Integrated Environment-sensing Path Planning Method for Electric Unmanned Sanitation Vehicle

Efficient urban waste collection and processing are crucial for achieving carbon neutrality, mitigating environmental pollution, and reducing economic losses. The electric unmanned sanitation vehicle integrates a variety of sensor technologies and can operate continuously at high intensity, which is expected to become a viable solution to alleviate urban waste. This paper introduces an integrated environment-sensing electric unmanned sanitation vehicle routing problem model (IEEUSV-VRP), which aims to address the challenges of actual route planning in unstructured outdoor working environments. The model uses four lidar sensors to map the operating environment, combines the advantages of the split delivery vehicle routing problem (SDVRP) and the capacitated vehicle routing problem (CVRP) and the optimal path is generated by optimizing the total distance. Experimental results demonstrate that in urban waste collection applications, the solution performance of IE-EUSV-VRP significantly outperforms traditional models. Specifically, compared to state-of-the-art classical model solutions, IE-EUSV-VRP reduces the cost of distance (Euclidean distance) by 8%, and the number of vehicles used is decreased by 14%. Moreover, in practical waste disposal experiments in actual environments, IE-EUSV-VRP reduces the actual total distance traveled by vehicles by 13.8% compared to classical model solutions. This further validates the superior performance of the model, providing a scientific theoretical basis and effective solutions for the future development of waste collection and disposal.