Artificial Intelligence
Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Moving-Target Search: A Real-Time Search for Changing Goals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eighteenth national conference on Artificial intelligence
Dynamic Programming
Deriving Link Travel-Time Distributions via Stochastic Speed Processes
Transportation Science
Artificial Intelligence
A Comparison of Fast Search Methods for Real-Time Situated Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Scientific Methods in Mobile Robotics
Scientific Methods in Mobile Robotics
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Study on the Application of A* Shortest Path Search Algorithm in Dynamic Urban Traffic
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 05
Robotics and Autonomous Systems
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Autonomous and cooperative guidance strategies for a convoy of electric vehicles in an urban context are challenging research topics in robotics and intelligent transportation systems. The vehicles that form the convoy eventually will have to leave it to perform a mission and return to the convoy formation once the mission has been accomplished. Nevertheless, the merging manoeuvres amongst the convoy and the units returning to it (pursuing units) is a complex task that involves the determination of the best merging point and the route across the city to reach it. This paper tackles this routing problem of a robot located in a map that is trying to join a convoy of robots in constant movement along a peripheral trajectory. We have developed two search strategies able to determine the optimal merging point and the best route to reach it: on one hand we describe a basic solution able to solve the problem when the time spent by the robot traveling along every street of the map is considered to be known and constant. On the other hand, we extended this basic approach to provide a new search strategy that considers uncertainty in traveling times. This increases considerably the complexity of the problem and makes necessary the inclusion of a risk factor that must be considered when determining the best route and the merging point for the manoeuvre. We also put our search strategies into practice in both, simulated and real scenarios. On one hand we have simulated the behavior of a convoy leader and a transport unit which is trying to join in the convoy, using Player&Stage. On the other hand we have used real P3-DX robot units as prototypes of electrical vehicles in a transport scenario.