Research on dynamic energy saving path planning algorithm based on real-time traffic information
Lin Liu, Yibin Zhang, Huizong Feng
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.62How to use a DOI?
- path planning, energy saving path, real-time traffic information, Dijkstra algorithm
- Path planning is an important way to alleviate traffic congestion, but the traditional path planning algorithm can only tell us the shortest distance path. Meanwhile, the traffic information is dynamic and changes over time, so the initial optimal path is likely to be invalid when traffic conditions change. A dynamic energy saving path planning algorithm (DESPP) based on real-time traffic information is proposed in this paper, which can plan the energy saving path for driver dynamically. A dynamic road network model is designed to reflect the actual traffic condition, and then an extended Dijkstra algorithm is elaborated, by setting the fuel consumption for the calculation of weight, changing the storage structure of road data, and using the improved quick sort algorithm to sort the weights, so that fast search to the adjacent node can be realized, then the dynamic energy saving path planning algorithm (DESPP) will be obtained. The simulation results show that DESPP algorithm is able to get the energy saving path correctly and effectively. It reduces about 15.19% of the total fuel consumption compared with the traditional Dijkstra algorithm. The DESPP algorithm can be applied in finding energy saving path for navigation system, which is more suitable for the actual need of drivers.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Lin Liu AU - Yibin Zhang AU - Huizong Feng PY - 2016/09 DA - 2016/09 TI - Research on dynamic energy saving path planning algorithm based on real-time traffic information PB - Atlantis Press SP - 314 EP - 319 SN - 2352-538X UR - https://doi.org/10.2991/amitp-16.2016.62 DO - https://doi.org/10.2991/amitp-16.2016.62 ID - Liu2016/09 ER -