Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers

The safety of automated vehicles (AVs) must be assured before their release and deployment. The current approach to evaluation relies primarily on 1) testing AVs on public roads or 2) track testing with scenarios defined in a test matrix. These two methods have completely opposing drawbacks: the for...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2018-03, Vol.19 (3), p.733-744
Main Authors: Zhao, Ding, Huang, Xianan, Peng, Huei, Lam, Henry, LeBlanc, David J.
Format: Article
Language:English
Subjects:
Accelerated tests
Acceleration
active safety
Automated vehicles
Automation
Car following
Computer simulation
crash avoidance
Data models
evaluation
Importance sampling
Lead
Maneuvers
Monte Carlo methods
Safety
Stochastic processes
Vehicles
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Summary:The safety of automated vehicles (AVs) must be assured before their release and deployment. The current approach to evaluation relies primarily on 1) testing AVs on public roads or 2) track testing with scenarios defined in a test matrix. These two methods have completely opposing drawbacks: the former, while offering realistic scenarios, takes too much time to execute and the latter, though it can be completed in a short amount of time, has no clear correlation to safety benefits in the real world. To avoid the aforementioned problems, we propose accelerated evaluation, focusing on the car-following scenario. The stochastic human-controlled vehicle (HV) motions are 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 are then modified to generate more intense interactions between 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 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 for accelerating the AV evaluation process.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2017.2701846