Abstract
Car accidents occur when headway distance is shorter than the stopping distance. Stopping distance consists of reaction distance and breaking distance. It is necessary for drivers to understand the stopping distance in real time to preventing traffic accidents from occurring. To estimate the breaking distance in real time, it is required to presume friction coefficient, which is one of the factors in determining breaking distance and it was difficult to calculate in real time in driving. So we examined whether it was possible to presume friction coefficient in real time. In this study, we analyzed the noise that was generated by friction between tire and road to presume friction coefficient in non real time, using Fast Fourier Transform (FFT) and a back propagation algorithm for the neural network. We could presume the proper friction coefficient and breaking distance from the analysis. It suggests that we can presume the friction coefficient in real time.
| Original language | English |
|---|---|
| Pages (from-to) | 65-68 |
| Number of pages | 4 |
| Journal | Research Reports on Information Science and Electrical Engineering of Kyushu University |
| Volume | 6 |
| Issue number | 1 |
| Publication status | Published - Mar 2001 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Engineering (miscellaneous)
- Electrical and Electronic Engineering
