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Unlike conventional traffic signal control strategies, which assume that an intersection's geometric configuration is given as an exogenous input, dynamic lane grouping (DLG) strategies aim to further improve roadway capacity utilization under significant traffic demand variation. This is accomplished by dynamically adjusting the turning movement assignments for each lane. Previous numerical analyses...
To solve the signal control problems created by the mutual interference between motor traffic and pedestrians in cities, the signal control model with pedestrians non-complying is proposed based on the traditional signal optimization model. A particle swarm algorithm is proposed to solve the signal control problem. Based on an intersection of Tianhe district in Guangzhou City, the model is calculated...
Traffic signal control is a challenging task for traffic systems. As fuzzy logic is proved to be well suited to control some complex systems with uncertainties and human perception, it has been widely used to control the traffic signal in recent years. This paper proposes a novel fuzzy logic controller for signalizing modern roundabouts. Different from existing fuzzy traffic-signal controllers, the...
A fuzzy signal control method for single intersection is presented in this paper. This control method selects queue length as input of the fuzzy controller, sets up the fuzzy control rule base and constructs the vehicular delay model. Simulation experiments are presented to compare the vehicular average delay of fuzzy control with traditional inductive control and timing control under various types...
Based on the digital hormone model, this paper established a new distributed coordination control scheme for traffic signals, which adopts some hormonal information. The experiments with a traffic network of 8 junctions shows that this new control method is obviously superior to the timing control, sensing control and real-time control.
In an urban road network, travel times are not uniquely determined by the traffic states due to stochastic properties of traffic flow, stochastic arrivals and departures at intersections and traffic signal control. As a result, for a given traffic state, a range of travel times (delays) is found. This can be represented by a distribution of travel times (delays). Calibrating a model for the travel...
Adaptive Traffic Control Systems (ATCS) aim at the improvement of traffic flow in terms of delay, number of stops, travel time etc. in urban networks under the regime of traffic signal control. Well known ATCS are SCOOT, SCATS, BALANCE and MOTION to name only a few. Lately the Cell Transmission Model (CTM) attracted some attention in the context of traffic signal control. It can be used to model the...
For improving the intersection traffic capacity and reducing the vehicle emission, the solution that aim at the multi-object optimization was presented by using genetic algorithm (GA), and urban traffic microscopic simulation model (UTMSM) combined with GA was developed. The simulation was performed and the result indicated that the optimization method in this paper was effective to get better traffic...
Nowadays Float Car Data (FCD) is playing an important role in real-time traffic information systems. However, traffic signal control in urban road network will cause random delay on float cars, and this kind of delay will result in considerable fluctuation of travel time. Thus, the accuracy of FCD system is seriously affected. In this paper, float car refining models are proposed to calculate the...
Urban network traffic is a complex, nonlinear, unstable system and is significantly affected by immeasurable factors. This paper presents an optimal model to the application of signal coordination for urban network based on real-time traffic volumes. It divides a large signalized network into several subgroups. The number of subgroups, phase-time and offsets can be optimized to achieve an optimal...
In order to reduce the delay of vehicles passing through junction, the signal timing of agent controlled intersection was optimized by Q-Learning approach. On the basis of fuzzy rule set, the effect of signal control was improved through optimizing the combination of control rules with Q-Learning. The result of simulation illustrates that the signal control method based on Q-Learning is better than...
The immunogenetics theory is applied into traffic signal control in this paper. Then a new algorithm is proposed to solve the problem of signal timing optimization. For obtaining the optimal schedule quickly, the mechanism of the antibody response antigen is simulated in the improved immunogenetic algorithm, in which cell memory base is used to preserved best antibodies. The method of computing the...
Intersection as the city's road network node, is the meeting point for distribution of traffic flow. In fact, traffic signal control is partition of traffic flows in time and space, so that the traffic flows no conflict obtain right-of-way in order. This paper present the real-time signal timing optimization in intersection, in which, the Kalman filter is used to forecast short-term traffic flow,...
Considering the traffic organization project and traffic signal control project of the small and medium-sized cities in China, based on the dynamic optimization theory of operations research, this paper puts forwards the method of optimization design between the traffic organization and the traffic signal control of urban traffic, sets up the frame of the dynamic optimization. The whole design of...
An adaptive neuro-fuzzy inference system is developed and tested for traffic signal controlling. From a given input data set, the developed adaptive neuro-fuzzy inference system can draw the membership functions and corresponding rules by its own, thus making the designing process easier and reliable compared to standard fuzzy logic controllers. Among useful inputs of fuzzy signal control systems,...
This paper proposes a fuzzy logic signal controller with adaptive dynamic programming optimizing for traffic intersection. Because fuzzy logic has a clear advantage that it is able to use expert knowledge well, we adopt it in our controller. As adaptive dynamic programming is an advanced technology which is suitable for solving non-linear stochastic system optimizing problems, we use it to optimize...
Traffic signal control for pedestrian crossing is an effective measure to improve safety and efficiency of pedestrian crossing. Fuzzy logic is known to be suited for dealing with a complex optimization problem, as pedestrian crossing control, with many objectives, many constrains, unclear input information, and vague decision criteria. In this study, a new fuzzy logic is introduced for controlling...
This paper applies fuzzy theory and machine learning in the process of intersection signal control. It provides a fuzzy traffic signal control approach based on Particle Swarm Optimization for intersection signal control. Through fuzzy classifying traffic flow in under control intersection and adjacent intersection, this paper puts decision schemes of signal control in different conditions as rule-set...
Dynamic signal control is considered an effective measure to deal with urban traffic congestion by increasing intersection capacity and decreasing delays at the same time. A hierarchical fuzzy logic controller for urban signalized intersections is developed in this paper. The controller is designed to be responsive to real-time traffic intensities. Vehicle detectors are placed upstream of the intersection...
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