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Path planning in automated driving environment

A path planning and path technology, applied in the field of vehicle risk estimation, can solve problems that are difficult to formally display

Pending Publication Date: 2022-03-18
哲内提
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For some scenarios, it can only integrate one type of operation (vertical or horizontal) for dealing with violations of its security zone, as this combination has proven difficult to show formally

Method used

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  • Path planning in automated driving environment
  • Path planning in automated driving environment
  • Path planning in automated driving environment

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Embodiment Construction

[0032] Those skilled in the art will appreciate that the steps, services and functions explained herein may be implemented using separate hardware circuits, using software running in conjunction with a programmed microprocessor or general purpose computer, using one or more application specific integrated circuits (ASICs) ) and / or using one or more digital signal processors (DSP). It will also be understood that while the present invention is described as a method, it can also be embodied in one or more processors and one or more memories coupled to the one or more processors, wherein the one or more memories store one or more Programs that, when executed by one or more processors, perform the steps, services and functions disclosed herein.

[0033] In the following description of the exemplary embodiments, the same reference numerals denote the same or similar components.

[0034] In this context, a risk map estimates and quantifies a "risk" view of the entire ADS surroundin...

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Abstract

The invention discloses path planning in an automated driving environment. The invention relates to a path planning method and system for a vehicle. The method includes acquiring a risk map of the surroundings of the vehicle. The risk map is formed based on an actuation capability of the vehicle and a location of a free space region in the ambient environment, the actuation capability including an uncertainty estimate of the actuation capability, and the location of the free space region including an uncertainty estimate of an estimated location of the free space region. Further, the risk map includes risk parameters included in each of a plurality of segments in the surroundings of the vehicle. The method further includes obtaining at least one candidate path of the vehicle, determining a total risk value for each candidate path based on risk parameters of a set of zone segments intersecting the at least one path, selecting a candidate path of the at least one candidate path that meets a risk value criterion, and generating, at an output, a first signal representing the selected candidate path.

Description

[0001] Cross References to Related Applications [0002] This patent application claims priority to European Patent Office Application No. 20196798.1, filed September 18, 2020, entitled "Path planning in the context of autonomous driving", which is assigned to the assignee of the present application and adopted by References are expressly incorporated herein. technical field [0003] The present disclosure relates to automated driving systems, and more particularly to risk estimation for vehicles equipped with automated driving systems. Background technique [0004] In the past few years, the development of self-driving cars has grown by leaps and bounds, and many different options are being explored. An increasing number of modern vehicles feature advanced driver assistance systems (ADAS) to improve vehicle safety and wider road safety. For example, ADAS, which can be represented by adaptive cruise control, ACC, collision avoidance system, forward collision warning, etc.,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/34B60W60/00
CPCG01C21/3446G01C21/3492B60W60/0016B60W2555/20G01C21/3407B60W60/0011G01C21/3807G01C21/3833G08G1/166B60W30/09G01C21/3461
Inventor 芒努斯·于伦哈马尔哈坎·西文克罗纳
Owner 哲内提
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