A new occupancy grid of the dynamic environment for autonomous vehicles

As an effective environment representation method, the obstacle occupancy grid has been widely applied on the autonomous vehicle, providing evidence for the behavior decision and path planning of autonomous vehicle. In this paper, a new obstacle occupancy grid named space-time occupancy grid map is presented. This map pays more attention on the dynamic obstacles in a period of future time, and maps the obstacle occupancy information in space-time dimension to two-dimensional grid. In this way, the useful obstacle occupancy information for the autonomous vehicle in a period of future time is provided, which enables the behavior decision and path planning to be more intelligent. The space-time occupancy grid map described in this paper has been applied on the two generations of autonomous vehicles, “Intelligent Pioneer I” and “Intelligent Pioneer II”, which have already completed 10,000 kilometers actual road tests in western suburb of Hefei, and won the first prize in the “Intelligent Vehicle Future Challenge of China” Competition funded by Natural Science Foundation of China.

[1]  Yoram Koren,et al.  Histogramic in-motion mapping for mobile robot obstacle avoidance , 1991, IEEE Trans. Robotics Autom..

[2]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[3]  Kurt Konolige,et al.  Improved Occupancy Grids for Map Building , 1997, Auton. Robots.

[4]  Viii Supervisor Sonar-Based Real-World Mapping and Navigation , 2001 .

[5]  Tao Mei,et al.  Lane change path planning based on piecewise Bezier curve for autonomous vehicle , 2013, Proceedings of 2013 IEEE International Conference on Vehicular Electronics and Safety.

[6]  Tao Mei,et al.  Design of a Control System for an Autonomous Vehicle Based on Adaptive-PID , 2012 .

[7]  Christian Laugier,et al.  Dynamic Environment Modeling with Gridmap: A Multiple-Object Tracking Application , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[8]  Jun Wang,et al.  Development of ‘Intelligent Pioneer’ unmanned vehicle , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[9]  Sebastian Thrun,et al.  A Personal Account of the Development of Stanley, the Robot That Won the DARPA Grand Challenge , 2006, AI Mag..

[10]  Sebastian Thrun,et al.  Junior: The Stanford entry in the Urban Challenge , 2008, J. Field Robotics.

[11]  Sebastian Thrun,et al.  Stanley: The robot that won the DARPA Grand Challenge , 2006, J. Field Robotics.

[12]  Sebastian Thrun,et al.  Integrating Grid-Based and Topological Maps for Mobile Robot Navigation , 1996, AAAI/IAAI, Vol. 2.

[13]  Tao Mei,et al.  A New Dynamic obstacle Collision Avoidance System for Autonomous Vehicles , 2015, Int. J. Robotics Autom..