Name
Abstract | ||
|---|---|---|
Map information is of crucial importance to ensure the safety and reliability of vehicle, no matter indoor or outdoor, it should reflect the real-time changes of environment. Existing indoor map update mechanisms have several common limitations such as small update range, long cycle, large amount of update data, high cost and poor currency. Therefore, we present a multi-vehicle collaborative indoor map update scheme based on edge cloud architecture to realize real-time autonomous map updating. This scheme can be achieved through continuous monitoring, tagging, identification, and layering of the environment during driving process. Compared with traditional map update schemes, experimental results show that our scheme can effectively realize the collaborative map update in indoor environment, enhance the map update efficiency, reduce the update delay, and improve the adaptability of vehicles. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/VTC2020-Fall49728.2020.9348454 | 2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zepeng Zhu | 1 | 0 | 0.34 |
| Jiajia Liu | 2 | 0 | 0.34 |
| Jiadai Wang | 3 | 1 | 1.70 |
| Nei Kato | 4 | 3982 | 263.66 |