Investigation of a Neural Network Model for Freeway Incident Detection
Author: B. Bavarian
Publisher:
Published: 1991
Total Pages: 19
ISBN-13:
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Author: B. Bavarian
Publisher:
Published: 1991
Total Pages: 19
ISBN-13:
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Publisher:
Published: 1991
Total Pages: 46
ISBN-13:
DOWNLOAD EBOOKAuthor: Dipti Srinivasan
Publisher:
Published: 2018
Total Pages: 20
ISBN-13:
DOWNLOAD EBOOKAutomated incident detection is an essential component of a modern freeway traffic monitoring system. A number of neural network-based incident detection models have been tested independently over the past decade. This paper evaluates the adaptability of three promising neural network models for this problem: multi-layer feed-forward neural network (MLF), basic probabilistic neural network (BPNN) and constructive probabilistic neural network (CPNN). These three models have been developed on an original freeway site in Singapore and then adapted to a new freeway site in California. Apart from their incident detection performances, their adaptation strategies and network sizes have also been compared. Results of this study show that the MLF model has the best incident detection performance at the development site while CPNN model has the best performance after model adaptation at the new site. In addition, the adaptation method for CPNN model is relatively more automatic. The efficient network pruning procedure for the CPNN network resulted in a smaller network size, making it easier to implement it for real-time application. The results suggest that CPNN model has the highest potential for use in an operational automatic incident detection system for freeways.
Author: H. Dia
Publisher:
Published: 1996
Total Pages: 62
ISBN-13:
DOWNLOAD EBOOKAuthor: Asim Salimul Karim
Publisher:
Published: 2001
Total Pages: 400
ISBN-13:
DOWNLOAD EBOOKAuthor: Hojjat Adeli
Publisher:
Published: 2001
Total Pages: 280
ISBN-13:
DOWNLOAD EBOOKAutomatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelligent system approach and several innovative algorithms were developed for solution of the freeway traffic incident detection problem employing advanced signal processing, pattern recognition, and classification techniques. The methodology effectively integrates fuzzy, wavelet, and neural computing techniques to improve reliability and robustness.
Author: Sherif S. Ishak
Publisher:
Published: 1998
Total Pages: 273
ISBN-13:
DOWNLOAD EBOOKAuthor: Samanwoy Ghosh Dastidar
Publisher:
Published: 2002
Total Pages: 454
ISBN-13:
DOWNLOAD EBOOKAuthor: Chien-Hua Hsiao
Publisher:
Published: 1994
Total Pages: 162
ISBN-13:
DOWNLOAD EBOOKAuthor: Veli Himanen
Publisher: Routledge
Published: 2019-07-09
Total Pages: 410
ISBN-13: 0429817630
DOWNLOAD EBOOKFirst published in 1998, this volume enters the debate on human behaviour in the form of neural networks in a spatial context. As most transportation research techniques had been developed in the 1960s and 1970s, these authors sought to bring that research into the modern era. Featuring 17 articles from 37 contributors, it begins with an overview and proceeds to examine aspects of travel behaviour, traffic flow and traffic management.