Hybrid trajectory planning approach for roundabout merging scenarios Despite the progress made in the Intelligent Transportation Systems (ITS) field, there is still a large amount of scenarios to be solved, such as urban roundabouts. In particular, the entrance must be emphasized due to most of accidents take place in this part. In such way, the article presents a method to solve the roundabout merging considering a nominal trajectory generated through Bezier curves combining with a Model Predictive Control (MPC) to assure safe future states. Tests are made using a real platform to execute the maneuver and a virtual platform to represent the other participant on the scenario. Experimental results demonstrate the good performance of the approach under merging scenarios.

Obstacle Avoiding Path Following based on Nonlinear Model Predictive Control using Artificial Variables This work presents a model predictive formulation for obstacle avoiding path following control for constrained vehicles. The obstacles are introduced as soft constraints in the value function, in order to maintain the convexity of state and output spaces. In this formulation, the path following and obstacle avoidance tasks may introduce local minima solutions due to their competing costs known as corner conditions. In order to address this problem, a heuristic switch in the form of additional decision variables is introduced into the cost function. The proposed solution is based on an extension of Model Predictive Control (MPC) by using Artificial Variables. An additional cost term is included in order to prevent early stops in the path following task. Simulations results considering an autonomous vehicle subject to input constraints are carried out to illustrate the performance of the proposed control strategy.