Incident detection system by sensor fusion network employing image sensors and supersonic wave

2006 ◽  
Author(s):  
N. Sumiya ◽  
K. Familiar ◽  
S. Kamijo
Keyword(s):  
Sensor Fusion ◽  
Detection System ◽  
Image Sensors ◽  
Incident Detection

Traffic incident detection system based on video image processing

2008 ◽  
Vol 28 (7) ◽  
pp. 1886-1889 ◽  
Author(s):  
Qin WANG ◽  
Shan HUANG ◽  
Hong-bin ZHANG ◽  
Quan YANG ◽  
Jian-jun ZHANG
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Video Image ◽  
Incident Detection ◽  
Traffic Incident ◽  
Video Image Processing

scholarly journals A support vector machine with the tabu search algorithm for freeway incident detection

2014 ◽  
Vol 24 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Mingheng Zhang ◽  
Maoqing Jin
Keyword(s):  
Support Vector Machine ◽  
Tabu Search ◽  
Traffic Management ◽  
Search Algorithm ◽  
Detection System ◽  
Support Vector ◽  
Incident Detection ◽  
Tabu Search Algorithm ◽  
Proposed Model ◽  
Parameter Values

Abstract Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.

Traffic Monitoring and Congestion Management in the SCOOT Urban Traffic Control System

1998 ◽  
Vol 1634 (1) ◽  
pp. 118-122 ◽  
Author(s):  
David Bretherton ◽  
Keith Wood ◽  
Neil Raha
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Detection System ◽  
Congestion Management ◽  
Traffic Monitoring ◽  
Urban Traffic ◽  
Incident Detection ◽  
The European Union ◽  
Traffic Control System ◽  
Urban Traffic Control

The SCOOT Urban Traffic Control system is now operating in over 170 cities worldwide, including 7 systems in North America. Since the first system was installed, there has been a continuous program of research and development to provide new facilities to meet the requirement of the traffic manager. The latest version of SCOOT (Version 3.1) incorporates a traffic information database, ASTRID, and an incident-detection system, INGRID, and provides a number of facilities for congestion control. The traffic monitoring facilities of SCOOT, including a new facility to estimate emissions from vehicles, and the current program of work to enhance the incident-detection system and to provide additional facilities to manage incidents and congestion are reported in this paper. The work is being carried out as part of the European Union, DGXIII 4th Framework project, COSMOS, with additional funding from the UK Department of Transport. The enhanced system is to be installed in the Kingston Borough of London, where it will be tested in combination with congestion warning information provided by variable message signs.

Current Developments in SCOOT: Version 3

1996 ◽  
Vol 1554 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Dave B retherton
Keyword(s):  
Control System ◽  
Data Base ◽  
Traffic Control ◽  
Detection System ◽  
Urban Traffic ◽  
Incident Detection ◽  
Bus Priority ◽  
Current Information ◽  
Traffic Control System ◽  
Urban Traffic Control

The SCOOT urban traffic control system is now operating successfully in more than 130 towns and cities worldwide. The latest version of SCOOT has been extended to include support for bus priority, the automatic SCOOT traffic information data base (ASTRID) system, and the INGRID incident detection system and has been given added flexibility, particularly for use in incident conditions. Bus priority in SCOOT was developed within the European Union DRIVE 2 project PROMPT. This software has now been issued as part of the latest SCOOT version, following the field trials in London and Southampton, United Kingdom, which showed that significant benefits to buses could be obtained. The ASTRID data base has now been integrated with SCOOT and can run in the same machine as the urban traffic control system. As well as providing current and historical information to traffic engineers, ASTRID now can feed historic information back into SCOOT, providing a substitute cyclic flow profile that can be used for optimization when there are faulty detectors. The INGRID incident detection system contains two algorithms to provide an indication of an incident; taking current information directly from SCOOT, INGRID detects abnormal changes in flow and occupancy, and comparing current information with historic information stored in the ASTRID data base, INGRID detects abnormal patterns in these parameters. The SCOOT optimizers have been made more flexible and can now make larger changes to the signal timings if required. This facility can be switched on or off and would be particularly useful where an incident has been detected.

Multi-Sensor N-P Criterion Fusion Detection Based on Weighting by SNR

2014 ◽  
Vol 1044-1045 ◽  
pp. 818-824
Author(s):  
Bo Fan Yang ◽  
Rui Wang ◽  
Gang Wang ◽  
Li Zhao
Keyword(s):  
Signal Detection ◽  
False Alarm ◽  
Sensor Fusion ◽  
Detection Probability ◽  
Detection System ◽  
False Alarm Probability ◽  
Radar Target ◽  
Low Snr ◽  
Simulation Results ◽  
Fusion Detection

Aiming at signal detection of radar target, concerning about on the basis of the influence of SNR on detection probability when false alarm probability is given based on N-P criterion, a kind of multi-sensor fusion detection based on SNR is put forward. It can improve system’s detection probability under the condition of required false alarm probability in the detection of low SNR signal. The simulation results show that the detection performance is significantly increased, no matter fusion detection system is composed of same sensors working in the same working point or different sensors.

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