In recent years, the rapid growth of the logistics and delivery industry has increased the demand for safe and efficient delivery planning. However, conventional navigation services do not take road and driver characteristics into account and recommend the same delivery route to every delivery person under the same settings. In this paper, the authors propose a safe and efficient delivery plan based on road characteristics by considering the risk and distance of each road segment estimated using telematics data. First, the proposed method uses clustering to determine the destinations to be handled by delivery personnel, and then uses a genetic algorithm to determine the route and order of delivery. The proposed method was simulated on two different road networks to evaluate its usefulness. The simulation results show that the proposed method can develop a delivery plan that satisfies the specific conditions and needs of delivery personnel and considers both safety and efficiency.

Route recommendation services have been widely used due to the spread of mobile devices such as smartphones. However, conventional route recommendation services often recommend difficult and unsafe routes which require skilled driving techniques because conventional services aim to recommend the shortest route considering the travel distance and time. In a previous study, we proposed the method of route recommendation that minimizes the accident rate by estimating the accident rate for each road segment according to the characteristics of the driver. The Dijkstra algorithm used for route selection could only consider one link weight, so we obtained some routes that were unnecessarily increasing the route length. Therefore, in this study, we applied a genetic algorithm to route selection and set a threshold for distance in the constraints. In the simulation, it was confirmed that it can recommend safe routes that reduce the accident rate satisfying the constraints by changing the thresholds by parameters and evaluating the results.