The Research Of Paths On Electronic Map With Minimum Fuel Comsumption Based On AIGAES

Electronic navigation has played in important role for people’s trip, and becomean integral part of travel, its related technology study is also highly valued. As thecore key of electronic map, path planning problem has been studied by many scholarson the subject. At present, the country is committed to develop roads of the city, onthe whole, Electronic navigation to provide a great convenience for the masses.However, unfamiliar roads, traffic jams, etc. will seriously affect the efficiency ofmass trip and the surrounding air quality. For this reason, research about very low fuelpath problems has practical significance. In the above context, this paper improvedimmune genetic algorithm (AIGAES) and its application in path planning is studied.Immune genetic algorithm is based on genetic algorithm, while introduceimmune function algorithm. Now immune genetic algorithm has been widelyapplication in number of areas, function optimization, combinatorial optimization,automatic control and robotics learning etc. For cars with the minimum fuelconsumption in path planning problem, we propose an improved immune geneticalgorithm based on immune genetic algorithm of demonstration antibody injection,The algorithm maintains the basic genetic algorithm for global search capability,introduces immune response and antibody injection mechanisms of a biologicalimmune system, Meanwhile, use a new method of calculating antibody concentration(ratio calculation method), insertion operator, etc, and also the algorithm be used inthe path planning problem with minimum fuel.Determine travel speed and fuel consumption function by on the previous roaddata analysis and the relationship between the road surface characteristics and thespeed. In this paper, the execution environment is the region of part of Nanchangeastern and applies topology algorithm to construct the topology relationship of roadnetwork. In order to save memory and ease the operation of the immune geneticoperator, the paper mainly uses the method of symbol encoding. Combining with theactual situation of the road, we use a new fitness function that simultaneouslyconsiderations road length, speed, speed and fuel consumption functions, etc, makingthe simulation environment more realistic. In order to speed up the algorithmcomputation and enhance the ability to choose the optimization path, we define the selection operator, crossover operator, mutation operator and the insertion operator.This paper utilizes VISUAL C++6.0and sql server2000as platform in the fifthchapter and does the real-time simulation of planning problem for the minimum fuelconsumption path map. During the simulation, compare deeply the GA with AIGAES,AIGAES is faster than the GA about the speed of convergence and the path isrelatively lower fuel consumption. The data obtained from the simulation is operatedin actual driving, the result shows that the minimum fuel consumption path planningcan be well qualified path planning problem, and is very practical.