Real-time Crash Prediction Based on High Definition Monitoring Systems

被引：0

作者：

You, Jinming ^{[1
]}

Zhang, Lanfang ^{[1
]}

Fang, Shouen ^{[1
]}

Guo, Jingqiu ^{[1
]}

机构：

[1] Tongji Univ, Minist Educ, Key Lab Rd & Traff Engn, Shanghai 201804, Peoples R China

来源：

2017 2ND IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING (ICITE) | 2017年

关键词：

crash prediction; high definition monitoring system; support vector machine; CAR-FOLLOWING MODELS; RISK-ASSESSMENT; FRAMEWORK; SAFETY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an innovative approach to investigate the inner mechanism between traffic status and crash potential based on High Definition Monitoring Systems (HDMS) data. HDMS records delicate vehicle trajectory data and characteristic details. Matched case-control method and Support Vector Machines (SVMs) were employed to identify risk status. The grid search method was utilized to find the optimized parameters for the decision function of the SVMs. The results indicate that the SVMs classifier could successfully classify 91.49% of the crashes on the test dataset with a false alarming rate 2.63%. This study contributes to decision supports for road safety management administrations.

引用

页码：208 / 211

页数：4

共 50 条

[1] High Definition Real-time Monitoring System Based on Embedded Network Streaming Media
Zhang Wei-wei
Zhao Ji-yin
Li Min
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 1796 - 1798
[2] On the Definition of Real-Time: Applications and Systems
Kejariwal, Arun
Orsini, Francois
2016 IEEE TRUSTCOM/BIGDATASE/ISPA, 2016, : 2213 - 2220
[3] Real-time crash prediction for expressway weaving segments
Wang, Ling
Abdel-Aty, Mohamed
Shi, Qi
Park, Juneyoung
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2015, 61 : 1 - 10
[4] The importance of flow composition in real-time crash prediction
Basso, Franco
Basso, Leonardo J.
Pezoa, Raul
ACCIDENT ANALYSIS AND PREVENTION, 2020, 137
[5] Real-time crash risk prediction on arterials based on LSTM-CNN
Li, Pei
Abdel-Aty, Mohamed
Yuan, Jinghui
ACCIDENT ANALYSIS AND PREVENTION, 2020, 135 (135):
[6] Spatio-temporal attention based real-time environmental monitoring systems for landslide monitoring and prediction
Babu, M. Vijay Sekhar
Ashokkumar, N.
Joshi, Anjali
Deshpande, Pallavi Sagar
Keshta, Ismail
Maaliw III, Renato R. R.
SPATIAL INFORMATION RESEARCH, 2023, 32 (2) : 207 - 207
[7] Definition of a high level language for real-time distributed systems programming
Ciocarlie, Horia
Simon, Lavinia
EUROCON 2007: THE INTERNATIONAL CONFERENCE ON COMPUTER AS A TOOL, VOLS 1-6, 2007, : 2521 - 2527
[8] Research on the prediction of high embankment settlement based on the real-time monitoring on-site
Huang Xing
Wei Ruming
Yuan Ling
Li Xiaoqing
ADVANCES IN CIVIL ENGINEERING II, PTS 1-4, 2013, 256-259 : 1754 - 1760
[9] A Genetic Programming Model for Real-Time Crash Prediction on Freeways
Xu, Chengcheng
Wang, Wei
Liu, Pan
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 14 (02) : 574 - 586
[10] Shadowing-based crash recovery schemes for real-time database systems
Shu, LC
Sun, HM
Kuo, TW
PROCEEDINGS OF THE 11TH EUROMICRO CONFERENCE ON REAL-TIME SYSTEMS, 1999, : 260 - 267

← 1 2 3 4 5 →