A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Abstract

Abstract:Taking the maximum vehicle driving distance, the distances from gas stations, the route length, and the number of refueling gas stations as the decision conditions, recommendation rules and an early refueling service warning mechanism for gas stations along a self-driving travel route were constructed by using the algorithm presented in this research, based on the spatial clustering characteristics of gas stations and the urgency of refueling. Meanwhile, by combining ArcEngine and Matlab capabilities, a scenario simulation system of refueling for self-driving travel was developed by using c#.net in order to validate and test the accuracy and applicability of the algorithm. A total of nine testing schemes with four simulation scenarios were designed and executed using this algorithm, and all of the simulation results were consistent with expectations. The refueling recommendation algorithm proposed in this study can automatically adapt to changes in the route length of self-driving travel, the maximum driving distance of the vehicle, and the distance from gas stations, which could provide variable refueling recommendation strategies according to differing gas station layouts along the route. Therefore, the results of this study could provide a scientific reference for the reasonable planning and timely supply of vehicle refueling during self-driving travel.

Research on Optimal Route Planning for Self-Driving Tour Based on Road Network Structure

“…By calculating the distance traveled on the GIS grid to deduce the accessibility [10] and fully considering various factors such as mountains and waters that hinder the movement, the accessibility to a certain location in the region can be better simulated. e weighted distance from one place on the GIS grid to another on the grid is calculated.…”