Showing papers on "Traffic wave published in 2009"

Automatic Calibration of the Fundamental Diagram and Empirical Observations on Capacity

Abstract: This paper will present a method for automated, empirical calibration of freeway traffic flow characteristics. The method uses 5-min flow and density values for a section of freeway and rapidly and reliably estimates key parameters such as free flow speed, capacity, critical density, congestion wave speed and jam density, which are key inputs to many macroscopic traffic simulation models. The method consists of data filtering, capacity identification, and approximate quantile regression steps. The method was used to calibrate a cell transmission model of Interstate-880 in San Francisco Bay Area, California, a 40-mile long urban freeway with lots of recurrent and non-recurrent congestion and with dozens of loop detector stations. The calibrated model reproduced the observed traffic congestion behavior within 9% error for performance measures VMT (vehicle miles traveled), VHT (vehicle hours traveled) and total flow. Also, the empirical results suggest that capacity, defined as the maximum observed 5-minute flow rate over several days, differs from breakdown flow, defined as the flow that is observed just before the freeway section becomes congested.

An Approach to Urban Traffic State Estimation by Fusing Multisource Information

Abstract: This paper presents an information-fusion-based approach to the estimation of urban traffic states. The approach can fuse online data from underground loop detectors and global positioning system (GPS)-equipped probe vehicles to more accurately and completely obtain traffic state estimation than using either of them alone. In this approach, three parts of the algorithms are developed for fusion computing and the data processing of loop detectors and GPS probe vehicles. First, a fusion algorithm, which integrates the federated Kalman filter and evidence theory (ET), is proposed to prepare a robust, credible, and extensible fusion platform for the fusion of multisensor data. After that, a novel algorithm based on the traffic wave theory is employed to estimate the link mean speed using single-loop detectors buried at the end of links. With the GPS data, a series of technologies are combined with the geographic information systems for transportation (GIS-T) map to compute another link mean speed. These two speeds are taken as the inputs of the proposed fusion platform. Finally, tests on the accuracy, conflict resistance, robustness, and operation speed by real-world traffic data illustrate that the proposed approach can well be used in urban traffic applications on a large scale.

Exciting traffic jams: Nonlinear phenomena behind traffic jam formation on highways

Abstract: A nonlinear car-following model is studied with driver reaction time delay by using state-of-the-art numerical continuations techniques. These allow us to unveil the detailed microscopic dynamics as well as to extract macroscopic properties of traffic flow. Parameter domains are determined where the uniform flow equilibrium is stable but sufficiently large excitations may trigger traffic jams. This behavior becomes more robust as the reaction time delay is increased.

Understanding stop-and-go traffic in view of asymmetric traffic theory

Abstract: Stop-and-go traffic is a frequently observed phenomenon in congested highway traffic, but it has not been accurately modeled in existing traffic models. Car-following models based on kinematic flow theory cannot model stop-and-go traffic. Other approach assumed traffic states deviating from the equilibrium curve in the fundamental diagram, and the transitions between them, but no explanation was provided on the reason for the existence of different states. There is a need to understand the mechanism of stop-and-go traffic in terms of generation, propagation and dissipation in order to accurately model traffic dynamics. We propose an asymmetric traffic theory and explain the stop-and-go traffic phenomenon in light of the developed theory. The proposed theory is verified using individual vehicle trajectories from two freeway sites in California, US, collected as part of the Next Generation Simulation (NGSIM) project.

Waves and Vibrations in Soils: Earthquakes, Traffic, Shocks, Construction works

Abstract: The main scientific and engineering goal of this book is to deal simultaneously with soil dynamics/vibrations and wave propagation in soils (including seismic waves). These various fields are generally considered separately and the important links between them, both from scientific and practical points of view, are unfortunately not investigated. They are usually considered in separate disciplines such as earthquake geotechnical engineering, civil engineering, mechanics, geophysics, seismology, numerical modelling, etc. The objective of the book is to offer in a single publication an overview of soil dynamics and wave propagation in soils with emphasis on engineering applications. It starts from a wide variety of practical problems (e.g. traffic induced vibrations, dynamic compaction, vibration isolation), then deals with 1D and 2D/3D wave propagation in heterogeneous and attenuating media (with application to laboratory and in situ dynamic characterization of soils), gives an overview of various numerical methods (e.g. FEM, BEM) to simulate wave propagation (including numerical errors, radiation/absorbing conditions, etc) and finally investigates seismic wave propagation and amplification in complex geological structures (e.g. irregular topographies, alluvial deposits).

Phase transitions in traffic flow on multilane roads.

Abstract: Based on empirical and numerical analyses of vehicular traffic, the physics of spatiotemporal phase transitions in traffic flow on multilane roads is revealed. The complex dynamics of moving jams observed in single vehicle data measured by video cameras on American highways is explained by the nucleation-interruption effect in synchronized flow, i.e., the spontaneous nucleation of a narrow moving jam with the subsequent jam dissolution. We find that (i) lane changing, vehicle merging from on-ramps, and vehicle leaving to off-ramps result in different traffic phases-free flow, synchronized flow, and wide moving jams-occurring and coexisting in different road lanes as well as in diverse phase transitions between the traffic phases; (ii) in synchronized flow, the phase transitions are responsible for a non-regular moving jam dynamics that explains measured single vehicle data: moving jams emerge and dissolve randomly at various road locations in different lanes; (iii) the phase transitions result also in diverse expanded general congested patterns occurring at closely located bottlenecks. Language: en

Continuum modeling of cooperative traffic flow dynamics

Abstract: This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.

Road Traffic Noise Prediction Model under Interrupted Traffic Flow Condition

Abstract: The objective of this study is to develop an empirical traffic noise prediction model under interrupted traffic flow conditions using two analytical the approaches, the first being the acceleration lane approach and second being the deceleration approach. The urban road network of Bangalore city has been selected as the study area. Sixteen locations are chosen in major traffic junctions of the study area. The traffic noise data collected from the study locations were analyzed separately for both acceleration and deceleration lanes when vehicles leave an intersection on a green traffic light and come to a stop on red traffic light. Based on the study, a regression noise prediction model has been developed for both acceleration and deceleration lanes.

Traffic Networks and Flows over Time

Abstract: In view of the steadily growing car traffic and the limited capacity of our street networks, we are facing a situation where methods for better traffic management are becoming more and more important. Studies [92] show that an individual "blind" choice of routes leads to travel times that are between 6% and 19% longer than necessary. On the other hand, telematics and sensory devices are providing or will shortly provide detailed information about the actual traffic flows, thus making available the necessary data to employ better means of traffic management.

Traffic light control for a single intersection based on wireless sensor network

Abstract: In view of the complicated traffic condition in the traffic lights monitoring-control system, the current conventional fixed-cycle traffic light control is unable to make full use of lanes. In this paper, a novel simple and economic way used the fuzzy theory to optimize the control of traffic lights for a single intersection is designed and presented based on Wireless Sensor Network. The traffic flow can be detected by the single-axis magnetic sensors and transmitted by wireless sensor network. In order to realize a real-time dynamic control of traffic lights and to reduce the vehicles' average trip waiting time (ATWT), the time for vehicles passing during the green lights would be dynamically adjusted through the fuzzy algorithm according to the current volume of vehicles. The test results show the lanes would be more unobstructed and the efficiency of vehicles traffic at an intersection would be enhanced. Compared with the traditional fixed-cycle system, it is more suitable to the complexity of current traffic conditions.

Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatio-Temporal Data

Abstract: We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatio-temporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e. the dynamic motions of multiple cars over time) in between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur.

The effects of bus stop on traffic flow

Abstract: In this paper, we use the traffic flow model proposed by Tang et al. [Physica A387, 6845 (2008)] to study the effects of bus stop on traffic flow. Our numerical tests show that bus stop will have great effects on the stability of traffic flow and that the effects are related to the initial density and the number of bus stops. The numerical results are accordant with the real traffic, which shows that the model proposed by Tang et al. can describe some complex traffic phenomena resulted by bus stop.

A novel model for intersections of vehicular traffic flow

Abstract: This paper deals with intersections' modeling for vehicular traffic flow governed by the Lighthill $\&$ Whitham [24] and Richards [26] model. We present a straightforward reformulation of recent intersections' models, introduced in [19] and [4], using a description in terms of supply and demand functions [22, 6]. This formulation is used to state the new model which takes into account a possible storage capacity of an intersection as seen in roundabouts or highway on-ramps. We discuss the Riemann problem at the junction and present numerical simulations.

The Use of Genetic Algorithm for Traffic Light and Pedestrian Crossing Control

Abstract: Summary The increase in urban traffic has resulted in traffic congestions, long travel times and increase hazards to pedestrians due to inefficient traffic light controls. These scenarios necessitate the use of new methods in the design of traffic light control for vehicles and pedestrian crossings. In a conventional traffic light controller, the traffic lights change at constant cycle times which are clearly not optimal. The preset cycle time regardless of the dynamic traffic load only adds to the problem. It would be more feasible and sensible to pass more vehicles at the green interval if there are fewer vehicles waiting behind the red lights or vice versa. We apply the genetic algorithm technology in the traffic control system and pedestrian crossing to provide intelligent green interval responses based on dynamic traffic load inputs, thereby overcoming the inefficiencies of the conventional traffic controllers. We apply such technology to a four-way, two-lane junction based on two sets of parameters: vehicles and pedestrians queues behind a red light and number of vehicles and pedestrians that passes through a green light. The algorithms dynamically optimize the red and green times to control the flow of both the vehicles and the pedestrians. To represent a typical traffic flow system, we use the Cellular Automata for modeling vehicular motion behind the traffic lights. We developed an algorithm to model the situation of a four-way two-lane junction based on this technology. We compare the performance between the genetic algorithms controller and a conventional fixed time controller and the results show that the genetic algorithms controller performs better than the fixed-time controller.

Effect of real-time information upon traffic flows on crossing roads

Abstract: The effect of real-time information on the traffic flows of the crossing roads is studied by simulations based on a cellular automaton model. At the intersection, drivers have to enter a road of a shorter trip-time, by making a turn if necessary, as indicated on the information board. Dynamics of the traffic are expressed as a return map in the density-flow space. The traffic flow is classified into six phases, as a function of the car density. It is found that such a behavior of drivers induces too much concentration of cars on one road and, as a result, causes oscillation of the flow and the density of cars on both roads. The oscillation usually results in a reduced total flow, except for the cases of high car density.

A New Macro Model for Traffic Flow on a Highway with Ramps and Numerical Tests

Abstract: In this paper, we present a new macro model for traffic flow on a highway with ramps based on the existing models. We use the new model to study the effects of on-off-ramp on the main road traffic during the morning rush period and the evening rush period. Numerical tests show that, during the two rush periods, these effects are often different and related to the status of the main road traffic. If the main road traffic flow is uniform, then ramps always produce stop-and-go traffic when the main road density is between two critical values, and ramps have little effect on the main road traffic when the main road density is less than the smaller critical value or greater than the larger critical value. If a small perturbation appears on the main road, ramp may lead to stop-and-go traffic, or relieve or even eliminate the stop-and-go traffic, under different circumstances. These results are consistent with real traffic, which shows that the new model is reasonable.

Automatic Traffic Shockwave Identification Using Vehicles’ Trajectories

Abstract: Knowledge of the location and speed of shockwaves in a traffic stream provides insight into the formation and dissipation of congestion – information which is important for system managers. Furthermore, this information can be used to estimate and predict travel time for a section of a roadway. Most of the past efforts at identifying shockwaves have been focused on performing shockwave analysis based on fixed sensors such as loop detectors which are commonly used in many jurisdictions. However, latest advances in wireless communications have provided an opportunity to obtain vehicle trajectory data that potentially could be used to derive traffic conditions over a wide spatial area. This paper proposes a new methodology to detect and analyze shockwaves based on vehicle trajectory data. In the proposed methodology first the points that correspond to the intersection of shockwaves and trajectories of probe vehicles are identified and then a linear clustering algorithm is employed to group different shockwaves. Finally, a linear regression model is used to find propagation speed and spatial and temporal extent of each shockwave. The framework is evaluated using data obtained from a simulation of a signalized intersection and also real trajectory data from freeway US-101 near Los Angeles and shows promising results.

Prediction of traffic density for congestion analysis under Indian traffic conditions

Abstract: Traffic congestion is a serious problem which traffic engineers all over the world are trying to solve. Congestion increases the uncertainty in travel times leading to human stress and unsafe traffic situations. Better management of traffic through Intelligent Transportation Systems (ITS) applications, especially by predicting the congestion on various roads and informing the travelers regarding the same is one possible solution. Accurate and quick prediction is one of the important factors on which the reliability of such a system depends. If one is able to predict congestion on a roadway, then the travelers can be warned of the same either pre-trip or enroute so that they can take well informed travel decisions. The number of vehicles in a given stretch of a roadway (usually referred to as “traffic density”) is one of the most commonly used congestion indicator. Also, the travelers in general will be more interested to know what they can expect when they make the trip in future rather than the present scenario. This makes the short term prediction to future time intervals important. In this study, some of the reported techniques for density prediction under homogeneous traffic conditions are attempted under heterogeneous traffic conditions in order to determine their feasibility under the Indian traffic scenario.

A dynamic traffic assignment model for the assessment of moving bottlenecks

Abstract: Moving bottlenecks in highway traffic are defined as a situation in which a slow-moving vehicle, be it a truck hauling heavy equipment or an oversized vehicle, or a long convey, disrupts the continuous flow of the general traffic. The effect of moving bottlenecks on traffic flow is an important factor in the evaluation of network performance. This effect, though, cannot be assessed properly by existing transportation tools, especially when the bottleneck travels relatively long distances in the network. This paper develops a dynamic traffic assignment (DTA) model that can evaluate the effects of moving bottlenecks on network performance in terms of both travel times and traveling paths. The model assumes that the characteristics of the moving bottleneck, such as traveling path, physical dimensions, and desired speed, are predefined and, therefore, suitable for planned conveys. The DTA model is based on a mesoscopic simulation network-loading procedure with unique features that allow assessing the special dynamic characteristics of a moving bottleneck. By permitting traffic density and speed to vary along a link, the simulation can capture the queue caused by the moving bottleneck while preserving the causality principles of traffic dynamics.

Design and simulation of an artificially intelligent VANET for solving traffic congestion

Abstract: Traffic congestion has been plaguing motorists for years, and it progressively continues to get worse as the population continues to increase, resulting in an increase in the number of vehicles on the road. There are many factors that contribute to traffic congestion, however; there is one that plays a major role in giving rise to a phenomenon called “Traffic Waves”, and that is driver behavior. Traffic waves also called “stop waves” or “traffic shocks”, and they are travelling disturbances in the distribution of cars on a highway, which seems to appear without any reason, propagating backwards and severely slowing traffic flow on roads. The proposed research aims at reducing/eliminating traffic waves by integrating Artificial Intelligence, and Vehicular Ad-hoc Network (VANET) to create a driver aid that helps in combating traffic congestion as well as embedding safety awareness by dynamically rerouting traffic depending on road conditions.

Numerical Investigation of Stop-and-Go Traffic Patterns Upstream of Freeway Lane Drop

Abstract: Freeway lane drops are typical sites where long queues and stop-start traffic waves can be observed. A theory was recently developed to explain the formation of traffic oscillations upstream of a freeway lane drop-in. Using that theory, this paper carries out a numerical investigation to explore how parameters characterizing the driving behavior at and the geometry of a lane-drop site may affect these oscillatory patterns. The effects of five factors—distance between the merging sign and the taper, travel demand, remaining capacity, overall aggressiveness of drivers, and geometry of the lane drop—are studied. It is found that a lane-drop site with low remaining capacity, high travel demand, short distance between the merging sign and the taper, closely matching numbers of drivers desiring to take the through lanes and to take the shoulder lanes, and an imbalance in merging priorities at the taper location is most likely to produce oscillations with short periods and high oscillation amplitudes in flow. Fu...

Asymptotic traffic dynamics arising in diverge–merge networks with two intermediate links

Abstract: Basic road network components, such as merging and diverging junctions, contribute much to formation and propagation of traffic congestion. However, in contrast to extensive studies of traffic dynamics on a road link, little is understood for those on a road network. In this study, we provide a comprehensive analysis of asymptotic traffic dynamics arising in diverge–merge networks with two intermediate links with first-order kinematic wave models. In addition, traffic demand at the origin and traffic demand at the destination are constant and maximum, and the proportion of vehicles choosing an intermediate link is constant. First, we examine all possible asymptotic stationary states and the sufficient and necessary conditions for their existence. With an example, we find that non-stationary states can include damped (DPO) and persistent periodic oscillations (PPO), and present an equivalent dynamical system that can be used to distinguish these two types of oscillations. This study can be a springboard for better understanding of traffic dynamics, especially formation and propagation of traffic congestion, on general road networks.

A new traffic model with the consideration of coupling effect with two lanes

Abstract: This paper introduces a new two-lane high-order continuum model by embedding the two delay time scales continuum traffic model presented by Xue (2003 Phys. Rev. E 68 066123) into the multi-lane model proposed by Daganzo (1997 Transpn. Res. B 31 83) with the consideration of the coupling effect between the vehicles of two lanes in instantaneous traffic situation and lane-change effect. In the novel model, the coupling effect of two lanes and phenomena of lane change, which were not discussed in Daganzo's model and Xue's model, are taken into account. Numerical simulation shows that it is in accordance with real traffic flow. This obviously indicates that the new phenomenon and behaviour are analogous results as single lane presented by Xue, and the proposed model is more reasonable on two lanes. Furthermore, the generation rate between two lanes is also investigated. The results show that the formation and diffusion of traffic shock wave can be better simulated on two lanes.

Impacts of variable message signs on traffic congestion

Abstract: The variable message signs (VMS) have been widely used in guiding and managing the dynamic traffic with development of intelligent transportation technologies. It is known that cell transmission model (CTM) can well reproduce such traffic dynamics as shock waves and jams. This paper presents a new method to estimate the route travel times by using the CTM in conjunction with a logit-based route choice rule. The impacts of VMS on a two-route scenario with recurrent and non-recurrent traffic congestion are numerically investigated by analyzing the changes of route flow and travel time. Simulation results show that in networks with suitable long links, the VMS can positively influence travelers’ decision making so as to improve the system performance. For non-recurrent congestion, the value space of the route choice parameter that affects the flow distribution between two routes is narrower in the case of high traffic demand than that in the low demand case.

Deceleration in advance in the Nagel–Schreckenberg traffic flow model

Abstract: Based on the Nagel–Schreckenberg model, we study the impact of deceleration in advance on the dynamics of traffic flow. In the process of deceleration in advance, the effect of reaction delay and the effect of expectation are considered respectively. The traffic flow properties are studied by analyzing the fundamental diagram, spatio-temporal patterns, distance headway distribution and car accidents. The simulation results show that reaction delay brings complex traffic flow patterns and expectation makes the serious car accidents rarely happen.

Stochastic Models of Traffic Flow Interrupted by Incidents

Abstract: We consider congestion that is caused by irregular occurrences such as traffic accidents, disabled vehicles, adverse weather conditions, spilled loads and hazardous materials. Due to these unexpected events, travel times on the roadways are uncertain. In this paper, we present stochastic models for traffic flow that incorporates uncertain conditions. These models include queueing systems in which customers experience service interruptions from time to time. When a traffic incident happens, either all lanes or part of a lane is closed to the traffic. As such, we model these interruptions either as complete service disruptions where none of the servers work or partial failures where servers work at a reduced service rate. Additionally, the affect of congestion on the traffic flow is also considered. These models are then utilized in estimating the travel times. We present traffic simulation results to show the validity of stochastic models in travel time estimation.