Incident Detection and Response

2016 ◽  
pp. 117-138
Author(s):  
Tyler Justin Speed
Keyword(s):  
Incident Detection

Fuzzy ART Neural Network Model for Automated Detection of Freeway Incidents

1998 ◽  
Vol 1634 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Sherif S. Ishak ◽  
Haitham M. Al-Deek
Keyword(s):  
Neural Networks ◽  
False Alarm ◽  
False Alarm Rate ◽  
Back Propagation ◽  
Incident Detection ◽  
Traffic Patterns ◽  
Traffic Pattern ◽  
Detection Algorithms ◽  
Fuzzy Art ◽  
Freeway Incidents

Pattern recognition techniques such as artificial neural networks continue to offer potential solutions to many of the existing problems associated with freeway incident-detection algorithms. This study focuses on the application of Fuzzy ART neural networks to incident detection on freeways. Unlike back-propagation models, Fuzzy ART is capable of fast, stable learning of recognition categories. It is an incremental approach that has the potential for on-line implementation. Fuzzy ART is trained with traffic patterns that are represented by 30-s loop-detector data of occupancy, speed, or a combination of both. Traffic patterns observed at the incident time and location are mapped to a group of categories. Each incident category maps incidents with similar traffic pattern characteristics, which are affected by the type and severity of the incident and the prevailing traffic conditions. Detection rate and false alarm rate are used to measure the performance of the Fuzzy ART algorithm. To reduce the false alarm rate that results from occasional misclassification of traffic patterns, a persistence time period of 3 min was arbitrarily selected. The algorithm performance improves when the temporal size of traffic patterns increases from one to two 30-s periods for all traffic parameters. An interesting finding is that the speed patterns produced better results than did the occupancy patterns. However, when combined, occupancy–speed patterns produced the best results. When compared with California algorithms 7 and 8, the Fuzzy ART model produced better performance.

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 Anti-HPV16 Antibody Titers Prior to an Incident Cervical HPV16/31 Infection

Viruses ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1548
Author(s):  
Ana Gradissimo ◽  
Viswanathan Shankar ◽  
Fanua Wiek ◽  
Lauren St. Peter ◽  
Yevgeniy Studentsov ◽  
...  
Keyword(s):  
High Risk ◽  
Hpv Vaccine ◽  
Enzyme Linked Immunosorbent Assay ◽  
Incident Detection ◽  
Antibody Titers ◽  
Circulating Antibodies ◽  
Prospective Association ◽  
Nested Case Control ◽  
Incident Cases

The goal of this study was to investigate the serological titers of circulating antibodies against human papillomavirus (HPV) type 16 (anti-HPV16) prior to the detection of an incident HPV16 or HPV31 infection amongst vaccinated participants. Patients were selected from a prospective post-HPV vaccine longitudinal cohort at Mount Sinai Adolescent Health Center in Manhattan, NY. We performed a nested case–control study of 43 cases with incident detection of cervical HPV16 (n = 26) or HPV31 (n = 17) DNA who had completed the full set of immunizations of the quadrivalent HPV vaccine (4vHPV). Two control individuals whom had received three doses of the vaccine (HPV16/31-negative) were selected per case, matched on age at the first dose of vaccination and follow-up time in the study: a random control, and a high-risk control that was in the upper quartile of a sexual risk behavior score. We conducted an enzyme-linked immunosorbent assay (ELISA) for the detection of immunoglobulin G (IgG) antibodies specific to anti-HPV16 virus-like particles (VLPs). The results suggest that the average log antibody titers were higher among high-risk controls than the HPV16/31 incident cases and the randomly selected controls. We show a prospective association between anti-HPV16 VLP titers and the acquisition of an HPV16/31 incident infection post-receiving three doses of 4vHPV vaccine.

A wavelet-based freeway incident detection algorithm with adapting threshold parameters

2011 ◽  
Vol 19 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Young-Seon Jeong ◽  
Manoel Castro-Neto ◽  
Myong K. Jeong ◽  
Lee D. Han
Keyword(s):  
Detection Algorithm ◽  
Incident Detection

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.

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