Abstract: Aiming at the contactless distribution mode for unmanned vehicle to deliver medical protective materials, an optimization model of unmanned vehicle distribution for medical protective materials considering the priority level of hospitals is established. According to the characteristics of real-time path planning, in the initial planning stage, with the objectives of shortest delivery time and highest comprehensive satisfaction rate, the dispatching paths of unmanned vehicles and material distribution are preliminarily planned. When the road condition information changes in an emergency, the paths are adjusted in real time based on the local update strategy to better meet the timeliness of the distribution. In order to improve the defects of the standard genetic algorithm (SGA), such as local search easily falling into prematurity and population evolution stagnation in later stage, genetic & simulated annealing algorithm (GSA) is designed to amplify individual differences with similar fitness, so as to make the effect of offspring of excellent individuals more obvious. Finally, the distribution of medical protective materials in Jianghan district and Jiangan district of Wuhan city under the new coronavirus epidemic is taken as an example to verify the model and algorithm. The results show that the model constructed can find the optimized distribution solution based on the realtime information of road network, and the GSA is more stable than SGA. Compared with the SGA, the GSA is more stable and the quality of solution is higher. Compared with the traditional model, the longer the vehicles pass through the congested road, the more obvious the advantages of the unmanned vehicle distribution model.

Key words: epidemic disease; unmanned vehicle; medical protective materials; contactless distribution