A Simple and Effective Method for Traffic Flow Density Detection

2013 ◽  
Vol 462-463 ◽  
pp. 122-125
Author(s):  
Wei Wang ◽  
Yong Gang Ma ◽  
Xian Chang Wang
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Practical Method ◽  
Urban Traffic ◽  
Flow Density

There has been a lot of research on traffic flow density detection in recent years. In this paper, we propose a simple and practical method for traffic flow density detection through using the multiple pairs of infrared photoelectric sensors and STC15F2K60S2 as the main controller. This method can be used for the multiple cars two-way or multi-way side by side traffic flow density detection. The circuit is simple, accurate and efficient. The proposed method is economical and practical. Thus it can promote the progress of urban traffic management.

Improve urban traffic efficiency with prohibiting left-turn policy

2021 ◽  
Author(s):  
Meng-Qin Cheng ◽  
Lele Zhang ◽  
Xue-Dong Hu ◽  
Mao-Bin Hu
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Critical Length ◽  
Urban Traffic ◽  
Flow Density ◽  
Route Guidance ◽  
Left Turn ◽  
Traffic Efficiency ◽  
Quickest Path ◽  
The Impact

Enhancing traffic flow plays an important role in the traffic management of urban arterial networks. The policy of prohibiting left-turn (PLT) at selected highly demanded intersections has been adopted as an attempt to increase the efficiency at these intersections. In this paper, we study the impact of PLT by mathematical analysis and simulations based on the cellular automaton model. Using the flow-density relation, three system performance indexes are examined: the average trip completion rate, the average traffic flow, and the average velocity of vehicles. Different route guidance strategies, including the shortest path and the quickest path, are investigated. We show that when left turn is prohibited, vehicles are distributed more homogeneously in the road network, and the system performs better and reaches a higher capacity. We also derive a critical length of link, above which the benefit of PLT will decrease.

scholarly journals Urban Wasteful Transport and Its Estimation Methods

2018 ◽  
Vol 10 (12) ◽  
pp. 4562 ◽  
Author(s):  
Xiangyang Cao ◽  
Bingzhong Zhou ◽  
Qiang Tang ◽  
Jiaqi Li ◽  
Donghui Shi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Transport Theory ◽  
Road Traffic ◽  
Urban Traffic ◽  
Flow Density ◽  
Urban Road ◽  
Road Capacity ◽  
Density Relationship

The paper studies urban road traffic problems from the perspective of resource science. The resource composition of urban road traffic system is analysed, and the road network is proved as a scarce resource in the system resource combination. According to the role of scarce resources, the decisive role of road capacity in urban traffic is inferred. Then the new academic viewpoint of “wasteful transport” was proposed. Through in-depth research, the paper defines the definition of wasteful transport and expounds its connotation. Through the flow-density relationship analysis of urban road traffic survey data, it is found that there is a clear boundary between normal and wasteful transport in urban traffic flow. On the basis of constructing the flow-density relationship model of road traffic, combined with investigation and analysis, the quantitative estimation method of wasteful transport is established. An empirical study on the traffic conditions of the Guoding section of Shanghai shows that there is wasteful transport and confirms the correctness of the wasteful transport theory and method. The research of urban wasteful transport also reveals that: (1) urban road traffic is not always effective; (2) traffic flow exceeding road capacity is wasteful transport, and traffic demand beyond the capacity of road capacity is an unreasonable demand for customers; (3) the explanation that the traffic congestion should apply the comprehensive theory of traffic engineering and resource economics; and (4) the wasteful transport theory and method may be one of the methods that can be applied to alleviate traffic congestion.

scholarly journals Application of Macroscopic Fundamental Diagram under Flooding Situation to Traffic Management Measures

2021 ◽  
Vol 13 (20) ◽  
pp. 11227
Author(s):  
Piyapong Suwanno ◽  
Rattanaporn Kasemsri ◽  
Kaifeng Duan ◽  
Atsushi Fukuda
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Road Network ◽  
Road Traffic ◽  
Control Measures ◽  
Flow Density ◽  
Fundamental Diagram ◽  
Urban Flood ◽  
Traffic Conditions ◽  
Macroscopic Fundamental Diagram

Bangkok, Thailand is prone to flooding after heavy rain. Many road sections become impassable, causing severe traffic congestion and greatly impacting activities. Optimal vehicle management requires the knowledge of flooding impact on road traffic conditions in specific areas. A method is proposed to quantify urban flood situations by expressing traffic conditions in specific ranges using the concept of macroscopic fundamental diagram (MFD). MFD-based judgement allows for a road manager to understand the current traffic situation and take appropriate traffic control measures. MFD analysis identified traffic flow–density and density–velocity relationships by using the shape of the estimated MFD travel time-series plots. Then, results were applied to develop a traffic model with vehicle-flow parameters as a measuring method for road-network performance. The developed model improved road-network traffic-flow performance under different flood conditions. A method is also presented for traffic management evaluation on the assumption that flooding occurs.

HETEROGENEOUS TRAFFIC FLOW MODEL FOR A TWO-LANE ROUNDABOUT AND CONTROLLED INTERSECTION

2007 ◽  
Vol 18 (01) ◽  
pp. 107-117 ◽  
Author(s):  
Y. FENG ◽  
Y. LIU ◽  
P. DEO ◽  
H. J. RUSKIN
Keyword(s):  
Traffic Flow ◽  
Queue Length ◽  
Traffic Management ◽  
Waiting Times ◽  
Arrival Rate ◽  
Urban Traffic ◽  
Heterogeneous Traffic ◽  
Traffic Density ◽  
Traffic Light ◽  
Heterogeneous Distribution

Modern urban traffic management depends heavily on the efficiency of road features, such as controlled intersections and multi-lane roundabouts. Vehicle throughput at any such configuration is modified by traffic mix, by rules governing manoeuvrability and by driver observance, as well as by traffic density. Here, we study heterogeneous traffic flow on two-lane roads through a cellular automata model for a binary mix of long and short vehicles. Throughput is investigated for a range of arrival rates and for fixed turning rate at an intersection: manoeuvres, while described in terms of left-lane driving, are completely generalisable. For a given heterogeneous distribution of vehicle type, there is a significant impact on queue length, delay times experienced and throughput at a fixed-cycle traffic light controlled two-way intersection and two-lane roundabout, when compared to the homogeneous case. As the proportion of long vehicles increases, average throughput for both configurations declines for increasing arrival rate, with average queue length and waiting time correspondingly increased. The effect is less-marked for the two-lane roundabout, due to absence of cross-traffic delays. Nevertheless, average waiting times and queue lengths remain uniformly high for arrival rates >0.25 vehicle per second (900 vph) on entry roads and for long vehicle proportion above 0.30–0.35.

Study on Traffic Multi-Source Data Fusion

2019 ◽  
Vol 13 (2) ◽  
pp. 63-75
Author(s):  
Suping Liu ◽  
Dongbo Zhang ◽  
Jialin Li
Keyword(s):  
Data Fusion ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Analysis Data ◽  
Urban Traffic ◽  
Data Sources ◽  
Flow Parameters ◽  
Fusion Methods ◽  
Single Detector

In order to alleviate urban traffic congestion, it is necessary to obtain roadway network traffic flow parameters to estimate the traffic conditions. Single-detector data may not be sufficient to obtain a comprehensive, effective, accurate and high-quality traffic flow data. Neural networks and regression analysis data fusion methods are employed to expand data sources as well as for improving data quality. The multi-source detector data can provide fundamental support for traffic management. An empirical analysis was conducted using acquisition technology employed by the Beijing urban expressway to estimate traffic flow parameters. The results show that the proposed data fusion method is feasible and provides reliable data sources.

scholarly journals Research on Intelligent City Traffic Management System based on WEBGIS

2021 ◽  
Author(s):  
You Li ◽  
Hui Jin ◽  
Jie Hong ◽  
Chunmu He ◽  
Xianbing Wang
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Management System ◽  
Traffic Accidents ◽  
Urban Traffic ◽  
Traditional System ◽  
The Road ◽  
Intelligent City ◽  
Traffic Management System ◽  
Low Efficiency

Abstract Aiming at the problem that the traditional urban traffic management system can't effectively integrate the data, which leads to the low efficiency of data processing and the effect of traffic management, a smart city traffic management system based on WEBGIS is designed. Based on the traditional system, the dynamic traffic data acquisition hardware module is designed. According to the weekly similarity characteristics of traffic flow data, the traffic flow in different time periods is predicted and the road signal is controlled. The WEBGIS technology is used to deal with the traffic accidents, and the effective management of the urban traffic is realized. Simulation results show that the designed management system can effectively reduce the congestion of urban trunk roads and improve the efficiency of traffic management.

scholarly journals Formation of the Traffic Flow Rate under the Influence of Traffic Flow Concentration in Time at Controlled Intersections in Tyumen, Russian Federation

2021 ◽  
Vol 13 (15) ◽  
pp. 8324
Author(s):  
Viacheslav Morozov ◽  
Sergei Iarkov
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Traffic Congestion ◽  
Traffic Management ◽  
System Analysis ◽  
Motor Vehicle ◽  
Experimental Studies ◽  
Transport Systems ◽  
Experiment Planning ◽  
Traffic Light

Present experience shows that it is impossible to solve the problem of traffic congestion without intelligent transport systems. Traffic management in many cities uses the data of detectors installed at controlled intersections. Further, to assess the traffic situation, the data on the traffic flow rate and its concentration are compared. Latest scientific studies propose a transition from spatial to temporal concentration. Therefore, the purpose of this work is to establish the regularities of the influence of traffic flow concentration in time on traffic flow rate at controlled city intersections. The methodological basis of this study was a systemic approach. Theoretical and experimental studies were based on the existing provisions of system analysis, traffic flow theory, experiment planning, impulses, probabilities, and mathematical statistics. Experimental data were obtained and processed using modern equipment and software: Traficam video detectors, SPECTR traffic light controller, Traficam Data Tool, SPECTR 2.0, AutoCad 2017, and STATISTICA 10. In the course of this study, the authors analyzed the dynamics of changes in the level of motorization, the structure of the motor vehicle fleet, and the dynamics of changes in the number of controlled intersections. As a result of theoretical studies, a hypothesis was put forward that the investigated process is described by a two-factor quadratic multiplicative model. Experimental studies determined the parameters of the developed model depending on the directions of traffic flow, and confirmed its adequacy according to Fisher’s criterion with a probability of at least 0.9. The results obtained can be used to control traffic flows at controlled city intersections.

scholarly journals Spatio-Temporal Visual Analysis for Urban Traffic Characters Based on Video Surveillance Camera Data

2021 ◽  
Vol 10 (3) ◽  
pp. 177
Author(s):  
Haochen Zou ◽  
Keyan Cao ◽  
Chong Jiang
Keyword(s):  
Video Surveillance ◽  
Traffic Management ◽  
Visual Analysis ◽  
Urban Traffic ◽  
License Plate ◽  
Road Vehicle ◽  
Urban Road ◽  
Surveillance Camera ◽  
Vehicle Density ◽  
Spatio Temporal

Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transport systems (ITS) for recognizing license plate numbers. This paper proposes a spatio-temporal visualization method to discover urban road vehicle density, city-wide regional vehicle density, and hot routes using license plate number data recorded by video surveillance cameras. To improve the accuracy of the visualization effect, during data analysis and processing, this paper utilized Internet crawler technology and adopted an outlier detection algorithm based on the Dixon detection method. In the design of the visualization map, this paper established an urban road vehicle traffic index to intuitively and quantitatively reveal the traffic operation situation of the area. To verify the feasibility of the method, an experiment in Guiyang on data from road video surveillance camera system was conducted. Multiple urban traffic spatial and temporal characters are recognized concisely and efficiently from three visualization maps. The results show the satisfactory performance of the proposed framework in terms of visual analysis, which will facilitate traffic management and operation.

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