2014Computer Engineering and Applications JournalOpen access

Construction and simulation of vehicle generation model based on MT random number generator

YU Zhiha

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Abstract

Aiming at the disadvantage of linear congruential method widely used in traffic flow simulation, MT random number generator is adopted after performance comparison. The traffic conditions is divided into the idle state and the busy one, and different stochastic distributions are applied in stochastic vehicle generation models based on random numbers generated by MT random number generator. The traffic flow procedures are developed in VC environment to achieve simulation experiment, then the results are compared with the field data, which proves the advantage of stochastic vehicle generation models based on MT random number generator.

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What this paper is about

Aiming at the disadvantage of linear congruential method widely used in traffic flow simulation, MT random number generator is adopted after performance comparison. The traffic conditions is divided into the idle state and the busy one, and different stochastic distributions are applied in stochastic vehicle generation models based on random numbers generated by MT random number generator. The traffic flow procedures are developed in VC environment to achieve simulation experiment, then the results are compared with the field data, which proves the advantage of stochastic vehicle generation models based on MT random number generator.

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Available abstract

Aiming at the disadvantage of linear congruential method widely used in traffic flow simulation, MT random number generator is adopted after performance comparison. The traffic conditions is divided into the idle state and the busy one, and different stochastic distributions are applied in stochastic vehicle generation models based on random numbers generated by MT random number generator. The traffic flow procedures are developed in VC environment to achieve simulation experiment, then the results are compared with the field data, which proves the advantage of stochastic vehicle generation models based on MT random number generator.

Key concepts: Random number generation, Generator (circuit theory), Computer science, Stochastic simulation, Linear congruential generator, Pseudorandom number generator, Idle, Convolution random number generator

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