Impact Analysis of Roadway Surface and Vehicle Conditions on Fleet Formation for Connected and Automated Vehicles
Ping Yi, Professor of Civil Engineering – The University of Akron
Ethan Shajie, Adjunct Faculty of Mechanical Engineering – The University of Akron
Factors that largely affect rolling resistance and emergency braking distance include not only pavement friction, but also tire condition, vehicle’s braking system, and the environmental conditions. Those conditions change with road sections and may vary from one vehicle to other. Therefore, passive estimation and use of a friction coefficient for safety assessment, which have been a common practice for decades, cannot sufficiently meet the requirements of advanced transportation system today as better and more diversified services are demanded by the motorists. In particular, to take advantage of connected and automated vehicles technologies a condition-dependent, time-resolved approach for estimating driving resistance should be developed and implemented. This project proposes to study how such roadway and vehicle-based factors, when working together, can jointly affect the braking distance and influence inter-vehicle spacing and flow dynamics of a connected and automated vehicle fleet.
Research Thrust(s): Modeling & Implementation
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