scholarly journals Support Vector Machine Applied to Road Traffic Event Classification

2018 ◽  
Vol 231 ◽  
pp. 04001
Author(s):  
Maciej Blaszke ◽  
Bozena Kostek
Keyword(s):  
Support Vector Machine ◽  
Feature Vector ◽  
Road Traffic ◽  
Traffic Monitoring ◽  
Support Vector ◽  
Intelligent Transport System ◽  
Signal Recognition ◽  
Event Classification ◽  
Intelligent Transport ◽  
Single Vehicle

The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application a feature vector containing 48 parameters was extracted and analyzed in the context of parameter separability and classification effectiveness employing SVM (Support Vector Machine) algorithm. In conclusion, the classifier developed and its effectiveness were discussed.

scholarly journals Overview of Intelligent Transport System (ITS) and Its Applications

2021 ◽  
Author(s):  
Purnendu S M Tripathi ◽  
Ambuj Kumar ◽  
Ashok Chandra
Keyword(s):  
Air Pollution ◽  
Radio Frequency ◽  
Transport System ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Information ◽  
Intelligent Transport System ◽  
Comprehensive Overview ◽  
Frequency Bands ◽  
Intelligent Transport

Since last decades world, predominantly urban areas, is experiencing huge voluminous road traffic growth, resulting in heavy congestion, air pollution, accidents, and poor efficiency.  Many people every day are the victims of this poor management of tremendous traffic. Since many years, there had been some automation in managing the traffic namely Electronic Toll Collection (ETC), Electronic parking payment, normal traffic information etc. However, there are little efforts for making the system more advanced. Recently, several kinds of research are being launched by many countries to develop Intelligent Transport System (ITS), with the objectives to minimize congestion, ensure better safety, reduce air pollution etc. ITS are planned to establish robust communication between vehicle to vehicle (V2V), vehicle to pedestrian (V2P), vehicle to infrastructure (V2I), and vehicle to network (V2N). Initially, for communication links ITS, deploys Wi-Fi network, but because of limited capacity and huge requirement, some links use 5.8 GHz radio frequency for such purposes. IEEE, International Telecommunications Union (ITU) and other advanced research organisations are studying 700 MHz band and mm frequency bands for advanced ITS. ITS is poised to use Information & Communication Technology (ICT) networks for such purposes. ITU has established Study Groups/study questions for addressing ITS issues. The World Radio Conference (WRC-2019) has made a Recommendation 208 regarding harmonization of frequency bands for ITS applications. This paper presents a comprehensive overview of ITS, its applications and analysis etc. The radio frequency spectrum aspects and role of 5 G in ITS are also described in detail.  

scholarly journals Research on Traffic Acoustic Event Detection Algorithm Based on Sparse Autoencoder

2020 ◽  
Vol 308 ◽  
pp. 05002
Author(s):  
Xiaodan Zhang ◽  
Yongsheng Chen ◽  
Guichen Tang
Keyword(s):  
Feature Vector ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Research Direction ◽  
Traffic Monitoring ◽  
Detection Algorithm ◽  
Acoustic Event ◽  
Traffic State ◽  
Sparse Autoencoder ◽  
New Research

Road traffic monitoring is very important for intelligent transportation. The detection of traffic state based on acoustic information is a new research direction. A vehicles acoustic event classification algorithm based on sparse autoencoder is proposed to analysis the traffic state. Firstly, the multidimensional Mel-cepstrum features and energy features are extracted to form a feature vector of 125 features; Secondly, based on the computed features, the five-layers autoencoder is trained. Finally, vehicle audio samples are collected and the trained autoencoder is tested. The experimental results show that detection rate of the traffic acoustic event reaches 94.9%, which is 12.3% higher than that of the traditional Convolutional Neural Networks (CNN) algorithm.

scholarly journals MONITORING A SEMAPHORED CROSSROADS USING FPGA DE0

2018 ◽  
Vol 18 (1) ◽  
pp. 34-39
Author(s):  
G. Predusca ◽  
M. Bogdan
Keyword(s):  
Transport System ◽  
Low Cost ◽  
Traffic Monitoring ◽  
Advanced Technology ◽  
Transport Systems ◽  
Intelligent Transport System ◽  
Intelligent Transport ◽  
Development Platform ◽  
Quartus Ii

Abstract Intelligent Transport System (ITS) is a worldwide movement meant to use advanced technology to make the ground transport systems more efficient, clogging-free, more secure and less polluting. The present technologies permit the development of applications for traffic monitoring in a semaphored crossroads. The solution proposed is a low-cost one, using FPGA DE0 development platform. The implementation and simulation of the application have been realized in Quartus II 13.1 and the diagrams corresponding to the outputs and inputs have been obtained using ModelSim- Altera 10.1d.

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