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Dynamic Parking Guidance Architecture Using Ant Colony Optimization and Multi-agent Systems

机译:使用蚁群优化和多功能系统的动态停车引导架构

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摘要

Nowadays, drivers have great difficulty finding a parking space easily due to the traffic congestion in some areas and the distribution of car parks within the city. This work aims to design a new system that will allow a vehicle driver to find the best route between his real-time position and parking with available places in a specific area. Our system is based on a distributed swarm intelligence strategy using the ant colony algorithm, cloud system, and multiagent systems to offer an optimal solution toward the nearest car park in the city. Our solution will improve the use of available parking in the city.
机译:如今,由于某些领域的交通拥堵以及城市内的停车场分配,司机很难很容易找到停车位。 这项工作旨在设计一种新系统,该系统将允许车辆驾驶员在其实时位置与特定区域的可用场所找到最佳路线。 我们的系统是基于使用蚁群算法,云系统和多才能系统的分布式群智能策略,为城市最近的停车场提供最佳解决方案。 我们的解决方案将改善市内可用停车位的使用。

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