This project investigates the design, implementation, and testing of a crowdsensing-based system that allows for pavement condition monitoring in a low-cost, reliable, and rapid manner. It also studies the incentive mechanisms for pavement crowdsensing that properly stimulate users to complete sensing tasks within the budget of platform cost and overall completion time. We have tested the pavement crowdsensing system with the goal to ensure that it conforms to functional and nonfunctional requirements. We have designed a platform-driven greedy algorithm with nine incentive mechanisms and evaluated their performance; our methods can avoid the cost explosion problem observed in data-reverse-auction incentive mechanisms, and the best of them can reduce the overall completion time by half compared to task-reverse-auction incentive mechanisms. Additional simulations and experiments are recommended to be carried out in the future to study the performance of the pavement crowdsensing system and associated incentive mechanisms in large-scale deployment.
The overarching goal of this project was to instrument the new MnDOT Navistar truck used at MN Road. Arugged data acquisition, data recording and wire...
Humans are social beings, and as such their choices are affected by the way they interact with other people. Recent changes to the nature of social in...
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United States Department of Transportation
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