Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is necessary to thoroughly evaluate the safety of Automated Vehicles (AVs) before their release and deployment. Current evaluation approach mainly relies on i) testing AVs on public roads or ii) track testing with scenarios defined in a test matrix. These two methods have completely opposite drawbacks: the former takes too much time to execute but is realistic; the latter can be finished in a short time but has no clear correlation to the safety benefits in the real world. To avoid the aforementioned problems,  propose the Accelerated Evaluation approach focusing on the car-following scenario. The stochastic human-controlled vehicle (HV) motions re modeled based on 1.3 million miles of naturalistic driving data collected by the University of Michigan Safety Pilot Model Deployment Program. The statistics of the HV behaviors re modified to generate more intense interactions beten HVs and AVs to accelerate the evaluation procedure. The Importance Sampling theory was used to ensure that the safety benefits of AVs are accurately assessed under accelerated tests. Crash, injury and conflict rates for a simulated AV are simulated to demonstrate the proposed approach. Results show that the test duration is reduced by a factor of 300 to 100,000 compared with the non-accelerated (naturalistic) evaluation. In other words, the proposed techniques have great potential to accelerate the AV evaluation process.
['Ding Zhao', 'X. Huang', 'Huei Peng', 'Henry Lam', 'David LeBlanc']
I am writing a research paper on a idea Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers
[{"from": "human", "value": "I am writing a research paper on a idea Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is necessary to thoroughly evaluate the safety of Automated Vehicles (AVs) before their release and deployment. Current evaluation approach mainly relies on i) testing AVs on public roads or ii) track testing with scenarios defined in a test matrix. These two methods have completely opposite drawbacks: the former takes too much time to execute but is realistic; the latter can be finished in a short time but has no clear correlation to the safety benefits in the real world. To avoid the aforementioned problems,  propose the Accelerated Evaluation approach focusing on the car-following scenario. The stochastic human-controlled vehicle (HV) motions re modeled based on 1.3 million miles of naturalistic driving data collected by the University of Michigan Safety Pilot Model Deployment Program. The statistics of the HV behaviors re modified to generate more intense interactions beten HVs and AVs to accelerate the evaluation procedure. The Importance Sampling theory was used to ensure that the safety benefits of AVs are accurately assessed under accelerated tests. Crash, injury and conflict rates for a simulated AV are simulated to demonstrate the proposed approach. Results show that the test duration is reduced by a factor of 300 to 100,000 compared with the non-accelerated (naturalistic) evaluation. In other words, the proposed techniques have great potential to accelerate the AV evaluation process."}]