Peak-period traffic congestion: A state-of-the-art analysis and evaluation of effective solutions

This paper reports on an analysis of a range of largely non-construction congestion reduction techniques which was funded by the U.S. National Cooperative Highway Research Program (NCHRP). A number of evaluations of the direct and indirect effec tiveness, costs, timing and feasibility of 22 major classes of promising techniques was performed. Based on this analysis, the study team evaluated 17 of these techniques as both effective and feasible in a U. S. institutional context.However, none of these 17 offered more than marginal reductions in peak-period traffic congestion when applied individually. Some techniques affected so small a percentage of travelers that reductions in congestion would not be discernible. Other techniques promised significant congestion reductions in theory but did not realize that promise in practice. It was concluded that many techniques could be implemented together with the potential for far greater combined effectiveness.An analysis was performed to determine how best to package or jointly implement promising techniques to optimize their combined effectiveness. It was found that all promising techniques could not be applied together because of conflicts in their impact. This analysis suggested eight sample packages or combinations of mutually supportive techniques. These eight packages were subjected to evaluations similar to those performed for individual techniques; while the packages are merely examples of potential combinations, the evaluation methodology employed should be of continuing use to local transportation planners.This paper was developed from NCHRP Report 169, Peak-Period Traffic Congestion, Options for Current Programs, and Peak-Period Traffic Congestion: State-of-the-Art and Recommended Research (NCHRP Agency Draft) By Robert Remak and Sandra Rosenbloom.This study was conducted under National Cooperative Highway Research Program Project 7/10. The opinions and findings expressed or implied in this paper are those of the author. They are not necessarily those of the Transportation Research Board, The National Academy of Sciences, the Federal Highway Administration, the American Association of State Highway and Transportation Officials, nor of the individual states participating in the National Cooperative Highway Research Program.On Leave to the U. S. Department of Transportation, Washington     

Traffic congestion and economic context: changes of spatiotemporal patterns of traffic travel times during crisis and post-crisis periods

Transportation - This paper aims to evaluate the impacts of the economic context on traffic congestion and its consequential effects on private vehicle accessibility. We conduct a long-term...     

基于收费站交通量及视频分析技术监测拥堵研究

随着我国汽车保有量的不断增长,高速公路收费站车辆拥堵的瓶颈问题越来越突出,对高速公路收费站的车辆拥堵情况及放行速度进行监测,对疏导交通、节约能源消耗及减少尾气排放有着重要的意义。本文从微波检测交通量及视频分析两个方面,阐述了利用交通量监测收费站车辆拥堵原理,利用智能视频技术自动对收费站车道上的车辆通行密度进行自动监测和预警。     

Empirical assessment of urban traffic congestion

This paper presents an empirical assessment of urban traffic congestion in Central London, UK. Compared with freeways or motorways, urban networks are relatively less studied because of its complexity and availability of required traffic data. This paper introduces the use of automatic number plate recognition technology to analyze the characteristic of urban traffic congestion in Central London. We also present the use of linear regression to diagnose the observed congestion and attribute them to different causes. In particular, we distinguish the observed congestion into two main components: one due to recurrent factors and the other due to nonrecurrent factors. The methodologies are illustrated through a case study of Central London Area. It is found that about 15% of the observed congestion in the region is due to nonrecurrent factors such as accidents, roadwork, special events, and strikes. Given the significance of London, the study will be valuable for transport policy evaluation and appraisal in other global cities. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulations of traffic congestion in Toronto

A traffic flow simulation program is used to estimate the external time costs that an additional vehicle using a congested city street imposes on other motorists on that street. The traffic flow on two street networks in Toronto is simulated for the morning rush hour and a mid-day period. After simulating the actual traffic load in these two periods, traffic volumes on individual streets were varied one at a time by one hundred vehicles per hour. The incremental delay to other vehicles from the addition of these vehicles is calculated by the program and the number of vehicle hours of delay per additional vehicle mile travelled is determined. Assuming a value of time for all motorists, the incremental external time cost attributed to the added traffic on each street in each direction during each of the two periods can be determined.The stimulated traffic variations show that the marginal external social cost of an added vehicle mile considering time costs alone ranges from zero on some roads to over one dollar per vehicle mile in the heavy direction in the morning rush hour. The average of this external congestion cost in the suburban area for inbound motorists in the morning period, weighted by the volume of traffic, was 38 cents per vehicle mile.This study demonstrates the usefulness of a traffic simulation program for estimating congestion costs, and identifies some problems inherent in previous empirical approaches to this problem.     

Simultaneous internalization of traffic congestion and noise exposure costs

This study elaborates on the interrelation of external effects, in particular road traffic congestion and noise. An agent-based simulation framework is used to compute and internalize user-specific external congestion effects and noise exposures. The resulting user equilibrium corresponds to an approximation of the system optimum. For traffic congestion and noise, single objective optimization is compared with multiple objective optimization. The simulation-based optimization approach is applied to the real-world case study of the Greater Berlin area. The results reveal a negative correlation between congestion and noise. Nevertheless, the multiple objective optimization yields a simultaneous reduction in congestion and noise. During peak times, congestion is the more relevant external effect, whereas, during the evening, night and morning, noise is the more relevant externality. Thus, a key element for policy making is to follow a dynamic approach, i.e. to temporally change the incentives. During off-peak times, noise should be reduced by concentrating traffic flows along main roads, i.e. inner-city motorways. In contrast, during peak times, congestion is reduced by shifting transport users from the inner-city motorway to smaller roads which, however, may have an effect on other externalities.     

Urban real-world driving traffic emissions during interruption and congestion

On-road emissions from urban traffic during interrupted and congested flow conditions are too high as compared to free-flow condition and often influenced by accelerating and decelerating speed due to frequent stop-and-go. In this study, we measured emissions from passenger cars and auto-rickshaws during peak and off-peak hours and analyzed according to different mileages with the instantaneous speed and acceleration for interrupted and congested traffic conditions. It was found that during flow, several short-events lasting over fractions of a second each lead to a sharp increase in pollutant emissions, indicating episodic conditions. The emission levels are sensitive to frequency and intensity of acceleration and deceleration, in accordance with the traffic-flow patterns and speed, besides mileages. Further, congestion conditions occur during both peak and off-peak hours, but last for different durations. The results are important in the sense that instantaneous estimates of pollutant emissions are necessary for the assessment of air quality in urban centers and for an effective traffic management plan.     

Induced traffic and economic appraisal

Economic appraisal of major roads in the UK is based on a set of standard procedures and conventions. A central assumption has been that the volume and pattern of traffic in any given year is independent of the quality of service offered by the network — the fixed trip matrix assumption. Failing to consider induced traffic can have serious consequences for the accuracy and robustness of the measured traffic benefits from road improvements. Assessment of the wider economic benefits of roads, which is an important political imperative for road investment, is also made more difficult. Two conclusions are reached. Variable trip matrix methods need to be introduced for the appraisal of major road schemes, and scheme appraisal needs to be complemented by a more strategic area-wide approach to evaluation. In responding to its advisory committee (SACTRA), the UK Department of Transport has accepted the first of these conclusions and is cautiously favourable to the second.     

Railroad noise: economic valuation and policy

In developed countries noise annoyance is an important source of environmental concern. Research on noise annoyance caused by railroad traffic is relatively underdeveloped. Here, a causal chain model is presented in which railroad traffic density, noise emission, noise immission and noise annoyance are causally related. Noise level, habituation and railroad usage are determinant factors. Noise annoyance causes social and economic costs, such as property value depreciation. Policy measures, aimed at reducing social and economic costs, are incorporated in various stages of the causal model. These measures can be subdivided into noise regulation and direct prevention measures. Stricter threshold values lead to higher total costs, but may lower social costs per capita. Economic feasibility of policy measures is usually analyzed by means of a cost-benefit case study. Methods of analysis used are diverse and ad hoc. Therefore, results of different case studies are not easily compared in terms of research synthesis.     

Reducing traffic congestion and increasing sustainability in special urban areas through one-way traffic reconfiguration

Transportation - In the contemporary sustainable urban set up, one of the critical issues adversely affecting the quality of life in urban areas and inflicting immense costs on cities is traffic...     

An integrated real-time traffic signal system for transit signal priority,incident detection and congestion management

This paper presents a traffic control system that can work standalone to handle various boundary conditions of the recurrent, non-recurrent congestion, transit signal priority and downstream blockage conditions to improve the overall traffic network vehicular productivity and efficiency. The control system uses field detectors’ data to determine the boundary conditions of all incoming and exit links. The developed system is interfaced with CORSIM micro-simulation for rigorous evaluations with different types of signal phase settings. The comparative performance of this control logic is quite satisfactory for some of the most frequently used phase settings in the network with a high number of junctions under highly congested conditions.     

Biofuel refinery location and supply chain planning under traffic congestion

This research focuses on planning biofuel refinery locations where the total system cost for refinery investment, feedstock and product transportation and public travel is minimized. Shipment routing of both feedstock and product in the biofuel supply chain and the resulting traffic congestion impact are incorporated into the model to decide optimal locations of biofuel refineries. A Lagrangian relaxation based heuristic algorithm is introduced to obtain near-optimum feasible solutions efficiently. To further improve optimality, a branch-and-bound framework (with linear programming relaxation and Lagrangian relaxation bounding procedures) is developed. Numerical experiments with several testing examples demonstrate that the proposed algorithms solve the problem effectively. An empirical Illinois case study and a series of sensitivity analyses are conducted to show the effects of highway congestion on refinery location design and total system costs.     

Tackling traffic congestion in Accra,Ghana: A road user's perspective

A fast emerging component of the urban transportation problem in cities of the Third World is the problem of traffic congestion. Rapid increases in car ownership coupled with poor land use planning, inadequate road space, lack of regulated parking systems, uneducated use of the road by pedestrians, and bad driving behavior of motorists have all combined to produce congestions comparable to those experienced in cities in the advanced parts of the world. Traffic management measures have been tried in some of the major cities such as road expansion and redistribution of land uses in city centers, but most have produced minimal results. It is recommended in this paper that city authorities adopt an integrated approach to congestion with emphasis on influencing the behavior of the road users.     

A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management

This paper describes , an innovative multi-agent architecture for the provision of real-time decision support to Traffic Operations Center personnel for coordinated, inter-jurisdictional traffic congestion management on freeway and surface street (arterial) networks. is composed of two interacting knowledge-based systems that perform cooperative reasoning and resolve conflicts, for the analysis of non-recurring congestion and the on-line formulation of integrated control plans. The two agents support incident management operations for a freeway and an adjacent arterial subnetwork and interact with human operators, determining control recommendations in response to the occurrence of incidents. The multi-decision maker approach adopted by reflects the spatial and administrative organization of traffic management agencies in US cities, providing a cooperative solution that exploits the agencies’ willingness to cooperate and unify their problem-solving capabilities, yet preserves the different levels of authority and the inherent distribution of data and expertise. The interaction between the agents is based on the functionally accurate, cooperative paradigm, a distributed problem solving approach aimed at producing consistent solutions without requiring the agents to have shared access to all globally available information. The cornerstone of this approach is the assumption that effective solutions can be efficiently obtained even when complete and up-to-date information is not directly available to the agents, thus reducing the need for complex data communication networks and synchronization time delays. The simulation-based evaluation of the system performance validates this assumption. The paper focuses on the distributed architecture of the agents and on their communication and decision making characteristics.     

The impact of congestion on traffic levels: The case of ferry transportation

A model which characterizes the passenger and vehicle demand for ocean transportation services is hypothesized and empirically tested using data for the British Columbia Ferry Corporation. An important feature of the problem, characteristic of many transportation modes, is the simultaneous interaction between congestion and the level of demand. A single equation model containing congestion as an explanatory variable is estimated as is a simultaneous model containing a demand function and the congestion function. Results of the two estimates are compared and it is concluded that the simultaneous equations model performs better.     

Identifying the onset of congestion rapidly with existing traffic detectors

From an operations standpoint the most important function of a traffic surveillance system is determining reliably whether the facility is free flowing or congested. The second most important function is responding rapidly when the facility becomes congested. These functions are complicated by the fact that conventional vehicle detectors are only capable of monitoring discrete points along the roadway while incidents may occur at any location on the facility. The point detectors are typically placed at least one-third of a mile apart and conditions between the detectors must be inferred from the local measurements.This paper presents a new approach for traffic surveillance that addresses these issues. It uses existing dual loop detector stations to match vehicle measurements between stations and monitor the entire roadway. Rather than expending a considerable effort to detect congested conditions, the research employs a relatively simple strategy to look for free flow traffic. Whenever a unique vehicle passes the downstream station, the algorithm looks to see if a similar vehicle passed the upstream station within a time window that is bounded by feasible travel times. The approach provides vehicle reidentification and travel time measurement on freeways during free flow and through the onset of congestion. If desired, other algorithms can be used with the same detectors to provide similar measurements during congested conditions. The work should prove beneficial for traffic management and traveler information applications, while promising to be deployable in the short term.     

Optimal tolls for multi-class traffic: Analytical formulations and policy implications

This paper puts together an analytical formulation to compute optimal tolls for multi-class traffic. The formulation is comprised of two major modules. The first one is an optimization component aimed at computing optimal tolls assuming a Stackelberg game in which the toll agency sets the tolls, and the equilibrating traffic plays the role of the followers. The optimization component is supported by a set of cost models that estimate the externalities as a function of a multivariate vector of traffic flows. These models were estimated using Taylor series expansions of the output obtained from traffic simulations of a hypothetical test case. Of importance to the paper is the total travel time function estimated using this approach that expresses total travel time as a multivariate function of the traffic volumes. The formulation presented in the paper is then applied to a variety of scenarios to gain insight into the optimality of current toll policies. The optimal tolls are computed for two different cases: independent tolls, and tolls proportional to passenger car equivalencies (PCE).The numerical results clearly show that setting tolls proportional to PCEs leads to lower values of welfare that are on average 15% lower than when using independent tolls, though, in some cases the total welfare could be up to 33% lower. This is a consequence of two factors. First, the case of independent tolls has more degrees of freedom than the case of tolls proportional to PCEs. Second, tolls proportional to PCEs do not account for externalities other than congestion, which is likely to lead to lower welfare values.The analytical formulations and numerical results indicate that, because the total travel time is a non-linear function of the traffic volumes, the marginal social costs and thus the optimal congestion tolls also depend on the traffic volumes for each vehicle class. As a result of this, for the relatively low volumes of truck traffic observed in real life, the optimal congestion tolls for trucks could indeed be either lower or about the same as for passenger cars. This stand in sharp contrast with what is implied in the use of PCEs, i.e., that the contribution to congestion are constant. This latter assumption leads to optimal truck congestion tolls that are always proportional to the PCE values.The comparison of the toll ratios (truck tolls divided by passenger car tolls) for both observed and optimal conditions suggests that the tolls for small trucks are about the right level, maybe a slightly lower than optimal. However, the analysis of the toll ratio for large trucks seems to indicate a significant overcharge. The estimates show that the average observed toll ratio for large trucks is even higher than the maximum optimal toll ratio found in the numerical experiments. This suggests that the tolls for large trucks are set on the basis of revenue generation principles while the passenger car tolls are being set based on a mild form of welfare maximization. This leads to a suboptimal cross-subsidization of passenger car traffic in detriment of an important sector of the economy.     

A piecewise-constant congestion taxing policy for repeated routing games

In this paper, we consider repeated routing games with piecewise-constant congestion taxing in which a central planner sets and announces the congestion taxes for fixed windows of time in advance. Specifically, congestion taxes are calculated using marginal congestion pricing based on the flow of the vehicles on each road prior to the beginning of the taxing window (and, hence, there is a time-varying delay in setting the congestion taxes). We motivate the piecewise-constant taxing policy by that users or drivers may dislike fast-changing prices and that they also prefer prior knowledge of the prices. We prove for this model that the multiplicative update rule and the discretized replicator dynamics converge to a socially optimal flow when using vanishing step sizes. Considering that the algorithm cannot adapt itself to a changing environment when using vanishing step sizes, we propose adopting constant step sizes in this case. Then, however, we can only prove the convergence of the dynamics to a neighborhood of the socially optimal flow (with the size of the neighbourhood being of the order of the selected step size). The results are illustrated on a nonlinear version of Pigou’s famous routing game.     

The evolution of urban traffic control: changing policy and technology

Abstract

The history of urban traffic control (UTC) throughout the past century has been a continued race to keep pace with ever more complex policy objectives and consistently increasing vehicle demand. Many benefits can be observed from an efficient UTC system, such as reduced congestion, increased economic efficiency and improved road safety and air quality.

There have been significant advances in vehicle detection and communication technologies which have enabled a series of step changes in the capabilities of UTC systems, from early (fixed time) signal plans to modern integrated systems. A variety of UTC systems have been implemented throughout the world, each with individual strengths and weaknesses; this paper seeks to compare the leading commercial systems (and some less well known systems) to highlight the key characteristics and differences before assessing whether the current UTC systems are capable of meeting modern transport policy obligations and desires.

This paper then moves on to consider current and future transport policy and the technological landscape in which UTC will need to operate over the coming decades, where technological advancements are expected to move UTC from an era of limited data availability to an era of data abundance.     

Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks

In this paper, we propose a new model for the within-day Dynamic Traffic Assignment (DTA) on road networks where the simulation of queue spillovers is explicitly addressed, and a user equilibrium is expressed as a fixed-point problem in terms of arc flow temporal profiles, i.e., in the infinite dimension space of time’s functions. The model integrates spillback congestion into an existing formulation of the DTA based on continuous-time variables and implicit path enumeration, which is capable of explicitly representing the formation and dispersion of vehicle queues on road links, but allows them to exceed the arc length. The propagation of congestion among adjacent arcs will be achieved through the introduction of time-varying exit and entry capacities that limit the inflow on downstream arcs in such a way that their storage capacities are never exceeded. Determining the temporal profile of these capacity constraints requires solving a system of spatially non-separable macroscopic flow models on the supply side of the DTA based on the theory of kinematic waves, which describe the dynamic of the spillback phenomenon and yield consistent network performances for given arc flows. We also devise a numerical solution algorithm of the proposed continuous-time formulation allowing for “long time intervals” of several minutes, and give an empirical evidence of its convergence. Finally, we carry out a thorough experimentation in order to estimate the relevance of spillback modeling in the context of the DTA, compare the proposed model in terms of effectiveness with the Cell Transmission Model, and assess the efficiency of the proposed algorithm and its applicability to real instances with large networks.