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Millimeter-Wave Radar in-the-Loop Testing for Intelligent Vehicles

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Intelligent vehicle testing and validation technology is a hotspot in the field of intelligent vehicles. Millimeter-wave radar has been widely used in intelligent vehicles and advanced driving assistant systems (ADASs).… Click to show full abstract

Intelligent vehicle testing and validation technology is a hotspot in the field of intelligent vehicles. Millimeter-wave radar has been widely used in intelligent vehicles and advanced driving assistant systems (ADASs). Owing to low efficiency, high maintenance cost and limited scenario types, the traditional real-vehicle-testing can make it difficult to meet the requirements of intelligent vehicle testing. Also, the degree of reality of millimeter-wave radar sensor models in the virtual test platform is not convincing enough. To solve the mentioned problems, the millimeter-wave radar in-the-loop (mmRil) testing for intelligent vehicles is proposed in this study. First, the radar echo simulation method is developed. Next, based on the millimeter-wave flight time, Doppler frequency shift and the radar power attenuation equation, the mmRil test system is built. A geometric model of a radar target detection and a power attenuation model under bad weather conditions are established. Then, the accuracy of the testbench is verified. Finally, a typical intelligent vehicle control strategy is used for testing under various working conditions and bad weather using the mmRil testbench. The test results show that the mmRil testing has higher authenticity and accuracy than the simulation testing and can be used to test the intelligent vehicle algorithms under severe weather conditions. Compared with the real vehicle testing, the mmRil testing has higher efficiency, repeatability and safety. Therefore, the mmRil testing represents an indispensable testing method in the field of intelligent vehicle testing.

Keywords: wave radar; intelligent vehicle; intelligent vehicles; millimeter wave; radar

Journal Title: IEEE Transactions on Intelligent Transportation Systems
Year Published: 2022

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