TITLE:
Real-Time Short-Term Forecasting Based on Information Management
AUTHORS:
Jamal Raiyn, Tomer Toledo
KEYWORDS:
Forecast Scheme; Moving Average; Intelligent Transportation System
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.4 No.1,
January
15,
2014
ABSTRACT:
Traffic congestions and road accidents continue to
increase in industry countries. There are three basic strategies to relieve
congestion. The first strategy is to increase the transportation
infrastructure. However, this strategy is very expensive and can only be
accomplished in the long-term. The second strategy is to limit the
traffic demand or make traveling more expensive that will be strongly opposed
by travelers. The third strategy is to focus on efficient and intelligent
utilization of the existing transportation infrastructures. This strategy is
gaining more and more attention because it’s well. Currently,
the Intelligent Transportation System (ITS) is the most promising approach to
implementing the third strategy. Various forecast schemes have been proposed to
manage the traffic data. Many studies showed that the moving average schemes
offered meaningful results compared to different forecast schemes. This
paper considered the moving average schemes, namely, simple moving average,
weighted moving average, and exponential moving average. Furthermore, the
performance analysis of the shortterm forecast schemes will be discussed.
Moreover, the real-time forecast model will consider the abnormal condition
detection.