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To address the local path planning problem for autonomous land vehicle in unstructured environments, a novel method combining navigation function and A* search is proposed. The computed navigation function in this paper embodies different constraints of vehicle, so in fact to be a near-feasible trajectory. Next the navigation function and sensed obstacles is used to construct the heuristic function,...
With the development of the intelligent transportation systems (ITS), and the widely used technologies of road testing, machine vision etc. in the field of intelligent vehicle, it is possible for the smart car to move automatically in well-structured environments. As for urban complex environments, the researches on unmanned intelligent vehicle are still at the initial stage. For the more complex...
In this paper, a motion planning algorithm based on differential flatness for an autonomous vehicle driving in a structured environment with moving obstacles is presented. A descriptions of the structured environment and definitions of safety and availability of the lane are proposed. In order to ensure that the trajectory is feasible and effective, dynamic longitudinal and lateral acceleration constraints...
This paper presents a novel and computationally inexpensive method for motion planning of autonomous parallel parking of four wheeled nonholonomic vehicles. The proposed method makes use of Trajectory Shaping Guidance, given in [1] and [2], which was originally developed for missiles to hit the target at a given angle. This paper uses a modified version of Trajectory Shaping Guidance (TSG) for path...
There are a lot of cases with vehicle parking methods. But, when we try to analyze the successful parking patterns, we will be known that all processing is accomplished within specific parking pattern. We collect and analyze various parking patterns, so suggest the parking planning algorithm that do mission safe and effectively, when Unmanned Ground Vehicle (UGV) starts parking mission.
This paper proposes a multi-level collaborative driving framework (MCDF) for human-autonomous vehicle interaction. There are three components in MCDF; the mission-behavior-motion block diagram, the functionality-module relationship and the human participation level table. Through integration of the three components, a human driver can cooperate with the vehicle's intelligence to achieve better driving...
We present a motion planning scheme for ground vehicles operating in a partially known environment. Kinematic constraints stemming from vehicle dynamics and from the requirement that the path must remain inside a free channel of a rectangular cell decomposition of the environment at all times, are dealt with by constructing a time-parameterized path using an appropriate combination of a finite number...
Safety is an important issue of driverless car. Yet, most current approaches fail to ensure safety even in a fully informed situation. In this paper we discuss how the safety criteria apply when the robot uses its on board sensors to evolve in an environment populated with static and moving obstacles. The sensors can only provide a partial and uncertain knowledge of the surroundings. We show that...
We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultra-reliability, high-speed operation, complex inter-vehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model-predictive trajectory generation algorithm for computing...
We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultra-reliability, high-speed operation, complex inter-vehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model-predictive trajectory generation algorithm for computing...
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