Perception of driving safety risks at urban intersections based on multidimensional data mining
L. Yao, X.L. Cao
Pages: 111-124
Abstract:
Research on the perception of
driving safety risks holds significant importance for enhancing traffic
safety and facilitating the development of smart cities. A new perception
method of driving safety risks at urban intersections based on
multidimensional data mining is proposed to solve the problems of low
accuracy, low recall, and long time consumption of traditional methods.
Mining multidimensional urban intersection data, smoothing the data using
Exponential Weighted Moving Average (EWMA) method, and repairing missing
values using Gradient Boosting Tree (GBDT). Using the Apriori algorithm to
mine association rules and determine key factors affecting driving safety, a
perception index system is established. The perception index is used as input
parameters to build a BP neural network, thereby achieving driving safety
risk perception. The experimental results show that the accuracy of the
proposed method is over 95%, the recall rate is over 90%, and it takes less
than 3s.
Keywords: multidimensional data mining;
urban intersection; driving safety; risk perception; apriori algorithm
2025 ISSUES
2024 ISSUES
LXII - April 2024LXIII - July 2024LXIV - November 2024Special 2024 Vol1Special 2024 Vol2Special 2024 Vol3Special 2024 Vol4
2023 ISSUES
LIX - April 2023LX - July 2023LXI - November 2023Special Issue 2023 Vol1Special Issue 2023 Vol2Special Issue 2023 Vol3
2022 ISSUES
LVI - April 2022LVII - July 2022LVIII - November 2022Special Issue 2022 Vol1Special Issue 2022 Vol2Special Issue 2022 Vol3Special Issue 2022 Vol4
2021 ISSUES
LIII - April 2021LIV - July 2021LV - November 2021Special Issue 2021 Vol1Special Issue 2021 Vol2Special Issue 2021 Vol3
2020 ISSUES
2019 ISSUES
Special Issue 2019 Vol1Special Issue 2019 Vol2Special Issue 2019 Vol3XLIX - November 2019XLVII - April 2019XLVIII - July 2019
2018 ISSUES
Special Issue 2018 Vol1Special Issue 2018 Vol2Special Issue 2018 Vol3XLIV - April 2018XLV - July 2018XLVI - November 2018
2017 ISSUES
Special Issue 2017 Vol1Special Issue 2017 Vol2Special Issue 2017 Vol3XLI - April 2017XLII - July 2017XLIII - November 2017
2016 ISSUES
Special Issue 2016 Vol1Special Issue 2016 Vol2Special Issue 2016 Vol3XL - November 2016XXXIX - July 2016XXXVIII - April 2016
2015 ISSUES
Special Issue 2015 Vol1Special Issue 2015 Vol2XXXV - April 2015XXXVI - July 2015XXXVII - November 2015
2014 ISSUES
Special Issue 2014 Vol1Special Issue 2014 Vol2Special Issue 2014 Vol3XXXII - April 2014XXXIII - July 2014XXXIV - November 2014
2013 ISSUES
2012 ISSUES
2011 ISSUES
2010 ISSUES
2009 ISSUES
2008 ISSUES
2007 ISSUES
2006 ISSUES
2005 ISSUES
2004 ISSUES
2003 ISSUES