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Jo, H., Lee, B., Na, Y.-C., Lee, H. and Oh, B. (2007) Prioritized Traffic Information Delivery Based on Historical Data Analysis. Proceedings of the 2007 IEEE Intelligence Transportation Systems Conference, Seattle, September 30-October 3 2007, 568-573.

has been cited by the following article:

• TITLE: Real-Time Road Traffic Anomaly Detection

  AUTHORS: Jamal Raiyn, Tomer Toledo

  KEYWORDS: Anomaly Traffic, Detection Scheme, Moving Average, Intelligent Transportation System

  JOURNAL NAME: Journal of Transportation Technologies, Vol.4 No.3, July 31, 2014

  ABSTRACT: Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of dollars to economy. The main reasons of major percentage of traffic congestion are the incidents. Road accidents continue to increase in digital age. There are many reasons for road accidents. This paper will discuss and introduce new algorithm for road accident detection. Various forecast schemes have been proposed to manage the traffic data. In this paper we will introduce road accident detection scheme based on improved exponential moving average. The proposed traffic incident detection algorithm is based on the automatic exponential moving average scheme. The detection algorithm is based on analyzing the collected traffic flow parameters. The detection algorithm is based on analyzing the collected traffic flow parameters. In addition a real-time accident forecast model was developed based on short-term variation of traffic flow characteristics.