scholarly journals Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information

2018 ◽  
Vol 30 (5) ◽  
pp. 589-599
Author(s):  
Fevzi Yasin Kababulut ◽  
Damla Kuntalp ◽  
Olcay Akay ◽  
Timur Düzenli
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Real Data ◽  
Urban Life ◽  
Prediction Errors ◽  
Control Center ◽  
Road Section ◽  
Efficient Prediction ◽  
Traffic Systems ◽  
Near Future

Intelligent traffic systems attempt to solve the problem of traffic congestion, which is one of the most important environmental and economic issues of urban life. In this study, we approach this problem via prediction of traffic status using past average traveler speed (ATS). Five different algorithms are proposed for predicting the traffic status. They are applied to real data provided by the Traffic Control Center of Istanbul Metropolitan Municipality. Algorithm 1 predicts future ATS on a highway section based on the past speed information obtained from the same road section. The other proposed algorithms, Algorithms 2 through 5, predict the traffic status as fluent, moderately congested, or congested, again using past traffic state information for the same road segment. Here, traffic states are assigned according to predetermined intervals of ATS values. In the proposed algorithms, ATS values belonging to past five consecutive 10-minute time intervals are used as input data. Performances of the proposed algorithms are evaluated in terms of root mean square error (RMSE), sample accuracy, balanced accuracy, and processing time. Although the  proposed algorithms are relatively simple and require only past speed values, they provide fairly reliable results with noticeably low prediction errors.

scholarly journals Proposed Orbital Products for Positioning Using Mega-Constellation LEO Satellites

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5806
Author(s):  
Kan Wang ◽  
Ahmed El-Mowafy
Keyword(s):  
Dominant Role ◽  
Total Error ◽  
Real Data ◽  
Low Earth Orbit ◽  
Prediction Errors ◽  
Polynomial Degree ◽  
Short Period ◽  
Leo Satellites ◽  
Navigation Service ◽  
Near Future

With thousands of low Earth orbit (LEO) satellites to be launched in the near future, LEO mega-constellations are supposed to significantly change the positioning and navigation service for ground users. The goal of this contribution is to suggest and discuss the feasibility of possible procedures to generate the LEO orbital products at two accuracy levels to facilitate different positioning methods—i.e., Level A orbits with meter-level accuracy as LEO-specific broadcast ephemeris, and Level B orbits with an accuracy of centimeters as polynomial corrections based on Level A orbits. Real data of the LEO satellite GRACE FO-1 are used for analyzing the error budgets. For the Level A products, compared to the orbital user range errors (OUREs) of a few centimeters introduced by the ephemeris fitting, it was found that the orbital prediction errors play the dominant role in the total error budget—i.e., at around 0.1, 0.2 and 1 m for prediction intervals of 1, 2 and 6 h, respectively. For the Level B products, the predicted orbits within a short period of up to 60 s have an OURE of a few centimeters, while the polynomial fitting OUREs can be reduced by a few millimeters when increasing the polynomial degree from one to two.

scholarly journals Design on Highway Information Publishing System and Benefit Analysis of Traffic Control System

2011 ◽  
Vol 1 ◽  
pp. 343-347
Author(s):  
Wei Li ◽  
Guo Dong Han
Keyword(s):  
Control System ◽  
Public Transportation ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Information Control ◽  
Control Center ◽  
Shared Information ◽  
Traffic Control System ◽  
Information Publishing

With the purpose of offering dynamic information services for road users, the information publishing scheme is proposed based on variable message sign and variable speed limit sign. And the information publishing system shared information control center with public transportation service system is established. The economic benefit of intelligent traffic control system is quantitatively studied by radar map method for the first time. Research shows that intelligent traffic control system has reached ideal-steady state. The research results reduce traffic congestion and improve the highway utilization and traffic management efficiency.

scholarly journals Free Signal Management in Cities Using Density and Average Speed

2020 ◽  
Vol 16 ◽  
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Heavy Traffic ◽  
Road Transport ◽  
Light Signaling ◽  
Dynamic Traffic ◽  
The Czech Republic ◽  
Signaling Device ◽  
Near Future

The article focuses on the issue of congested roads in cities. The problems of heavy traffic both large and smaller towns. Some towns in the Czech Republic do not have built bypasses and so there is a heavy traffic congestion at favorite times. Road transport has become one of the most popular forms of transport. This trend is unlikely to change in the near future. The current market offers dynamic traffic management but not with the appropriate effect. Our proposed method belongs to dynamic traffic control based on real traffic control. The proposed method works in real time with the light signaling device behind the monitoring sections. The function of the proposed method is to extend the free passage of the light-signaling device.

scholarly journals Large-Scale Road Network Congestion Pattern Analysis and Prediction Using Deep Convolutional Autoencoder

2021 ◽  
Vol 13 (9) ◽  
pp. 5108
Author(s):  
Navin Ranjan ◽  
Sovit Bhandari ◽  
Pervez Khan ◽  
Youn-Sik Hong ◽  
Hoon Kim
Keyword(s):  
Traffic Congestion ◽  
Network Architecture ◽  
Road Network ◽  
Large Scale ◽  
Pattern Analysis ◽  
Image Data ◽  
Urban Life ◽  
Prediction Algorithm ◽  
Rapid Urbanization ◽  
Convolutional Autoencoder

The transportation system, especially the road network, is the backbone of any modern economy. However, with rapid urbanization, the congestion level has surged drastically, causing a direct effect on the quality of urban life, the environment, and the economy. In this paper, we propose (i) an inexpensive and efficient Traffic Congestion Pattern Analysis algorithm based on Image Processing, which identifies the group of roads in a network that suffers from reoccurring congestion; (ii) deep neural network architecture, formed from Convolutional Autoencoder, which learns both spatial and temporal relationships from the sequence of image data to predict the city-wide grid congestion index. Our experiment shows that both algorithms are efficient because the pattern analysis is based on the basic operations of arithmetic, whereas the prediction algorithm outperforms two other deep neural networks (Convolutional Recurrent Autoencoder and ConvLSTM) in terms of large-scale traffic network prediction performance. A case study was conducted on the dataset from Seoul city.

scholarly journals Privacy-Preserving Smart Road-Pricing System with Trustworthiness Evaluation in VANETs

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3658
Author(s):  
Qingfeng Zhu ◽  
Sai Ji ◽  
Jian Shen ◽  
Yongjun Ren
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Location Privacy ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Security Analysis ◽  
Geographical Location ◽  
Experimental Simulation ◽  
Control Center

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.

Improvement of METANET Model Based on Critical Density Modeling for Traffic Control

2021 ◽  
Author(s):  
Lina Fu ◽  
Jie Fang ◽  
Yunjie Lyu ◽  
Huahui Xie
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Field Data ◽  
Critical Density ◽  
Predictive Performance ◽  
Density Model ◽  
Model Based ◽  
Freeway Control ◽  
Density Modeling

Freeway control has been increasingly used as an innovative approach to ease traffic congestion, improve traffic safety and reduce exhaust emissions. As an important predictive model involved in freeway control, the predictive performance of METANET greatly influences the effect of freeway control. This paper focuses on modifying the METANET model by modeling the critical density. Firstly, the critical density model is deduced based on the catastrophe theory. Then, the perturbation wave and traveling wave that are obtained using the macro and micro data, respectively, have been developed to modify the above proposed critical density model. Finally, the numerical simulation is established to evaluate the effectiveness of the modified METANET model based on the field data from the realistic motorway network. The results show that overall, the predicted data from the modified METANET model are closer to the field data than those obtained from the original model.

Prediction of Vehicular Traffic Flow using Levenberg-Marquardt Artificial Neural Network Model: Italy Road Transportation System

2022 ◽  
Vol 24 (2) ◽  
pp. E74-E86
Author(s):  
Isaac Oyeyemi Olayode ◽  
Alessandro Severino ◽  
Tiziana Campisi ◽  
Lagouge Kwanda Tartibu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Time Of Day ◽  
Vehicle Speed ◽  
Road Transportation ◽  
Artificial Neural

In the last decades, the Italian road transport system has been characterized by severe and consistent traffic congestion and in particular Rome is one of the Italian cities most affected by this problem. In this study, a LevenbergMarquardt (LM) artificial neural network heuristic model was used to predict the traffic flow of non-autonomous vehicles. Traffic datasets were collected using both inductive loop detectors and video cameras as acquisition systems and selecting some parameters including vehicle speed, time of day, traffic volume and number of vehicles. The model showed a training, test and regression value (R2) of 0.99892, 0.99615 and 0.99714 respectively. The results of this research add to the growing body of literature on traffic flow modelling and help urban planners and traffic managers in terms of the traffic control and the provision of convenient travel routes for pedestrians and motorists.

The Application of Correlation ILS Techniques to Terminal Area Traffic Control

1969 ◽  
Vol 22 (04) ◽  
pp. 464-478
Author(s):  
J. Benjamin
Keyword(s):  
Hyperbolic Geometry ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Fundamental Aspect ◽  
Recent Contribution ◽  
Detection Techniques ◽  
Data Links ◽  
Area Problem ◽  
Integrate Data ◽  
Terminal Area

This paper outlines possible applications in the terminal area of an ILS based on hyperbolic geometry and correlation detection.1. Introduction. A recent contribution to thisJournalhas surveyed the terminal area problem at London and outlined the research which is necessary to improve traffic handling capability. It was shown that contributions from many different development efforts will need to be integrated in order to achieve a worthwhile result. A fundamental aspect is that the problem of traffic congestion begins and ends at the runways and that the performance of the instrument landing system is of major importance. This paper will indicate how an approach and landing aid based on hyperbolic geometry and using correlation detection techniques can offer solutions to many of the known causes of traffic delay. The same principles can be used to integrate data links and monitoring into a complex which should be designed to aid the pilot as well as the controller.

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