Advanced formation and delivery of traffic information in intelligent transportation systems

被引:41
作者
Cheng, Hsu-Yung [1 ]
Gau, Victor [2 ]
Huang, Chih-Wei [3 ]
Hwang, Jenq-Neng [4 ]
机构
[1] Natl Cent Univ, Dept Comp Sci & Informat Engn, Chungli, Taiwan
[2] Microsoft Corp, Redmond, WA 98052 USA
[3] Natl Cent Univ, Dept Commun Engn, Chungli, Taiwan
[4] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
关键词
Intelligent transportation systems; Traffic parameters; Event Detection; WiMAX; WiFi; TRACKING; SURVEILLANCE; RECOGNITION; APPEARANCE; MOTION;
D O I
10.1016/j.eswa.2012.01.184
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
To meet the safety requirement for the increasing traffic densities nowadays, there exists a growing demand for advanced systems that can provide drivers essential traffic and travel information to improve road safety and traffic efficiency. In this paper, we combine the video analysis and multimedia networking technologies to present a highly integrated intelligent system that can achieve the above goals. For traffic information, the system presented in this paper collects traffic parameters and detects relevant events by analyzing traffic surveillance videos. Through robust tracking algorithms and reasoning logics, important traffic parameters and events are extracted from the surveillance videos accurately. Afterwards, summarized real-time traffic conditions and important events along with corresponding live traffic videos are formed into layers and multicasted through an integration of WiMAX infrastructure and vehicular ad hoc networks (VANET). By the support of adaptive modulation and coding in WiMAX, the radio resources can be optimally allocated when performing multicast so as to dynamically adjust the number of data layers received by users. In addition to multicast supported by WiMAX, we also design a knowledge propagation and information relay scheme by VANET. Through this relaying technology, about 80% of the mobile stations that were unable to subscribe additional layers of data due to insufficient downlink bandwidth from WiMAX could regain more than 90% of the data in the additional layers within tolerable buffering time. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:8356 / 8368
页数:13
相关论文
共 34 条
[1]
A based approach to collision prediction at traffic intersections [J].
Atev, S ;
Arumugam, H ;
Masoud, O ;
Janardan, R ;
Papanikolopoulos, NP .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2005, 6 (04) :416-423
[2]
Baldick R, 2009, 2009 IEEE/PES POWER SYSTEMS CONFERENCE AND EXPOSITION, VOLS 1-3, P83
[3]
A real-time computer vision system for measuring traffic parameters [J].
Beymer, D ;
McLauchlan, P ;
Coifman, B ;
Malik, J .
1997 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1997, :495-501
[4]
Optimal distance between two branches of uncontrolled split intersection [J].
Ceder, A ;
Eldar, K .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2002, 36 (08) :699-724
[5]
Intelligent transportation control system design using wavelet neural network and PID-type learning algorithms [J].
Chen, Chiu-Hsiung .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (06) :6926-6939
[6]
Cheng H. Y., 2007, 2007 IEEE INT C AC S, P1
[7]
Adaptive particle sampling and adaptive appearance for multiple video object tracking [J].
Cheng, Hsu-Yung ;
Hwang, Jenq-Neng .
SIGNAL PROCESSING, 2009, 89 (09) :1844-1849
[8]
A window-based image processing technique for quantitative and qualitative analysis of road traffic parameters [J].
Fathy, M ;
Siyal, MY .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 1998, 47 (04) :1342-1349
[9]
Road-traffic monitoring by knowledge-driven static and dynamic image analysis [J].
Fernandez-Caballero, Antonio ;
Gomez, Francisco J. ;
Lopez-Lopez, Juan .
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (03) :701-719