SENSING TECHNOLOGY TIRE SYSTEM FOR ROAD SURFACE CONDITION JUDGMENT

摘要

For the purpose of safety improvement, it is considered to be important to monitor the information concerning the tire in the vehicle systems because it is an important interface between the road and vehicle. The intelligent tire concept is the one which utilizes a tire as a part of the sensor system for such information of the tire state and, moreover, the road condition. In the previous study, using an acceleration signal measured around a contact patch, we developed the algorithm to judge the road surface conditions like dry, wet and low frictional surfaces with high accuracy. Especially it can judge the conditions continuously while driving in a steady state. By utilizing this information to the vehicle control system or the warning system, the reduction of traffic accidents can be expected. Also, besides the general-purpose vehicle, the road patrol car for winter road maintenance is considered another possible application. To find out the feasibility for this purpose, the prototype of tire sensing system, which includes the novel hardware as well as the modified algorithm, has been developed. In this paper, the sensing principle, the system configuration of the prototype and the results of the long-term winter test on public roads are described, respectively. Developed prototype of tire sensing system consists of followings. 1. Modified judgment algorithm to classify the road surfaces into more detailed six conditions which are dry, wet, slush, fresh snow, compacted snow and ice surfaces 2. Tire sensor module which consists of a one-axis accelerometer, a charge amplifier, wireless data communication devices and the wireless electric energy supply system 3. Additional vehicle sensors to improve the judgment accuracy on wet surface, which are a microphone for the tire sound and a thermometer for the road surface temperature 4. Informational website to check the system judgment results, measured data and still road images which are transmitted to the server computer by mobile computing Since 2008, using above prototype system, the long-term winter test on public roads is being carried out around Shibetsu city in Hokkaido (first season: 12/2008-03/2009, second season: 12/2009-03/2010 ongoing). In the first season, the test vehicle was driven for approximately 8,000km in the various situations. The system worked steadily through the season, and a lot of useful data was obtained. The system outputs were compared with the visual judgments by a road observer who sat in the passenger seat. Overall percentage of correct answers was 74%. High percentages were obtained on dry, wet, fresh snow and ice surfaces, but those on slush and compacted snow were low relatively. Prior to the second season, obtained data was analyzed and the discrimination functions for those problematic conditions were refined. The interim results of the second season have shown much better accuracies on those surfaces.