Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that have the potential to help prevent/mitigate crashes and injuries in intersection crashes. I-ADAS may use side-looking sensors, e.g. radar and lidar, in order to detect potential collisions with vehicles from crossing paths. The success of I-ADAS depends on the range and azimuth capabilities of these sensors. In order to specify the capabilities of sensors for an I-ADAS, designers need a distribution of range and azimuth between vehicles as they enter intersections prior to crashes. This study generated range and azimuth distributions using crash data from the National Motor Vehicle Crash Causation Survey (NMVCCS) for vehicles just prior to entering the intersection in straight crossing paths (SCP) crashes. Using the reconstructions and specifications in existing radar technology, the potential crash mitigation benefits of this technology were determined. Three radar-based I-ADAS were analyzed using published sensor specifications. The sensors included a wide beam, intermediate beam, and narrow beam. The wide beam I-ADAS was found to detect 20.3% of oncoming vehicles, the intermediate beam was found to detect 89.2% of oncoming vehicles, and the narrow beam was found to detect 98.3% of oncoming vehicles. The results indicate that a narrow beam I-ADAS is the most capable because of its long range detection ability. These results have practical relevance for the design and implementation of I-ADAS.
Potential of intersection driver assistance systems to mitigate straight crossing path crashes using U.S. nationally representative crash data
2015 IEEE Intelligent Vehicles Symposium (IV) ; 1207-1212
2015-06-01
881378 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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