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Author: Dipti Srinivasan
Publisher:
ISBN:
Category :
Languages : en
Pages : 20
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Book Description
Automated 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: Dipti Srinivasan
Publisher:
ISBN:
Category :
Languages : en
Pages : 20
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Book Description
Automated 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: Dipti Srinivasan
Publisher:
ISBN:
Category :
Languages : en
Pages : 23
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Book Description
Automated incident detection (AID) is an essential component of an Advanced Traffic Management and Information Systems (ATMIS), which provides round the clock incident detection, and helps initiate the required action in case of an accident or incident. This paper evaluates three promising neural network models: multi-layer feed-forward neural network (MLF), basic probabilistic neural network (BPNN) and constructive probabilistic neural network (CPNN) for their incident detection performance. An important consideration in neural network-based incident detection systems is the deployment of a trained neural network on traffic systems with considerably different driving conditions. The models were developed and tested on an original freeway site in Singapore, and tested on a new freeway site in the US for their adaptability. The paper presents comparative evaluation in terms of their classification accuracy, adaptability, and network size. Results indicate that although the MLF model gives excellent classification results on the development site, the CPNN model outperforms the other two in terms of its adaptability and flexible structure. 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:
ISBN:
Category : Disabled vehicles on express highways
Languages : en
Pages : 62
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Author: Hussein Dia
Publisher:
ISBN:
Category : Electronic traffic controls
Languages : en
Pages : 526
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Author:
Publisher: Elsevier
ISBN: 0081026722
Category : Law
Languages : en
Pages : 4418
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Book Description
In an increasingly globalised world, despite reductions in costs and time, transportation has become even more important as a facilitator of economic and human interaction; this is reflected in technical advances in transportation systems, increasing interest in how transportation interacts with society and the need to provide novel approaches to understanding its impacts. This has become particularly acute with the impact that Covid-19 has had on transportation across the world, at local, national and international levels. Encyclopedia of Transportation, Seven Volume Set - containing almost 600 articles - brings a cross-cutting and integrated approach to all aspects of transportation from a variety of interdisciplinary fields including engineering, operations research, economics, geography and sociology in order to understand the changes taking place. Emphasising the interaction between these different aspects of research, it offers new solutions to modern-day problems related to transportation. Each of its nine sections is based around familiar themes, but brings together the views of experts from different disciplinary perspectives. Each section is edited by a subject expert who has commissioned articles from a range of authors representing different disciplines, different parts of the world and different social perspectives. The nine sections are structured around the following themes: Transport Modes; Freight Transport and Logistics; Transport Safety and Security; Transport Economics; Traffic Management; Transport Modelling and Data Management; Transport Policy and Planning; Transport Psychology; Sustainability and Health Issues in Transportation. Some articles provide a technical introduction to a topic whilst others provide a bridge between topics or a more future-oriented view of new research areas or challenges. The end result is a reference work that offers researchers and practitioners new approaches, new ways of thinking and novel solutions to problems. All-encompassing and expertly authored, this outstanding reference work will be essential reading for all students and researchers interested in transportation and its global impact in what is a very uncertain world. Provides a forward looking and integrated approach to transportation Updated with future technological impacts, such as self-driving vehicles, cyber-physical systems and big data analytics Includes comprehensive coverage Presents a worldwide approach, including sets of comparative studies and applications
Author: Tania Banerjee
Publisher: CRC Press
ISBN: 1000969770
Category : Computers
Languages : en
Pages : 213
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Book Description
Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions. The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection. Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development. Key Features: Describes the development and challenges associated with Intelligent Transportation Systems (ITS) Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersection Has the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts
Author: Asim Salimul Karim
Publisher:
ISBN:
Category :
Languages : en
Pages : 400
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Author: Hojjat Adeli
Publisher:
ISBN:
Category : Disabled vehicles on express highways
Languages : en
Pages : 280
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Book Description
Automatic 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: S. G. Ritchie
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 38
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Author: Samanwoy Ghosh Dastidar
Publisher:
ISBN:
Category :
Languages : en
Pages : 454
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