According to the 2013 annual report file by the Fatality Analysis Reporting System (FARS), 14 percent of all traffic fatalities and an estimated 3 percent of those injured in traffic crashes were pedestrians. Fatal pedestrian crashes are about 9 times smaller when both drivers and pedestrians have a blood alcohol concentration (BAC) of .08 gram per deciliter (g/dL) than when both drivers and pedestrians have a BAC of .00 g/dL. It means that the reasons for fatal pedestrian crashes are a lack of driver’s pedestrian detection and road attentiveness (e.g., ped. behind obstacle, and driver using smartphone.), and a lack of pedestrian’s road attentiveness (e.g., a ped. using smartphone or earphones, and a bicycle to cross road without looking behind the rider.). Our system is an active safety system based on pedestrian detection to give a warning for precaution of accident to both driver and pedestrian. This system has largely four steps: 1) detecting pedestrian, 2) estimating vehicle speed, 3) calculating distance, and 4) turning on LEDs. This system detects pedestrian using measurements of distance and speed through sensors (e.g., microwave radar, infrared distance, and ultrasonic distance sensor). We assume that the average speed and maximum speed of pedestrian are 1.4m/s, and 2.5m/s, respectively. If a speed of an object on the road is larger than maximum speed of pedestrian, we define the object as a vehicle (i.e., this system distinguishes whether an object is pedestrian using the assumption for pedestrian speed). If there are a pedestrian, and a vehicle and the distance between the pedestrian and the vehicle is close to pedestrian safety distance, this system turns on the LEDs according to stopping distance and pedestrian safety distance. If LEDs are turned on suddenly, the driver and the pedestrian will give more attention to the road condition. Therefore, the system will proactively prevent the possible fatal pedestrian crashes.
Hojin Jung, Seong Kyung Kwon, Haengju Lee, and Sang Hyuk Son, “Poster Abstract: Traffic Caution System for Pedestrian Safety,” IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Daegu, Korea, Aug 2016.