This presentation was made at the NAFEMS Americas "Creating the Next Generation Vehicle" held on the 14th of November in Troy.

The automotive engineering community is now confronting the largest technology transformation since its inception. This includes the electrification of powertrains for more efficient consumption and cleaner emissions, the reinvention of the battery with fast wireless charging capabilities and finally the advent of a fully autonomous vehicle. Compounding to these technology changes, the automotive companies design verification process is moving away from a major reliance on physical testing to almost a full virtual simulation product verification process.

The automotive engineering community is now confronting the largest technology transformation since its inception. This includes the electrification of powertrains for more efficient consumption and cleaner emissions, the reinvention of the battery with fast wireless charging capabilities and finally the advent of a fully autonomous vehicle. Compounding to these technology changes, the automotive companies design verification process is moving away from a major reliance on physical testing to almost a full virtual simulation product verification process.

Resource Abstract

Advanced driver assistance systems (ADAS) have emerged as one of the fastest areas in the technology market. Past trends in the automotive industry limited the implementation of ADAS to high end, low volume vehicles. However, recent trends have seen the integration of ADAS in low cost, high volume models. Such adoption of ADAS has made it one of the fastest growing areas in automotive electronics. Projections have predicted that original equipment manufacturers (OEM’s) will be spending over $37 Billion on ADAS and safety related electronics by 2021. Such a surge in ADAS interest and adoption has been propelled by the need to make vehicles safer. Specifically, according to the NHTSA, 37 133 people lost their lives in motor vehicle crashes in 2017. Therefore, there is a need to make roads safer by equipping vehicles with advanced driver assistance systems that provide the driver with greater situational awareness. Furthermore, these systems will possibly carry out manoeuvres that can prevent accidents.



Another propelling factor has been the race by OEMs to deploy fully autonomous vehicles. With a $54 billion market size value in 2019, the market size value of autonomous vehicles is projected to catapult to $557 billion by 2026. The ADAS equipped, fully autonomous vehicle will have radar, lidar, optical cameras and ultrasonic sensors to provide the vehicle with situational awareness in a highly dynamic environment. 77 GHz automotive radar has emerged as the clear backbone sensor technology for fully autonomous vehicles. This is because radar is a robust and relatively inexpensive technology that can simultaneously detect the range, velocity and bearing of multiple targets even in inclement weather.



As radar sensors evolve from merely providing situational information such as blind spot detection to being used for full autonomous driving manoeuvres, a larger burden of reliability will be placed on them. Specifically, extensive tests will need to be carried out to demonstrate the implementation and reliability of radar sensors in fully autonomous vehicles. A corner case of interest is the detectability of pedestrians who are in the vicinity of high radar cross section (RCS) infrastructure on roads. Specifically, if a low RCS target such as a pedestrian stands near high RCS road infrastructure, their presence can be impossible to detect. This is because the radar returns of strong RCS targets can overwhelm the radar sensor and possibly cause the radar sensor to ignore an otherwise present soft target such as a pedestrian.



In this work, a simulation study of the impact of guardrails and overpasses on the visibility of pedestrians is presented. Results from this study demonstrate how guardrails and overpasses affect the doppler-range maps obtained at 77 GHz. Such results can be used to develop more robust target identification algorithms to detect soft targets in the vicinity of strong RCS targets. Using simulation, a low RCS alternative guardrail design is presented. Such a low RCS guardrail system can reduce the RCS of conventional guardrails by 25 dB. Results from this study show that simulation can be used to accurately and efficiently evaluate 77 GHz radar performance in corner cases that would be dangerous and costly to test in the real world.