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Along with the continuous improvement of the road transportation network, the number of private cars is also increasing, and the urban traffic problem is becoming more and more serious. The most indispensable part of people's transportation is the use of urban intelligent transportation system, which can help drivers plan the optimal route and solve the driving path planning problem. At present, many path optimization algorithms have been proposed to solve the driving path planning, but there are still some deficiencies. Based on this, this paper proposes an ant colony algorithm, which is applied to optimal path planning to solve the driving path planning problem. Experimental results confirm that the algorithm can effectively avoid falling into the local optimal solution, improve the efficiency and accuracy of the calculation, and has good optimization and convergence, which can meet the needs of optimal path planning.
Song et al. (Wed,) studied this question.