scholarly journals Non-Roundabout design of cancel the intersection signal light on horizontal plane

2019 ◽  
Vol 91 ◽  
pp. 05003 ◽  
Author(s):  
He Yuilin ◽  
Andrii Beljatynskij ◽  
Alexander Ishchenko
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Evaluation System ◽  
Horizontal Plane ◽  
Design Theory ◽  
Urban Traffic ◽  
Channel Design ◽  
Traffic Lights ◽  
Quantitative Calculation ◽  
Signal Light

Traffic congestion is a world problem and an important factor restricting urban development. In order to solve the problem of urban traffic congestion, this paper takes the traffic flow theory and the intersection channel design theory as the research foundation, and conducts in-depth research on the causes of congestion at the intersection and the corresponding solutions, and proposes to cancel the traffic lights at the intersection without any stagnation. This paper proposes a new intersection design scheme, which is like the veins of the flower veins to channel the design intersection, cancel the signal light, and the vehicle can pass through the intersection without stagnation. It proposes a new solution to solve the traffic congestion problem. This new design allows the traffic flow to be spatially separated on the horizontal plane, and due to the cancellation of the signal lights, there is no signal waiting at the intersection, and the vehicle can travel without stopping at the intersection. At the same time, this paper also establishes a plane intersection service capability evaluation system based on simulation and quantitative calculation, which provides an evaluation index and proof basis for the non-stagnation driving channel design of the non-roundabout intersection.

Real-Time Monitoring Unit of Traffic Flow

2012 ◽  
Vol 588-589 ◽  
pp. 1058-1061
Author(s):  
Ting Zhang ◽  
Zhan Wei Song
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Traffic ◽  
Traffic Information ◽  
Real Time Monitoring ◽  
Traffic Lights ◽  
Real Time Traffic ◽  
Transit Use ◽  
Control Traffic

With the sustained growth of vehicle ownerships, traffic congestion has become obstacle of urban development. In addition to developing public transport and accelerating the construction of rail transit, use scientific managing and controlling method in real-time monitoring traffic flow to divert the traffic stream is an effective way to solve urban traffic problems. In this paper, cross-correlation algorithm is used to obtain real-time traffic information, such as capacity and occupancy of a lane, so as to control traffic lights intelligently.

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.

Path Reconstruction of Intelligent Traffic Based on Positive Feedback System

2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Supply And Demand ◽  
Demand Management ◽  
Reference Value ◽  
Feedback System ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Demand

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.

Image Measurement of Traffic Flow Parameters and its Traffic Congestion Evaluation

2014 ◽  
Vol 538 ◽  
pp. 455-459
Author(s):  
Dong Yao Jia ◽  
Po Hu
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Evaluation Model ◽  
Evaluation Methods ◽  
Urban Traffic ◽  
Flow Parameters ◽  
Shape Match ◽  
Flow Information ◽  
Vehicle Delay ◽  
Vehicle Shape

Current evaluation methods on urban traffic congestion are mostly based on traffic flow information. However, the measurement of traffic flow remains to be controversial and difficult for the community. This paper points out an algorithm to acquire traffic parameters and studies the evaluation methods based on it. By extracting multi-color-feature information from image and vehicle shape match algorithm based on fuzzy rules, this method can efficiently distinguish vehicles from each other thus to calculate the traffic state parameters according to the results of this method. Then it can build congestion evaluation model with vehicle delay rate as the critical parameter. The experiment indicates that this method can acquire the accurate real-time road parameters and also proves it is valid to apply this method in urban traffic congestion evaluation in different situations.

Two Dimensional Cellular Automaton Model of the Mixed Traffic Flow for Urban Traffic

2012 ◽  
Vol 241-244 ◽  
pp. 2082-2087
Author(s):  
Li Yang ◽  
Jun Hui Hu ◽  
Ling Jiang Kong
Keyword(s):  
Boundary Conditions ◽  
Cellular Automaton ◽  
Traffic Flow ◽  
Flow Model ◽  
Urban Traffic ◽  
Mixed Traffic ◽  
Traffic Flow Model ◽  
Traffic Lights ◽  
Mixed Traffic Flow ◽  
Transit Traffic

Based on the two-dimension cellular automaton traffic flow model (BML model), a mixed traffic flow model for urban traffic considering the transit traffic is established in this paper. Under the don't block the box rules and the opening boundary conditions, the impacts of transit traffic, the central station, traffic lights cycle, the vehicles length on the mixed traffic flow is studied by computer simulation. Some important characters appearing in the new model are also elucidated. It shows that traffic flow is closely related to traffic lights cycle, the geometric structure of transport network and boundary conditions. Under certain traffic light cycle time, the traffic flow has a periodical oscillation change. The comparison to practical measured data shows that our stimulation results are accordant with the changes of real traffic flow, which confirms the accuracy and rationality of our model.

Self-organization models of urban traffic lights based on digital infochemicals

SIMULATION ◽  
2018 ◽  
Vol 95 (3) ◽  
pp. 271-285 ◽  
Author(s):  
Guangyu Zou ◽  
Levent Yilmaz
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Urban Transportation ◽  
Urban Traffic ◽  
Self Organization ◽  
Traffic Lights ◽  
Traffic Systems ◽  
Signaling Strategies ◽  
Better Than ◽  
Organization Models

This paper presents a self-organizing model to design effective traffic signaling strategies in order to reduce traffic congestion in urban areas. The proposed traffic signaling system is based on a pattern model of self-organization, i.e., digital infochemicals (DIs), which are analogous to chemical substances that convey information between interactive elements mediated via the environment. In the context of traffic systems, the DIs refer to information generated by vehicles and dissipated by the urban transportation infrastructure. Based on the exploratory analysis with one single intersection, we demonstrate that the DI-based strategy performs significantly better than both the fixed and trigger-based scheduling strategies in terms of queue length and waiting time under both fixed and dynamic traffic demands.

scholarly journals Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction

2014 ◽  
Vol 26 (5) ◽  
pp. 393-403 ◽  
Author(s):  
Seyed Hadi Hosseini ◽  
Behzad Moshiri ◽  
Ashkan Rahimi-Kian ◽  
Babak Nadjar Araabi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Weather Conditions ◽  
Traffic Data ◽  
Data Loss ◽  
Traffic Lights ◽  
Traffic Flow Prediction ◽  
Traffic Flow Forecasting ◽  
Flow Prediction ◽  
Forecasting Method

Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI) technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and future traffic flow. In numerical case studies, the proposed traffic flow forecasting method was tested against data loss, changes in weather conditions, traffic congestion, and accidents. The outcomes were highly acceptable for all cases and showed the robustness of the proposed flow forecasting method.

Real-Time Traffic Signal Control Based on Kalman Filtering Theory

2015 ◽  
Vol 713-715 ◽  
pp. 915-918
Author(s):  
Yuan Xin Xu ◽  
Wan Ying Yang ◽  
Wen Shi
Keyword(s):  
Kalman Filter ◽  
Traffic Flow ◽  
Control Method ◽  
Urban Traffic ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Traffic Flows ◽  
Traffic Lights ◽  
Real Time Traffic ◽  
Stable Signal

Aiming at the problem that individual control of urban traffic lights and stable signal timing. This paper proposed a real timing control method of traffic lights which based on Kalman filter. This method use Kalman filter to predict the next time traffic flows and then update the signal timing. By field researching the traffic flow of intersection in peak hour and predicting the traffic flow. Then update the signal timing. Meanwhile using the VISSIM to simulate the intersection. The result of the simulation shows that the length of vehicle queue decreased significantly and the number of stops dropped. The efficiency of access has been greatly improved.

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