Multi-Mode Regional Transportation

Daniel DeLaurentis Headshot
Daniel DeLaurentis
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Principal Investigator(s):

Daniel DeLaurentis, Professor of Aeronautics and Astronautics – Purdue University

Project Abstract:
Increasing the level of autonomy in both small aircraft and automobile has the potential to generate greater efficiency and utility in multimodal regional transportation systems. In previous research, the PI and collaborators developed a computational analysis framework to assess the impact of aircraft technology advancement in electric propulsion and autonomy on the future of on-demand, regional air transportation system. A sensitivity analysis revealed increasing level of autonomy and an improved ride-sharing model (on the ground and in the air) could lead to significant increase in the total number of individuals who could afford this new mode of transportation. Activities in the proposed project would enhance our current computational framework with models for autonomous automobile option and thereby take a holistic approach to evaluate the impact of autonomy at a multi-modal level of operation. The end results will help identify the promising regions, via an optimization formulation, where enabling autonomy makes economic sense to the stakeholders. Outcome models, analysis, and metrics is expected to further increase the research community’s ability to characterize the impacts of differing levels of autonomy as well as the synergistic benefit of a ride-sharing economy within the context of a multi-modal transportation system.

Research Thrust(s): Enabling Technology, Modeling & Implementation, Policy & Planning

Project Form(s):
Project Information Form