Symbolic aggregate approximation based data fusion model for dangerous driving behavior detection-Reference-Cited by-同舟云学术

Symbolic aggregate approximation based data fusion model for dangerous driving behavior detection

Published:2022-09 Issue: Volume:609 Page:626-643
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Liu Jia,Li Tianrui,Yuan Zhong,Huang Wei,Xie Peng,Huang Qianqian

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference43 articles.

1. Automatic recognition of low-quality vehicles and bus stops in bus services;Barabino;Public Transport,2018

2. Taxi dispatching strategies with compensations;Billhardt;Expert Syst. Appl.,2019

3. A graphical modeling method for individual driving behavior and its application in driving safety analysis using gps data;Chen;Transp. Res. Part F: Traffic Psychol. Behav.,2019

4. Optimal pricing and availability strategy of a bike-sharing firm with time-sensitive customers;Chen;J. Clean. Prod.,2019

5. A survey on driver behavior detection techniques for intelligent transportation systems;Chhabra,2017

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