A Parallel Environment for a Real-Time Traffic Management and Information System (original) (raw)
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The 7th International Conference on Advanced Communication Technology, 2005, ICACT 2005., 2005
Abslrncl -This paper presents a computing environment for building hierarchical traffic telematlcs distributed systems based on non-locking distributed shared memory algorithm. The algorithm aims mainly at minimising the total amount of time for data retrieval in network of workstations, considering the point of view of distributed traffic modules. The framework presented in this paper adopts I non-locking model to achieve the required performance. The presented framework develops further the successful features of DIME (developed and designed at SOCI, NTU) and at the same time avoids its shortcomings. The experimental resJts show that the new framework outperforms the old design of the system.
Transportation Research Record, 1992
The advent of parallel computing architectures presents an 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 modeling algorithm to take full advantage of parallel computing. Such a methodology to simulate traffic network with the Connection Machine, a massively parallel computer, is described. The basic parallel computing architectures are introduced, along with a list of commercially available parallel computers. This 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. It has been implemented on the Connection Machine with 16,384 processors. Preliminary simulation experiments indicate that massively parallel com...
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On-Line Monitoring System for Real-Time Traffic Management Applications
Transportation Research Record, 1999
Typically, in DTA the time-dependent origin-destination (O-D) demands are estimated a priori on the basis of historical data. These estimated O-D demands are then assigned to paths computed by simulation-based or analytical equilibration procedures. Vehicles are propagated on these assigned paths according to some type of traffic flow relationships embedded in optimization or simulation models. In RT-DTA, the time frame is divided into many roll periods. The DTA process above is carried out for every roll period to form the rolling horizon RT-DTA process. The accuracy of the estimated demands at the beginning of each roll period is influenced by the results at the end of the previous roll period, that is, the number of vehicles left in the network at the end of the previous roll period (2). This process generally might generate many sources of error that can cause its internal network representation to deviate from that of the actual traffic network. Broadly, these error sources can be categorized as follows:
Real Time Traffic Models, Decision Support for Traffic Management
Procedia Environmental Sciences, 2014
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various control strategies and enhance the performance of the overall network. By taking proactive action deploying traffic management measures, congestion may be prevented or its effects limited. An approach of short-term traffic state prediction is presented and implemented in a real life case for the city of Assen in the Netherlands. This prediction is based on connecting online traffic measurements with a real time traffic model using the macroscopic dynamic traffic assignment model StreamLine in a rolling horizon implementation. Different monitoring data sources consisting of both fixed-point and floating car data are used. The advantage of the rolling horizon approach is that no warming-up period is needed for the dynamic traffic assignment taking less computation time while keeping results consistent. Further, the current traffic state estimation is done by combining model estimates of previous predictions and current measurements. The results of predictions made in the real life case are presented as well as several tested methods for improving the current state estimations showing promising results.
A framework of real-time traffic information system
International Conference on Applied Mathematics, 2005
In this paper, a framework of real-time macroscopic traffic simulation is proposed. Real-time traffic simulation using macroscopic traffic flow model on freeway have been studied and implemented in the past. We introduced a framework of implementing real-time traffic simulation on urban network. To implement the simulation on an urban network, the estimation of origin-destination (O-D) matrix must be considered. Thus the framework consists of 1) Path generation, 2) Dynamic Origin-Destination Estimation and 3) Link Dynamics. Path generation is based on the Wardrop's user equilibrium concept and modified convex combination algorithm. State space model is used in dynamic O-D estimation, while the LWR model is used to describe the macroscopic traffic flow in Link Dynamics. This study implements the simulation with real-time traffic input and predict traffic condition in real-time. An empirical example is conducted on a real network consists of 91 nodes and 244 links.
A Real-Time Traffic Simulation System
IEEE Transactions on Vehicular Technology, 1998
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.