Dynamic Message Prioritisation for ITS Using Fuzzy Neural Network Technique 2001-01-0068
The increasing number of electronic and communication devices used as part of Intelligent Transport System (ITS), brings with it an increasing importance for the employment of message prioritisation technique within in-vehicle networks. As the integration of these devices increases within the vehicle network, there is a requirement for intelligence within the message prioritisation system. The question that arises is, under the increasing ITS nodes within vehicle networks, how can the device messages be prioritised. Especially when there is an occurrence of incidents on-board or off-board the vehicle. Therefore, an incidence based expert system is needed. This paper presents an intelligent message prioritisation system using FNN (fuzzy neural network) techniques for deciding data priority. Such a system is aiming to provide message priority dynamically, especially when a new device is introduced into an in-vehicle system network and when there is a prioritised incident. The application of FNN into the system results in many useful features. The suggested system is expected to be able to provide message prioritisation on any given incident or occasion.