DEVELOPING INCIDENT DETECTION ALGORITHM BASED ON THE MAMDANI FUZZY INFERENCE ALGORITHM

• Main Authors: Andrey Borisovich Nikolaev, Yuliya Sergeevna Sapego
• Format: Article
• Language: English
• Published: Science and Innovation Center Publishing House 2017-09-01
• Series: International Journal of Advanced Studies
• Subjects: Mamdani fuzzy inference algorithm; incident detection system
• Online Access: http://journal-s.org/index.php/ijas/article/view/10113

Application of fuzzy logic in the incident detection system allows making a decision under uncertainty. The phase of incident detection is a process of finding difficulties in traffic. The difficulty in traffic is the main sign that there was a road accident and requires a reaction for its elimination. This leads to the use of input data that must be relevant to the vehicles and the road. These data must be considered together, and should be compared with the corresponding values for further analysis. The main parameters of the traffic flow, which can characterize its current state, are a flow rate, a volume flow. Necessary to analyze the input data received from the sensors. After processing the input data, using the previously entered fuzzy rules, will be taken action that will improve the situation in traffic or at least not allow it worse.