Real-time Traffic Simulation Research Articles

A Feature Comparative Study of RealTime Traffic Simulation Over OBS Network

Network simulator is a significant tool for researchers to simulate the actual network. The main advantage of the simulator is that it gives results much closer to the reality than the mathematical modeling. Furthermore, its cost is much lesser as compared to the real experimentation. The scale and size of the large networks (e.g. Internet) complicate both the mathematical modeling and the real experimentation. Therefore, researchers depend mainly on simulators to study, evaluate and design the performance of network. Optical Burst Switching (OBS) network is one of the most popular research areas in the optical Internet. However, it is just recently that some of these networks simulators start to provide the ability to simulate OBS network. In this paper, the concepts behind the some main OBS simulators are presented. Furthermore, a feature comparison is made among them in terms of the module-based structure, simulating methodology, compilation, and Graphic User Interface (GUI). The comparison of these simulators has been made based on the needs of simulating real time traffic over OBS network and not to define which network simulator is the best as there are too many different parameters variations and different possible network scenarios to adequately determine this in a single section. The comparison results show that NCTUns can provide much better functions and performance in the simulation of real time traffic in OBS network, because of its several unique features which are suitable for real time traffic over OBS.

A real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tuning fuzzy parameters

Traffic lights are installed at intersections mostly for traffic management. Traffic signals turn on during the amount of time determined. Intelligent traffic management systems emerge as a need to handle the dynamicity of traffic. These systems are first implemented on simulators in order to mimic the real life situations before realization. Yet, we have implemented a real time traffic simulator with an adaptive fuzzy inference algorithm that arranges the foreseen light signal duration. It changes the time duration of lights depending on waiting vehicles behind green and red lights at crossroad. The simulation has also been supported with real time graphical visualization. Given a scenario, it creates random traffic flows according to specified parameters. Next, obtained results have been interpreted in the simulation environment. According to inferences from adaptive environment, TSK (Takagi-Sugeno-Kang) and Mamdani models have also been implemented to give baselines for verification. Several experiments have been conducted and compared against classical techniques such as Webster (1958) Road research technical paper No 39 and HCM (2000) TRB, special report 209, statistically to demonstrate the effectiveness of the proposed method.

Kernel Smoothing Method Applicable to the Dynamic Calibration of Traffic Flow Models

Abstract: Real time traffic flow simulation models are used to provide traffic information for dynamic traffic management systems. Those simulation models are supplied by traffic data in order to estimate and predict traffic conditions in unobserved sections of a traffic network. In general, most of recent real time traffic simulators are based on the macroscopic model because the macroscopic model replicates the average traffic behavior in terms of observable variables such as (time–space) flow and speed at a relatively fast computational time. Like other simulation models, an important aspect of the real time macroscopic simulator is to calibrate the model parameters online. The most conventional way of the online calibration is to add a random walk to the parameters to constitute an augmentation of the traffic variables and the model parameters to be estimated. Actually, this method allows the parameters to vary at every time step and, therefore, describes the adaptation of the model to the prevailing traffic conditions. However, it has been reported that the use of the random walk results in a loss of information and an increase of the covariance of parameters, which consequently leads to posteriors that are far more diffuse than the theoretical posteriors for the true parameters. To this end, this article puts forward a Kernel density estimation technique in the calibration process to handle the covariance issue and to avoid the information loss. The Kernel density estimation technique is embedded in the particle filter algorithm, which is extended to the calibration problems. The proposed framework is investigated using real-life data collected in a freeway in England.

Application of a simulation-based dynamic traffic assignment model

The evaluation of on-line intelligent transportation system (ITS) measures, such as adaptive route-guidance and traffic management systems, depends heavily on the use of faster than real time traffic simulation models. Off-line applications, such as the testing of ITS strategies and planning studies, are also best served by fast-running traffic models due to the repetitive or iterative nature of such investigations. This paper describes a simulation-based, iterative dynamic equilibrium traffic assignment model. The determination of time-dependent path flows is modeled as a master problem that is solved using the method of successive averages (MSA). The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the space-time queuing approach of Mahut. This loading method has been shown to provide reasonably accurate results with very little computational effort. The model was applied to the Stockholm road network, which consists of 2100 links, 1191 nodes, 228 zones, representing and 4964 turns. The results show that this model is applicable to medium-size networks with a very reasonable computation time.

Integration of Geographic Information System for Transportation with Real-Time Traffic Simulation System: Application Framework

Real-time traffic information applications (RTIA) collect real-time traffic data from a wide variety of detectors. The problem with these applications is that they are complex and hard to maintain because of the large number of distributed detectors involved. However, it is well recognized that traffic simulation systems have the ability to improve the efficiency of traffic analysis, prediction, and control. This paper presents an application framework that integrates a real-time traffic simulation system with RTIA. Within this framework, a geographic information system for transportation (GIS-T) architecture, combined with a temporal–spatial database, provides a flexible way to present the real-time traffic information for road users. Several critical system components are introduced as well, including a real-time dynamic traffic data exchange model. The real-time simulation system, a static traffic model in GIS-T, and a Java-based application architecture are also briefly discussed.

Integration of Geographic Information System for Transportation with Real-Time Traffic Simulation System

Real-time traffic information applications (RTIA) collect real-time traffic data from a wide variety of detectors. The problem with these applications is that they are complex and hard to maintain because of the large number of distributed detectors involved. However, it is well recognized that traffic simulation systems have the ability to improve the efficiency of traffic analysis, prediction, and control. This paper presents an application framework that integrates a real-time traffic simulation system with RTIA. Within this framework, a geographic information system for transportation (GIS-T) architecture, combined with a temporal–spatial database, provides a flexible way to present the real-time traffic information for road users. Several critical system components are introduced as well, including a real-time dynamic traffic data exchange model. The real-time simulation system, a static traffic model in GIS-T, and a Java-based application architecture are also briefly discussed.

Increasing the level of service in 2-lane, 2-way roads: a simulation-based approach

Increasing the level of service in congested 2-lane, 2-way roads is a problem of great economical importance. Due to the complexity of this task, simulation can give an invaluable help in guiding the search for better and more cost effective road configurations. This paper describes Traveller, a 3D real time traffic simulator developed in the C++ language using Software Design Pattern (SDP) techniques. The simulator permits one to assess the impact in the level of service, caused by different relative locations and lengths of overtaking and non-overtaking areas. Preliminary data has been obtained for a few representative scenarios. Those data include traffic vehicle delays. Simulation has shown to be an effective tool in optimizing road configuration.

A high fidelity traffic simulation model based on cellular automata and car-following concepts

A high fidelity cell based traffic simulation model (CELLSIM) has been developed for simulation of high volume of traffic at the regional level. Straightforward algorithms and efficient use of computational resources make the model suitable for real time traffic simulation. The model formulation uses concepts of cellular automata (CA) and car-following (CF) models, but is more detailed than CA models and has realistic acceleration and deceleration models for vehicles. A simple dual-regime constant acceleration model has been used that requires minimal calculation compared to detailed acceleration models used in CF models. CELLSIM is simpler than most CF models; a simplified car-following logic has been developed using preferred time headway. Like CA models, integer values are used to make the model run faster. Space is discretized in small intervals and a new concept of percent space occupancy (SOC) is used to measure traffic congestion. CELLSIM performs well in congested and non-congested traffic conditions. It has been validated comprehensively at the macroscopic and microscopic levels using two sets of field data. Comparison of field data and CELLSIM for trajectories, average speed, density and volume show very close agreement. Statistical comparison of macroscopic parameters with other CF models indicates that CELLSIM performs as good as detailed CF models. Stability analyses conducted using mild and severe disturbances indicate that CELLSIM performs well under both conditions.

A real-time traffic simulation using a communication latency hiding parallelization

This paper implements and analyzes a highway traffic-flow simulation based on continuum modeling of traffic dynamics. A traffic-flow simulation was developed and mapped onto a parallel computer architecture. Two algorithms (the one-step and two-step algorithms) to solve the simulation equations were developed and implemented. Tests with real traffic data collected from the freeway network in the metropolitan area of Minneapolis, MN, were used to validate the accuracy and computation rate of the parallel simulation system (with 256 processors): The execution time for a 24-h traffic-flow simulation over a 15.5-mi freeway, which takes 65.7 min on a typical single-processor computer, took only 88.51 s on the nCUBE2 and only 2.39 s on the CRAY T3E. The two-step algorithm, whose goal is to trade off extra computation for fewer interprocessor communications, was shown to save significantly on the communication time on both parallel computers.

Driver Behaviour Modelling and Traffic Simulation

The ARCHISIM multidisciplinary project was aimed at gaining a deeper understanding of road situations and driver activity, constructing a model of these activities and, on that basis, designing a real-time traffic simulation system capable of hosting a driving simulator. In this paper, we will present the general approach adopted in our project and the main results obtained so far. We will conclude by discussing prospects for further research that continues this work.

Evaluating Off-Peak Traffic Signal Control Strategies

This article discusses the evaluation of flashing yellow as an off-peak traffic signal control strategy by establishing an interface between a real-time traffic simulation software HUTSIM (Helsinki University of Technology Simulation Model) and a standard NEMA (National Electrical Manufacturers Association) traffic signal controller. The analysis was performed as part of research dealing with evaluation of different off-peak traffic signal operation strategies and their relative impacts on delay, fuel consumption, vehicle emissions, and driver safety. Because of its widespread use, the main emphasis was on the flashing yellow signal control. Delay field study was performed to obtain and analyze real-world data and compare the efficiency of flashing yellow and fixed time control strategies. To widen the research effort and eliminate inaccuracies due to certain assumptions made during the field study, computer simulation was chosen as an effective tool for comparison of different control strategies. Four different strategies were evaluated: fixed time, fully and semiactuated, and flashing yellow. Flashing yellow was found to be the most efficient of the signal strategies. The impact of this type of off-peak signal control on driver safety also was studied, and a summary of results is presented.

A real-time traffic simulation system

This article studies the usefulness of parallel processing in real-time traffic-flow simulation based on continuum modeling of traffic dynamics. Computational fluid dynamics (CFDs) methods for solving simple macroscopic traffic-flow continuum models have been studied and efficiently implemented in traffic simulation codes (on serial computers) in the past. We designed a traffic-flow simulation code and mapped it onto a parallel computer architecture. This traffic simulation system is capable of simulating freeway traffic flow in real time. Tests with real traffic data collected from the freeway network in the metropolitan area of Minneapolis, MN, were used to validate the accuracy and computational rate of the parallel simulation system. The execution time for a 2-h traffic-flow simulation of about 200 619 vehicles in an 18-mi freeway, which takes 2.35 min of computer time (on a single-processor computer simulator), took only 5.25 s on the parallel traffic simulation system. This parallel system has a lot of potential for real-time traffic engineering applications.

A REAL-TIME NETWORK TRAFFIC SIMULATION MODEL FOR ATMS APPLICATIONS: PART II—MASSIVELY PARALLEL MODEL

Abstract This paper presents three traffic network simulation models implemented on massively parallel computer, the Connection Machine CM-2. The proposed simulation models have been parallelized to take advantage of the parallel computers since they can offer the required computational power at an economical cost/performance ratio. The paper presents detailed discussion of parallel data structure and parallel logic for each simulation model. Several simulation experiments have been carried out to compare the execution speed of each methodology. The preliminary research results indicate that parallel computing architecture offers a very promising alternative for the implementation of real-time traffic simulation.

Exploring real-time traffic simulation with massively parallel computing architecture

The advent of parallel computing architectures presents an attainable opportunity for transportation professionals to simulate a large-scale traffic network with sufficiently fast response time for real-time operation. However, it necessitates a fundamental change in the modelling algorithm to take full advantage of parallel computing. Currently there are two general types of parallel processing architectures: (a) single instruction multiple data (SIMD) streams, and (b) multiple instruction multiple data streams (MIMD). This paper describes a model to simulate network traffic with the Connection Machine, a massively parallel SIMD computer. First we introduce the basic parallel computing architectures along with a list of commercially available parallel computers. It is followed by an in-depth presentation of the proposed simulation methodology with a massively parallel computer. The proposed traffic simulation model has an inherent path-processing capability to represent drivers' route choice behavior at the individual/vehicle level. Such a feature is critical to its integration with a real-time dynamic assignment model in IVHS applications. The proposed model has been implemented on the Connection Machine. Several simulation experiments were carried out which show that massively parallel computers provide a viable alternative for use in the real-time application. The results show that the CM-2 with 16,384 processors can simulate 32,000 vehicles for 30 minutes at a one-second interval within 3 1 2 minutes.

Entrasim: A real-time traffic environment simulator for SPC switching systems : M. Gruszecki. Electl Commun.53, (1) 50 (1978)

Entrasim: A real-time traffic environment simulator for SPC switching systems : M. Gruszecki. Electl Commun.53, (1) 50 (1978)

Real-Time Testing of Automatic Overload Control Systems in a Laboratory Environment

In order to investigate overload control strategies for large electronic switching systems (ESS), it is extremely valuable to be able to load test actual switching machines in a controlled laboratory environment. This method is superior when compared to both testing actual machines in service (where service deterioration cannot be tolerated) and simulating test of virtual machines (where sufficient realism may not be attainable). In the past, this form of experimentation has not been feasible for large ESS's because of both technical and economic problems associated with existing methods of generating the high volume of traffic required for overload testing. With the advent of the real-time traffic simulator known as the programmed electronic traffic simulator (PETS), however, it has become practical to conduct real-time tests of on-line overload control systems. PETS has been utilized to perform overload control experiments on an ESS to demonstrate the feasibility of conducting controlledenvironment overload testing on an actual ESS. It is the intent of this paper to describe the methodology used in the simulation experiments conducted and summarize some of the simulation results. In particular, the results of the three overload control systems will be compared with respect to both the total number of calls completed within a specified period of time and the grade of service provided. The sensitivity of system performance to the peakedness factor of the offered traffic will also be presented.