Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
A Scheduling Plan Model for Metro Crew Incorporating Fatigue and Biological Rhythms Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Road Traffic Accident Prediction Based on BP Neural Network

Authors : Yan Xing, Wen-hao Song, Wei-dong Liu, Shu-shida Gao

Published in: Green Transportation and Low Carbon Mobility Safety

Publisher: Springer Nature Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In order to predict road traffic accident indicators scientifically and accurately, this paper established a road traffic accident prediction model based on the basic theory of BP neural network. The 14 main influencing factors of traffic accidents were selected by using correlation analysis theory as the input variable of the prediction model and traffic accident deaths was taken as the output variable of the prediction model. Data related to road traffic accidents in China from 2000 to 2017 were selected as training samples of the model, MATLAB nntool was used to train the prediction model by using traingdm, traingda, trainlm and traingd training functions, and predict the deaths of road traffic accidents in 2018 in China. It is verified that the relative error of the constructed road traffic accident prediction model is within 1%, which can be used for road traffic accident prediction.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Regionally Differentiated Real-Time Energy Consumption Prediction of Electric Vehicles Oriented to Travel Characteristics
next chapter Autonomous Vehicle Path Planning Based on Improved Ant Colony Algorithm
Literature
1.
Milton J, Mannering F (1998) The relationship among highway geometrics, traffic-related elements and motor-vehicle accident frequencies. Transportation 25(4):395–413CrossRef
2.
Ma C, Zhang S-R, Ma Z-L et al (2018) Nonlinear negative binomial model of expressway traffic accident frequency prediction. China J Highw Transp 31(11):176–185
3.
Shen K (2017) Casualty toll prediction and management countermeasures for road traffic accident in China. Saf Environ Eng 24(05):138–144
4.
Wang W-B, Chen H, Wei L-X (2016) Study on method for prediction of traffic accident time series. China Saf Sci J 26(06):52–56
5.
Sun Y-X, Shao C-F, Ji X et al (2014) Urban traffic accident time series prediction model based on combination of ARIMA and information granulation SVR. J Tsinghua Univ (Sci Technol) 54(03):348–353, 359
6.
Yang S-X, Hu Y (2017) Traffic accident loss prediction based on dynamic grey prediction. J Wuhan Univ Technol (Inf Manag Eng) 39(06):674–678
7.
Li Q, Hou F-Z (2017) Grey combined forecasting model for road traffic accidents based on coefficient of variation method. Saf Environ Eng 24(06):130–133
8.
Wang X, Liu X-Y (2017) Research of traffic accident prediction based on gray Markov model. Technol Econ Areas Commun 19(04):9–13
9.
Liu J, Deng W (2011) Research on microcosmic forecast methods of road accident based on fuzzy neural network. J Transp Eng Inf 9(04):69–75
10.
Yi F-J, Han Z, Deng W (2012) Application of RBF neural network optimized by genetic algorithm for traffic accident microcosmic forecast of highway tunnel group. J Transp Eng Inf 10(01):64–72
11.
Zhang Z-H, Yang W-Z, Yuan T-T et al (2019) Traffic accident prediction based on LSTM neural network model. Comput Eng Appl 55(14):249–253
12.
Nationl Bureau of Statistics (2000–2018) China statistical yearbook. China Statistics Press, Beijing
13.
Hecht-Nielsen (2002) Theory of the backpropagation neural network. In: International 1989 joint conference on neural networks. IEEE
Metadata
Title
Road Traffic Accident Prediction Based on BP Neural Network
Authors
Yan Xing
Wen-hao Song
Wei-dong Liu
Shu-shida Gao
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Green Transportation and Low Carbon Mobility Safety

Print ISBN: 978-981-19-5614-0

Electronic ISBN: 978-981-19-5615-7

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-5615-7_46

Premium Partner

    Image Credits