United States Department of Transportation
i
Infrastructure Safety Support System for Smart Cities with Autonomous Vehicles
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2021-12-01
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[PDF-800.21 KB]
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Edition:Final report
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Abstract:Driverless vehicles must be self-aware to make learned and ethical decisions to avoid crashes in multimodal and diverse settings. This proposed effort will develop an Infrastructure Safety Support System by embedding vehicle-to-infrastructure (V2I) enabled sensor networks into the transportation infrastructure to provide autonomous vehicles and human drivers with inputs to improve their decision making when obvious decisions may not possible. The research objectives of this project are to: (1) Develop an infrastructure embedded sensor network to provide real-time traffic and road condition information such as traffic volume (e.g. ADT, peak-hour traffic), traffic composition (vehicle classification), vehicle speed, dynamic weight via weigh-in-motion (WIM), traffic density, traffic flow rate, road roughness, and other data; (2) Develop algorithms that the infrastructure safety support system will use to process the sensor-based real-time traffic data and pavement conditions to support the decision-making processes of autonomous vehicles such as driving speed and safe vehicle following distances when sharing the road with human-driven vehicles; (3) Develop real-time warnings based on the data derived from the infrastructure support system; (4) Optimize the infrastructure support system such as the sensor and V2I facility layout; (5) Validate the developed infrastructure support system through simulations and field tests. In addition, the team will use the results from this development to enhance curricula that would engage and mentor students in the practice of developing safe smart cities. This project will involve three graduate students and several undergraduate students. The trainings through this project will prepare students for potential careers in smart city developments.
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