plhsu19/ii2202-project_shortest-path-algorithms-based-path-planning-for-autonomous-vehicles

Implement and benchmark two graph search algorithms (hybrid A* and Dijkstra) for autonomous vehicles when considering vehicles' physical constraints. A research project at KTH University.

II2202 Project: Comparison of Grid Based Search Path Planning Dijkstra and A* Algorithm

The purpose of this project is to implement a state-of-the-art hybrid planning algorithm (hybrid A*) that is widely used in auto-driving applications for path exploration. The performance and efficiency of the algorithm is evaluated and compared with a more traditional planning algorithm (hybrid Dijkstra) experimentally in order to examine the effect of heuristic in the context of hybrid systems for autonomous vehicle simulation.

Disclaimer: The main purpose is to implement and evaluate the core path-planning algorithms for self-driving applications.The simulation environment, e.g., mazes, and the plot modules are provided by the Github repository (https://github.com/cisprague/dubins.git) of course "DD2410 Introduction to Robotics" offered by KTH University.

Run the simulation by executing following commands within hybrid_A*_and_Dijkstra directory:

# run the simulation
>>> python3 main.py

Run the simulation with additional arguments:

# show a plot
python3 main.py -p
# print trajectory information
python3 main.py -v

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