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A great deal of research and development has been invested in collision avoidance systems. A few such systems are now available commercially, including backup warning systems, backup vision systems for heavy vehicles, forward impact warning systems for heavy vehicles, and side collision avoidance systems for heavy vehicles. Relatively little data are published regarding basic sensor performance. A limited amount of performance data have been presented in the form of fleet accident avoidance, predictive reliability models, and individual driver accuracy (“Right clear?” questioning samples). However, few instances of actual sensor accuracy measurements are presented in the literature. This paper discusses parameters which can be used to characterize sensor performance. Methods of data collection are also considered, and two measures are recommended: Detection Accuracy and Mean Time Between False Alarms. Real-world data collection on public roadways is recommended.

Considerable effort has been invested in the development of models to predict the effectiveness of side collision avoidance systems (“SCAS”). These estimates, based on reliability theory, indicate that SCAS can produce a measurable improvement in safety, but that safety improvement is sensitive to the method of sensor use. The support of real-world data for these models is inconclusive. Objectively measured “right-clear” data show varying improvement with the use of SCAS, yet professional drivers of large vehicles (buses, heavy trucks) report favourable responses to the idea of SCAS use. Unscientific surveys of the general driving public support this favorable reaction, and also indicate a significant perceived cost to near miss incidents. This paper proposes a mathematical model of SCAS reliability that takes the above factors into consideration. This model is heavily based on earlier work in the field.

Vehicle Blind Spot Detection (BSD) represents a logical first step towards a comprehensive Collision Avoidance strategy as envisioned in plans for the Intelligent Transportation System. BSD systems have been developed based on a number of technologies, but cost and performance issues have prevented widespread commercial success, particularly for light vehicles. This paper presents a new Vehicle Blind Spot Detector. The device is based on a recently developed, novel thermal infrared sensor technology. A description of the operation of the sensor is provided, together with a brief comparison with existing technologies. Experimental data are also presented, showing results of operation of the sensor.