Route Planning for Heavy Vehicles on Real World Maps

Sammanfattning: Fast route planning for a standard car is well explored, lots of research, and many algorithms exist. For trucks or other heavy vehicles, the available research and quick algorithm alternatives dwindle. This thesis focuses on available alternatives for trucks and other vehicles with attributes hindering them from traversing parts of the road network. Attributes like height are one among many, which can hinder a vehicle on its path. These attributes can vary greatly and is the reason why known solutions can’t be applied. Many well-known solutions rely partially on precalculated data regarding the shortest path for its performance. Precalculating for all possible combinations of attributes is not practical due to the number of possible configurations and the amount of computing needed for each one. The implemented solution is derived from multiple existing solutions and was evaluated on a graph representing Sweden’s road network. The solution is sufficiently fast to allow commercial use and allows changes to the road network with nightly updates. The solution is based on trying to predict which roads are more important when searching for the shortest path. With this knowledge, a search for the shortest path can be said to prioritize the before mentioned roads, which results in it finding its goal faster.