Abstract

AbstractFully autonomous vehicles and the need to improve road safety have led to increased demands on the reliability of various advanced driver assistance systems (ADAS). Automotive radar is a key component of ADAS as it adds both safety and comfort features in vehicles. A key challenge in developing automotive radar is demonstrating reliability especially in corner cases. Building and testing radar systems for corner cases is time‐consuming, costly, and impractical. Simulation is the only practical way of investigating the countless possible automotive radar corner cases. An interesting corner case is the reduction of radar returns due to sharp road bends. Specifically, crucial targets with low radar cross sections (RCS) such as pedestrians can become invisible to radar when driving around sharp road bends. In this article, a high fidelity, full physics‐based simulation of a 77 GHz automotive radar scene will be used to investigate this corner case. The dependence of radar returns on the position of an ego vehicle negotiating a sharp bend will be presented. Results from these simulations show a pedestrian disappearing from view at an approaching angle of 60∘ with a degradation of over 40 dB in pedestrian radar returns. Using results from this study, a terrain‐adaptive technique for improving radar target detection capabilities is proposed. This technique is shown to improve pedestrian radar returns by over 26 dB. Improved radar returns can help in early detection of pedestrians and other relevant targets. Early target detection can help reduce accidents while potentially saving pedestrian lives.

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