Toward efficient trajectory planning: the path-velocity decomposition
International Journal of Robotics Research
An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
Robot Motion Planning
Coordinating Multiple Robots with Kinodynamic Constraints Along Specified Paths
International Journal of Robotics Research
Multiple Mobile Robots Path-Planning with MCA
ICAS '06 Proceedings of the International Conference on Autonomic and Autonomous Systems
Junior: The Stanford entry in the Urban Challenge
Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part II
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 04
Shared Potential Fields and their place in a multi-robot co-ordination taxonomy
Robotics and Autonomous Systems
Multiple path coordination for mobile robots: a geometric algorithm
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Robotic path planning using multi neuron heuristic search
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Conflict-probability-estimation-based overtaking for intelligent vehicles
IEEE Transactions on Intelligent Transportation Systems
Multi-robot coordination using generalized social potential fields
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Generalized velocity obstacles
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Independent navigation of multiple mobile robots with hybrid reciprocal velocity obstacles
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning
Artificial Intelligence Review
Situation assessment for automatic lane-change maneuvers
IEEE Transactions on Intelligent Transportation Systems
Journal of Intelligent and Robotic Systems
Reactive navigation in real environments using partial center of area method
Robotics and Autonomous Systems
Mission design for a group of autonomous guided vehicles
Robotics and Autonomous Systems
Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatiotemporal Data
IEEE Transactions on Visualization and Computer Graphics
A Road Following Approach Using Artificial Neural Networks Combinations
Journal of Intelligent and Robotic Systems
Obstacle-Free Pathway Detection by Means of Depth Maps
Journal of Intelligent and Robotic Systems
Robotic path planning using evolutionary momentum-based exploration
Journal of Experimental & Theoretical Artificial Intelligence
Adaptive evolutionary planner/navigator for mobile robots
IEEE Transactions on Evolutionary Computation
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The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem that contributes towards the goal of making road travel by vehicles free of human drivers. An algorithm needs to ensure optimal real time planning of multiple vehicles (moving in either direction along a road), in the presence of a complex obstacle network. Unlike other approaches, here we assume that speed lanes are not present and that different lanes do not need to be maintained for inbound and outbound traffic. Our basic hypothesis is to carry forward the planning task to ensure that a sufficient distance is maintained by each vehicle from all other vehicles, obstacles and road boundaries. We present here a 4-layer planning algorithm that consists of road selection (for selecting the individual roads of traversal to reach the goal), pathway selection (a strategy to avoid and/or overtake obstacles, road diversions and other blockages), pathway distribution (to select the position of a vehicle at every instance of time in a pathway), and trajectory generation (for generating a curve, smooth enough, to allow for the maximum possible speed). Cooperation between vehicles is handled separately at the different levels, the aim being to maximize the separation between vehicles. Simulated results exhibit behaviours of smooth, efficient and safe driving of vehicles in multiple scenarios; along with typical vehicle behaviours including following and overtaking.