Intelligent transport systems - eSafety - eCall: Tests to enable PSAPs to demonstrate conformance and performance

2018 ◽  
Keyword(s):  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
And Performance

Pedestrian Crossings Detection by using Driving Assistance Systems

2017 ◽  
Vol 9 ◽  
pp. 17
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Detection System ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Histograms Of Oriented Gradients ◽  
Driving Assistance ◽  
Detection Of Objects ◽  
Assistance Systems ◽  
And Performance ◽  
And Control

This paper mainly studies Driving Assistance Systems and Detection Pedestrian Crossings of traffic and control, many years around the world and company studies have been conducted on intelligent transport systems (ITS). Intelligent vehicle, (IV) the system is part of a system which is designed to assist drivers in the perception of any dangerous situations before, to avoid accidents after sensing and understanding the environment around it.  Methodology: we made an analysis of the peculiarities of the task of surveillance for pedestrian crossings and presented a detection system which these features into account. The system consists of a detector based on histograms of oriented gradients, and activity detector. The proposed Results tested detection precision and performance of the proposed system. The motion of the work is to combine the proposed system and the tracker. The results show that an adequate application of the quality and performance of the developed algorithm of detection of objects of interest in the work.

scholarly journals Proposal of Methodology to Calculate Necessary Number of Autonomous Trucks for Trolleys and Efficiency Evaluation

2020 ◽  
Vol 10 (1) ◽  
pp. 255-264
Author(s):  
Jozef Gnap ◽  
Zdenek Riha ◽  
Stefania Semanova
Keyword(s):  
Automotive Industry ◽  
Best Practice ◽  
Transport Systems ◽  
Future Research ◽  
The European Union ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Scientific Project ◽  
And Performance

AbstractThe introduction of the paper highlights best practice in the area of deploying autonomous trucks in warehouses and the automotive industry, including the current technical possibilities of selected autonomous trucks. The next chapter presents the selected outputs of the scientific project “Center of Excellence for Intelligent Transport Systems” focused on a proposal of the methodology for calculating the necessary number of autonomous trucks and trolleys deployed in logistics warehouses. The methodology is based on the requirement that autonomous trucks do not have downtime. This represents a model solution with possible application in warehouse logistics but also in the automotive industry. The follow-up chapter proposes a methodological procedure to evaluate the efficiency of introducing autonomous trucks to pull trolleys in a logistics warehouse compared to conventional trucks operated by trained personnel. Autonomous trucks can theoretically be operated 365 days and 24 hours depending on the technology of their operation, battery charging, etc. On the other hand, there is generally a shortage of logistics personnel in the European Union as well as reliability and performance have been declining in recent years. The conclusion of the paper includes a discussion of the research results obtained and possibilities for future research.

scholarly journals A New Indonesian Traffic Obstacle Dataset and Performance Evaluation of YOLOv4 for ADAS

2021 ◽  
Vol 14 (3) ◽  
pp. 286-298
Author(s):  
Agus Mulyanto ◽  
Wisnu Jatmiko ◽  
Petrus Mursanto ◽  
Purwono Prasetyawan ◽  
Rohmat Indra Borman
Keyword(s):  
Obstacle Detection ◽  
Transport Systems ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Intelligent Transport Systems ◽  
Street Vendors ◽  
Intelligent Transport ◽  
Promising Area ◽  
Assistance Systems ◽  
And Performance

Intelligent transport systems (ITS) are a promising area of studies. One implementation of ITS are advanced driver assistance systems (ADAS), involving the problem of obstacle detection in traffic. This study evaluated the YOLOv4 model as a state-of-the-art CNN-based one-stage detector to recognize traffic obstacles. A new dataset is proposed containing traffic obstacles on Indonesian roads for ADAS to detect traffic obstacles that are unique to Indonesia, such as pedicabs, street vendors, and bus shelters, and are not included in existing datasets. This study established a traffic obstacle dataset containing eleven object classes: cars, buses, trucks, bicycles, motorcycles, pedestrians, pedicabs, trees, bus shelters, traffic signs, and street vendors, with 26,016 labeled instances in 7,789 images. A performance analysis of traffic obstacle detection on Indonesian roads using the dataset created in this study was conducted using the YOLOv4 method.

Multiple vehicles detection and tracking for intelligent transport systems using machine learning approaches

2019 ◽  
Vol 70 (3) ◽  
pp. 214-224
Author(s):  
Bui Ngoc Dung ◽  
Manh Dzung Lai ◽  
Tran Vu Hieu ◽  
Nguyen Binh T. H.
Keyword(s):  
Machine Learning ◽  
Gaussian Mixture ◽  
Research Field ◽  
Transport Systems ◽  
Learning Approaches ◽  
Subtraction Method ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Detection And Tracking ◽  
Multiple Vehicles

Video surveillance is emerging research field of intelligent transport systems. This paper presents some techniques which use machine learning and computer vision in vehicles detection and tracking. Firstly the machine learning approaches using Haar-like features and Ada-Boost algorithm for vehicle detection are presented. Secondly approaches to detect vehicles using the background subtraction method based on Gaussian Mixture Model and to track vehicles using optical flow and multiple Kalman filters were given. The method takes advantages of distinguish and tracking multiple vehicles individually. The experimental results demonstrate high accurately of the method.

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