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Intelligent traffic light control (ITLC) aims to relieve traffic congestion. Some multi-agent deep reinforcement learning (MADRL) algorithms have been proposed for ITLC, and most of them use deep neural networks to make decisions. However, the abundant parameters of deep structure lead to the time-consuming training process of MADRL. Recently, a broad reinforcement learning (BRL) approach has been proposed to improve the efficiency of training for an agent. Unlike MADRL algorithms that use deep architecture, BRL utilizes a broad architecture. In this paper, we propose a multi-agent broad reinforcement learning (MABRL) algorithm for ITLC. The MABRL algorithm adopts the broad network to process the joint information and updates the parameters using ridge regression. To increase the effectiveness of interaction among agents, we design a dynamic interaction mechanism (DIM) based on the attention mechanism. The DIM enables agents to aggregate information on particular intersections at appropriate moments. We conduct experiments on three different datasets. The results demonstrate that the effectiveness of MABRL outperforms several state-of-the-art algorithms in alleviating traffic congestion with shorter training time. [ABSTRACT FROM AUTHOR]

Urban traffic congestion is not only an important cause of traffic accidents, but also a major hinder to urban development. By learning the historical traffic flow data, we can forecast the traffic flow of some regions in the future, which is of great significance to urban road planning, traffic management, traffic control and many more. However, due to the complex topology of traffic network and the diversity of influencing factors to traffic flow, the traffic modes are usually complicated and volatile, which makes traffic flow prediction very difficult. In this paper, we propose a new graph convolution neural network, namely Multi-mode Dynamic Residual Graph Convolution Network (MDRGCN), to capture the dynamic impact of different factors on traffic flow in a road network simultaneously. Firstly, we design a multi-mode dynamic graph convolution module (MDGCN), which is employed to capture the impact of different traffic modes by learning two types of relationship matrices. Then, we design a multi-mode dynamic graph convolution gated recurrent unit (MDGRU) to realize the combination of spatial and temporal dependences. Finally, we use a dynamic residual module (DRM) to integrate the orginal traffic data and the spatio-temporal features extracted by the MDGRU module to forecast the future traffic flow. Experimental reulsts conducted on the NYCTaxi and NYCBike datasets validate that the MDRGCN model performs better than the other eight baselines. [ABSTRACT FROM AUTHOR]

Traffic congestion is a global problem that cannot be solved by continuing to add new roads and extra capacity, which is accentuated in the areas where roads of unlimited-access (e.g. arterial streets) interface those of limited-access (e.g. freeways). Many researchers have addressed this problem but we present here a novel method to utilize a fuzzy logic model to reduce traffic congestion in such interfacing areas during saturated traffic conditions. More specifically this paper presents a control method for a complex traffic control system: Diverging Diamond Interchange (DDI) - Ramp Metering (RM), under oversaturated traffic conditions. The DDI is a relatively new concept of an alternative intersection geometry where two intersections serve left-turn movements without conflicts. However, such DDI left-turn movements, along with the right-turn movements from the opposite direction, put additional 'pressure' on the on-ramp of the freeways or multilane highways that intersect with DDIs. If freeway operations are saturated or near saturation, which may be the result of RM operations, this type of traffic control system can lead to a fully jammed condition with a potential spillback. The purpose of the proposed fuzzy-logic control is to prevent such a queue spillback from the metering ramp to the DDI. After presenting the fuzzy-logic control (FLC) model, we compare it to the conventional fixed time control (FTC) to evaluate potential benefits. To assess the quality of proposed analytical solutions in the real-traffic-like environment we evaluated the two logics in a VISSIM microsimulation model. The results show that, when compared to FTC, the FLC method improves traffic conditions moderately but in the oversaturated environment where there is very little room for improvement. [ABSTRACT FROM AUTHOR]

For the multi-agent traffic signal controls, the traffic signal at each intersection is controlled by an independent agent. Since the control policy for each agent is dynamic, when the traffic scale is large, the adjustment of the agent's policy brings non-stationary effects over surrounding intersections, leading to the instability of the overall system. Therefore, there is the necessity to eliminate this non-stationarity effect to stabilize the multi-agent system. A collaborative multi-agent reinforcement learning method is proposed in this work to enable the system to overcome the instability problem through a collaborative mechanism. Decentralized learning with limited communication is used to reduce the communication latency between agents. The Shapley value reward function is applied to comprehensively calculate the contribution of each agent to avoid the influence of reward function coefficient variation, thereby reducing unstable factors. The Kullback-Leibler divergence is then used to distinguish the current and historical policies, and the loss function is optimized to eliminate the environmental non-stationarity. Experimental results demonstrate that the average travel time and its standard deviation are reduced by using the Shapley value reward function and optimized loss function, respectively, and this work provides an alternative for traffic signal controls on multiple intersections. • A Shapley value reward function is used to encourage collaboration between agents. • Kullback-Leibler divergence eliminates the negative effects of previous experience. • The traffic congestion is reduced by a cooperative reinforcement learning method. [ABSTRACT FROM AUTHOR]

• This paper proposes the traffic system with mixed autonomous vehicles and human-driven vehicles. • This paper is the first to study the mixed traffic system from a micro perspective based on the cellular automation model. • An AV only need to gather the information for 5 vehicles in front of it. • Within a certain range of vehicle density, there is an optimal ratio of AVs at which the traffic system has the maximum average flow. • We obtain theoretical solutions of mixed critical vehicle density which are crucial to control the traffic networks. Autonomous vehicles (AVs) being an essential component of the future smart city traffic system is a hot topic in recent years, even though it is still in its development stage. It is conceivable that in the near future, AVs and human-driven vehicles (HVs) will have to co-exist in traffic systems. This is the first paper to study a mixed traffic system from a micro perspective based on the cellular automation model. In this system, by the use of sensors or mutual information exchange, each AV will have a 'foresight' and will be able to know the speeds and positions of vehicles in front of it. In the circular road scenario, we studied how the traffic capacity is influenced by the degree of foresight, the ratio of AVs to HVs, vehicle density, and the probability of random deceleration of HVs. Then we came up with the below conclusions: (a) The optimal foresight is k = 5. An AV only needs to gather the information of the 5 vehicles in front of it. (b) The two critical factors to measure the capacity of a traffic network are the critical vehicle density and the maximum average flow. When the ratio of AVs to HVs is increased, these two critical factors increase at an accelerating rate. (c) Even if a low ratio of HVs is running in the system, it will have an appreciable negative impact. An increased probability of random deceleration can expand the hysteresis loop range and reduce average flow. (d) Within a specific range of vehicle density, there is an optimal ratio of AVs at which the traffic system has the maximum average flow. This has implications in controlling the ratio of AVs. Finally, theoretical solutions of critical vehicle density are obtained by using the mean-field theory in physics. If the vehicle density is larger than these critical values, the traffic system will be in a deadlock state, and all vehicles cannot move. These formulas are crucial to controlling the density and the ratio of AVs and HVs in future intelligent traffic systems and will help to avoid large-scale traffic congestion. The above findings will have practical ramifications for precise traffic management and traffic control in a mixed AV and HVs system. [ABSTRACT FROM AUTHOR]

The article reports on the rising levels of traffic on U.S. roadways. The surge in road congestion is due to rising populations and increased car ownership. Heavy traffic can cause psychological distress, sleep deprivation and digestive problems as well as affecting leisure pursuits. Cities have attempted to counter the problem by building new roadways, raising tolls, and enhancing public transportation by bus, rail and subway. Automated traffic control systems are being developed and tested.

The article discusses technology in traffic engineering aimed at reducing congestion and making traffic flow more smoothly. In Los Angeles, California a system employing closed-circuit cameras and sensors has helped reduce automobile commuting times. A system being tested in Singapore involved the monitoring of traffic by roadway induction loops. Professor Carolina Osorio and colleagues at the Massachusetts Institute of Technology are testing a traffic-monitoring system they developed in Lausanne, Switzerland.

The article discusses the social impact of traffic congestion and efforts to relieve traffic as a development project, focusing on the example of Dhaka, Bangladesh. Topics include the infrastructure challenges of "megacities" in developing countries, the economic costs of traffic from delays, air pollution, and social capital, and the political complication of reforming the road system or developing public transportation.

Abstract Modern cities experience heavy traffic flows and congestions regularly across space and time. Monitoring traffic situations becomes an important challenge for the Traffic Control and Surveillance Systems (TCSS). In advanced TCSS, it is helpful to automatically detect and classify different traffic incidents such as severity of congestion, abnormal driving pattern, abrupt or illegal stop on road, etc. Although most TCSS are equipped with basic incident detection algorithms, they are however crude to be really useful as an automated tool for further classification. In literature, there is a lack of research for Automated Incident Classification (AIC). Therefore, a novel AIC method is proposed in this paper to tackle such challenges. In the proposed method, traffic signals are firstly extracted from captured videos and converted as spatial-temporal (ST) signals. Based on the characteristics of the ST signals, a set of realistic simulation data are generated to construct an extended large-scale traffic database to cover a variety of traffic situations. Next, a local mean filter is introduced to suppress the effect of noise and extract significant features from the ST signals. The extracted features are then associated with various types of traffic data: one normal type (inliers) and multiple abnormal types (outliers). For the classification, an adaptive boosting classifier is trained to detect outliers in traffic data automatically. Further, a Support Vector Machine (SVM) based method is adopted to train the model for identifying the categories of outliers. In short, this hybrid approach is called an Adaptive Boosting Support Vector Machines (AB-SVM) method. Experimental results show that the proposed AB-SVM method achieves a satisfied result with more than 92% classification accuracy on average. [ABSTRACT FROM AUTHOR]

Uninfluenced social systems often exhibit suboptimal performance; specially designed taxes can influence agent choices and thereby bring aggregate social behavior closer to optimal. A perfect system characterization may enable a planner to apply simple taxes to incentivize desirable behavior, but system uncertainties may necessitate highly sophisticated taxation methodologies. Using a model of network routing, we study the effect of system uncertainty on a designer's ability to influence behavior with financial incentives. We show that, in principle, it is possible to design taxes that guarantee that selfish network flows are arbitrarily close to optimal flows, despite the fact that agents’ tax sensitivities and the network topology are unknown to the designer. In general, these taxes may be large; accordingly, for affine-cost parallel-network routing games, we explicitly derive the optimal bounded tolls and the best-possible performance guarantee as a function of a toll upper bound. Finally, we restrict attention to simple fixed tolls and show that they fail to provide strong performance guarantees if the designer lacks accurate information about the network topology or user sensitivities. [ABSTRACT FROM AUTHOR]

The reports on the need for congestion zone in New York. It mentions the city has the worst traffic in America, average speed has decreased between 2010 and 2019 in the proposed zone. It also mentions to avoid paying tolls in Manhattan, lorries are likely to use the Cross-Bronx expressway, a congested motorway.

An interview with traffic expert, Jonas Eliasson is presented. When asked about public transportation and traffic jams with development of cities, he refers to narrowing of roads and increase in railroad traffic. He expresses his views on traffic planning and high traffic volume. He comments on sustainable transport solutions.

Travelers’ route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers’ route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model. [ABSTRACT FROM AUTHOR]

In November 2017, the delegated regulation 2017/1926 was forced into law. The member states are obliged to supply traffic data including their updating via a national access point (NAP) in order to make the same available to every mobility provider or directory inquiries. By using DELFI e.V., the technical and organizational preconditions to provide public transport data are created. [ABSTRACT FROM AUTHOR]

Presents a speech by C. Kenneth Orski, president of Urban Mobility Corp., delivered before the 22 Anniversary Luncheon of the Traffic Improvement Association of Oakland County in Bloomfield Hills, California, on November 3, 1989. Anecdotes describing the traffic congestion problem; Factors affecting perceptions on traffic congestion; Strategies for congestion management.

Discusses the technique of road pricing, one way of reducing traffic jams by charging motorists extra fees when they drive in congested city streets. Historical background on the emergence of the road pricing technique in Singapore and its applicability to the congested roads of the Western region; Key features of road pricing; Implications on efforts to solve the problem of traffic congestion.

The article addresses the cost of roadway congestion to the U.S. Topics include the Texas A&M Transportation Institute's "2012 Urban Mobility Report," how local transportation agencies cannot fully integrate traffic control strategies in their transportation system management and operations (TSM&O) frameworks, and the goals of the National Operations Center of Excellence whose framework stems from the Federal Highway Administration's (FHWA) Strategic Highway Research Program 2 (SHRP2).

Purpose -- Traffic congestion is becoming a serious problem that has adverse consequences on the socio-economy, environment, and public health of various cities worldwide. The purpose of this paper is to contribute to the continuous search for new alternative solutions to prevent or alleviate these concerns. It particularly deals with the development of decision support system based on a data fusion for the management and control of traffic at signalized intersections. The role of such systems is to manage the existing infrastructure to ease congestion and respond to crises. The proposed system is based on multi-detector data fusion, a data processing function that combines imperfect information collected from systems involving several detectors. The developed system is then tested on a virtual junction, and the results obtained are reported and discussed. Design/methodology/approach -- This paper presents a new traffic light control based on multi-detectors data fusion theory. The system uses a new multi-detectors data fusion method for traffic data analysis. Moreover, the system integrates a method for the estimation of the reliability degree of different detectors taking into account their imperfection and the conflict between them. These estimated reliability degrees are combined using Dempster's rule of combination. Findings -- The paper provides a decision support system for traffic regulation at intersection based on multi-sensors. It suggests the fusion of captured data by many sensors for measuring information. The system use the Belief Functions Theory for information fusion and decision making using combination and decision rules. Originality/value -- The paper proposes a new Adaptive Traffic Control System based on a new data fusion approach that include a method for the estimation of the reliability degree of different detectors taking into account their imperfection and the conflict between them. These estimated reliability degrees are combined using Dempster's rule of combination. [ABSTRACT FROM AUTHOR]

The article focuses on the results of the survey on active traffic management (ATM) in the U.S. published in National Cooperative Highway Research Program (NCHRP). It states that the survey provides an overview of state of practice related with designing, implementing, and operating ATM. It mentions that it focuses on strategies to manage traffic and congestion actively on arterials.

The article presents the author's views regarding rush hour commutes, transportation projects, and automobile traffic on U.S. highways including the New Jersey Turnpike as of 2013. Topics include conservative and liberal political views on government investments in transportation development; the effects of traffic jams on people's quality of life; and highway infrastructure and traffic engineering in the U.S.

The article discusses new strategies and supporting institutional arrangements to address congestion problems. Incident management, snow and ice advanced treatments, and appropriately timed traffic signals are cited as some cost-effective strategies that are quickly implemented with minimal disruptions. Aggressive transportation systems management and operations applications at the network operational level is suggested to be best at countering capacity loss due to congestion and disruptions.

The article discusses six projects initiated by the U.S. Federal Highway Administration (FHWA) to manage traffic congestion in U.S. highways. The U.S. Department of Transportation (DOT) sponsored the Congestion Reduction Demonstration (CRD) Initiative in Atlanta, Florida, Miami, Florida, Seattle, Washington and three other Urban Partners to relieve urban congestion. The Urban Partners implemented tolling and pricing strategies, transit strategies, telecommuting and technology strategies of multi-modal traveler information and enhanced traffic operations.

The article discusses the traffic situation in Moscow, Russia. The construction of the city, the influence of capitalism, and the increased availability of automobiles are examined. The roles of driver behavior, the traffic system, and the social system on the traffic situation are explored. The effect of traffic problems on the efficacy of emergency services is also discussed.

Abstract: In this paper, we study the effects of traffic light period in two-dimensional Biham–Middleton–Levine (BML) traffic flow model. It is found that a phase separation phenomenon, in which the system separates into coexistence of free flow and jam, could be observed in intermediate vehicle density range when traffic light period . We have explained the reason of occurrence of phase separation and investigated its behavior in different traffic light period. [Copyright &y& Elsevier]

The article reports on additional construction and widening of the Orange Crush interchange in Orange County, California. The goal of the construction planned by the Orange County Transportation Authority (OCTA) and the California Department of Transportation (Caltrans) is to lessen traffic congestion. Under the project, three new bridges will be built while 22 will be widened and retrofitted.

Abstract: Detection and recognition of the level of congestion at an intersection is a very important problem and a valuable source of information in traffic management. Although it is just one of all the aspects that make up a traffic management system, it seems to be a crucial point for gathering information. In this paper, we present a technique based on a k-means clustering algorithm for classification, which has been already successfully used in a number of pattern recognition problems, namely: as an algorithm for face recognition problems and in a number of medical diagnosis problems and it compares very well with the state of the art techniques. [Copyright &y& Elsevier]

Se trata el problema de la circulación en la Ciudad de México. Se asevera que el problema es debido en parte a la realización simultanea de varios proyectos importantes de construcción vial. Se informa que la aglomeración dura hasta 13 horas al día, según investigadores de la Universidad Nacional Autónoma de México (UNAM). Se sugiere que los problemas de circulación tienen un efecto negativo en el comercio en la ciudad.

The article focuses on the Central Artery/Tunnel project or Big Dig which was started in 1982 in Boston, Massachusetts. It highlights the benefits brought about by the project including the reduction of daily traffic congestion and air pollution and revitalization of commercial and residential activity as well as setbacks including cost escalation and fatalities. The project includes the construction of tunnels, freeways, viaducts and tollways and has cost more than $14.6 billion.

Abstract: Multifractality, present in traffic flow, usually connected with irregular scaling behavior and self-similarity. A multifractal spectrum is used to classify traffic behavior measurements. The width spread and the maximum of spectrum, two measures characterizing the spectrum of observations, are proposed as the distinguishing features among the samples. Data, observed on Beijing Yuquanying highway over a period of about 40 months, from January 16, 2001 to June 17, 2004, were used in the study. Analysis based on descriptive statistics is provided to obtain the statistical description of the inherited multifractality. The multifractal process was validated to be appropriate in the classification of the traffic flow. [Copyright &y& Elsevier]

The article focuses on the traffic congestion attributed to drive-through queue for coffee-and-doughnut store, Tim Hortons in Fredericton, New Brunswick. Topics covered include decision of some cities in Canada to introduce bylaws banning or limiting drive-throughs, proposal devised by Fredericton municipal traffic engineer Jon Lewis to address the demand for traffic efficiency in the location of drive-throughs, and reasons for modern urban planning's aversion to drive-throughs.

The article focuses on traffic congestion in nine of Canada's largest cities, which costs an estimated $3.7 billion a year in lost time and gas, according to a report released by federal Transportation Minister Lawrence Cannon. The lost productivity costs of small businesses which are not included in the estimate are discussed, as well as options for alleviating traffic. INSET: The ugly truth about free parking.

The article reports that a New Jersey highway project turns a traffic jam into an open space plan for neighboring residents. In the middle-1990s, the New Jersey Department of Transportation (NJDOT) recognized that the situation was unacceptable from the traffic, environmental and human perspective and undertook the Route 29 tunnel and its companion deck park project to ensure efficient traffic operations and improve the quality of life in the area. The Route 29 South Riverwalk Park, which has become the focal point of the Trenton waterfront, was constructed on the roof of a cut-and-cover tunnel section of Route 29. Landscape architects developed a series of arched structures, each designed to be evocative of the century it represents, and located in an octagonal area representing that century. In addition to NJDOT's Route 29 park, Trenton is performing planning, design and coordination services for a number of interrelated park projects along the Delaware River waterfront. These include a one-mile pedestrian path and bikeway, and reconstruction of an existing fishing wharf and park.

Provides information on the guidelines issued by the U.S. Federal Highway Administration on improving traffic simulation models to reduce traffic congestion and improve safety. Factors that need to be considered in defining traffic-related questions; Tips on establishing a traffic analysis team; Overview of traffic analysis tools.

Discusses the importance of establishing a traffic incident management. Impacts of incidents on traffic congestion and delay; Eight major disciplines that form the core constituency of traffic incident management; States in the U.S. that have used successful operational strategies as part of their traffic incident management programs. INSET: Who Are the Major Players in Traffic Incident Management?.

Provides an overview of strategies to mitigate traffic congestion in the U.S. as of November 2004. Characteristics of transportation agencies, according to the Federal Highway Administration; Technologies to improve transportation operations; Components of effective highway-based transportation. INSET: National Transportation Operations Coalition.

Presents a social, moral and environmental case for driving more. The impact of technology on traffic congestion; Author's attitude regarding his car; Advantages of automobiles; Perception of the car as one of history's greatest forces for good; Prevailing beliefs of Americans; Issue of pollution; Intellectuals' distaste for the car; Thoughts on the so-called car-culture war; View that many urbanites fled to the suburbs reluctantly.

Focuses on the traffic control system in Beijing, China. Average speed of motor vehicles in downtown Beijing; Causes of traffic congestion; Capacity of traffic police and wardens to effectively control traffic.

Provides information on the success of a road project in Indianapolis, Indiana dubbed as Hyperfix 65/70. Changes made in anticipation of the heavy traffic; Program launched to alleviate congestion and offer an alternative for commuters heading downtown; Role of media in the road project; Details of the construction process.

Focuses on the use of information technology to alleviate traffic congestion in the U.S. Disadvantages of traffic congestion; Factor associated with traffic congestion; Reason for the interest of politicians to maintain traffic congestion in areas important to them; Motivation for innovations in solving traffic congestion.

The article discusses research on predictive traffic routing, a technology that is envisioned to be a means for minimizing traffic delays overlooked by standard in-car navigation systems. Engineer Jeff Ban is cited regarding the technology and its assessment of likely changes in traffic patterns with time. Data requirements for the technology are discussed.

Reports on traffic congestion problems in the United States. Unpredictability of traffic which makes traffic problems hard to solve; Increase in the number of cars on the road while highway systems have not expanded; Discussion of onboard devices to avoid traffic jams.

The article deals with traffic engineering in the United States as opposed to Germany. Research by German theoretical physicists about traffic flow is discussed. The moving-gas model of traffic, in which cars are believed to behave like gas molecules, is presented. "Synchronized traffic" and several discoveries in chaos theory are also addressed.

The article reports that London, England has improved traffic congestion by imposing a fee on drivers who travel within the most heavily congested areas. The system uses cameras and prepaid fees, and has resulted in 20% less congestion in central London and 15% lower emissions. Profits from the system were used to fund public transit.

The article cites Houston, Texas, as an example of a city that builds more roads as a solution to traffic congestion, because surrounding land is cheap and open. Congestion has increased in Houston nonetheless, and remains a major concern for Houstonians. Solutions being tested by the city's mayor, Bill White, are noted.

Offers three solutions for congestion. Smart growth, a policy that encourages development that requires less dependence on cars; How tolls can be changed in response to congestion, encouraging people to carpool; So-called intelligent transportation systems, which generate up-to-the-minute traffic reports.

• A lattice hydrodynamic model under cyber-attacks and connected vehicle environment. • The stability condition is obtained based on the Hurwitz criteria and the H ∞ - norm. • A continuous delay feedback controller is designed to suppress traffic congestion. • The influences of the weight of cyber-attacks and delay time are investigated. • We explore how far ahead information about the downstream lattices should be integrated into the control process. The rapid adoption of sensors has improved the communication capacity of vehicles, while connected vehicles are expected to become commercially available in the near future. In a connected vehicle environment, the dynamic continuous kinetic information on roadway could be readily available through sensors and internet of vehicular technologies. Nevertheless, in practice the vehicular networks may suffer from cyber-attacks, such that the perceived traffic data can deviate from the actual situation. Such potential risks may greatly worsen traffic condition. There is increasing need for developing a framework to control traffic flow effectively using continuous traffic information under cyber-attacks and connected vehicle environment. In this study, we propose an extended lattice model incorporating not only multiple connected vehicles but also the continuous delay feedback control signals. The stability condition is obtained based on the Hurwitz criteria and the H ∞ - norm. We further devise a continuous delay feedback controller to regularize the propagation of the enhanced lattice model in the case when the stability condition is not satisfied. The Bode-plot of transfer function shows that the stability region enhances with the continuous delayed feedback controller. We study how far ahead information about the downstream lattices should be integrated into the control process. Results show that the continuous traffic information and the controller contribute to mitigating traffic jam. [ABSTRACT FROM AUTHOR]

Discusses the occurrence of traffic congestion. Advantages of traveling by car over that of a mass transit; Traffic paradoxes; Distinction between the private and the social costs of a trip.

Summarizes the study conducted by the Organization for Economic Co-operation and Development (OECD) on the worldwide state of the practice for traffic congestion control and demand management. Impact of traffic congestion; Causes of congestion; Relieving congestion through management; Categories of congestion management measures; Objectives and applications of congestion management measures; Policy recommendations.

Reports on the advantages of congestion pricing of roads. Congestion pricing as a way of easing vehicular traffic; Arguments against the constitutionality of congestion pricing; Highlights of the Transportation Research Board's 1994 report `Curbing Gridlock: Peak Period Fees to Relieve Traffic Congestion'; Equipment needed for congestion pricing.

The article contradicts the notion that traffic lights affect the traffic flow in New York City. Traffic lights have lessened congestion wherever they have been applied in the city. The traffic lights in the city are automatically operated which reduced labor cost to $3 per light signal. The placement of traffic signals is usually done after a survey of the scene by the officials of the police department.