City traffic prediction based on real-time traffic information for Intelligent Transport Systems

2013 ◽  
Author(s):  
Zilu Liang ◽  
Yasushi Wakahara
Keyword(s):  
Real Time ◽  
Traffic Information ◽  
Transport Systems ◽  
Traffic Prediction ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Real Time Traffic

scholarly journals Information Source Quality in Intelligent Transport Systems

2012 ◽  
Vol 22 (2) ◽  
pp. 125-131 ◽  
Author(s):  
Niko Jelušić ◽  
Mario Anžek ◽  
Božidar Ivanković
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Information Sources ◽  
Information Source ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Traffic System ◽  
Intelligent Transport ◽  
Real Time Information ◽  
Time Information

Advanced automatic traffic control systems and various other ITS (Intelligent Transport Systems) applications and services rely on real-time information from the traffic system. This paper presents the overview and general functions of different information sources which provide real-time information that are used or could be used in ITS. The objective is to formally define the quality of information sources suitable for ITS based on formal models of the traffic system and information sources. The definition of quality encompasses these essential factors: traffic system information that exists or may be requested, user requirements and attributes that describe the information sources. This provides the framework and guidelines for the evaluation of information sources that accounts for relevant factors that influence their selection for specific ITS applications. KEY WORDS: information source, information source quality, Intelligent Transport Systems (ITS), automatic traffic control

scholarly journals Speed Profile Prediction in Intelligent Transport Systems Exemplified by Vehicle to Vehicle Interactions

2015 ◽  
Vol 15 (5) ◽  
pp. 63-77 ◽  
Author(s):  
Ivan Bosankic ◽  
Lejla Banjanovic-Mehmedovic ◽  
Fahrudin Mehmedovic
Keyword(s):  
Large Scale ◽  
Traffic Information ◽  
Transport Systems ◽  
Flow Density ◽  
High Temporal Resolution ◽  
Speed Profile ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Vehicle To Vehicle ◽  
Prediction Approach

Abstract Intelligent Transport Systems (ITS) fall in the framework of cyberphysical systems due to the interaction between physical systems (vehicles) and distributed information acquisition and dissemination infrastructure. With the accelerated development of wireless Vehicle-to-Vehicle (V2V) and Vehicle-to Infrastructure (V2I) communications, the integrated acquiring and processing of information is becoming feasible at an increasingly large scale. Accurate prediction of the traffic information in real time, such as the speed, flow, density has important applications in many areas of Intelligent Transport systems. It is a challenging problem due to the dynamic changes of the traffic states caused by many uncertain factors along a travelling route. In this paper we present a V2V based Speed Profile Prediction approach (V2VSPP) that was developed using neural network learning to predict the speed of selected agents based on the received signal strength values of communications between pairs of vehicles. The V2VSPP was trained and evaluated by using traffic data provided by the Australian Centre for Field Robotics. It contains vehicle state information, vehicle-to-vehicle communications and road maps with high temporal resolution for large numbers of interacting vehicles over a long time period. The experimental results show that the proposed approach (V2VSPP) has the capability of providing accurate predictions of speed profiles in multi-vehicle trajectories setup.

Analysis on Effectiveness of Intelligent Transport Systems on National Highways

2011 ◽  
Vol 271-273 ◽  
pp. 645-650
Author(s):  
Sung Han Lim
Keyword(s):  
Co2 Reduction ◽  
Information Provision ◽  
Economic Feasibility ◽  
Traffic Information ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Time Saving ◽  
Effect Analysis ◽  
Intelligent Transport ◽  
Fuel Savings

Intelligent transport systems(ITS) designed for solving traffic problems have actively been promoted in recent years. ITS is aimed at maximizing the use of existing transportation facilities by providing users with traffic information, and much effort is currently putting into the safety of users. However, there have been many difficulties in analyzing feasibility of ITS project since there was no methodology to calculate the effectiveness due to ITS construction. On this, a study on the methodology for effect analysis of ITS project is required. In this study, the method to quantify the effectiveness scale was suggested by selecting travel time saving, CO2 reduction, fuel savings and VMS information provision as benefit items for effect analysis on the national highway ITS project. As a result of analysis on the economic feasibility, it turned out that B/C ratio is 1.20, IRR 12.4% and NPV 1.48 billion won, which shows that the ITS construction project has economic feasibility.

scholarly journals EUROPEAN ITS PLATFORM: RETHINKING ITS

2021 ◽  
Vol 1202 (1) ◽  
pp. 012001
Author(s):  
Orestis Giamarelos ◽  
Tobias Reiff
Keyword(s):  
Transport Infrastructure ◽  
Traffic Information ◽  
Transport Systems ◽  
Core Network ◽  
Design Development ◽  
Intelligent Transport Systems ◽  
Technical Standards ◽  
Intelligent Transport ◽  
Strategic Approach ◽  
The One

Abstract The expectations placed on the existing European transport infrastructure are increasing due to the growing mobility needs of the population on the one hand and the rising volume of freight traffic on the other. The aim of the European ITS Platform is to increase the efficiency of the TEN-T core network through a better use of the existing infrastructure by implementing Intelligent Transport Systems (ITS). It fosters interoperability and the development of uniform technical standards by monitoring and disseminating the results delivered by the five CEF ITS Road Corridor Projects. One major outcome is the drafting of the “Reference Handbook for harmonized ITS Core Service Deployment in Europe”. This digital freely available handbook comprises a series of guidance and advice for use by road authorities and operators to support them in the development of their strategic approach, design development, deployment, installation and operation of ITS and remain compliant with European legislation. Its key features include: Deployment Guidance for 14 different ITS Services, including DATEX reference profiles, Guidance on the provision and use of traffic information provided under the European Directive (2010/40/EU), C-ITS developments, Knowledge gained from the collection of 100 Best Practices etc.

scholarly journals The Multi-Station Based Variable Speed Limit Model for Realization on Urban Highway

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 801 ◽  
Author(s):  
Soobin Jeon ◽  
Chongmyung Park ◽  
Dongmahn Seo
Keyword(s):  
Real Time ◽  
Transportation Systems ◽  
Traffic Information ◽  
Transport Systems ◽  
Speed Limit ◽  
Stability Assessment ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Conditions ◽  
Real Time Traffic

Intelligent transport systems (ITS) are a convergence of information technology and transportation systems as seen in the variable speed limit (VSL) system. Since the VSL system controls the speed limit according to the traffic conditions, it can improve the safety and efficiency of a transport network. Many researchers have studied the real-time VSL (RVSL) algorithm based on real-time traffic information from multiple stations recording traffic data. However, this method can suffer from inaccurate selection of the VSL start station (VSS), incorrect VSL calculations, and is unable to quickly react to the changing traffic conditions. Unstable VSL systems result in more congestion on freeways. In this study, an enhanced VSL algorithm (EVSL) is proposed to address the limitations of the existing RVSL algorithm. This selects preliminary VSL start stations (pVSS), which is expected to end congestion using acceleration and allocates final VSSs for each congestion interval using selected pVSS. This controls the vehicles that entered the congestion area based on the selected VSS. We used four metrics to evaluate the performance of the proposed VSL (VSS stability assessment, speed control stability assessment, travel time, and shockwave), which were all enhanced when compared to the standard RVSL algorithm. In addition, the EVSL algorithm showed stable VSL performance, which is critical for road safety.

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.

PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Rusmadi Suyuti
Keyword(s):  
Information System ◽  
Real Time ◽  
Travel Demand ◽  
Urban Traffic ◽  
Road User ◽  
Traffic Information ◽  
Estimation Methods ◽  
Traffic Counts ◽  
Real Time Traffic ◽  
Demand Models

Traffic information condition is a very useful  information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.  

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