A 77 GHz Simulation Study of Roadway Infrastructure Radar Signatures for Smart Roads

With exponentially increasing interest in driver-less cars, much focus has been placed on various sensor technologies that the vehicles will be equipped with. At the core of these sensor technologies is 77 GHz automotive radar. Recent simulation studies of 77 GHz automotive radar corner cases have revealed that the existing roadway infrastructure will need to be updated for safer and more robust compatibility with fully autonomous vehicles. In this paper, we present a full-physics based simulation study of the radar signatures of road guardrails and road covering, construction steel plates at 77 GHz. Results from this study show that current road infrastructure has a high radar cross section (RCS) that can overwhelm radar sensors and render crucial targets such as pedestrians invisible while also possibly triggering false detection. Using an asymptotic, full-physics electromagnetics solver, we demonstrate two techniques that can significantly reduce the RCS of guardrails and construction steel plates. Using these techniques, simulation studies predict a 25dB and 15dB reduction in the RCS of guardrails and construction steel plates, respectively.

[1]  Janusz Szpytko,et al.  Safety problems in vehicles with adaptive cruise control system , 2017 .

[2]  Bongsob Song,et al.  Detection and Tracking of Road Barrier Based on Radar and Vision Sensor Fusion , 2016, J. Sensors.

[3]  David Johnson,et al.  Radar Sensing for Intelligent Vehicles in Urban Environments , 2015, Sensors.

[5]  T. Zwick,et al.  Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band , 2012, IEEE Transactions on Microwave Theory and Techniques.

[6]  Ushemadzoro Chipengo,et al.  Full Physics Simulation Study of Guardrail Radar-Returns for 77 GHz Automotive Radar Systems , 2018, IEEE Access.

[7]  Alberto Broggi,et al.  Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion , 2007, IEEE Transactions on Intelligent Transportation Systems.

[8]  Adrian Hilton,et al.  A survey of advances in vision-based human motion capture and analysis , 2006, Comput. Vis. Image Underst..

[9]  Ralph Helmar Rasshofer,et al.  Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions , 2005 .

[10]  Shawn Carpenter,et al.  From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation , 2018, Modelling and Simulation in Engineering.

[11]  P. Bakker Theory of edge diffraction in terms of dynamic ray tracing , 1990 .

[12]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[13]  Gabriel M. Rebeiz,et al.  A 77–81-GHz 16-Element Phased-Array Receiver With $\pm {\hbox{50}}^{\circ}$ Beam Scanning for Advanced Automotive Radars , 2014, IEEE Transactions on Microwave Theory and Techniques.

[14]  Fujitsu Ten Masayuki KISHIDA 79 GHz Band Ultra-Wideband Automotive Radar , 2014 .

[15]  Ronald Poppe,et al.  Vision-based human motion analysis: An overview , 2007, Comput. Vis. Image Underst..