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With the evolution of autonomous vehicle (AV), especially its ability to cope with harsh conditions, which is attracting intense attention from both academia and industry practitioners. Due to the high risk, high cost, and great difficulties of real road testing for AV, the hardware-in-the-loop (HIL) simulation platform is considered as a safe, economical, and effective testing method. In this paper, we developed a novel indoor virtual-reality combined HIL simulation platform for AV testing. This platform consists of a series of subsystems including math models, physical hardware and software components, on which all parts of an AV can be tested separately and jointly. To validate the functionality and performance of the platform, we adopt Udwadia-Kalaba(U-K) approach to build autonomous emergency braking (AEB) control algorithm as a case study due to explicitness and simplicity of U-K approach. Further, a group of comparison experiments on both real road environment and the proposed indoor HIL platform is conducted. The experimental results show that the testing data obtained from the proposed HIL platform have a high similarity to those of the real road tests. Simultaneously, the testing time and repeatability of the former perform better, which confirms its feasibility and effectiveness on the vehicle AEB testing.
Gao et al. (Sun,) studied this question.