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Dr. Jill Hough is an associate professor and the director of the Small Urban and Rural Transit Center within the Upper Great Plains Transportation Institute at North Dakota State University. She has authored or co-authored more than 75 research reports and journal articles and given more than one hundred presentations at the regional, national, and international level. She is the instructor of a graduate level course on Public Transportation and of a graduate course on Leadership, Ethics and Academic Conduct. Hough served two three-year terms on the National Academies of Science’s Transit Cooperative Research Program Oversight Project Selection Committee (TOPS). Dr. Hough has testified during the USDOT’s Transportation Reauthorization Outreach Tour and she has testified before the U.S. Senate Budget Committee regarding the importance of infrastructure. Hough earned her BS and MS degrees in agricultural economics from NDSU and her Ph.D. in transportation technology and policy from the University of California, Davis.

Sessions

  • June 11: Fifty shades of public transport

    The fuzzy rule-based pricing scheme for dock-less shared-use systems

    We investigate a rule-based pricing scheme considering an agent-based approach for dock-less shared-use systems including bike-sharing and scooter-sharing programs. The existing pricing scheme relies on a fixed cost per minute/mile with some occasional incentives under every spatial and temporal condition. Moreover, optimization models either take a holistic view over the problem or not robust enough to utilize the system at finer granularity for very large transportation network. We propose a hierarchal fuzzy rule-based pricing scheme of which each vehicle as an agent can follow predefined rules in a transportation network. The fare for each vehicle is iteratively adjusted to offer incentives to users based on spatiotemporal conditions. The model tries to utilize not only the profitability of the system but also key performance indicators (KPIs) such as average daily trips per vehicle, average daily trips per 1,000 residents (in service area), accessibility by low-income users. A case study of a medium size network will be carried out using an agent-based simulator. The developed pricing scheme is expected to demonstrate robustness and flexibility in fare adjustments and smooth behavioral stabilization in long-term operation. The project investigates a rule-based pricing scheme for dock-less (bike sharing, scooter) systems. A hierarchical fuzzy scheme where each bike, as an agent, can follow predefined rules given its spatial and temporal condition for maximum utilization in a transportation network.
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