WO2021116081A1 - A method and system for detecting traffic lane boundaries - Google Patents
A method and system for detecting traffic lane boundaries Download PDFInfo
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- WO2021116081A1 WO2021116081A1 PCT/EP2020/085028 EP2020085028W WO2021116081A1 WO 2021116081 A1 WO2021116081 A1 WO 2021116081A1 EP 2020085028 W EP2020085028 W EP 2020085028W WO 2021116081 A1 WO2021116081 A1 WO 2021116081A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
Definitions
- the present disclosure relates to a method and system for detecting traffic lane boundaries. More specifically, the system and method provides an accurate detection of lane boundaries for a semi-autonomous or an autonomous vehicle.
- FIGs. 1A-1H show road markings, which are classified as continuous 102b or solid 102b and dashed 102a road markings (e.g. see FIG. 1A). Multiple line boundaries are also common on the road (e.g. see FIGs. 1 B-1 FI).
- Lane detection in semi-autonomously or autonomously driven vehicles depend on detection of said road markings, therefore lane detection is critical for manoeuvring an autonomous vehicle.
- Many sophisticated lane detection methods have been proposed, for example ‘Vision Lane Marking Detection and Classification for Vision-based Navigation System (IEEE, 2015)’ and patent publication numbers CN105426864b and CN103295403.
- FIGs. 1B-1H exemplarily illustrates double lane markings
- FIGs. 1F-1H exemplarily illustrates triple lane markings, which define lane boundaries on roads.
- FIG. 2 exemplarily illustrates such determination of lane boundaries 201a-201e detected from lane markings 201a-202e respectively using prior art techniques. It may be observed that prior art techniques do not take multiple lane markings into consideration and thus the lane boundaries do not usually correspond to actual lane boundaries on the road 201b-201d. This inaccuracy in determination of lane boundaries may cause line model fitting to fail. Thus, cause the autonomous vehicle to inadvertently manoeuvre or stray partially into the adjacent lane, which can be dangerous.
- the present invention relates to a method and system for detecting traffic lane boundaries, as set out in the appended claims. More specifically, the system and method provides an accurate detection of lane boundaries for a semi- autonomous vehicle or an autonomous vehicle.
- the method begins with reception of one or more images of a road surface comprising road markings.
- One or more edge lines of the road markings are detected from said images, where said edge lines are substantially parallel to the longitudinal axis of the ego-vehicle.
- a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle are plotted, where each virtual line is periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle.
- a number of intersection points are determined between said each virtual line and said one or more edge lines.
- the distance between each intersection point and the longitudinal axis of the ego- vehicle are sorted.
- a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle are selected. Said first set of edge lines demarcates the inner edge of a first road marking.
- the method further comprises selecting a second set of edge lines having intersection points having second minimum distance from the longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
- the method further comprises selecting a n th set of edge lines having intersection points having n th minimum distances from longitudinal axis of the ego-vehicle, said n th set of edge lines demarcating the inner edge of a n th road marking.
- the system for detecting inner boundaries of road markings for manoeuvring a vehicle comprises at least an image capture device, a processor operatively coupled to said image capture device and a memory operatively coupled to the processor, said memory stores computer readable instructions and said computer readable instructions configures the processor for: receiving one or more images, from the image capture device, said one or more images comprise a road surface comprising road markings; detecting one or more edge lines of the road markings detected from said images, said edge lines substantially parallel to the longitudinal axis of the ego- vehicle; plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle, each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle; for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle; and selecting
- the processor is further configured for selecting a nth set of edge lines having intersection points having nth minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a nth road marking.
- the vehicle comprises a semi-autonomous vehicle or an autonomous vehicle.
- the method and system in accordance to the present invention provides precise demarcation of road markings to aid manoeuvring of an autonomous vehicle.
- FIG. 1A exemplarily illustrates an ego-vehicle along with road markings
- FIG. 1 B-1 E exemplarily illustrates various types of double road markings
- FIG. 1 F-1 FI exemplarily illustrates various types of triple road markings
- FIG. 2 exemplarily illustrates road marking demarcation lines detected in accordance with the prior art
- FIG. 3 exemplarily demonstrates detection of a single road marking in accordance with some of the embodiments of the present invention
- FIG. 4 exemplarily demonstrates detection of a triple road marking in accordance with some of the embodiments of the present invention
- FIG. 5 exemplarily demonstrates detection of a single road marking on either side of the ego-vehicle in accordance with some of the embodiments of the present invention.
- FIG. 6 exemplarily illustrates the architecture of the various components of the system in accordance with some of the embodiments of the present invention. Detailed Description of the Drawings
- the present invention relates to a method and system for method and system for detecting traffic lane boundaries. More specifically, the system and method provides an accurate detection of lane boundaries for a semi-autonomous vehicle.
- FIG. 3 exemplarily demonstrates detection of a single road marking in accordance with some of the embodiments of the present invention.
- the method begins with reception of one or more images of a road surface comprising road markings 302 within the region of interest 303 on the left of an ego-vehicle 301.
- the ego-vehicle herein described can refer to both a semi-autonomous vehicle or an autonomous vehicle or in use.
- One or more edge lines of the road markings are detected from said images, where said edge lines are substantially parallel to the longitudinal axis ‘X’ of the ego-vehicle 301.
- a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle are plotted, where each virtual line is periodically plotted at corresponding predetermined distances di-4 from the ego- vehicle and along the longitudinal axis ‘X’ of the ego-vehicle 301.
- a number of intersection points h ,i , 11 ,2, 11 ,3, 11 ,4 are determined between said each virtual line and said one or more edge lines. The distance between each intersection point 11 ,1 , 11 ,2, 11 ,3, 11 ,4 and the longitudinal axis ‘X’ of the ego-vehicle is sorted.
- a first set of edge lines having an intersection point having minimum distance from longitudinal axis ‘X’ of the ego- vehicle is selected.
- Said first set of edge lines demarcates the inner edge of a first road marking.
- FIG. 4 shows triple road markings 402 in the region of interest 403 on the left of the ego-vehicle.
- a number of intersection points are determined between said each virtual line and said one or more edge lines.
- a person skilled in the art would appreciate that a plurality of intersection points on a virtual line signifies multiple road/lane markings.
- Said first set of edge lines demarcates the inner edge of a first road marking 402a.
- the method may further comprise selecting a n th set of edge lines having intersection points having n th minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcating the inner edge of a n th road marking.
- FIG. 5 exemplarily demonstrates detection of a single road marking on either side of the ego-vehicle in accordance with some of the embodiments of the present invention.
- road markings 502a, 502b on the region of interest of the left side 503a of the ego-vehicle 501 and the region of interest of the right side 503b of the ego-vehicle 501 are shown.
- FIG. 6 exemplarily illustrates the architecture of the various components of the system in accordance with some of the embodiments of the present invention.
- the system comprises at least an image capture device 603, a processor 601 operatively coupled to said image capture device 603 and a memory 602 operatively coupled to the processor 601, said memory 602 stores computer readable instructions and said computer readable instructions configures the processor 601 for: receiving one or more images, from the image capture device 603, said one or more images comprise a road surface comprising road markings; detecting one or more edge lines of the road markings detected from said images, said edge lines substantially parallel to the longitudinal axis of the ego- vehicle; plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle, each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle; for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle; and selecting a first set of edge
- the processor 601 is further configured for selecting a second set of edge lines having intersection points having second minimum distance from longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
- the processor 601 is further configured for selecting a n th set of edge lines having intersection points having n th minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a n th road marking.
- the method and system in accordance to the present invention provides precise demarcation of road markings to aid maneuvering of an autonomous vehicle.
- the apparatus described in the present disclosure may be implemented in hardware, firmware, software, or any combination thereof.
- the processing units, or processors(s) or controller(s) may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, or a combination thereof.
- ASICs application specific integrated circuits
- DSPs digital signal processors
- DSPDs digital signal processing devices
- PLDs programmable logic devices
- FPGAs field programmable gate arrays
- processors controllers, micro-controllers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, or a combination thereof.
- software codes may be stored in a memory and executed by a processor.
- Memory may be implemented within the processor unit or external to the processor unit.
- memory refers to any type of volatile memory or nonvolatile memory.
Abstract
The system and method provides an accurate detection of lane boundaries for an autonomous vehicle where there are multiple road/lane markings on the road for a semi-autonomous vehicle. The edge lines of the road markings substantially parallel to the longitudinal axis of the ego-vehicle is detected. Further, a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle are plotted, where each virtual line is periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle. For each virtual line, a number of intersection points are determined between said each virtual line and said one or more edge lines. The distance between each intersection point and the longitudinal axis of the ego-vehicle are sorted. Further, a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle are selected where said first set of edge lines demarcates the inner edge of a first road marking.
Description
Title
A method and system for detecting traffic lane boundaries
Field The present disclosure relates to a method and system for detecting traffic lane boundaries. More specifically, the system and method provides an accurate detection of lane boundaries for a semi-autonomous or an autonomous vehicle.
Background Road markings are drawn on the road surface for guidance, warning or information for road users. They have the advantage that they can often be seen when an erected sign is obscured. FIGs. 1A-1H show road markings, which are classified as continuous 102b or solid 102b and dashed 102a road markings (e.g. see FIG. 1A). Multiple line boundaries are also common on the road (e.g. see FIGs. 1 B-1 FI).
Lane detection in semi-autonomously or autonomously driven vehicles depend on detection of said road markings, therefore lane detection is critical for manoeuvring an autonomous vehicle. Many sophisticated lane detection methods have been proposed, for example ‘Vision Lane Marking Detection and Classification for Vision-based Navigation System (IEEE, 2015)’ and patent publication numbers CN105426864b and CN103295403. However, such methods and systems do not take into consideration multiple lane markings as shown in FIGs. 1B-1H. FIGs. 1B-1E exemplarily illustrates double lane markings and FIGs. 1F-1H exemplarily illustrates triple lane markings, which define lane boundaries on roads.
FIG. 2 exemplarily illustrates such determination of lane boundaries 201a-201e detected from lane markings 201a-202e respectively using prior art techniques. It may be observed that prior art techniques do not take multiple lane markings into consideration and thus the lane boundaries do not usually correspond to actual lane boundaries on the road 201b-201d. This inaccuracy in determination
of lane boundaries may cause line model fitting to fail. Thus, cause the autonomous vehicle to inadvertently manoeuvre or stray partially into the adjacent lane, which can be dangerous.
Therefore, there is a long felt and unresolved need for accurate lane boundary detection in cases where multiple lane markings define a lane of a road.
Summary
The present invention relates to a method and system for detecting traffic lane boundaries, as set out in the appended claims. More specifically, the system and method provides an accurate detection of lane boundaries for a semi- autonomous vehicle or an autonomous vehicle.
In one embodiment the method begins with reception of one or more images of a road surface comprising road markings. One or more edge lines of the road markings are detected from said images, where said edge lines are substantially parallel to the longitudinal axis of the ego-vehicle. Further, a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle are plotted, where each virtual line is periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle.
In one embodiment, for each virtual line, a number of intersection points are determined between said each virtual line and said one or more edge lines. The distance between each intersection point and the longitudinal axis of the ego- vehicle are sorted. Further, a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle are selected. Said first set of edge lines demarcates the inner edge of a first road marking.
In one embodiment the method further comprises selecting a second set of edge lines having intersection points having second minimum distance from the
longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
The method further comprises selecting a nth set of edge lines having intersection points having nth minimum distances from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcating the inner edge of a nth road marking.
The system for detecting inner boundaries of road markings for manoeuvring a vehicle, comprises at least an image capture device, a processor operatively coupled to said image capture device and a memory operatively coupled to the processor, said memory stores computer readable instructions and said computer readable instructions configures the processor for: receiving one or more images, from the image capture device, said one or more images comprise a road surface comprising road markings; detecting one or more edge lines of the road markings detected from said images, said edge lines substantially parallel to the longitudinal axis of the ego- vehicle; plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle, each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle; for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle; and selecting a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle where the first set of edge lines demarcates the inner edge of a first road marking.
The processor is further configured for selecting a second set of edge lines having intersection points having second minimum distance from longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
The processor is further configured for selecting a nth set of edge lines having intersection points having nth minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a nth road marking.
In one embodiment the vehicle comprises a semi-autonomous vehicle or an autonomous vehicle.
Thereby, the method and system in accordance to the present invention provides precise demarcation of road markings to aid manoeuvring of an autonomous vehicle.
Brief Description of the Drawings
The invention will be more clearly understood from the following description of an embodiment thereof, given by way of example only, with reference to the accompanying drawings, in which:-
FIG. 1A exemplarily illustrates an ego-vehicle along with road markings; FIG. 1 B-1 E exemplarily illustrates various types of double road markings;
FIG. 1 F-1 FI exemplarily illustrates various types of triple road markings;
FIG. 2 exemplarily illustrates road marking demarcation lines detected in accordance with the prior art;
FIG. 3 exemplarily demonstrates detection of a single road marking in accordance with some of the embodiments of the present invention;
FIG. 4 exemplarily demonstrates detection of a triple road marking in accordance with some of the embodiments of the present invention;
FIG. 5 exemplarily demonstrates detection of a single road marking on either side of the ego-vehicle in accordance with some of the embodiments of the present invention; and
FIG. 6 exemplarily illustrates the architecture of the various components of the system in accordance with some of the embodiments of the present invention. Detailed Description of the Drawings
The present invention relates to a method and system for method and system for detecting traffic lane boundaries. More specifically, the system and method provides an accurate detection of lane boundaries for a semi-autonomous vehicle.
FIG. 3 exemplarily demonstrates detection of a single road marking in accordance with some of the embodiments of the present invention. The method begins with reception of one or more images of a road surface comprising road markings 302 within the region of interest 303 on the left of an ego-vehicle 301. It will be appreciated that the ego-vehicle herein described can refer to both a semi-autonomous vehicle or an autonomous vehicle or in use. One or more edge lines of the road markings are detected from said images, where said edge lines are substantially parallel to the longitudinal axis ‘X’ of the ego-vehicle 301. Further, a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle are plotted, where each virtual line is periodically plotted at corresponding predetermined distances di-4 from the ego- vehicle and along the longitudinal axis ‘X’ of the ego-vehicle 301.
For each virtual line, a number of intersection points h ,i , 11 ,2, 11 ,3, 11 ,4 are determined between said each virtual line and said one or more edge lines. The distance between each intersection point 11 ,1 , 11 ,2, 11 ,3, 11 ,4 and the longitudinal axis ‘X’ of the ego-vehicle is sorted. Further, a first set of edge lines having an intersection point having minimum distance from longitudinal axis ‘X’ of the ego- vehicle is selected. Said first set of edge lines demarcates the inner edge of a first road marking. The above is more clearly demonstrated in FIG. 4, which shows triple road markings 402 in the region of interest 403 on the left of the ego-vehicle. In FIG. 4 a plurality of virtual lines X=ki and X=k2 perpendicular to the longitudinal axis ‘X’ of the ego-vehicle 401 are plotted, where each virtual line is periodically plotted at corresponding predetermined distances k-1-2 from the ego-vehicle and along the longitudinal axis ‘X’ of the ego-vehicle 401.
For each virtual line, a number of intersection points (shown as * in FIG. 4) are determined between said each virtual line and said one or more edge lines. A person skilled in the art would appreciate that a plurality of intersection points on a virtual line signifies multiple road/lane markings. Further, the distance between each intersection point and the longitudinal axis ‘X’ of the ego-vehicle is sorted. In this example, for virtual line X=ki distances do, di, d2are sorted and for virtual line X=k2 distances do, di are sorted. Further, a first set of edge lines having an intersection point having minimum distance from longitudinal axis ‘X’ of the ego-vehicle is selected i.e. at do of X=ki and do of X=k2. Said first set of edge lines demarcates the inner edge of a first road marking 402a. The method further comprises selecting a second set of edge lines having intersection points having second minimum distance (di of X=ki and di of X=k2)
from longitudinal axis ‘X’ of the ego-vehicle 401 , said second set of edge lines demarcating the inner edge of a second road marking 402b.
Similarly, the method may further comprise selecting a nth set of edge lines having intersection points having nth minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcating the inner edge of a nth road marking.
FIG. 5 exemplarily demonstrates detection of a single road marking on either side of the ego-vehicle in accordance with some of the embodiments of the present invention. In accordance to the method disclosed above, road markings 502a, 502b on the region of interest of the left side 503a of the ego-vehicle 501 and the region of interest of the right side 503b of the ego-vehicle 501 are shown. Similarly, virtual lines X=di, X=d2, X=d3, and X=d4 are plotted, which results in intersections iu, ii_2, ii_3, ii_4 on the left and im, IR2 on the right, where a line passing through iu, ii_2, ii_3, ii_4 demarcates the inner boundary of the left road marking 502a and a line passing through im, IR2 demarcates the inner boundary of the right road marking 502b. FIG. 6 exemplarily illustrates the architecture of the various components of the system in accordance with some of the embodiments of the present invention. The system comprises at least an image capture device 603, a processor 601 operatively coupled to said image capture device 603 and a memory 602 operatively coupled to the processor 601, said memory 602 stores computer readable instructions and said computer readable instructions configures the processor 601 for: receiving one or more images, from the image capture device 603, said one or more images comprise a road surface comprising road markings; detecting one or more edge lines of the road markings detected from said images, said edge lines substantially parallel to the longitudinal axis of the ego- vehicle;
plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle, each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of the ego-vehicle; for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle; and selecting a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle where the first set of edge lines demarcates the inner edge of a first road marking.
The processor 601 is further configured for selecting a second set of edge lines having intersection points having second minimum distance from longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
The processor 601 is further configured for selecting a nth set of edge lines having intersection points having nth minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a nth road marking.
Thereby, the method and system in accordance to the present invention provides precise demarcation of road markings to aid maneuvering of an autonomous vehicle.
Further, a person ordinarily skilled in the art will appreciate that the various illustrative logical/functional blocks, modules, circuits, and process steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or a combination of hardware and software. To clearly illustrate this interchangeability of hardware and a
combination of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or a combination of hardware and software depends upon the design choice of a person ordinarily skilled in the art. Such skilled artisans may implement the described functionality in varying ways for each particular application, but such obvious design choices should not be interpreted as causing a departure from the scope of the present invention.
The process described in the present disclosure may be implemented using various means. For example, the apparatus described in the present disclosure may be implemented in hardware, firmware, software, or any combination thereof. For a hardware implementation, the processing units, or processors(s) or controller(s) may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, or a combination thereof.
For a firmware and/or software implementation, software codes may be stored in a memory and executed by a processor. Memory may be implemented within the processor unit or external to the processor unit. As used herein the term “memory” refers to any type of volatile memory or nonvolatile memory.
In the specification the terms "comprise, comprises, comprised and comprising" or any variation thereof and the terms include, includes, included and including" or any variation thereof are considered to be totally interchangeable and they should all be afforded the widest possible interpretation and vice versa.
A person skilled in the art would appreciate that the above invention provides a robust and economical solution to the problems identified in the prior art.
The invention is not limited to the embodiments hereinbefore described but may be varied in both construction and detail.
Claims
1. A method for detecting inner boundaries of road markings for manoeuvring a vehicle, comprising: receiving one or more images of a road surface comprising road markings (302); detecting one or more edge lines of the road markings (302) detected from said images, said edge lines substantially parallel to the longitudinal axis of an ego-vehicle (301); characterised by the steps of: plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle (301), each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle and along the longitudinal axis of an ego-vehicle (301); for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle (301); and selecting a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle (301 ).
2. The method of claim 1 , wherein said first set of edge lines demarcates the inner edge of a first road marking (402a).
3. The method of claim 1 or 2, further comprising selecting a second set of edge lines (402b) having intersection points having second minimum distance from longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
4. The method of any preceding claim, further comprising selecting a nth set of edge lines having intersection points having nth minimum distance from
longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a nth road marking.
5. The method of any preceding claim wherein the vehicle comprises a semi- autonomous vehicle or an autonomous vehicle.
6. A system for detecting inner boundaries of road markings for manoeuvring a vehicle, comprising at least an image capture device (603), a processor (601) operatively coupled to said image capture device (603) and a memory (602) operatively coupled to the processor (601), said memory (602) storing computer readable instructions and said computer readable instructions configuring the processor for: receiving one or more images, from the image capture device (603), said one or more images comprise a road surface comprising road markings (302); detecting one or more edge lines of the road markings (302) detected from said images, said edge lines substantially parallel to the longitudinal axis of an ego-vehicle (301); characterised by: plotting a plurality of virtual lines perpendicular to the longitudinal axis of the ego-vehicle (301), each virtual line periodically plotted at corresponding predetermined distance from the ego-vehicle (301) and along the longitudinal axis of the ego-vehicle (301 ); for each virtual line: determining a number of intersection points between said each virtual line and said one or more edge lines; sorting the distance between each intersection point and the longitudinal axis of the ego-vehicle (301); and selecting a first set of edge lines having an intersection point having minimum distance from longitudinal axis of the ego-vehicle (301).
7. The system of claim 6, wherein said first set of edge lines demarcates the inner edge of a first road marking (402a).
8. The system of claim 6 or 7, wherein the processor (601 ) is further configured for selecting a second set of edge lines (402b) having intersection points having second minimum distance from longitudinal axis of the ego-vehicle, said second set of edge lines demarcates the inner edge of a second road marking.
9. The system of claim 6, 7 or 8, wherein the processor (601 ) is further configured for selecting a nth set of edge lines having intersection points having nth minimum distance from longitudinal axis of the ego-vehicle, said nth set of edge lines demarcates the inner edge of a nth road marking.
10. The system of any preceding claim wherein the vehicle comprises a semi- autonomous vehicle or an autonomous vehicle.
11. A computer readable medium having stored thereon computer readable instructions for carrying out the method of any of claims 1 -5.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102019134320.8A DE102019134320A1 (en) | 2019-12-13 | 2019-12-13 | Method and system for detecting lane boundaries |
| DE102019134320.8 | 2019-12-13 |
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| WO2021116081A1 true WO2021116081A1 (en) | 2021-06-17 |
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| PCT/EP2020/085028 WO2021116081A1 (en) | 2019-12-13 | 2020-12-08 | A method and system for detecting traffic lane boundaries |
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| WO (1) | WO2021116081A1 (en) |
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| DE102019134320A1 (en) | 2021-06-17 |
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