Model Based Vehicle Extraction and Tracking for Road Traffic Control

2007 ◽  
pp. 844-851 ◽  
Author(s):  
Bartlomiej Płaczek ◽  
Marcin Staniek
Keyword(s):  
Traffic Control ◽  
Road Traffic ◽  
Model Based

Development and Implementation of a Model-Based Road Traffic-Control Scheme

2017 ◽  
Vol 31 (3) ◽  
pp. 04016063 ◽  
Author(s):  
Vincy Verghese ◽  
Liu Chenhui ◽  
Shankar C. Subramanian ◽  
Lelitha Vanajakshi ◽  
Anuj Sharma
Keyword(s):  
Traffic Control ◽  
Road Traffic ◽  
Model Based ◽  
Control Scheme

Color image analysis for vehicle speed measurement

1993 ◽  
Vol 20 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Yean-Jye Lu ◽  
Xidong Yuan
Keyword(s):  
Image Analysis ◽  
Traffic Control ◽  
Road Traffic ◽  
Color Image ◽  
Image Data ◽  
Difficult Problem ◽  
Vehicle Speed ◽  
Color Image Analysis ◽  
Speed Measurement ◽  
Monochrome Image

Image analysis for traffic data collection has been studied throughout the world for more than a decade. A survey of existing systems shows that research was focused mainly on the monochrome image analysis and that the field of color image analysis was rarely studied. With the application of color image analysis in mind, this paper proposes a new algorithm for vehicle speed measurement in daytime. The new algorithm consists of four steps: (i) image input, (ii) pixel analysis, (iii) single image analysis, and (iv) image sequence analysis. It has three significant advantages. First, the algorithm can distinguish the shadows caused by moving vehicles outside the detection area from the actual vehicles passing through the area, which is a difficult problem for the monochrome image analysis technique to handle. Second, the algorithm significantly reduces the image data to be processed; thus only a personal computer is required without the addition of any special hardware. The third advantage is the flexible placement of detection spots at any position in the camera's field of view. The accuracy of the algorithm is also discussed. Key words: speed measurement, vehicle detection, image analysis, image processing, traffic control, traffic measurement and road traffic.

scholarly journals Reasoning-predicting Model based on Strong Relevant Logic in Road Traffic Forecasting

2012 ◽  
Vol 33 ◽  
pp. 1105-1110 ◽  
Author(s):  
Dancheng Li ◽  
Zhiliang Liu ◽  
Cheng Liu ◽  
Binsheng Liu ◽  
Wei Zhang
Keyword(s):  
Road Traffic ◽  
Relevant Logic ◽  
Predicting Model ◽  
Traffic Forecasting ◽  
Model Based

Road Safety in Developing Countries - The Case of Transportation Management in Dar Es Salaam City

2012 ◽  
Vol 178-181 ◽  
pp. 1806-1814
Author(s):  
Philemon Kazimil Mzee ◽  
Yan Chen
Keyword(s):  
Public Transport ◽  
Traffic Control ◽  
Road Safety ◽  
Road Traffic ◽  
High Growth ◽  
Dar Es Salaam ◽  
Rapid Urbanization ◽  
Policy Objective ◽  
Transportation Management ◽  
Transport Services

Countries of the developing world are characterized by rapid urbanization, high growth rates in traffic and congestion and decreasing regulation of public transport. Because the majority of the developing world's inhabitants are dependent on public transport services for their mobility needs, the need for safe, effective and efficient public transport is essential to ensure adequate, affordable, accessibility and the continuing sustainable development of livelihoods in the rural and urban. Finally, recommendations are made to reduce both the severity and number of public transport accidents in the future. This paper highlights the historical road safety and the transportation management in Dar es Salaam. In the field of road traffic control and management, the primary policy objective is to develop appropriate institutional and organizational arrangement towards further efficient road use.

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.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

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