Journal ArticleDOI
Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints
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TLDR
The simulation results show that the proposed path-planning approach is effective for many driving scenarios, and the MMPC-based path-tracking controller provides dynamic tracking performance and maintains good maneuverability.Abstract:
A path planning and tracking framework is presented to maintain a collision-free path for autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field is constructed as a superposition of trigonometric functions of the road and the exponential function of obstacles, which can generate a desired trajectory for collision avoidance when a vehicle collision with obstacles is likely to happen. Next, to track the planned trajectory for collision avoidance maneuvers, the path-tracking controller formulated the tracking task as a multiconstrained model predictive control (MMPC) problem and calculated the front steering angle to prevent the vehicle from colliding with a moving obstacle vehicle. Simulink and CarSim simulations are conducted in the case where moving obstacles exist. The simulation results show that the proposed path-planning approach is effective for many driving scenarios, and the MMPC-based path-tracking controller provides dynamic tracking performance and maintains good maneuverability.read more
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Journal ArticleDOI
A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles
TL;DR: A model predictive path-planning controller is introduced in this paper such that its objective includes potential functions along with the vehicle dynamics terms and is capable of treating different obstacles and road structures distinctly while planning the optimal path utilizing vehicle dynamics.
Journal ArticleDOI
Model predictive control power management strategies for HEVs: A review
TL;DR: In this article, a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time is presented.
Reference BookDOI
Dynamics and Control
TL;DR: 1. Control Methodology 2. Dynamical Systems 3. Applications to Social and Environmental Problems 4.
Journal ArticleDOI
A Motion Planning and Tracking Framework for Autonomous Vehicles Based on Artificial Potential Field Elaborated Resistance Network Approach
TL;DR: The APF method is used to assign different potential functions to different obstacles and road boundaries; while the drivable area is meshed and assigned resistance values in each edge based on the potential functions.
Journal ArticleDOI
Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles
TL;DR: In this article, a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles is presented, which determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle.
References
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Book
Principles of Robot Motion: Theory, Algorithms, and Implementations
Howie Choset,Jean-Claude Latombe +1 more
TL;DR: In this paper, the mathematical underpinnings of robot motion are discussed and a text that makes the low-level details of implementation to high-level algorithmic concepts is presented.
Book
Model Predictive Control System Design and Implementation Using MATLAB
TL;DR: In this article, the authors present methods for design and implementation of MPC systems using basis functions that confer the following advantages: continuous-and discrete-time MPC problems solved in similar design frameworks; a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and a more general discrete time MPC design that becomes identical to the traditional approach for an appropriate choice of parameters.
Automotive Control Systems: For Engine, Driveline, and Vehicle
Uwe Kiencke,Lars Nielsen +1 more
TL;DR: In this paper, the authors have large experiences in industrial development (Bosch) as well as in academic research and introduce mechanical engineers into vehicle-specific signal processing and automatic control.
Reference BookDOI
Dynamics and Control
TL;DR: 1. Control Methodology 2. Dynamical Systems 3. Applications to Social and Environmental Problems 4.
Journal ArticleDOI
Dynamic motion planning of autonomous vehicles
Zvi Shiller,Y.-R. Gwo +1 more
TL;DR: A method for planning the motions of autonomous vehicles moving on general terrains is presented that obtains the geometric path and vehicle speeds that minimize motion time considering vehicle dynamics, terrain topography, obstacles, and surface mobility.