基于免疫遗传优化的智慧交通路径诱导算法

Intelligent Traffic Path Guidance Algorithm Based on Immune Genetic Optimization

针对现有交通路径选择方法存在效率较低,解决交通拥堵情况不理想的问题,提出基于免疫遗传优化的智慧交通路径诱导算法。构建免疫遗传优化算法,基于二进制的交叉与变异抗体参数,调整不同的进化率值与适应度差值。利用优异度与多样性指标,精确修正交叉位置与变异率。根据路径诱导算法的滚动循环形式,创建最短路径数学模型。依据无环路径集合计算最优、最短路径集合。按照路径距离完成顺序排列得出最优路径,实现路径诱导算法的求解。实验证明,所提算法可以为用户提供最优路径,具备较好的全局收敛性能,且响应速度较快,交通拥堵情况得到显著改善。

In this article,an intelligent traffic path guidance algorithm based on immune genetic optimization was presented.Firstly,the immune genetic optimization algorithm was constructed.Based on binary cross and mutation antibody parameters,different evolution rate and fitness were adjusted.Secondly,the indexes of goodness and diversity were used to correct the cross position and variation rate accurately.According to the rolling cycle of path guidance algorithm,the mathematical model with shortest path was build.According to the set of acyclic paths,the sets of optimal and shortest paths were calculated.According to the sequence of completing path distance,the optimal path was obtained.Finally,the solution for the proposed algorithm was realized.Simulation results show that the proposed algorithm can provide the optimal path for users,with better global convergence performance and faster response speed.After applying this method,the traffic congestion has been significantly improved.