Urban Traffic Signal Research Articles

A MULTI-INTERSECTION MODEL AND SIGNAL TIMING PLAN ALGORITHM FOR URBAN TRAFFIC SIGNAL CONTROL

The urban traffic signal control system is complex, non-linear and non-equilibrium in real conditions. The existing methods could not satisfy the requirement of real-time and dynamic control. In order to solve these difficulties and challenges, this paper proposes a novel Multi-Intersection Model (MIM) based on Cellular Automata (CA) and a Multi-Intersection Signal Timing Plan Algorithm (MISTPA), which can reduce the delay time at each intersection and effectively alleviate the traffic pressure on each intersection in the urban traffic network. Our work is divided into several parts: (1) a multi-intersection model based on CA is defined to build the dynamic urban traffic network; (2) MISTPA is proposed, which truly reflects the real-time demand degree to green time of the traffic flow at each intersection. The MISTPA is composed Single Intersection Volume Algorithm (SIVA), Single-Lane Volume Algorithm (SLVA) and single intersection signal timing plan algorithm (SISTPA). Extensive experiments show that when the saturation is greater than 0.3, the MIM and the MISTPA achieve good performance, and can significantly reduce the vehicle delay time at each intersection. The average delay time of the traffic flow at each intersection can obviously be reduced. Finally, a practical case study demonstrates that the proposed model and the corresponding algorithm are correct and effective.

Coordinated Ramp Metering and Intersection Signal Control

The operations of freeway ramp metering and urban traffic network signal control are independent in most areas. Such situation may cause some conflict between traffic streams of the two subsystems, or, at least, their dynamic interactions have not been taken into account from an overall system viewpoint. Traffic performance can be improved if the controls of these two subnetworks are integrated. This paper proposes a novel signal control strategy for the feeding intersection and a coordination strategy for integrating it with the corresponding freeway onramp metering. UP ALINEA with queue-overwrite is used for the ramp metering. A signal optimization, which takes into account the available ramp space and traffic demand, is developed for intersection signal control. A calibrated micro-simulation is used to compare the proposed control/coordination strategies and current control plans in the field. Simulation result shows that, even though the overall system performance only gets a marginal improvement, intersection delay reduces significantly.

A Study of Signal Timing Fuzzy Control Based on the Collaborative Strategy of Road Green Wave Effect and Path Selection Entropy

With the growth of urban road traffic volume and the increase of road network density, correlation between ad- jacent road intersections is becoming more and more obvious. An intersection traffic signal adjustment tends to affect the smooth traffic flow of a number of adjacent intersections. Its congestion may gradually spread to a few blocks and regions all around the intersection. Therefore, increasingly high demands for urban traffic signal control make a variety of ad- vanced control technology integrated, so as to adjust the intersection control parameter and accordingly achieve a dynamic coordination control over the city traffic. Hopefully, it can satisfy traffic demands and achieve a new dynamic balance be- tween road traffic and transport demand. This paper focuses on the fuzzy control over green time extension at adjacent in- tersections of trunk road by using the collaborative strategy of road green wave effect and path selection entropy, in order to solve the problem of coupling between adjacent intersections, so as to realize the signal coordination control on trunk road. This algorithm makes Signal Timing more flexible.

Modeling and Simulation of Urban Arterial Traffic Signal Coordinated Control

Traffic congestion is a major concern for many cities throughout the world. Developing a sophisticated traffic monitoring and control system would result in an effective solution to this problem. In order to reduce traffic delay, a novel urban arterial traffic signal coordinated control method is presented. The total delay of downstream and upstream vehicles is considered and the function describing the relationship between vehicles delay and signal offset among intersections is established. Finally, comparing the performance of traffic signal under method proposed in this paper with the traditional isolated traffic signal control method, the microscopic simulation results show that the method proposed in this paper has better performance in the aspect of reducing the vehicles delay. The offset model is tested in a simulation environment consisting of a core area of three intersections. It can be concluded that the proposed method is much more effective in relieving oversaturation in a network than the isolated intersection control strategy.

Design and Optimization of Urban Signal Fuzzy Controller Based on IQPSO

In order to overcome the shortcomings of traffic signal fixed-time control method, a fuzzy control algorithm for urban traffic signal is proposed. The signal phase switching order is adjustable. The improved quantum particle swarm optimization(QPSO) is also introduced to optimize fuzzy control rules of traffic signal controller. Take four-phase traffic signal commonly used in current practice for example. Compared with traffic signal fixed-time control and single fuzzy control method, the control method put forward in this paper can reduce the vehicles’ average delay time in junction. The simulation results show that the proposed algorithm is proved to be an effective and practicable method for urban traffic self-adaptive control.

Analytical Formulation of the Trip Travel Time Distribution

This paper validates an analytical and tractable approximation of trip travel time variance for general topology networks. The main challenge in the derivation of such an approximation is to account for spatial between-link dependencies in an analytical yet also tractable manner. The approximation considered in this paper achieves tractability by extending Little's law for higher-order moments of finite capacity Markovian queueing networks. This paper presents a detailed validation of this approach. We compare the analytical approximations of path travel time variance to simulation-based estimates for two general topology queueing networks. Ongoing work, to be presented at the conference, uses this approach to address an urban traffic signal control problem that explicitly accounts travel time variability.

Extremum-Seeking for Adaptation of Urban Traffic Signal Control

This paper investigates the application of an extremum-seeking scheme to fine-tune the parameters of a “local” urban traffic signal control strategy to improve its performance. A set of conditions that the local traffic controller has to satisfy for stability of the closed-loop system are introduced. Employing a self-organised traffic light scheme as the local controller, it is shown that this strategy satisfies the aforementioned conditions, and its optimality is dependent on the selection of a certain parameter. It is then demonstrated that, by employing an ES scheme, it is possible to always regulate this parameter close to its optimum given any traffic conditions.

MOTION - A Developing Urban Adaptive Traffic Signal Control System

This paper mainly focuses on the recent development of MOTION system. MOTION system, as a developing urban adaptive traffic signal control system, is now more and more worldwide recognized. In this paper, first the original idea of MOTION is descript. Calculation procedures of MOTION algorithm are followed. Then methods of optimization, including optimization of green split, optimization of cycle time, optimization of offset times are introduced. Platoon Model, as a vital concept in optimization of offset times, are explained in details. Multi functional levels in MOTION system including the tactical level and the operational level are introduced in figures. At last, implementation results of MOTION system in Germany are shown to prove MOTION as a very efficient method in improving urban traffic quality.

A Study of Signal Timing Control Based on the Collaborative Strategy of Road Green Wave Effect and Path Selection Entropy

With the growth of urban road traffic volume and the increase of road network density, correlation between adjacent road intersections is becoming more and more obvious. An intersection traffic signal adjustment tends to affect the smooth traffic flow of a number of adjacent intersections. Its congestion may gradually spread to a few blocks and regions all around the intersection. Therefore, increasingly high demands for urban traffic signal control make a variety of advanced control technology integrated, so as to adjust the intersection control parameter and accordingly achieve a dynamic coordination control over the city traffic. Hopefully, it can satisfy traffic demands and achieve a new dynamic balance between road traffic and transport demand. This paper focuses on the signal timing control over green time extension at adjacent intersections of trunk road by using the collaborative strategy of road green wave effect and path selection entropy, in order to solve the problem of coupling between adjacent intersections, so as to realize the signal coordination control on trunk road. This algorithm makes Signal Timing more flexible.

Based on Road Green Wave Effect of Collaborative Strategy of Signal Timing Fuzzy Control

With growth of Urban Road Traffic Volume and the increase of Road Network Density, correlation between adjacent road intersections is becoming more and more obvious. An intersection traffic signal adjustment tends to affect the health of a number of adjacent intersections road traffic flow. Its congestion may over time gradually spread to within a few blocks and regions all around the intersection. Therefore increasingly high demands of urban traffic signal control make a variety of advanced control technology integration, achieve the purpose to adjust a control parameter, in order to achieve dynamic coordination within the city - wide traffic control, to satisfy traffic demands, and then let the road traffic and the transport demand make a new balance. And This article introduces is the use of the green wave effect collaborative strategies adjacent green extension of fuzzy control in order to solve the problem of coupling between intersections road. This algorithm makes Signal Timing to be more flexible.

Cellular automata on FPGA for real-time urban traffic signals control

Among different traffic features, the urban traffic has received a lot of attention due to the ongoing traffic congestion as a result of increased car usage, population growth, and changes in population density. In urban networks, the vehicles flow differs when compared with highways flow because of the freeway's low speed limit but mostly because of the traffic lights control. In this paper, a real-time hardware implemented bio-inspired model for traffic lights control is presented. The proposed model arrives from Cellular Automata (CAs), which have been proven very flexible and powerful computational traffic models, in that they are able to capture all previously mentioned basic phenomena that occur in traffic flows. The resulting CA model was hardware implemented on FPGA to take full advantage of the inherent parallelism of the CAs and to support the function of an advanced electronic system able to provide real-time adaptive control of traffic lights designed to consider traffic conditions for the whole intersections. The analytical results, obtained by application of the aforementioned FPGA CA processor are found in excellent agreement with the numerical simulations.

Urban Traffic Adaptive Signal Control through Intelligent Agent

As the population of the world grows rapidly, the problem of traffic has been increased in many parts of the world. Many governments of the world are devising ways to cater this with new and improved methods. Advances in computer technologies have changed transportation field. Based on those, Intelligent Transportation System has been proposed for the next generation transportation system. This system requires more utilisation of Artificial Intelligence. Intelligent agent may use Knowledge Based Expert System. Intelligent agent is suggested to be implemented in Traffic Adaptive Signal Control System as a part of Intelligent Transportation System. Previous applications of Knowledge Based Expert System in transportation field are briefly reviewed, and potential implementations are discussed by focusing on Traffic Adaptive Signal Control System. The project aim to simplify the problem at level of single traffic control due to limited capability of resources at a traffic signal in open space. So, an artificial agent at each signal must be rugged one system to face the extreme weather conditions and dusty and noisy area along-with shock prove because at road side it can be hit by some vehicle if situated in pole. So it should work in all extreme conditions.

Modeling and Simulation of Urban Traffic Signals

Traffic signals play a vital role in effective traffic management. In this paper we apply Arena simulation tool box for modeling and simulation of urban traffic signal system. It has been shown that Arena could be used in simulation of traffic signals system, despite the fact that Arena is not designed for modeling urban traffic signal control. We presented a non-trivial case study to illustrate how Arena is capable of modeling traffic systems.

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

Research on Fast Dynamic Division Method of Coordinated Control Subarea

摘要: 通过建立基于交叉口关联度的协调控制子区划分模型,设计最佳控制子区划分方 案获取流程,实现了交通信号控制子区的动态划分;针对最佳控制子区划分方案求 解过程中可能面临的维数灾难问题,提出利用降维处理与遗传算法两种方法进行 子区划分方案的快速寻优,并给出了一套协调控制子区快速动态划分流程.通过算 例分析说明,在一定规模路网之下本文提出的控制子区快速动态划分方法将以一个 较大概率搜索到次优子区划分方案,且因其计算时间可以被有效控制,因此完全能够 满足控制子区划分的实时性要求,可推广应用于城市区域交通信号实时控制系统中. 关键词: 交通信号控制 / 控制子区 / 快速划分 / 降维处理 / 遗传算法

Evaluating the impacts of urban corridor traffic signal optimization on vehicle emissions and fuel consumption

This study investigates the impacts of traffic signal timing optimization on vehicular fuel consumption and emissions at an urban corridor. The traffic signal optimization approach proposed integrates a TRANSIMS microscopic traffic simulator, the VT-Micro model (a microscopic emission and fuel consumption estimation model), and a genetic algorithm (GA)-based optimizer. An urban corridor consisting of four signalized intersections in Charlottesville, VA, USA, is used for a case study. The result of the case study is then compared with the best traffic signal timing plan generated by Synchro using the TRANSIMS microscopic traffic simulator. The proposed approach achieves much better performance than that of the best Synchro solution in terms of air quality, energy and mobility measures: 20% less network-wide fuel consumption, 8–20% less vehicle emissions, and nearly 27% less vehicle-hours-traveled (VHT).

Urban Traffic Signal Coordinated Control Optimization with Bus Priority Based on Quantum Genetic Algorithm

An optimization algorithm of urban traffic signal coordinated control with bus priority, which is aiming at achieving optimal comprehensive traffic efficiency, is proposed in this paper. Six kinds of key parameters that dominate signal control effects are extracted from abundant factors. Based on these parameters, an advance and flexible coding scheme which can generate detail signal control information in QGA is put forward. Considering travel time, no wait passing rate, crossing delay, green wave effect and other factors, a new fitness function is constructed. Verified by simulations in PARAMICS, the optimized signal control scheme can obviously improve comprehensive regional traffic efficiency.

Study on Urban Intersection Traffic Flow Forecasting and Traffic Signal Control

Short-traffic flow forecasting is an important part of ITS, and its accuracy and real-time is directly related to the effect of traffic control and traffic induce. Gathering and analyzing the real-time data of urban road network ,short-time traffic flow forecasting could estimate the state of traffic flow for a few minutes in future and provide support to intelligent transportation control, so it is one of the important premise for ITS.

Research on Urban Traffic Signal Control Method at Single Intersection

A fuzzy logic controller is presented for a four-phase isolated signalized intersection on normal and abnormal conditions. It controls the traffic light timings to ensure smooth flow of traffic with minimal delay, according to the real-time traffic flow information detected by the vehicle detector. A new controller is proposed, in which the fuzzy membership functions are optimized by neural network and the control rules are optimized by genetic algorithm. Results show that the traditional fuzzy controller achieves good control effect and the performance of the controller optimized is better than the traditional one on both normal and abnormal conditions.

Multi-objective Optimization Method of Signal Timing for the Non-motorized Transport at Intersection

Considering the coordination between vehicle and non-motorized, different traffic composition have different signal control operates at the urban road intersection. In view of the multi-objective property of urban traffic signal control, the paper presents a multi-objective signal timing optimization model with vehicle volume and the non-motorized transport number as the inputs and traveler delay, stops and traffic capacity as the optimization objectives, and saturation degree is taken as restrictions. Furthermore, the method can adjust the weight of performance indexes according to mixed traffic composition. The multi-objective model is solved by genetic algorithm. The result shows that the model can give better signal timing than Webster method on the trade-off among various objectives and improve the traffic congestion effectively under mixed traffic condition.