Fuzzy neural traffic control and forecasting

摘要

Fuzzy systems can be used to represent human knowledge. Traffic technology is a science where this property of fuzzy logic can be very well adapted because it is hard to make mathematical models due to human influences and complex connections between input parameters. One example of the use of fuzzy logic in traffic control is in highway speed control systems. The goal is to optimally use the highway. We first describe a fuzzy system for traffic flow control and incident recognition that has been in use for some time. Another example that we describe is fuzzy logic in forecasting whether a particular parking garage is full or not. We describe the input parameters and the structure of the fuzzy system. Furthermore, we show how neural networks can be used to improve the performance of the system.