A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel
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 construct...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-03-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2220-9964/7/3/94 |
| _version_ | 1818616847347482624 |
|---|---|
| author | Quanli Xu Kun Yang Shuangyun Peng Liang Hong |
| author_facet | Quanli Xu Kun Yang Shuangyun Peng Liang Hong |
| author_sort | Quanli Xu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-16T16:56:18Z |
| format | Article |
| id | doaj.art-82e0b7c7cdcb411180ce4afec7eade82 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-16T16:56:18Z |
| publishDate | 2018-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-82e0b7c7cdcb411180ce4afec7eade822022-12-21T22:23:52ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-03-01739410.3390/ijgi7030094ijgi7030094A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving TravelQuanli Xu0Kun Yang1Shuangyun Peng2Liang Hong3School of Tourism and Geographic Science, Yunnan Normal University, Kunming 650500, ChinaGIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Kunming 650500, ChinaSchool of Tourism and Geographic Science, Yunnan Normal University, Kunming 650500, ChinaSchool of Tourism and Geographic Science, Yunnan Normal University, Kunming 650500, ChinaTaking 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.http://www.mdpi.com/2220-9964/7/3/94intelligent transportationrecommendation algorithmdistance adaptivespatial clusterK-MeansrefuelingAPP |
| spellingShingle | Quanli Xu Kun Yang Shuangyun Peng Liang Hong A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel ISPRS International Journal of Geo-Information intelligent transportation recommendation algorithm distance adaptive spatial cluster K-Means refueling APP |
| title | A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel |
| title_full | A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel |
| title_fullStr | A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel |
| title_full_unstemmed | A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel |
| title_short | A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel |
| title_sort | distance adaptive refueling recommendation algorithm for self driving travel |
| topic | intelligent transportation recommendation algorithm distance adaptive spatial cluster K-Means refueling APP |
| url | http://www.mdpi.com/2220-9964/7/3/94 |
| work_keys_str_mv | AT quanlixu adistanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT kunyang adistanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT shuangyunpeng adistanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT lianghong adistanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT quanlixu distanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT kunyang distanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT shuangyunpeng distanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel AT lianghong distanceadaptiverefuelingrecommendationalgorithmforselfdrivingtravel |