WO2012089274A1

WO2012089274A1 - System and method for automatic road detection

Info

Publication number: WO2012089274A1
Application number: PCT/EP2010/070944
Authority: WO
Inventors: Radoslaw Chmielewski
Original assignee: Tele Atlas Polska Sp.Z.O.O.
Priority date: 2010-12-30
Filing date: 2010-12-30
Publication date: 2012-07-05

Abstract

A method for determining road data, for example, for use in satellite navigation systems, is provided. Laser scan data is acquiring for at least one road section (10), the laser scan data representing distances from a laser scanner (6, 8) to one or more points on and/or adjacent the at least one road section (10). At least one boundary or perimeter (1205) of the road section is then determined from the laser scan data.

Description

SYSTEM AND METHOD FOR AUTOMATIC ROAD DETECTION

Field of the Invention

The present invention relates to a system and method for generating maps and/or map data, particularly for generating road maps and/or road map data.

Background to the Invention

Navigation systems, electronic maps (also referred to herein as digital maps), and geographical positioning devices have been increasingly used in vehicles to assist the driver with various navigation functions, such as: determining the overall position and orientation of the vehicle; finding destinations and addresses; calculating optimal routes (perhaps with the assistance of real time traffic information); and providing real-time driving guidance, including access to business listings or yellow pages. Typically the navigation system portrays a network of streets as a series of line segments, including a centreline running approximately along the centre of each roadway. The moving vehicle can then be generally located on the map close to or co-located with regard to that centreline.

Some early vehicle navigation systems relied primarily on relative-position determination sensors, together with a "dead-reckoning" feature, to estimate the current location and heading of the vehicle. This technique is prone to accumulating small amounts of positional error, which can be partially corrected with "map matching" algorithms. The map matching algorithm compares the dead-reckoned position calculated by the vehicle's computer with a digital map of street centrelines, to find the most appropriate point on the street network of the map, if such a point can indeed be found. The system then updates the vehicle's dead-reckoned position to match the presumably more accurate "updated position" on the map.

With the introduction of reasonably-priced Global Positioning System (GPS) satellite receiver hardware, a GPS receiver or GPS unit can be added to the navigation system to receive a satellite signal and to use that signal to directly compute the absolute position of the vehicle. However, map matching is still typically used to eliminate errors within the GPS system and within the map, and to more accurately show the driver where he/she is on (or relative to) that map. Even though on a global or macro-scale, satellite technology is extremely accurate; on a local or micro-scale small positional errors still do exist. This is primarily because the GPS receiver can experience an intermittent or poor signal reception or signal multipath, and also because both the centreline representation of the streets and the actual position of the GPS system may only be accurate to within several meters. Higher performing systems use a combination of dead-reckoning (DR)/inertial navigation systems (INS) and GPS to reduce position determination errors, but even with this combination, errors can still occur at levels of several meters or more. Inertial sensors can provide a benefit over moderate distances, but over larger distances even systems with inertial sensors accumulate error. While vehicle navigation devices have gradually improved over time, becoming more accurate, feature-rich, cheaper, and popular; they still fall behind the increasing demands of the automobile industry. In particular, it is expected that future vehicle navigation applications will require higher positional accuracy, and even more detailed, accurate, and feature-rich maps. Possible enhanced applications are likely to include: adding more precise navigation guidance features to vehicles, that can be supported by improved mapping capabilities, and provide better usability and convenience for the driver; and adding various safety applications, such as collision avoidance, which may, in turn, depend on having accurate knowledge of the position and heading of the vehicle relative to other nearby moving and stationary objects, including other vehicles. Within this context, the accuracy within the current generation of consumer navigation systems, on the order of 5 to 10 meters, was thought to be inadequate. It was believed that systems many times more accurate were needed. In order to meet these future needs, the automobile industry sought ways to improve both the accuracy of digital maps and the accuracy of on-board position determination (e.g. GPS, etc.) sensors.

At the same time, the digital mapping industry, represented by companies such as Tele Atlas, is putting greater amounts of information into its digital maps. This increased information is being combined with much higher accuracy so as to better support advanced future applications. Examples of the features now included in digital maps include: the accurate representation of the number of lanes within a particular street or road; the positions of those lanes and barriers; the identification and location of objects such as street signs and buildings footprints; and the inclusion of objects within a rich three-dimensional (3D) representation that portrays actual building facades and other features.

Current navigation systems have sufficient accuracy and map detail to allow the onboard position determination to match the vehicle's position to the appropriate street centreline, and thereby show the vehicle on the proper place in relation to a centreline map. From there the system can help the driver with orientation, routing and guidance functions. However, this level of precision is insufficient both in detail and in accuracy to tell the driver what driving lane he/she may be in (and thereby give more detailed driving guidance), or to warn the driver that he/she may be in danger of a collision. In fact, in today's mapping systems the majority of non-highway roads are depicted on the map with a single centreline which is used for vehicles travelling in both directions. Using contemporary map matching techniques, the vehicles appear to be travelling along the same line, and thus if viewed in relation to each other would always appear to be in danger of collision. Alternatively, for those digital maps in which roads are represented on the map by a centre line in each direction, the cars travelling in each direction would match to the appropriately oriented element of that road segment pair, and the cars, if viewed in relation to each other, would never appear to be in a position to collide, even if in reality the situation was quite different.

Therefore, generation of accurate map data that can indicate not only the centreline of the road but also the dimensions or sides of the road, i.e. a road corridor, is desirable. However, collection of such road corridor map data may be slow, time consuming and/or labour intensive.

The known systems described above can provide accurate and effective mapping and navigation. Nevertheless it is an aim of the present invention to provide an improved or at least alternative mapping system and/or method.

Summary of Invention

According to a first aspect of the present invention is a method of determining road data, comprising:

acquiring laser scan data for at least one road section, the laser scan data representing distances from a laser scanner to one or more points on and/or adjacent the at least one road section; and

determining at least one boundary or perimeter of the road from the laser scan data. The laser scan data may be collected using a laser scanner. The laser scanner may be a mobile laser scanner. The laser scanner may be mounted on a vehicle such as a van, truck, car or the like. The laser scanner may be mounted on an upper portion of the vehicle. The laser scanner may be operable to produce one or more laser beams. The laser scanner may be mounted at a front or rear of the vehicle. The laser scanner may be mounted so as to project at least one and preferably a plurality of laser beams onto a road upon which the vehicle is travelling and/or an area adjacent or proximate to the road. The laser scanner may be mounted so as project at least one laser beam onto a surface of the road below or immediately in front of or behind the vehicle. A point on the road for which a laser beam has been projected and distance data determined may be a measurement point.

The method may comprise retrieving existing road data for the road, for example, from a database, which may comprise retrieving centreline location information.

The method may comprise determining the height or altitude of at least one point on the road, which may be at least partially determined from the laser scan data.

The method may comprise determining at least one reference point of the road surface. The at least one reference point may comprise at least one measurement point that was below the vehicle when collected or determined to have passed below the vehicle, for example being immediately in front or behind and centrally of the vehicle.

The method may comprise offsetting the height or altitude of at least one measurement point by the height or altitude of at least one reference point. The method may comprise offsetting the height or altitude of measurement points by the height or altitude of a reference point until a further reference point is collected, whereupon the height of subsequently determined measurement points are offset by a height or altitude of the further reference point.

In this way a normalised laser scan data set may be generated. Since road surfaces are generally substantially flat in the widthwise direction, the heights or altitudes of each measurement point representative of a section of road surface are effectively set to the same value.

Since reference points are selected that are representative of the road surface, it will be appreciated that data points of objects that project above the surface of the road, such as cars, kerbs, signs, lamp posts and the like, will still have a height or altitude greater than that of the road surface, even though the measurement data has been offset in height or altitude.

The height or altitude offset may not be applied for data points toward an edge or perimeter of the laser scan data, such as a portion of the laser scan data representing the edge of the road.

The method may comprise separating the measurement points by traffic direction associated with a road or part of a road associated with the measurement point.

The method may comprise producing or providing composite laser scan data. The laser scan data may comprise composite laser scan data. The composite laser scan data may comprise at least two laser scan data sets, which may be laser scan data sets collected by laser scanners moving in substantially opposite directions. Laser scan data relating to one side of a centreline of the road may comprise laser scan data collected by a laser scanner moving in a first direction, whilst laser scan data relating to another side of the road may comprise laser scan data collected by a laser scanner moving in an opposite direction.

The method may comprise determining a centreline of the road. The method may comprise removing at least a portion of the centre points associated with the centreline of the road, which may comprise removing measurement points within a predetermined threshold of the centreline of the road and/or a centre of the scan data.

The method may comprise applying a height or altitude filter to the laser scan data. Applying the height or altitude filter may comprise removing any laser scan data associated with a height or altitude above an upper filter threshold. The upper filter threshold may be between 0.2 and 2 metres, such as 0.25 metres.

The method may comprise removing any laser scan data points within a predetermined threshold distance of any points that are above the upper filter threshold. The threshold distance may be between 1 m and 2m.

The method may comprise applying edge detection. The edge detection may comprise determining a widthwise gradient indicated by the laser scan data. The edge detection may comprise determining portions of the laser scan data having a widthwise gradient above a threshold, wherein these portions of the laser scan data may be associated with a kerb or road edge. The edge detection may comprise removing any laser scan data where a horizontal distance to at least one adjacent measurement point is greater than the vertical distance between the measurement points.

The method may comprise applying a noise filter. Applying the noise filter may comprise determining a number of remaining laser scan data points that lie at a plurality of distances from a centreline of the road and removing any laser scan data points having distances from the centreline where there are fewer than a threshold number of data points at that distance. The threshold number of data points may be a predetermined threshold or be a fraction or percentage of the number of measurement point associated with a distance from the centreline having the largest number of measurement data points.

The method may comprise connecting at least a portion of the remaining points in order to determine road corridor edges.

The method may comprise acquiring location data associated with the laser scan data. The position data may comprise at least one of GPS data, inertial sensor data, odometer data, pressure data, altitude data, bearing or heading data, and the like.

By applying the above processing scheme, a fully automated road edge or road corridor detection method may be implemented.

According to a second aspect of the present invention is a system for determining road data, comprising:

a processor configured to acquire laser scan data for at least one road section, the laser scan data representing distances from a laser scanner to one or more points on and/or adjacent the at least one road section; and determine at least one boundary or perimeter of the road from the laser scan data.

The laser scan data may be pre-generated laser scan data, which may be retrievable from a database via a communications system or from a memory.

The system may comprise at least one laser scanner. The system may comprise at least one location determining sensor, such as a GPS, an inertial sensor, an odometer, a direction or bearing sensor such as an electronic compass, a speed sensor or the like. The system may comprise or be comprised in a vehicle such as a car, van or truck.

The at least one laser scanner may be mounted on a front or rear of the vehicle. The at least one laser scanner may be mounted on an upper portion of the vehicle.

The laser scanner may be configured to project the laser beam downwardly, such as obliquely downwardly. The laser scanner may be configured to project at least one laser beam onto a road upon which the vehicle is travelling.

According to a third aspect of the present invention, there is provided a computer program element comprising computer program code means to make a computer execute the method as set forth above in relation to the first aspect of the invention or to implement the apparatus as set forth in the second aspect of invention.

The computer program element may be embodied on a computer readable medium.

According to a fourth aspect of the present invention is an apparatus when programmed with the computer program product of the third aspect.

Advantages of these embodiments are set out hereafter, and further details and features of each of these embodiments are defined in the accompanying dependent claims and elsewhere in the following detailed description.

It will be appreciated that features described in relation to any of the above aspects of invention may also optionally be applicable to any other aspect of invention. Furthermore, it will also be appreciated that method features analogous to any described apparatus features are intended to fall within the scope of the disclosure and vice versa.

Brief Description of the Drawings

At least one embodiment of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

Figure 1 is a schematic illustration of a vehicle including a navigation or mapping system according to one embodiment;

Figure 2 shows a block diagram of a computer based arrangement with may be used in the implementation of the invention;

Figure 3 shows a flow chart of an example of a process for generating images of map objects according to the invention;

Figure 4 shows laser scan data collected using the vehicle of Figure 1 ;

Figure 5 shows a perspective view of a part of the road surface associated with the laser data of Figure 4;

Figure 6 shows a normalised set of laser scan data associated with the part of the road surface shown in Figure 5;

Figure 7 shows the laser scan data set of Figure 4 after having been subjected to a normalization procedure; Figure 8 shows a composite laser scan data set;

Figure 9 shows a height filtering operation being performed on the laser scan data set of Figure 8;

Figure 10 shows the laser scan data set of Figure 9 after being subjected to height filtering operation shown in Figure 9;

Figure 11 shows a histogram illustrating a variation of altitude with distance from a road centre in a width wise cross section of the laser scan data of Figure 10;

Figure 12 shows the laser scan data set of Figure 10 after being subjected to a width wise gradient filter;

Figure 13 shows a histogram illustrating the number of measurement points of the laser scan data set of Figure 12 at certain distances to the road centre line; and

Figure 14 shows a road corridor generated from the laser scan data set of Figure 12.

Detailed Description of Preferred Embodiments

Throughout the following description, identical reference numerals will be used to identify like parts.

Figure 1 is an illustration of a mobile mapping system (MMS) in the form of a vehicle 2 that includes a vehicle navigation system 4 and associated laser sensors in the form of laser scanners 6, 8. The laser scanners 6, 8 are arranged on the rear of the vehicle and on an upper portion of the vehicle. The laser scanners 6, 8 are arranged so as to project one or more beams obliquely downwardly, and in this case also forwardly, onto a road upon which the vehicle is located. In this way, the laser scan data can be indicative of, or usable to determine, a height or altitude of points of a surface of the road. The scanners 6, 8 comprise a laser transmitter for transmitting a pulsed or continuous beam of laser radiation, a laser detector for detecting reflected laser radiation, and a processor for controlling the scanning of a laser beam by the scanners and for processing and recording the results of measurements. The laser sensor processor is operable to determine the distance to a surface of a road 10, or other object or surroundings with which the laser sensor is aligned and from which the laser radiation is reflected using, for example, time-of-flight measurements or other known ranging techniques. Each laser scanner is configured to scan the laser beam across a laser scanned area and to perform range measurements along different directions within the laser scanned area. Any suitable laser scanners 6, 8 can be used, for example Sick (RTM) LMS291 -S05 scanners. The processor of the MMS 2 may be part of, or communicatively linked to, a computer based system 9 for processing the laser scan data resulting from the laser scan measurements of the road. In an optional embodiment, the computer based system is a map generation system. The computer based system can optionally be comprised in the MMS 2 or be a remote system, for example, for post processing of the laser scan data.

In figure 2, an overview is given of a suitable computer based system 9 comprising a processor 11 . The system is also provided with a graphics processor unit 7. The processor 1 1 is connected to a plurality of memory components, including a hard disk 12, Read Only Memory (ROM) 13, Electrically Erasable Programmable Read Only Memory (EEPROM) 14, and Random Access Memory (RAM) 15. Not all of these memory types need necessarily be provided. Moreover, these memory components need not be located physically close to the processor 11 but may be located remote from the processor 11.

The processor 11 is also connected to means for inputting instructions, data etc. by a user, like a keyboard 16, and a mouse 17. Other input means, such as a touch screen, a track ball and/or a voice converter, known to persons skilled in the art may also be provided. A reading unit 19 connected to the processor 11 is provided. The reading unit 19 is arranged to read data from and/or write data to a data carrier like a floppy disk 20 or a CDROM 21. Other data carriers may be tapes, DVD, CD-R. DVD-R, memory sticks etc. as is known to persons skilled in the art.

The processor 11 is also connected to a printer 23 for printing output data on paper, as well as to a display 18, for instance, a monitor or LCD (Liquid Crystal Display) screen, or any other type of display known to persons skilled in the art.

The processor 11 may be connected to a loudspeaker 29.

The processor 11 may be connected to a communication network 27, for instance, the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), the Internet etc. by means of communications system 25. The processor 11 may be arranged to communicate with other communication arrangements through the network 27. The data carrier 20, 21 may comprise a computer program product in the form of data and instructions arranged to provide the processor with the capacity to perform a method in accordance with the invention. However, such computer program product may, alternatively, be downloaded via the telecommunication network 27. The processor 11 can optionally be implemented as a standalone system, or as a plurality of parallel operating processors each arranged to carry out subtasks of a larger computer program, or as one or more main processors with several sub-processors. Parts of the functionality of the invention can even be carried out by remote processors communicating with processor 11 through the network 27. The computer arrangement does not need to have all of the components shown in figure 2, particularly when applied in an MMS 2. For instance, the computer arrangement does not need to have a loudspeaker and printer. As for the implementation in the MMS 2, the computer arrangement needs at least processor 11 , some memory to store a suitable program and some kind of interface to receive instructions and data from an operator and to show output data to the operator.

For post-processing the laser scan data taken by the laser scanner(s), a similar system to the one shown in Figure 2 can be used. The system need not be located in the MMS 2 but may conveniently be located, for example, in a building for off-line postprocessing. The laser scans taken by scanner(s) 6, 8 are stored in one of the memories 12- 15. That can be done by first storing the laser scan data on a DVD, memory stick or the like, or transmitting them via the communications system 25, possibly wirelessly, from the memory 9.

Figure 3 shows a method for automatically generating road corridors from laser scan data. In step 205, laser scan data for a road section is acquired.

The laser scanners 6, 8 of the MMS 2 are operable to project a plurality of beams 12 onto the surface of the road 10 and an area surrounding the road 10 (as shown in Figure 1 ). The MMS 2 is driven along the road 10 whilst laser scan data is collected, using a matrix of laser scan measurement points. The distance between the laser scanners 6, 8 and various measurement points on and adjacent to the road surface 10 is determined in order to form laser scan data for the road, as illustrated in Figure 4. The laser scan data can be correlated to a location determined using location determining apparatus 4 of the MMS 2, such as GPS and/or inertial sensors. Other location or geographical properties that can be associated with the laser scan data can also be collected, for example, a height or altitude using barometric or other sensors, a bearing or orientation using an electronic compass, or the like. The laser scan data is then processed by the processor 11 in order to determine map data in the form of a road corridor for the road.

It will be appreciated that the map data may be determined in-situ by a suitable computer system comprised in the MMS 2 or carried out by way of post processing, for example, at a location remote from the MMS 2, such as a remote building, which may be carried out later than collection of the data. In this case, the laser scan data is transferred to processing apparatus at the remote building from the processor of the MMS 2 via means known in the art, such as a wireless network, the internet, a cabled connection or via a computer readable medium such as a CD-ROM, a memory stick or the like.

As indicated by step 210 of Figure 3 and shown in Figures 5 and 6, the laser scan data for the road 10 is processed using a height or altitude offset procedure, which comprises selectively offsetting the height or altitude of the measurement data points such that a normalised laser scan data set for the road surface is produced in which each laser scan data point representative of the road surface has substantially the same height or altitude.

An example of a suitable offset procedure comprises determining reference laser scan data points 405, 405b, 405c, 405d, as illustrated in Figure 5. The reference laser scan data points 405, 405b, 405c, 405d comprise laser scan data point for which there is a high degree of certainty that the data points relate to the road surface 10. Advantageously, the reference data points 405, 405b, 405c, 405d may be data points taken from below the MMS 2, or would have a high probability of being points that have or will have passed below the MMS 2, such as centrally and immediately behind the MMS 2. The height or altitude of the reference data point 405, 405b, 405c, 405d is determined and stored. The heights or altitudes of subsequently determined measurement points of the road surface are lowered by an offset equal to the height or altitude of the most recently stored reference point 405, 405b, 405c, 405d. When a new reference point 405, 405b, 405c, 405d is taken, the subsequently collected laser scan data points have their altitude or height offset by a height or altitude equivalent to the latest reference point 405, 405b, 405c, 405d and so on. The reference points 405, 405b, 405c, 405d may be collected periodically or according to other predetermined criteria.

Since roads are generally level in a width wise direction, this procedure results in a normalised or offset laser scan data set, as illustrated in Figures 6 and 7, wherein each laser scan data point associated with the road has substantially the same height or altitude. Of course, it will be appreciated that laser scan data points associated with other features that project above or below the height of the road, such as kerbs, cars, lamp posts, signs and the like, will still have a differing height or altitude relative to that of data points associated with the road. A local offset, using a most recently determined reference point is used rather than a global offset, thereby allowing the local height or altitude differences to be kept for further analysis.

Use of the normalization process permits the possibility of analyzing more than one data set for the same road and choosing which is the best for analysis, As indicated as step 215 of Figure 3, a portion of the laser scan data points that are collected by a vehicle going in a travelling direction are selected for use, and optionally, a composite laser scan data set may be formed. For example, in many countries, traffic tends to drive on the right hand side of the road. In this case, the laser scan data for the right hand carriageway may be of better quality than laser scan data for the left hand carriageway. In order to utilise this, a composite laser scan data set can be created, as shown in Figure 8, wherein the laser scan points 805 for one side of a centreline 810 of the road are acquired from a MMS 2 travelling in that prevailing direction, whilst the laser scan data points 815 from the other side of the centreline 810 are collected from a MMS 2 travelling in an opposite direction. Some data points around the centreline 810 may be removed according to a predetermined criterion in order to prevent interference between the data sets.

As indicated in step 220 of Figure 3 and shown in Figures 9 and 10, a height or altitude filter is applied to the composite normalised laser scan data set. In this case, any laser scan data points 905 indicative of a height from the road surface of greater than an upper filter threshold are removed from the laser scan data set. The upper filter threshold is set to a value greater than the height of items that may indicate a road side, such as kerbs or barriers, but lower than a height associated with potentially interfering objects such as cars or other vehicles. An upper filter threshold of between 0.2m and 1 m, such as 0.25m may be used. Examples of the laser scan data points 905 to be removed from the laser scan data using the above technique is shown in Figure 9. In this way, the laser scan data points that have been reflected from parked or other cars or other undesired objects such as lamp posts, and the like (having a height larger than the threshold, e.g. 0.25m) are removed from the laser scan data set. In order to ensure that these undesired objects do not unduly affect the road corridor determination, the laser scan data points within a certain radius of the laser scan data points having a height or altitude above the upper filter threshold are also removed. Examples of suitable radii include radii of between 1 to 2m. The resulting laser scan data set is shown in Figure 10.

As indicated in step 225 of Figure 3, an edge detection procedure is applied to the laser scan data set. In this example, the edge detection comprises application of a widthwise gradient filter, illustrated with reference to Figure 11 . Figure 11 shows a histogram representing a cross section in a widthwise direction of the laser scan data set, illustrating the variation in height or altitude of the normalized measurement points represented by the laser scan data set with distance from the centre line of the road. The gradient or rate of change of the height or altitude of the measurement points in the widthwise direction of the road is used to determine the road edges. Laser scan data points associated with a widthwise gradient less than a threshold are removed from the data set. For example, if the horizontal distance between adjacent measurement points is greater than the vertical distance between those points, then those measurement points are removed from the laser scan data set. The resulting laser scan data set is illustrated in Figure 12. It can be seen from Figure 12 that the remaining laser scan data points 1205 are those associated with a road edge or kerb on each side of the centreline 810, along with some noise. The remaining laser scan data points are subjected to a noise filter, as indicated by step 230 of Figure 3. For example, this may comprise constructing a histogram representing the number of remaining laser scan data points at certain distances relative to the centreline of the road, as illustrated in Figure 13. It can be seen from this that certain distances are associated with preferential or large numbers of data points. The laser scan data points associated with distances from a centre of the road having less than a threshold number of remaining associated laser scan data points are determined to be noise and are removed from the laser scan data set.

The remaining laser scan data points are representative of road edges. As indicted by step 235 of Figure 3, these remaining data points may be connected appropriately in order to form edges of the road in a road map, as illustrated by Figure 14.

In this way, the edges and extent of the road can be automatically detected from the laser scan data with minimal or no manual intervention. Optionally, the resulting road edges may be combined with location data associated with the remaining laser scan data points in order to form at least part of a road map.

It will also be appreciated that whilst various aspects and embodiments of the present invention have heretofore been described, the scope of the present invention is not limited to the particular arrangements set out herein and instead extends to encompass all arrangements, and modifications and alterations thereto, which fall within the scope of the appended claims.

Whilst embodiments described in the foregoing detailed description refer to GPS, it should be noted that the mobile device 200 may utilise any kind of position sensing technology as an alternative to (or indeed in addition to) GPS. For example the navigation device may utilise using other global navigation satellite systems such as the European Galileo system. Equally, it is not limited to satellite based but could readily function using ground based beacons or any other kind of system that enables the device to determine its geographic location, such as location determination systems based on image recognition, laser based systems and/or user input.

Furthermore, various examples of non-GPS sensors have been described, it will be appreciated that a suitable system need not have all of the non-GPS sensors described but may instead have alternative or varying combinations of non-GPS sensors, which may include non-GPS sensors other than those described herein that would be apparent to a person skilled in the art in view of the teaching of the present application.

Although the laser scanners are described and shown as being located at the rear of the vehicle, it will be appreciated that other laser scanner positions having a sight-line to the road may be used, such as in front of the vehicle.

Alternative embodiments of the invention can be implemented as a computer program product for use with a computer system, the computer program product being, for example, a series of computer instructions stored on a tangible data recording medium, such as a diskette, CD-ROM, ROM, or fixed disk, or embodied in a computer data signal, the signal being transmitted over a tangible medium or a wireless medium, for example, microwave or infrared. The series of computer instructions can constitute all or part of the functionality described above, and can also be stored in any memory device, volatile or nonvolatile, such as semiconductor, magnetic, optical or other memory device.

It will also be well understood by persons of ordinary skill in the art that whilst the preferred embodiment implements certain functionality by means of software, that functionality could equally be implemented solely in hardware (for example by means of one or more ASICs (application specific integrated circuit)) or indeed by a mix of hardware and software. As such, the scope of the present invention should not be interpreted as being limited only to being implemented in software.

Lastly, it should also be noted that whilst the accompanying claims set out particular combinations of features described herein, the scope of the present invention is not limited to the particular combinations hereafter claimed, but instead extends to encompass any combination of features or embodiments herein disclosed irrespective of whether or not that particular combination has been specifically enumerated in the accompanying claims at this time.

Claims

1 . A method for determining road data, comprising:

acquiring laser scan data for at least one road section (10), the laser scan data representing distances from a laser scanner (6, 8) to one or more points on and/or adjacent the at least one road section (10); and

determining at least one boundary or perimeter (1205) of the road section (10) from the laser scan data.

The method as claimed in claim 1 , wherein the method comprises determining the height or altitude of at least one point on the road section (10) at least partially from the laser scan data.

The method according to any claim 1 or claim 2, wherein the method comprises determining at least one reference point (405a-d) of a surface of the road section (10), the at least one reference point (405a-d) comprising at least one laser scan measurement point that was below or had passed below or will pass below a vehicle comprising the laser scanner (6, 8).

The method according to claim 3, wherein the method comprises offsetting the height or altitude of at least one laser scan measurement point by the height or altitude of the at least one reference point (405a-d).

The method according to any preceding claim, wherein the laser scan data comprises composite laser scan data, the composite laser scan data comprising at least two laser scan data sets (805, 815), the laser scan data sets (805, 815) collected by laser scanners (6, 8) moving in substantially opposite directions.

The method according to claim 5, wherein the laser scan data relating to one side of a centreline (810) of the road section (10) comprises laser scan data (805) collected by a laser scanner (6, 8) moving in a first direction, whilst laser scan data (815) relating to another side of the centreline (810) comprises laser scan data (810) collected by a laser scanner (6, 8) moving in an opposite direction.

The method according to any preceding claim, wherein the method comprises applying a height or altitude filter which comprises removing any laser scan data associated with a height or altitude above an upper filter threshold.

8. The method according to claim 7, wherein the method comprises removing any laser scan data within a predetermined threshold distance of any laser scan data points that are above the upper filter threshold.

9. The method according to any preceding claim, wherein the method comprises applying edge detection to determine edges (1205) of the road.

10. The method according to claim 9, wherein the edge detection comprises determining a widthwise gradient indicated by the laser scan data and determining portions of the laser scan data having a widthwise gradient above a threshold.

1 1 . The method according to claim 10, wherein the edge detection comprises removing any laser scan data where a horizontal distance to at least one adjacent laser scan measurement point is greater than the vertical distance between the measurement points.

12. The method according to any preceding claim, wherein the method comprises applying a noise filter, the application of the noise filter comprising determining a number of laser scan data points that lie at a plurality of distances from a centreline (810) of the road section (10) and removing any laser scan data points having distances from the centreline (810) where there are fewer than a threshold number of data points at that distance.

13. The method according to any preceding claim, comprising connecting at least a portion of the laser scan data points in order to determine road corridor edges.

14. A system (2, 10) for determining road data, comprising:

a processor (11 ) configured to acquire laser scan data for at least one road section (10), the laser scan data representing distances from a laser scanner (6, 8) to one or more points on and/or adjacent the at least one road section (10); and further configured to determine at least one boundary or perimeter of the road section (10) from the laser scan data.

15. The system (2, 10) according to claim 14, wherein the system (2, 10) comprises or is comprised in a vehicle, the vehicle comprising the laser scanner (6, 8), the laser scanner (6, 8) being configured to project at least one laser beam onto the road section (10) upon which the vehicle is travelling.

16. A computer program element comprising computer program code means to make a computer execute the method claimed in any of claims 1 to 13 or to implement the apparatus as claimed in any of claims 14 or 15.

17. An apparatus when programmed with the computer program product of claim 16.