Traffic accidents prediction model based on fuzzy logic

Hao Wang; Lai Zheng; Xianghai Meng

doi:10.1007/978-3-642-22418-8_14

Traffic accidents prediction model based on fuzzy logic

Hao Wang^*
, Lai Zheng
, Xianghai Meng

^*Corresponding author for this work

Heilongjiang Province Highway Construction Bureau
School of Transportation Science and Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

Traffic accidents prediction has an important meaning to the improvement of traffic safety management, and urban traffic accidents prediction model which based on fuzzy logic is taken forward in this paper by contrasting to traditional traffic accidents prediction models. This model is trained and tested by the traffic and traffic accident data of 133 Harbin city roads, and finally gets a fuzzy logic prediction model which has 41 effective rules. The test result shows that there is a good relationship between the observed numbers and predicted numbers. Thus, prediction of the urban traffic accidents by fuzzy logic is viable. Besides, the concept of safety improvement factor is taken forward, which can be used to find out the prominent influence factors of high risk road and then to improve the safety of these roads.

Original language	English
Title of host publication	Advances in Information Technology and Education - International Conference, CSE 2011, Proceedings
Pages	101-108
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-22418-8_14
State	Published - 2011
Externally published	Yes
Event	2011 International Conference on Computer Science and Education, CSE 2011 - Qingdao, China Duration: 9 Jul 2011 → 10 Jul 2011

Publication series

Name	Communications in Computer and Information Science
Number	PART 1
Volume	201 CCIS
ISSN (Print)	1865-0929

Conference

Conference	2011 International Conference on Computer Science and Education, CSE 2011
Country/Territory	China
City	Qingdao
Period	9/07/11 → 10/07/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

control rules
fuzzy logic
prediction
prominent influence factors
traffic accident

Access to Document

10.1007/978-3-642-22418-8_14

Cite this

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title = "Traffic accidents prediction model based on fuzzy logic",

abstract = "Traffic accidents prediction has an important meaning to the improvement of traffic safety management, and urban traffic accidents prediction model which based on fuzzy logic is taken forward in this paper by contrasting to traditional traffic accidents prediction models. This model is trained and tested by the traffic and traffic accident data of 133 Harbin city roads, and finally gets a fuzzy logic prediction model which has 41 effective rules. The test result shows that there is a good relationship between the observed numbers and predicted numbers. Thus, prediction of the urban traffic accidents by fuzzy logic is viable. Besides, the concept of safety improvement factor is taken forward, which can be used to find out the prominent influence factors of high risk road and then to improve the safety of these roads.",

keywords = "control rules, fuzzy logic, prediction, prominent influence factors, traffic accident",

author = "Hao Wang and Lai Zheng and Xianghai Meng",

year = "2011",

doi = "10.1007/978-3-642-22418-8\_14",

language = "英语",

isbn = "9783642224171",

series = "Communications in Computer and Information Science",

number = "PART 1",

pages = "101--108",

booktitle = "Advances in Information Technology and Education - International Conference, CSE 2011, Proceedings",

edition = "PART 1",

note = "2011 International Conference on Computer Science and Education, CSE 2011 ; Conference date: 09-07-2011 Through 10-07-2011",

}

Wang, H, Zheng, L & Meng, X 2011, Traffic accidents prediction model based on fuzzy logic. in Advances in Information Technology and Education - International Conference, CSE 2011, Proceedings. PART 1 edn, Communications in Computer and Information Science, no. PART 1, vol. 201 CCIS, pp. 101-108, 2011 International Conference on Computer Science and Education, CSE 2011, Qingdao, China, 9/07/11. https://doi.org/10.1007/978-3-642-22418-8_14

Traffic accidents prediction model based on fuzzy logic. / Wang, Hao; Zheng, Lai ; Meng, Xianghai.
Advances in Information Technology and Education - International Conference, CSE 2011, Proceedings. PART 1. ed. 2011. p. 101-108 (Communications in Computer and Information Science; Vol. 201 CCIS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Traffic accidents prediction model based on fuzzy logic

AU - Wang, Hao

AU - Zheng, Lai

AU - Meng, Xianghai

PY - 2011

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N2 - Traffic accidents prediction has an important meaning to the improvement of traffic safety management, and urban traffic accidents prediction model which based on fuzzy logic is taken forward in this paper by contrasting to traditional traffic accidents prediction models. This model is trained and tested by the traffic and traffic accident data of 133 Harbin city roads, and finally gets a fuzzy logic prediction model which has 41 effective rules. The test result shows that there is a good relationship between the observed numbers and predicted numbers. Thus, prediction of the urban traffic accidents by fuzzy logic is viable. Besides, the concept of safety improvement factor is taken forward, which can be used to find out the prominent influence factors of high risk road and then to improve the safety of these roads.

AB - Traffic accidents prediction has an important meaning to the improvement of traffic safety management, and urban traffic accidents prediction model which based on fuzzy logic is taken forward in this paper by contrasting to traditional traffic accidents prediction models. This model is trained and tested by the traffic and traffic accident data of 133 Harbin city roads, and finally gets a fuzzy logic prediction model which has 41 effective rules. The test result shows that there is a good relationship between the observed numbers and predicted numbers. Thus, prediction of the urban traffic accidents by fuzzy logic is viable. Besides, the concept of safety improvement factor is taken forward, which can be used to find out the prominent influence factors of high risk road and then to improve the safety of these roads.

KW - control rules

KW - fuzzy logic

KW - prediction

KW - prominent influence factors

KW - traffic accident

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SN - 9783642224171

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BT - Advances in Information Technology and Education - International Conference, CSE 2011, Proceedings

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Y2 - 9 July 2011 through 10 July 2011

ER -

Traffic accidents prediction model based on fuzzy logic

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this