Showing papers on "Traffic wave published in 2013"

Short term traffic flow prediction in heterogeneous condition using artificial neural network

Abstract: Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea to avoid traffic instabilities and to homogenize traffic flow in such a way that risk of accidents is minimized and traffic flow is maximized. There is a need to predict traffic flow data for advanced traffic management and traffic information systems, which aim to influence traveller behaviour, reducing traffic congestion and improving mobility. This study applies Artificial Neural Network for short term prediction of traffic volume using past traffic data. Besides traffic volume, speed and density, the model incorporates both time and the day of the week as input variables. Model has been validated using actual rural highway traffic flow data collected through field studies. Artificial Neural Network has produced good results in this study even though speeds of each category of vehicles were considered separately as input variables.

Traffic dynamics in empirical probe vehicle data studied with three-phase theory: Spatiotemporal reconstruction of traffic phases and generation of jam warning messages

Abstract: Empirical and theoretical analyses of the spatiotemporal dynamics of traffic flow reconstructed from randomly distributed probe vehicle data are presented. For the empirical analysis, probe vehicle data generated by TomTom’s navigation devices in the commercial TomTom’s HD-traffic service as well as road detector data measured at the same road section are used. A stochastic microscopic (car-following) three-phase model is further developed for simulations of a real empirical complex spatiotemporal traffic dynamics measured over a three-lane long road stretch with several different bottlenecks. Physical features and limitations of simulations of real spatiotemporal traffic dynamics are revealed. Phase transition points between free flow (F), synchronized flow (S), and wide moving jam (J) are identified along trajectories of empirical and simulated probe vehicles randomly distributed in traffic flow. As predicted by three-phase theory, the empirical probe vehicle data shows that traffic breakdown is an F → S transition and wide moving jams emerge only in synchronized flow, i.e., due to S → J transitions. Through the use of the simulations, it has been found that already about 2% of probe vehicle data allows us to reconstruct traffic dynamics in space and time with an accuracy that is high enough for most applications like the generation of jam warning messages studied in the article.

Increasing the Capacity of Signalized Intersections with Dynamic Use of Exit Lanes for Left-Turn Traffic

Abstract: Many congested intersections have a heavy traffic volume on movements for which capacity is insufficient because of geometric limitations. An unconventional approach that increases the capacity of heavily congested intersections is presented: this approach opens up exit lanes for left-turn traffic dynamically with the help of an additional traffic light installed at the median opening (the presignal); this situation is referred to as exit lanes for left-turn (EFL) control. An optimization problem for EFL control was formulated as a mixed-integer nonlinear program, in which the geometric layout, main signal timing, and presignal timing were integrated. The mixed-integer nonlinear program was solved by transformation into a series of mixed-integer linear programs. The latter problem can be solved with the standard branch-and-bound technique. The results of extensive numerical analysis and VISSIM simulation showed that the EFL approach could increase intersection capacity and reduce traffic delay substantial...

A general theory of traffic movement

Abstract: This paper seeks to put forth a simple theory on traffic movement that explains origin and destination of various trip types in urban areas. To construct this theory, the author considers trip frequency, trip destination, and mode of travel. He suggests that the theory described is particularly useful for estimating traffic volumes and estimating required street patterns in undeveloped areas.

A microscopic lane changing process model for multilane traffic

Abstract: In previous simulations lane-changing behavior is usually assumed as an instantaneous action. However, in real traffic, lane changing is a continuing process which can seriously affect the following cars. In this paper, a microscopic lane-changing process (LCP) model is clearly described. A new idea of simplifying the lane-changing process to the car-following framework is presented by controlling fictitious cars. To verify the model, the results of flow, lane-changing frequency, and single-car velocity are extracted from experimental observations and are compared with corresponding simulation. It is found that the LCP model agrees well with actual traffic flow and lane-changing behaviors may induce a 12%–18% reduction of traffic flow. The results also reflect that most of the drivers on the two roads in a city are conservative but not aggressive to change lanes. Investigation of lane-changing frequency shows that the largest lane-changing frequency occurs at a medium density range from 15 vehs km − 1 lane − 1 to 35 vehs km − 1 lane − 1 . It also implies that the lane-changing process might strengthen velocity variation at medium density and weaken velocity variation at high density. It is hoped that the idea of this study may be helpful to promote the modeling and simulation study of traffic flow.

Lane change assistant for optimizing the traffic flow (traffic flow assistant)

Abstract: A device for a traffic flow assistant for a vehicle includes a surroundings sensor system, which recognizes traffic-relevant objects on a traffic lane, on which the vehicle is traveling, and on at least one further adjacent lane, gaps in the traffic are recognized with the aid of the surroundings sensor system and vehicle-dynamic parameters of the objects are determined and future gaps in the flow of traffic are able to be predicted therefrom. For these recognized gaps and predicted gaps, lane change options are ascertained and, from this and the present and/or predicted presence of gaps in the traffic suitable for changing lanes and the vehicle-dynamic state of the vehicle, a signal for the lane selection is generated, which is dependent on the lane change options and an optimization strategy.

Suppressing traffic flow instabilities

Abstract: While many models of traffic flow predict the instabilities commonly observed-particularly at higher traffic densities-there are few suggestions for suppressing them. A method is described here for suppressing instabilities, thereby reducing gas consumption, accidents, wear and tear on vehicles and roadways as well as travel times while increasing traffic throughput. The method uses information about the following vehicle as well as the leading vehicle. Using information from both sources allows the gain of feedback to be reduced below one, thus eliminating the instability characteristic of “car following.” The needed inputs to the control system can be provided by machine vision (or radar or lidar). Previous proposals for smoothing traffic flow instabilities do not use information about the vehicles behind-“car following” cruise control methods, for example, focus only on the vehicle ahead. The method presented here is based on information flowing both downstream and upstream, in distinction to traditional approaches where information flows only upstream.

Generated Traffic and Induced Travel

Abstract: Traffic congestion tends to maintain equilibrium. Congestion reaches a point at which it constrains further growth in peak-period trips. If road capacity increases, the number of peak-period trips also increases until congestion again limits further traffic growth. The additional travel is called “generated traffic.” Generated traffic consists of diverted traffic (trips shifted in time, route and destination), and induced vehicle travel (shifts from other modes, longer trips and new vehicle trips). Research indicates that generated traffic often fills a significant portion of capacity added to congested urban road. Generated traffic has three implications for transport planning. First, it reduces the congestion reduction benefits of road capacity expansion. Second, it increases many external costs. Third, it provides relatively small user benefits because it consists of vehicle travel that consumers are most willing to forego when their costs increase. It is important to account for these factors in analysis. This paper defines types of generated traffic, discusses generated traffic impacts, recommends ways to incorporate generated traffic into evaluation, and describes alternatives to roadway capacity expansion.

Synchronized flow in oversaturated city traffic.

Abstract: Based on numerical simulations with a stochastic three-phase traffic flow model, we reveal that moving queues (moving jams) in oversaturated city traffic dissolve at some distance upstream of the traffic signal while transforming into synchronized flow. It is found that, as in highway traffic [Kerner, Phys. Rev. E 85, 036110 (2012)], such a jam-absorption effect in city traffic is explained by a strong driver's speed adaptation: Time headways (space gaps) between vehicles increase upstream of a moving queue (moving jam), resulting in moving queue dissolution. It turns out that at given traffic signal parameters, the stronger the speed adaptation effect, the shorter the mean distance between the signal location and the road location at which moving queues dissolve fully and oversaturated traffic consists of synchronized flow only. A comparison of the synchronized flow in city traffic found in this Brief Report with synchronized flow in highway traffic is made.

Proportion of Vehicles Moving Freely Depending on Traffic Volume and Proportion of Trucks and Buses

Abstract: Adequate description of traffic in all intersections where traffic is not controlled by traffic lights is substantially affected by the adopted model of proportion of vehicles which move freely in traffic flow. The present study attempts to evaluate the proportion of vehicles moving freely in traffic flow depending on traffic volume and the effect of proportion of trucks and buses on this parameter. The analyses were carried out with an example of flows of vehicles moving in small roundabouts. It was observed based on the results of the analyses that the proportion of vehicles moving freely in traffic flow depending on traffic volume is best characterized by a spline, composed of three components which include quasifree traffic, uniform traffic and non-uniform traffic.

Visco‐elastic traffic flow model

Abstract: SUMMARY To increase our understanding of the operations of traffic system, a visco-elastic traffic model was proposed in analogy of non-Newtonian fluid mechanics. The traffic model is based on mass and momentum conservations, and includes a constitutive relation similar to that of linear visco-elastic fluids. The further inclusion of the elastic effect allows us to describe a high-order traffic model more comprehensively because the use of relaxation time indicates that vehicle drivers adjust their time headway in a reasonable and safe range. The self-organizing behaviour is described by introducing the effects of pressure and visco-elasticity from the point of view in fluid mechanics. Both the viscosity and elasticity can be determined by using the relaxation time and the traffic sound speed. The sound speed can be approximately represented by the road operational parameters including the free-flow speed, the jam density, and the density of saturation if the jam pressure in traffic flows is identical to the total pressure at the flow saturation point. A linear stability analysis showed that the traffic flow should be absolutely unstable for disturbances with short spatial wavelengths. There are two critical points of regime transition in traffic flows. The first point happens at the density of saturation, and the second point occurs at a density relating on the sound speed and the fundamental diagram of traffic flows. By using a triangular form flow–density relation, a numerical test based on the new model is carried out for congested traffic flows on a loop road without ramp effect. The numerical results are discussed and compared with the result of theoretical analysis and observation data of traffic flows. Copyright © 2011 John Wiley & Sons, Ltd.

Vehicle-class specific control of freeway traffic

Abstract: The increase of mobility of the past decades has led to substantial congestion on the freeways. Traffic jams emerge both on a daily basis at the same location, as well as during accidents when a part of the freeways is temporarily blocked. In those cases, traffic management centers intervene into traffic in order to reduce or even dissolve congestion. This is called Dynamic Traffic Management (DTM). Common DTM measures are rerouting traffic, ramp metering at the on-ramps of freeways and opening peak-hour lanes. DTM is performed in two steps. First, the current traffic state is estimated by fusing sensor data, usually from dual-inductive loops or from in-car sensors. The traffic state describes where the traffic is located in the network and how fast it travels. Second, based on the current traffic state, a controller determines appropriate actions for each DTM measure in order to improve the traffic performance. In current practice, DTM controls traffic as a whole, not differentiating between the different vehicle classes. However, vehicles can be classified according to length, maximum speed or value of time. The vehicle classes therefore have different effects on the network performance. For example, short vehicles can travel with a shorter time headway than longer ones. Consequently, more short vehicles can pass any given location than long one. The capacity for shorter vehicles is therefore larger than for long ones. In this thesis, Dynamic Traffic Management is generalized to take the properties of different vehicle classes into account. The effects of the vehicle classes on the traffic flow and the network performance are analyzed based on the macroscopic multi-class traffic flow model Fastlane. Furthermore, existing DTM measures are generalized in order to control traffic vehicle-class specifically. A multi-class ramp meter is developed that is able to meter each vehicle class individually. Prioritizing short vehicles increases the network throughput; conversely, prioritizing valuable vehicles decreases the total cost. Multi-class route guidance enables the routing of a vehicle class around a congested area. At bottleneck locations, a class-specific lane makes it possible to keep a specified vehicle class in free-flow. In order to apply DTM in real-time, two existing traffic state estimators are analyzed and reformulated so that they now estimate the traffic state of realistically-size freeways within a few seconds. The Adaptive Smoothing Method is reformulated to use the Fast Fourier Transform. The Extended Kalman Filter technique is localized so that measurements are used to correct the system state only in the vicinity of the measurement instead of correcting the state of the whole network. Furthermore, a tool is developed that extracts the position and speed of shock waves from spatiotemporal traffic data, which are used to calibrate traffic state estimators or traffic flow models. The developed components of estimation and control are then combined in a case study to optimize class-specific control advices for the Dutch freeway A15 near the harbor of Rotterdam. The case study shows that multi-class DTM improves the network performance compared to conventional, mixed-class DTM. Currently, those control advices are calculated continuously and are published at a website in real-time. In addition, the current traffic state, the future traffic for the next hour without control, and the future traffic with multi-class control are published.

Modelling Mixed Traffic Flow at Signalized IntersectionUsing Social Force Model

Abstract: It is urgent to understand the traffic performance by modelling traffic streams under mixed traffic conditions, in which motorcycles contribute to a dominant rate of the total traffic composition. This study aims to analyze the interactions between the left-turn and the opposite straight-through vehicles and estimate the capacity of both flows. An attempt is made to develop a social force model for the vehicles. The result indicates that the social force model is an appropriate approach to model the mixed traffic flow at signalized intersections. The study also outlines various aspects of integrating such a model into the existing methods for microscopic traffic flow simulation and capacity analysis.

An extended macroscopic model for traffic flow on a highway with slopes

Abstract: In this paper, we present an extended car-following model with consideration of the gravitational force. A new macroscopic model taking into account the slope effects is developed using the relationship between the microscopic and macroscopic variables. The proposed model is applied to reflect the effect of the slope on uniform flow, traffic waves and small perturbation. The simulation results demonstrate that both the angle and the length of the slope have important impacts on traffic flow. The effect of the slope becomes more significant with the increase of the slope angle.

An instantaneous kinematic wave theory of diverging traffic

Abstract: Diverging junctions are an important type of bottlenecks, which can reduce capacities and initiate and propagate traffic congestion in a road network. In this paper, we propose a kinematic wave theory for modeling dynamics of non-cooperative diverging traffic, in which traffic dynamics of vehicles to one direction are assumed to be independent of those to other directions instantaneously. During a short time interval, the kinematic wave model of diverging traffic is decoupled into a number of nonlinear resonant systems. From analytical solutions to the Riemann problem of a decoupled system, a new definition of partial traffic demand is introduced, so that diverging flows can be easily computed with the supply-demand method. Then a Cell Transmission Model is proposed to solve the kinematic wave model of diverging traffic by taking into account of the interactions among different traffic streams. Simulation results demonstrate that vehicles follow the First-In-First-Out principle in the long run, and the model converges when we decrease the cell and time-step sizes. In addition, it is shown that traffic streams to different directions segregate in a selfish manner, and the total throughput of a diverging junction is not maximized as in existing diverge models. In the future, more theoretical and empirical studies are needed for a better understanding of this and other diverge models.

Evaluation of Variable Speed Limit under Connected Vehicle environment

Abstract: The Variable Speed Limit (VSL) application provides travelers with dynamic speed advisory information to keep optimal traffic flow conditions for freeways and corridors under both recurrent and non-recurrent congestion incurred by incidents and/or work-zones. By coupling VSL and Connected Vehicle (CV) environment enabling two-way wireless communications for vehicle-to-vehicle and vehicle-to-infrastructure, it is expected to achieve improved performance of VSL as a viable traffic congestion mitigation tool. This digest paper presents the impact of connected vehicle on the effectiveness of VSL on a freeway bottleneck section by using a microscopic simulation model. Simulation experimental results show that CV-powered VSL improves the traffic congestion conditions up to 7-12% depending on CV market penetration rates.

Autonomous road surveillance system: A proposed model for vehicle detection and traffic signal control

Abstract: Traffic Signal Light (TSL) can be optimized using vehicle flow statistics obtained by the developed Autonomous Road Surveillance System (ARSS). This research proposes an efficient traffic control system by detecting and counting the vehicle numbers at various times and locations. At present, one of the biggest problems in the main cities in many countries are the traffic jam during office hour and office break hour. Sometimes it can be seen that the traffic signal green light is still ON even though there is no vehicle on road. Similarly, it is also observed that long queues of vehicles are waiting even though the road is empty due to inefficient traffic control system. This is due to TSL selection without proper investigation on vehicle flow. This can be handled by adjusting TSL timing proposed by the developed ARSS. A number of experimental results of vehicle flows are discussed in this research in order to test the feasibility of the developed system. Finally, several advantages and features of ARSS are discussed in successfully implementing the developed system in order to reduce traffic jam in big cities and towns as well as other necessary places.

The comfortable driving model revisited: Traffic phases and phase transitions

Abstract: We study the spatiotemporal patterns resulting from different boundary conditions for a microscopic traffic model and contrast it with empirical results. By evaluating the time series of local measurements, the local traffic states are assigned to the different traffic phases of Kerner's three-phase traffic theory. For this classification we use the rule-based FOTO-method, which provides `hard' rules for this assignment. Using this approach, our analysis shows that the model is indeed able to reproduce three qualitatively different traffic phases: free flow (F), synchronized traffic (S), and wide moving jams (J). In addition, we investigate the likelihood of transitions between the three traffic phases. We show that a transition from free flow (F) to a wide moving jam (J) often involves an intermediate transition; first from free flow F to synchronized flow S and then from synchronized flow to a wide moving jam. This is supported by the fact that the so called F->S transition (from free flow to synchronized traffic) is much more likely than a direct F->J transition. The model under consideration has a functional relation between traffic flow and traffic density. The fundamental hypothesis of the three-phase traffic theory, however, postulates that the steady states of synchronized flow occupy a two-dimensional region in the flow-density plane. Due to the obvious discrepancy between the model investigated here and the postulate of the three-phase traffic theory, the good agreement that we found could not be expected. For a more detailed analysis, we also studied the vehicle dynamics at a microscopic level and provide a comparison of real detector data with simulated data of the identical highway segment.

A novel method based on VANET for alleviating traffic congestion in urban transportations

Abstract: The traffic congestion frequently occurs in urban transportations. In order to alleviate the traffic congestion, the vehicle information and communication system (VICS) has been developed. However, since each vehicle can obtain global information on traffic congestion using VICS, all vehicles in the congested areas tend to move to non-congested areas. As a result, the non-congested areas become congested areas. To avoid such the oscillation between the congested and non-congested areas, this paper proposes a novel method based on the vehicle ad hoc network (VANET) for alleviating traffic congestion in urban transportations. In the proposed method, since each vehicle independently collects local information on traffic congestion using VANET, traffic can be distributed from congested areas to non-congested areas. Through simulation experiments, this paper shows that the proposed method provides faster velocity and shorter trip time than VICS in the environments that traffic varies temporally and spatially, which occur in urban transportations.

Optimization method for signal coordination control of urban road intersections under over-saturation condition

Abstract: The invention discloses an optimization method for signal coordination control of urban road intersections under an over-saturation condition. Compared with the prior art, based on analysis of upstream and downstream traffic stream states of adjacent intersections, through using the wave theory for reference, and by comparing sizes of stop waves of upstream intersections and start waves of downstream intersections as well as vehicle queue conditions of upstream intersections in an artery direction, status values of signal control intersections are determined, and the signal coordination control reliable interval (phase difference) under different states is obtained, accordingly, queue overflow of over-saturation intersections can be controlled within a certain range, the probability of deadlocks at the over-saturation intersections can be reduced greatly, and the queue overflow becomes beneficial self-adjustment of the road intersections under the over-saturation condition.

A traffic light extension to Cell Transmission Model for estimating urban traffic jam

Abstract: Urban traffic congestions have become a financial and societal burden in many cities. Efficient traffic management solutions mitigating such congestions require a reliable modeling and estimation of traffic jams. In urban traffic, the modeling challenges are related to flow collisions and gridlocks created at intersections. In this paper, we propose a traffic light extended Cell Transmission Model (CTM), where the influence of flow collisions and gridlocks are modeled by a single CK parameter. Our approach only requires adapting CK for each intersection type/geometry instead of a complex mathematical formulae proposed in related works. We formalize the description of our urban CTM, and evaluate its capability to model traffic volumes and jams against the microscopic traffic simulator SUMO (Simulation of Urban MObility). Results show that the CK parameter is able to closely reproduce the impact of collisions and gridlocks on traffic jam, making the proposed urban CTM suitable to predict traffic congestions in urban environments.

Microscopic traffic behaviour modelling and simulation for lane-blocking arterial incidents

Abstract: Incident-induced driver behaviour modelling is essential to analyse non-recurrent traffic congestion problems However, such research is inadequate in such areas as traffic flow prediction, traffic simulation and incident management This article presents microscopic lane traffic models to characterise incident-induced driver behaviour including car following and lane changing conducted under conditions of lane-blocking arterial incidents To demonstrate the validity of the proposed models, a specific microscopic traffic simulation program embedded with the proposed incident-induced lane traffic behaviour models is tested by comparing simulation data with video-based incident data collected from five incident events Preliminary test results indicate that the proposed microscopic traffic behaviour models permit not only reproducing incident-induced traffic behaviour but also characterising incident effects on lane traffic phenomena

Traffic breakdowns and freeway capacity as extreme value statistics

Abstract: An analysis of traffic volume time series for dense traffic shows traffic breakdowns, which can be sorted by the frequency of breakdowns dependent on the traffic volume at the beginning of the breakdown. From this empirical breakdown a probability can be extrapolated and breakdowns can be described as extreme events. Three different traffic situations can be distinguished: (a) stable traffic flow where any fluctuations decay over time, (b) metastable traffic flow where fluctuations neither decay nor grow, and (c) unstable traffic flow where a breakdown can be expected with certainty, if a reasonable observation time is provided. The results open new insights in probabilistic description and prognosis of the traffic break-downs. They lead directly to the probabilistic definition of the capacity as a traffic volume leading to an unstable traffic pattern with a given probability within a given observation time. This definition can substitute the existing definitions for the capacity of a freeway and opens the possibility to quantitatively describing the influence of traffic control systems on the traffic flow.

A Marine Traffic Flow Model

Abstract: A model is developed for studying marine traffic flow through classical traffic flow theories, which can provide a better understanding of the phenomenon of traffic flow of ships. On one hand, marine traffic has its special features and is fundamentally different from highway, air and pedestrian traffic. The existing traffic models cannot be simply extended to marine traffic without addressing marine traffic features. On the other hand, existing literature on marine traffic focuses on one ship or two ships but does not address the issues in marine traffic flow.

Formation and Propagation of Local Traffic Jam

Abstract: Large scale traffic congestion often stems from local traffic jam in single road or intersection. In this paper, macroscopic method was used to explore the formation and propagation of local traffic jam. It is found that (1) the propagation of traffic jam can be seen as the propagation of traffic signal parameters, that is, virtual split and virtual green time; (2) for a road with endogenous flow, entrance location influences the jam propagation. With the same demand (upstream links flow and entrance flow), the upstream got more influence; (3) when a one-lane road is thoroughly congested, virtual signal parameters everywhere are the same as that at stop line; for a basic road, the virtual signals work in a cooperative manner; (4) phase sequence is one important parameter that influences traffic performances during peak hour where spill back of channelization takes place. The same phase plan for left-turn flow and through flow would be preferred; (5) signal coordination plays an important role in traffic jam propagation and hence effective network signal parameters should be designed to prevent jam from propagation to the whole network. These findings would serve as a basis for future network traffic congestion control.

Exploiting probe data to estimate the queue profile in urban networks

Abstract: Queues at signalized intersections are one of the main causes of traffic delays and urban traffic state variability. Hence, a method to estimate queue characteristics provides a better understanding of urban traffic dynamics and a performance measurement of signalized arterials. In order to capture the evolution of queues, we aim at leveraging the collective effect of spatially and temporally dispersed probe data to identify the formation and dissipation of queues in the time-space plane. The queue profile characterizes the evolution of both queue front and back, which consequently can be separated in a two-step estimation process resulting to the queue profile polygon. The evolution of queue front, in the time-space diagram, based on the kinematic traffic shockwave theory is modeled as a line with the known slope of queue-discharging shockwave and estimated with a constrained optimization and a technique known as support vector machine. The evolution of back of queue is more challenging and modeled as a piecewise linear function where slope of segments is between the queue-discharging shockwave and zero. In the proposed method, the input data consists of position and velocity of probe vehicles. The queue profile estimation method does not require any explicit information of signal settings and arrival distribution. The proposed method is tested with various penetration rates and sampling intervals of probe data, which reveals promising results once compared to a uniform arrival queue profile estimation procedure. The proposed method could be beneficial for spillback identification, vehicle trajectory construction, and fuel consumption and emission estimation.