Autonomous vehicle controlled by safety path planner with collision risk estimation coupled with a non-linear MPC

Conference paper (2015)

Authors

S. Arrigoni Politecnico di Milano

F. Cheli Politecnico di Milano

S.S. Manazza Politecnico di Milano

P. Gottardis Politecnico di Milano

R. Happee OLD Intelligent Vehicles & Cognitive Robotics

M.A. Arat Dynamics of Micro and Nano Systems - Mechanical, Maritime and Materials Engineering

D. Kotiadis OLD Intelligent Vehicles & Cognitive Robotics

Research Group

Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)

Obstacle avoidance Autonomous vehicle Collision risk estimation MPC algorithm Safety path planner

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http://resolver.tudelft.nl/uuid:5985a4e4-a67e-41d1-89e6-4d63a96a9edc

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Published Date

2015

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

Abstract

Research efforts in both academia and industry connected with the development and implementation of autonomous driving systems are increasing exponentially in last years. The project designed and presented is part of the so called Dutch Automated Vehicle Initiative (DAVI) which aims to investigate, improve and demonstrate automated driving on public roads. The work presented focuses on the path planning and following in highway environment, presenting a novel approach. A modular solution was designed, where the evaluation of risk is implemented in a path planner that select the optimal trajectory among a discrete set of feasible ones in term of comfort. The tracking is performed through a non linear model predictive controller (NMPC), that also consider collision-risk assessment information. In order to test critical situations that can commonly occur, several scenarios were designed and tested through extensive numerical simulations. Simulation results demonstrate that the proposed system is capable of dealing with complex driving situation, maintaining a human-like behavior.