ACME specializes in performing economic analysis and performance evaluation of autonomous and connected transportation solutions. This program leverages academic and technical resources of the College of Engineering and the Center for Urban Transportation Research. Researchers specialize in advanced econometric methods, traffic engineering and safety, data mining, machine learning and artificial intelligence applications to produce quick response solutions to better inform practitioners and policy maker in selecting and prioritizing cost-feasible alternatives.
With an emphasis on institutional innovation, ACME assists transit agencies, local, state and federal authorities with policy development, operational enhancements, and exploration of new technologies. ACME’s projects cover these main areas of research:
Infrastructure Investment and Economic Development – ACME bring more than 20 years of experience in conducting economic impact analyses and performance assessments of public transportation, airport and roadway projects. The group’s analytical expertise helps organizations assess the economic impacts and effectiveness of policy, planning, and investment decision making.
The Economic and Social Consequences of Connected and Autonomous Vehicles – ACME evaluates the evaluation and performance assessment of connected and autonomous vehicles in terms of safety, mobility, economic productivity, energy and environmental benefits. ACME is currently leading the performance evaluation and assessment the Federal Highway Administration (FHWA) Connected Vehicle Pilot Deployment Program – Tampa Pilot.
Travel Behavior, Land Use and Urban Form – ACME researchers focus on theoretical modeling of the relationship between urban form, residential location and travel patterns. By formulating implementable models that define how household travel behavior responds to changes in transportation infrastructure.
Transportation Demand Management Evaluation (TDM) – ACME specializes on the development and implementation of practitioner-oriented applications to quantify the societal costs and benefits of congestion-reduction strategies with a focus on energy conservation.
The underlying interest in these areas is in providing scientific investigation to evaluate mechanisms supporting livable and sustainable communities.
Ph.D., Civil Engineering (Transportation), University of Kansas, Lawrence, Kansas, 2020.
M.S., Civil Engineering (Transportation), University of Kansas, Lawrence, Kansas, 2017.
B.S., Civil Engineering, University of Cape Town, Cape Town, South Africa, 2014.
Vishal is a Postdoctoral researcher at Center for Urban Transportation Research (CUTR). His research areas of interest include connected mobility, human factors and driving simulators, traffic modeling, human-machine interfaces and automation, car-following dynamics, big data, and roadway safety. He has worked on several Kansas DOT, FHWA, and USDOT funded projects. He also serves as a reviewer for the Accident, Analysis & Prevention journal.
- Kummetha, V. C., A. Kondyli, E. Chrysikou, and S. Schrock. “Safety Analysis of Work Zone Complexity with Respect to Driver Characteristics – A Simulator Study Employing Performance and Gaze Measures.” Accident Analysis & Prevention, July 2020.
- Kummetha, V. C., A. Kondyli, and S. Schrock. “Analysis of the Effects of Adaptive Cruise Control on Driver Behavior and Awareness Using a Driving Simulator.” Journal of Transportation Safety and Security, November 2017.
- Manjunatha, P., V. C. Kummetha, A. Kondyli, and L. Elefteriadou. “Validating the Task-Capability Extension to the Intelligent Driver Model (IDM) Using Driving Simulator Data.” Transportation Research Board 98th Annual Meeting, November 2018.