F2010E010
Sensing Technology Tire System for Road Surface Condition Judgment
For the purpose of safety improvement, Bridgestone has been developing tire sensing technology, which is named CAIS (Contact Area Information Sensing) technology. Sensing technology tire concept is the one which utilizes a tire as a part of sensor system, and the CAIS technology is focusing on signal analysis around contact area for more direct sensing of tire and road. Among sensing targets, one which is considered very important for warning or vehicle control system is road surface condition like dry, wet, snow and so on. This is one index of slipperiness. This technology is also expected to be utilized for a probe car of road administrator to manage winter road surface. The sensing technology tire for road surface condition judgment has an accelerometer at inner-liner side of tread portion to detect small changes of tire behavior on different surfaces. Based on the characteristics of acceleration waveform on each surface, like vibration level of specific frequency band at specific position around the contact area, it judges continuously while steady state driving. In recent years, prototype system for a probe car has been developed. Sensing algorithm was modified to classify road surface conditions into 7 groups, and also necessary hardware systems were developed. The system consists mainly of followings. 1. Wireless electric power supply system to tire module 2. Tire acceleration data acquisition and wireless transmission module (tire to vehicle) 3. On- vehicle sensors (microphone, thermometer) to improve judgment accuracy 4. Analysis device for real-time sensing and on-board display 5. Wireless data communication system (vehicle to data server), and view system of road condition map on the internet Thanks to the cooperation of the Shibetsu city government office in Hokkaido, 4months' public road test of the prototype system was carried out in winter season. The test vehicle was driven for approximately 8,000km in various situations, and a lot of useful data was obtained. The system outputs were compared with visual judgment results by a tester on passenger seat. The sensing algorithm worked properly, and road surface conditions judged by the prototype system agreed fairly well with the tester's ones.
This abstract is supplemented by a PDF, which can be viewed here.
Session: Intelligent Traffic Systems