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Distributed simulation of freeway traffic flow using personal computers

delete2002-12-17
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PRE
AI
E
Eil Kwon *
B
Baek‐Young Choi
H
Haesun Park
DOI:10.1111/0885-9507.00181delete
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摘要

摘要

En 中文
This article presents a personal computer (PC)-based distributed simulation methodology that can be applicable for real-time estimation of time-variant parameters in freeway traffic flow The method uses the interprocess communication procedures currently available under Windows NT and adopts two types of distributed computing architectures, i.e., a distributed-memory structure with a network of PCs communicating through Named Pipe and a multithread-based shared-memory structure with a multiprocessor PC. The proposed method, based on the macroscopic traffic model developed and tested in previous studies, first divides a given freeway into a set of subsections depending on the number of available processors or personal computers. At every time step, each processor simulates its own subsection and exchanges the internal boundary data with another processor that simulates the adjacent subsection. The performance of the parallel algorithm was compared with that of a single-processor-based sequential simulation using two different types of hardware configurations: a network of two PCs and a dual-processor PC. The test results with the two-PC network parallel system showed the speedup of 1.94 over the sequential simulation with a single PC, i.e., 48.4 percent reduction in the execution time, for the 1-hour simulation of a 20-mile freeway section. The speed up for 1-hour simulation of an 80-mile section was increased to 1.96 with two processors, which is close to the ideal speedup. The performance rests with the dual-processor PC resulted in consistently, but not significantly, faster execution than those with the two-PC network, which indicates the feasibility of developing a practical on-line decision support system with a network of personal computers for freeway operations.
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期刊

C
Computer-Aided Civil and Infrastructure Engineering
IF:
9.1
论文数:
2.0K
被引数:
10.0K

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