Intelligent traffic light control of isolated intersections using machine learning methods

Traffic congestion is one of the major problems in modern cities. This study applies machine learning methods to determine green times in order to minimize in an isolated intersection. Q-learning and neural networks are applied here to set signal light times and minimize total delays. It is assumed that an intersection behaves in a similar fashion to an intelligent agent learning how to set green times in each cycle based on traffic information. Here, a comparison between Q-learning and neural network is presented. In Q-learning, considering continuous green time requires a large state space, making the learning process practically impossible. In contrast to Q-learning methods, the neural network model can easily set the appropriate green time to fit the traffic demand. The performance of the proposed neural network is compared with two traditional alternatives for controlling traffic lights. Simulation results indicate that the application of the proposed method greatly reduces the total delay in the network compared to the alternative methods.

Analysis of backward congestion notification with delay for enhanced Ethernet networks

At present, companies and standards organizations are enhancing Ethernet as the unified switch fabric for all of the TCP/IP traffic, the storage traffic and the high performance computing traffic in data centers. Backward congestion notification (BCN) is the basic mechanism for the end-to-end congestion management enhancement of Ethernet. To fulfill the special requirements of the unified switch fabric, i.e., losslessness and low transmission delay, BCN should hold the buffer occupancy around a target point tightly. Thus, the stability of the control loop and the buffer size are critical to BCN. Currently, the impacts of delay on the performance of BCN are unidentified. When the speed of Ethernet increases to 40 Gbps or 100 Gbps in the near future, the number of on-the-fly packets becomes the same order with the buffer size of switch. Accordingly, the impacts of delay will become significant. In this paper, we analyze BCN, paying special attention on the delay. We model the BCN system with a set of segmented delayed differential equations, and then deduce sufficient condition for the uniformly asymptotic stability of BCN. Subsequently, the bounds of buffer occupancy are estimated, which provides direct guidelines on setting buffer size. Finally, numerical analysis and experiments on the NetFPGA platform verify our theoretical analysis.

Measures for controlling traffic congestion

Traffic congestion has become a severe scourge in large cities, in both the industrialized and developing countries. Increasing demand for urban transport and transit has led to longer travel times, and a greater incidence of accidents, environmental problems and deterioration in the quality of life than is considered acceptable for citizens. A multidisciplinary approach is required in order to keep the negative effects of congestion under control and to ensure standards of living remain sustainable. In view of the seriousness of the problem, ECLAC with the support of the German Agency for Technical Cooperation (GTZ) is carrying out a project to study measures that contribute to traffic control. As part of this project, initiatives regarding the supply of, and the demand for, transport have been examined, and a programme to disseminate information is being conducted.For further information, please contact Mr Alberto Bull .

Alternatives for controlling urban traffic congestion

Traffic congestion is nothing new in Latin American cities but has worsened in recent years. Eliminating it is a pipedream, but it should be brought under control. Many economists and transport planners think electronic road pricing would be the best way of tackling it, now that the appropriate technology for implementing it is available. On the other hand, experience shows that, for political reasons, it would be better to begin by adopting simpler methods. To start with, simple road pricing would seem to be the best option. But, over 20 years of experience in London and more than six in Santiago, Chile, made it clear that socio-political barriers have to be surmounted before even this option can be applied in practice. There is more political support for measures to control parking, due in part to the fact that the legal powers do not normally extend to restricting the number of parking spaces available to high-income and influential motorists who have the right to park near their offices and who cause a great deal of the congestion whilst getting there. In Latin America, the relative importance of taxis also diminishes the effectiveness of measures geared to parking, since taxis contribute to congestion although but they do not park. The problem of congestion cannot be solved by using tame measures. The time has come for something bolder, i.e., measures that, at the very least, exercise control over those parking spaces, which so far have been beyond the reach of governments and local authorities, ideally, simple road pricing systems would be even more effective.

A distributed end-to-end overload control mechanism for networks of SIP servers.

The Session Initiation Protocol (SIP) is an application-layer control protocol standardized by the IETF for creating, modifying and terminating multimedia sessions. With the increasing use of SIP in large deployments, the current SIP design cannot handle overload effectively, which may cause SIP networks to suffer from congestion collapse under heavy offered load. This paper introduces a distributed end-to-end overload control (DEOC) mechanism, which is deployed at the edge servers of SIP networks and is easy to implement. By applying overload control closest to the source of traf?c, DEOC can keep high throughput for SIP networks even when the offered load exceeds the capacity of the network. Besides, it responds quickly to the sudden variations of the offered load and achieves good fairness. Theoretic analysis and extensive simulations verify that DEOC is effective in controlling overload of SIP networks.

Probe-based end-to-end overload control for networks of SIP servers

The Session Initiation Protocol (SIP) has been adopted by the IETF as the control protocol for creating, modifying and terminating multimedia sessions. Overload occurs in SIP networks when SIP servers have insufficient resources to handle received messages. Under overload, SIP networks may suffer from congestion collapse due to current ineffective SIP overload control mechanisms. This paper introduces a probe-based end-to-end overload control (PEOC) mechanism, which is deployed at the edge servers of SIP networks and is easy to implement. By probing the SIP network with SIP messages, PEOC estimates the network load and controls the traffic admitted to the network according to the estimated load. Theoretic analysis and extensive simulations verify that PEOC can keep high throughput for SIP networks even when the offered load exceeds the capacity of the network. Besides, it can respond quickly to the sudden variations of the offered load and achieve good fairness.

Full road closure for work zone operations : a cross-cutting study : reducing congestion and crashes through full road closure for maintenance and construction.

"EDL# 13795."

Transportation infrastructure: benefits of traffic control signal systems are not being fully realized.

Mode of access: Internet.

Decentralized control of street networks /

"September 1982."

DEVELOPMENT OF A DECISION/DEPLOYMENT SUPPORT TOOL FOR VARIABLE SPEED LIMITS IN RECURRENT CONGESTION

Traffic demand increases are pushing aging ground transportation infrastructures to their theoretical capacity. The result of this demand is traffic bottlenecks that are a major cause of delay on urban freeways. In addition, the queues associated with those bottlenecks increase the probability of a crash while adversely affecting environmental measures such as emissions and fuel consumption. With limited resources available for network expansion, traffic professionals have developed active traffic management systems (ATMS) in an attempt to mitigate the negative consequences of traffic bottlenecks. Among these ATMS strategies, variable speed limits (VSL) and ramp metering (RM) have been gaining international interests for their potential to improve safety, mobility, and environmental measures at freeway bottlenecks. Though previous studies have shown the tremendous potential of variable speed limit (VSL) and VSL paired with ramp metering (VSLRM) control, little guidance has been developed to assist decision makers in the planning phase of a congestion mitigation project that is considering VSL or VSLRM control. To address this need, this study has developed a comprehensive decision/deployment support tool for the application of VSL and VSLRM control in recurrently congested environments. The decision tool will assist practitioners in deciding the most appropriate control strategy at a candidate site, which candidate sites have the most potential to benefit from the suggested control strategy, and how to most effectively design the field deployment of the suggested control strategy at each implementation site. To do so, the tool is comprised of three key modules, (1) Decision Module, (2) Benefits Module, and (3) Deployment Guidelines Module. Each module uses commonly known traffic flow and geometric parameters as inputs to statistical models and empirically based procedures to provide guidance on the application of VSL and VSLRM at each candidate site. These models and procedures were developed from the outputs of simulated experiments, calibrated with field data. To demonstrate the application of the tool, a list of real-world candidate sites were selected from the Maryland State Highway Administration Mobility Report. Here, field data from each candidate site was input into the tool to illustrate the step-by-step process required for efficient planning of VSL or VSLRM control. The output of the tool includes the suggested control system at each site, a ranking of the sites based on the expected benefit-to-cost ratio, and guidelines on how to deploy the VSL signs, ramp meters, and detectors at the deployment site(s). This research has the potential to assist traffic engineers in the planning of VSL and VSLRM control, thus enhancing the procedure for allocating limited resources for mobility and safety improvements on highways plagued by recurrent congestion.

Optimizing last mile delivery using public transport with multiagent based control

The majority of research work carried out in the field of Operations-Research uses methods and algorithms to optimize the pick-up and delivery problem. Most studies aim to solve the vehicle routing problem, to accommodate optimum delivery orders, vehicles etc. This paper focuses on green logistics approach, where existing Public Transport infrastructure capability of a city is used for the delivery of small and medium sized packaged goods thus, helping improve the situation of urban congestion and greenhouse gas emissions reduction. It carried out a study to investigate the feasibility of the proposed multi-agent based simulation model, for efficiency of cost, time and energy consumption. Multimodal Dijkstra Shortest Path algorithm and Nested Monte Carlo Search have been employed for a two-phase algorithmic approach used for generation of time based cost matrix. The quality of the tour is dependent on the efficiency of the search algorithm implemented for plan generation and route planning. The results reveal a definite advantage of using Public Transportation over existing delivery approaches in terms of energy efficiency.

TRAFFIC IMPACT ANALYSIS OF SEVERAL DYNAMIC LANE MANAGEMENT STRATEGIES FOR CONGESTION MITIGATION BASED ON DTA MODEL

Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.

A second order control-volume finite-element least-squares strategy for simulating diffusion in strongly anisotropic media

An unstructured mesh �nite volume discretisation method for simulating di�usion in anisotropic media in two-dimensional space is discussed. This technique is considered as an extension of the fully implicit hybrid control-volume �nite-element method and it retains the local continuity of the ux at the control volume faces. A least squares function recon- struction technique together with a new ux decomposition strategy is used to obtain an accurate ux approximation at the control volume face, ensuring that the overall accuracy of the spatial discretisation maintains second order. This paper highlights that the new technique coincides with the traditional shape function technique when the correction term is neglected and that it signi�cantly increases the accuracy of the previous linear scheme on coarse meshes when applied to media that exhibit very strong to extreme anisotropy ratios. It is concluded that the method can be used on both regular and irregular meshes, and appears independent of the mesh quality.