Abstract: Lateral motion control of vision-based unmanned vehicle DLUIV-1 is researched .Firstly, the lateral motion control model of vision-based navigation unmanned vehicle is established, which can describe the lateral motion behavior of unmanned vehicles. On this basis, the influence of look-ahead distance on lateral control system is analyzed, and the formula of look-ahead distance with the effect of velocity considered is established. Then, in view of highly nonlinear and parametric uncertain properties of non-holonomic unmanned vehicle, an efficient fuzzy control strategy based on genetic algorithm is presented, the membership functions and rules of fuzzy controller are optimized by genetic algorithm, therefore, the membership functions and rules are effectively determined. Finally, the simulation and real vehicle experiment analysis and validation of proposed control strategy are carried out. Both simulation and experimental results show that the unmanned vehicle controlled by the proposed control strategy can stably track the reference path under various conditions with high accuracy and robustness.

Key words: Fuzzy control, Genetic algorithm, Lateral control, Unmanned vehicles, Vision-based navigation