Traffic Congestion Model Research Articles

Bottleneck model with heterogeneous information

This paper studies the effects of heterogeneous information on traffic equilibria and the resulting travel costs (both individual and social) when commuters make departure time choices to cross an unreliable bottleneck link. Increasing adoption and improved predictive abilities of Traveler Information Systems (TIS) enable commuters to plan their trips; however, there are inherent heterogeneities in information access and TIS accuracies. Our work addresses the open problem posed in Arnott et al. (1991) about the need to consider asymmetrically informed commuters in the bottleneck model of traffic congestion. We consider a Bayesian game with two heterogeneous commuter populations: one population is privately informed of the realized network state while the other only knows the public information about the distribution of states. We characterize the equilibrium of the game, in which each population chooses a departure rate function over time to minimize its expected cost based on its private belief about the state and the behavior of the other population. We provide a full equilibrium characterization for the complete range of values of link reliability, incident probability, and information penetration. The populations’ equilibrium strategies can broadly be categorized into two distinct regimes. Specifically, when information penetration is above a certain threshold, the populations’ equilibrium strategies are non-unique, and the relative Value of Information (VoI) is 0, i.e. the two populations face the same cost. On the other hand, when information penetration is below the threshold, equilibrium is unique, and VoI is positive and decreasing in information penetration. Importantly, we find that the lowest social cost is always achieved when a non-zero fraction of commuters are uninformed. The more unreliable the link, the higher the information penetration that achieves this minimum. We define the Value of Heterogeneity (VoH) as the difference between the minimum social cost and the cost under complete information penetration, and find that it can be significant under practically relevant conditions.

Real-time predication and navigation on traffic congestion model with equilibrium Markov chain

With the explosive growth of vehicles on the road, traffic congestion has become an inevitable problem when applying guidance algorithms to transportation networks in a busy and crowded city. In our study, the authors proposed an advanced prediction and navigation models on a dynamic traffic network. In contrast to the traditional shortest path algorithms, focused on the static network, the first part of our guiding method considered the potential traffic jams and was developed to provide the optimal driving advice for the distinct periods of a day. Accordingly, by dividing the real-time Global Positioning System data of taxis in Shenzhen city into 50 regions, the equilibrium Markov chain model was designed for dispatching vehicles and applied to ease the city congestion. With the reveals of our field experiments, the traffic congestion of city traffic networks can be alleviated effectively and efficiently, the system performance also can be retained.

Dynamical analysis of Lorenz System on traffic problem in Yogyakarta, Indonesia

The traffic congestion becomes a routine problem which occurs in Yogyakarta. This study was to develop a mathematical model of traffic congestion using Lorenz System. This system was used to analyze the traffic condition in Yogyakarta road. The data was taken from the observation of the road and it had been validated. Routh Hourwith used to analyse the stability of free jamm equlibrium. The dynamic analysis showed that the system was stabil. Numerical solution showed that the bigger value of ratio of the distance relaxsation time to velocity relaxsation time resulting the more time to reach the stabil condition. It showed that more and more time to reach optimal velocity, needed more and more time as well to reach equilibrium. Traffic condition at the time of observation was ideal and there was no transition of traffic jam.

Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions.

Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.

Congestion-aware route selection in automatic evacuation guiding based on cooperation between evacuees and their mobile nodes

When a large-scale disaster occurs, evacuees have to evacuate to safe places quickly. For this purpose, an automatic evacuation guiding scheme based on cooperation between evacuees and their mobile nodes has been proposed. The previous work adopts shortest-distance based route selection and does not consider the impact of traffic congestion caused by evacuation guiding. In this paper, we propose congestion-aware route selection in the automatic evacuation guiding. We first adopt a traffic congestion model where each evacuee’s moving speed on a road is determined by the population density of the road and his/her order among evacuees traveling in the same direction. Based on this congestion model, each evacuee’s mobile node estimates the cost, i.e., traveling time, of each road in the area. Each mobile node collects information about blocked road segments and positions of other evacuees through communication infrastructures or other mobile nodes. Based on the obtained information, it calculates and selects the smallest-cost route. Through simulation experiments, we show that the congestion-aware route selection can reduce both average and maximum evacuation times compared to the shortest-distance-based route selection, especially under highly congested situations. Furthermore, we show that the congestion-aware route selection can work well even under highly damaged situations where only direct wireless communication among mobile nodes is available.

Effect model of urban traffic congestion on driver’s lane-changing behavior

Road traffic congestion has become a normal state and caused many problems in large cities of China, and lane-changing model has attracted increased attention in recent years. This study is aimed t...

Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies

The macroscopic fundamental diagram (MFD) is introduced in recent studies to present the relationship between the flow and the density of the network in large urban regions (neighborhoods). The MFD can be also rescaled to approximate network outflow as a function of the vehicular accumulation of the system in the morning commute problem. In this research, we develop a bathtub model (macro-scale traffic congestion model) by combining Vickrey's (1969) model of dynamic congestion with the MFD to formulate the user equilibrium over the peak as an ordinary differential equation (ODE). This problem can be solved numerically to estimate the exact solution of the morning commute problem. Alternatively, the morning commute problem can be solved analytically by approximating the solution of the ODE using a well-behaved function. Here, we present a quadratic and also a linear approximation of the equilibrium solution for a semi-quadratic MFD, considering that the declining part of the MFD is shown to be well estimated by a quadratic function. To optimize the system, we present pricing strategies for network users (dynamic tolling) and employers inside the region (dynamic taxing) that can minimize the generalized cost of the system by keeping the outflow maximized over the peak. Finally, we compare the exact and the approximate solutions of the problem, and also the proposed pricing strategies of the region in a numerical example.

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Intelligent Transportation System Based Traffic Congestion Modeling for Urban Corridor

Inside the Queue: Hypercongestion and Road Pricing in a Continuous Time - Continuous Place Model of Traffic Congestion

This paper develops a continuous-time - continuous-place economic model of road traffic congestion with a bottleneck, based on car-following theory. The model integrates two archetype congestion technologies used in the economics literature: 'static flow congestion', originating in the works of Pigou, and 'dynamic bottleneck congestion', pioneered by Vickrey. Because a closed-form analytical solution of the formal model does not exist, its behaviour is explored using a simulation model. In a setting with endogenous departure time choice and with a bottleneck along the route, it is shown that 'hypercongestion' can arise as a dynamic - transitional and local - equilibrium phenomenon. Also dynamic toll schedules are explored. It is found that a toll rule based on an intuitive dynamic and space-varying generalization of the standard Pigouvian tax rule can hardly be improved upon. A naive application of a toll schedule based on Vickrey's bottleneck model, in contrast, appears to perform much worse and actually even reduces welfare in the numerical model.

Step by Step: Revisiting Step Tolling in the Bottleneck Model

In most dynamic traffic congestion models, congestion tolls must vary continuously over time to achieve the full optimum. This is also the case in Vickrey's (1969) 'bottleneck model'. To date, the closest approximations of this ideal in practice have so-called 'step tolls', in which the toll takes on different values over discrete time intervals, but is constant within each interval. Given the prevalence of step tolling schemes they have received surprisingly little attention in the literature. This paper compares two step-toll schemes that have been studied using the bottleneck model by Arnott, de Palma and Lindsey (1990) and Laih (1994). It also proposes a third scheme in which late in the rush hour drivers slow down or stop just before reaching a tolling point, and wait until the toll is lowered from one step to the next step. Such behaviour has indeed been observed in reality. Analytical derivations and numerical modelling show that the three tolling schemes have different optimal toll schedules and reduce total social costs by different percentages. These differences persist even in the limit as the number of steps approaches infinity. Braking lowers the welfare gain from tolling by 14% to 21% in the numerical example. Therefore, preventing or limiting braking seems important in designing step-toll systems.

Traffic Congestion Model: Challenges and Opportunities

This paper discusses models to detect traffic congestion using two approaches: road detection and moving object detection. There are two methods proposed to detect roads and moving objects. The methods involve the detection of both moving and non-moving objects. The system presented in this paper is able to detect roads as well as moving objects. However, further development is needed to detect extreme road curves. The system presented in this paper is relatively inexpensive since it only uses one camera and capable of capturing satisfactorily detailed images.

Congestion in the bathtub

This paper presents a model of urban traffic congestion that allows for hypercongestion. Hypercongestion has fundamental importance for the costs of congestion and the effect of policies such as road pricing, transit provision and traffic management, treated in the paper. In the simplest version of the model, the unregulated Nash equilibrium is also the social optimum among a wide range of potential outcomes and any reasonable road pricing scheme will be welfare decreasing. Large welfare gains can be achieved through road pricing when there is hypercongestion and travelers are heterogeneous.

Trip-timing decisions and congestion with household scheduling preferences

Most traffic congestion models assume that agents make trip-timing decisions independently and receive payoffs at the origin and destination that do not depend on whether other agents are present. We depart from this paradigm by considering a variant of Vickrey׳s bottleneck model of the morning commute in which individuals live as couples and value time at home more when together than when alone. We show that the costs of congestion can be higher than for a comparable population of individuals living alone. The costs can be even higher if spouses collaborate with each other when choosing their departure times. To calibrate the model we estimate trip-timing preferences for married and unmarried men and women in the Greater Paris region.

Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

Intelligent Transportation System (ITS) technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

Models on Real-Time State Identification for Unban Traffic Based on Fixed Detector

For the advantages and disadvantages of the traffic state identification based on fixed detector, a kind of method on the real-time state identification for the unban traffic was presented in order to improve accuracy and practical level of the traffic state identification. From analysis on detectors distribution and data collection methods, this paper carried out data preprocessing which collected from fixed detectors, then established the identification methods and thresholds for traffic state, developed the evaluation models of urban traffic congestion. Finally, the practicality of models was validated according to the traffic data collected by fixed detectors on typical roads in Qingdao city. The results show that the traffic state identification of the models is effective and with high precision.

Curbside parking time limits

Previous work in the economic theory of parking has treated parkers as homogeneous. In almost all policy contexts, however, heterogeneity among individuals matters not only quantitatively but also qualitatively. For example, providing both tolled and untolled alternatives allows those with high values of time to pay largely with money and those with low values of time to pay only with time. This paper extends the authors’ (2009) integrated model of parking and traffic congestion in an isotropic downtown in steady state to treat heterogeneity in the value of time and parking duration. It develops the theory, and then presents an extended numerical example that applies the theory to several policy scenarios. With homogeneous individuals, underpricing curbside parking leads to wasteful cruising for parking. With heterogeneous individuals, however, curbside time limits can be used to ration out those with longer parking durations, so that cruising for parking is eliminated. With curbside parking time limits, underpricing curbside parking downtown may be a sound policy response to the free parking provided by suburban shopping centers.

The Research of Clock Traffic Congestion Model and Synchronization Technology

Considering the limited bandwidth, delay and the flow of mutual association, the greater the flow, the delay lags the more obvious; when flow close to saturation, delay will become very serious. According to the PTP local clock offset correction mechanism; this paper proposed an adaptive routing algorithm based on through node flow congestion forecast message. The method based on least squares support vector machine on the discharge time series online regression estimate future period of time clock node network flow value, from this investigation clock node congestion degree index, so the choice of adaptability PTP since the minimum delay routing, improve the synchronous message delivery success rate, reduce the complex network of synchronous accuracy vulnerable data flow congestion hysteresis effect.

A bathtub model of downtown traffic congestion

In standard economic models of traffic congestion, traffic flow does not fall under heavily congested conditions. But this is counter to experience, especially in the downtown areas of major cities during rush hour. This paper analyzes a bathtub model of downtown rush-hour traffic congestion that builds on ideas put forward by William Vickrey. Water flowing into the bathtub corresponds to cars entering the traffic stream, water flowing out of the bathtub to cars exiting from it, and the height of water in the bathtub to traffic density. Velocity is negatively related to density, and outflow is proportional to the product of density and velocity. Above a critical density, outflow falls as density increases (traffic jam situations). When demand is high relative to capacity, applying an optimal time-varying toll generates benefits that may be considerably larger than those obtained from standard models and that exceed the toll revenue collected.

Traffic Congestion Estimation for Short-Highway in Pre- Timed Systems

developed traffic congestion estimation model for highway by using only flow rate and average velocity in each minute from a single CCTV camera which is installed in the middle of the road without using traffic signal data or departure- flow rate on the pre-timed system. However, the model could only predict traffic congestion on un-congested condition, but could not predict traffic congestion on congested condition. Hence, so far to the best of our knowledge, traffic congestion estimation on highway requires at least two type of raw data, one is the data from a CCTV camera which some work requires at least two cameras and the others is traffic signal data or departure-flow rate. Although, Buranasing and Prayote attempted to develop traffic congestion model for highway by using only a single camera for saving cost, but the model could not predict traffic congestion on congested condition. Therefore, in this paper, the proposed model are able to estimate traffic congestion on short-highway by using only average velocity from a single camera which is installed at the beginning of the road by without using traffic signal data or departure-flow rate on the pre-timed system and the model are also able to predict traffic congestion in any traffic condition (both congested and un-congested condition). This paper is organized into the following sections: Section II simulation software and experiment setting. Equivalent queue length estimation model in Section III. Characteristic of CCTV's velocity in Section IV. Velocity and congestion model in section V. Traffic congestion estimation model and performance in section VI and a conclusion and remark is drawn in section VII.