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- W4280651878 abstract "With traffic congestion gradually becoming the heart problem of many cities, the traffic congestion phenomenon usually occurs at the intersection of large traffic flow. Traffic lights are the key to solving the problem of traffic congestion. To reasonably schedule traffic lights and alleviate traffic congestion at intersections, this paper first constructed a vehicle road traffic simulation system based on finite state machine, which can simulate and calculate the total score of vehicles under any scheduling scheme. Then, a genetic algorithm based on probability distribution is designed to optimize the scheduling scheme. Finally, the validity of the model and algorithm is verified by a case study. Compared with the traditional genetic algorithm, the genetic algorithm based on probability distribution can speed up the time more than 7 times and can calculate the convergence scheduling scheme more quickly. shorten the running time more than 7 times and has a faster convergence speed." @default.
- W4280651878 created "2022-05-22" @default.
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- W4280651878 date "2022-05-17" @default.
- W4280651878 modified "2023-09-26" @default.
- W4280651878 title "Control of traffic light timing using probability distribution genetic algorithm and finite state machine" @default.
- W4280651878 doi "https://doi.org/10.1117/12.2639045" @default.
- W4280651878 hasPublicationYear "2022" @default.
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