With the development of globalization and artificial intelligence, as well as the outbreak of COVID-19, unmanned vehicles have played an important role in cargo distribution. In order to better analyze the research directions of unmanned vehicle distribution, this paper summarizes the models and algorithms of unmanned vehicle distribution optimization. The research results show that most of the studies have established the goal of optimizing the total costs or travel time. Many researchers have begun to study multi-objective optimization problems, but there are certain limitations, so some studies convert these problems into single-objective optimization for solving, such as converting time and energy consumption into cost, waiting time into distance, and time delay into penalty cost. With the development of unmanned vehicle distribution technology, in future research, a multi-objective model with the lowest cost, the shortest distance and the best security should be established and solved. Most studies have proposed heuristic algorithms for solving the unmanned vehicle distribution problem, and improved optimization solutions have been obtained. In order to ensure the diversity of solution methods, and give consideration to solution time and solution quality, hybrid methods with other algorithms will be a future research direction, for example, the combination of heuristic algorithm and exact algorithm. With the gradual deepening of research, integrated distribution of multiple types of unmanned equipment will become the focus of future research.