PREDICTING AND IDENTIFYING TRAFFIC HOT SPOTS APPLYING NEURO-FUZZY SYSTEMS IN INTERCITY ROADS

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HAJI HOSSEIN LOU M.; SOHRABI M.

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Paper Information

Journal: INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY (IJEST) Year:2009 | Volume:6 | Issue:2 (22) Page(s): 309-314

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Title

PREDICTING AND IDENTIFYING TRAFFIC HOT SPOTS APPLYING NEURO-FUZZY SYSTEMS IN INTERCITY ROADS

Author(s)

HAJI HOSSEIN LOU M. | SOHRABI M. | Issue Writer Certificate

Keywords

ACCIDENT

SAFETY

OPTIMIZATION

LEAST SQUARE

SUGENO

HYBRID

BACK PROPAGATION

Abstract

Providing SAFETY in roads for the purpose of protecting human assets and preventing social and economic losses resulted from road ACCIDENTs is a significant issue. Identifying the traffic hot spots of the roads provides the possibility of promoting the road SAFETY which is also related to investigate frequency and intensity of occurred ACCIDENTs. ACCIDENTs are multidimensional and complicated events. Identifying the ACCIDENT factors is based on applying a comprehensive and integrated system for making decisions. Therefore, applying common mathematical and statistical methods in this field can be resulted in some problems. Hence, the new research methods with abilities to infer meaning from complicated and ambiguous data seem useful. Therefore, along with identifying the traffic hot spots, adaptive Neuro-Fuzzy inference system is used to predict traffic hot spots on rural roads. In this process, a fuzzy inference system from SUGENO type is trained applying HYBRID OPTIMIZATION routine (back propagation algorithm in combination with a LEAST SQUARE type of method) and ACCIDENT data of Karaj-Chalus road in Tehran province. Then the system was tested by a complete set of data. Finally, the stated system could predict 96.85 % of ACCIDENT frequencies in the studied blocks. Furthermore, the amount of effective false negative in all cases included only 0.82 % of predictions, which indicated a good approximation of predictions and model credibility.

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APA: Copy

HAJI HOSSEIN LOU, M., & SOHRABI, M.. (2009). PREDICTING AND IDENTIFYING TRAFFIC HOT SPOTS APPLYING NEURO-FUZZY SYSTEMS IN INTERCITY ROADS. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY (IJEST), 6(2 (22)), 309-314. SID. https://sid.ir/paper/285147/en

Vancouver: Copy

HAJI HOSSEIN LOU M., SOHRABI M.. PREDICTING AND IDENTIFYING TRAFFIC HOT SPOTS APPLYING NEURO-FUZZY SYSTEMS IN INTERCITY ROADS. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY (IJEST)[Internet]. 2009;6(2 (22)):309-314. Available from: https://sid.ir/paper/285147/en

IEEE: Copy

M. HAJI HOSSEIN LOU, and M. SOHRABI, “PREDICTING AND IDENTIFYING TRAFFIC HOT SPOTS APPLYING NEURO-FUZZY SYSTEMS IN INTERCITY ROADS,” INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY (IJEST), vol. 6, no. 2 (22), pp. 309–314, 2009, [Online]. Available: https://sid.ir/paper/285147/en

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