Browsing by Keyword "Trajectory"
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Item Fast Real-Time Trajectory Planning Method with 3rd-Order Curve Optimization for Automated Vehicles(IEEE, 2020-09-20) Lattarulo, Ray; Perez, Joshue; CCAMAutomated driving (AD) is one of the fastest-growing tendencies in the Intelligent Transportation Systems (ITS) field with some interesting demonstrations and prototypes. Currently, the main research topics are aligned with vehicle communications, environment recognition, control, and decision-making. A real-time trajectory planning method for Automated vehicles (AVs) is presented in this paper; the contribution is part of AD’s decision-making module. This novel approach uses the properties of the 3er order Bézier curves to generate fast and reliable vehicle trajectories. Online execution and vehicle tracking capacities are considered on the approach. A feasible trajectory is selected based on the criteria: (i) the vehicle must be contained by a collision-free corridor given by an upper decision layer, (ii) the vehicle must be capable to track the generated trajectory, and (iii) the continuity of the path and curvature must be preserved in the joints. Our approach was tested considering a vehicle length (automated bus) of 12 meters. The scenario has the dimension of a real test location with multiple roundabouts.Item A Linear Model Predictive Planning Approach for Overtaking Manoeuvres Under Possible Collision Circumstances(IEEE, 2018-10-18) Lattarulo, Ray; He, Daniel; Perez, Joshue; Heß, Daniel; CCAMOvertaking is one of the most difficult tasks during driving. This manoeuvre demands good skills to accomplish it correctly. In the overtaking considering multiple vehicles (more than a couple) is necessary to understand, predict and coordinate future actions of the other participants. These reasons make it a significant scenario for testing in the connected and automated driving field, with the main goal of predicting safe future states. In this sense, this work presents an overtaking method based on a linear Model Predictive Control (MPC) approach, which considers multiple participants involved in the scenario. This method adapts dynamically the trajectory for the manoeuvre in case of unexpected situations. Some of these changes consider other vehicles coming on the opposite lane or variations on participants' driving decisions. Additionally, the system considers passengers' comfort, the vehicle physical constraints and lateral actions of the vehicle decoupled of the longitudinal ones to simplify the problem.Item Real-Time Trajectory Planning Method Based On N-Order Curve Optimization(Institute of Electrical and Electronics Engineers Inc., 2020-10-08) Lattarulo, Ray; Gonzalez, Leonardo; Perez, Joshue; Barbulescu, Lucian-Florentin; CCAMIn recent years, many functionalities were developed for Automated Vehicles (AVs) and some of them with close-to-market prototypes. A required topic is the generation of continuous trajectories that reduces the amount of discrete and pre-coded instructions while leading the vehicle safely. Consequently, this work presents a novel real-time trajectory planning approach based on numerical optimization of n-order Bézier curves and lane-based information. The generation of a feasible trajectory considers the vehicle dimension while driving into a lane-corridor. The nonlinear optimization problem was solved with the Bound Optimization BY Quadratic Approximation method (BOBYQA), and it uses the passengers' comfort, safety, and vehicle dynamics as constraints of the problem. The solution is validated in a simulation environment using a bus with a length of 12 meters. Moreover, the validation considered the roundabouts due to its complexity, nevertheless, the solution is scalable to other scenarios.Item Safety assessment of automated vehicle functions by simulation-based fault injection(IEEE, 2017-07-27) Juez, Garazi; Amparan, Estibaliz; Lattarulo, Ray; Rastelli, Joshue Perez; Ruiz, Alejandra; Espinoza, Huascar; Tecnalia Research & Innovation; CIBERSEC&DLT; CCAM; QuantumAs automated driving vehicles become more sophisticated and pervasive, it is increasingly important to assure its safety even in the presence of faults. This paper presents a simulation-based fault injection approach (Sabotage) aimed at assessing the safety of automated vehicle functions. In particular, we focus on a case study to forecast fault effects during the model-based design of a lateral control function. The goal is to determine the acceptable fault detection interval for permanent faults based on the maximum lateral error and steering saturation. In this work, we performed fault injection simulations to derive the most appropriate safety goals, safety requirements, and fault handling strategies at an early concept phase of an ISO 26262-compliant safety assessment process.Item Towards conformant models of automated electric vehicles(IEEE, 2018-10-31) Lattarulo, Ray A.; Heb, Daniel; Matute, Jose A.; Perez, Joshue; Hes, Daniel; CCAMAutomated driving is one of the major tendencies in last decades, and it is presented as a reliable option to improve comfort during driving, including disable and elder in society and increasing persons safety in roads. This last topic produces the question how is it possible to verify planning and control algorithms for a reliable commercial use of this technology. The question can be answered from two perspective: experimental or formal methods, where the formal one is selected as the most robust between both. Hence, the current work presents a case study verification in automated driving for lane change and double lane change maneuvers, using as basis a trace conformance method presented in [1]. The verification method is performed in Dynacar as a precise multibody simulator tuned for a commercial Renault Twizy vehicle.