Patent Publication Number: US-2022221296-A1

Title: Computer implemented method for guiding traffic participants

Description:
BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The invention relates to a computer implemented method for guiding a traffic participant, especially a pedestrian, especially a visually impaired or blind person, especially for guiding in urban environments, between at least two places. 
     Description of the Related Art 
     With the public accessibility of the Global Positioning System (GPS) and the development of continuously stronger, transportable computational devices—such as smartphones—the use of computerized navigational systems has become wide spread among motorized and unmotorized traffic participants alike. However, visually impaired and blind people who probably need assistance the most when navigating in traffic cannot use the current navigational systems. 
     SUMMARY OF THE INVENTION 
     Hence it is an object of the invention to overcome the aforementioned obstacles and drawbacks and to provide a navigational system that can be used by any traffic participants and in particular by visually impaired and blind people. 
     This problem is solved by the method disclosed and claimed. 
     Further preferred and advantageous embodiments of the invention are also disclosed. 
     In the following a depiction of a preferred embodiment of the invention and the problems within the current technology are described. 
     The described embodiments and aspects are solely meant to exemplify the invention and its related problems, which is not limited to the shown examples but may be implemented in a wide range of applications. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will be described with reference to the included drawings, in which: 
         FIG. 1  shows a draft urban scene exemplifying the problem, 
         FIG. 2  shows the scene from  FIG. 1  with a path that is generated according to the invention, 
         FIG. 3  another urban scene with a path that is generated according to the invention, 
         FIG. 4  a two-dimensional map, 
         FIG. 5  an aerial view the region shown in  FIG. 4 , 
         FIG. 6  a conventional three-dimensional map of the region shown in  FIG. 4 , 
         FIG. 7  a depth image of the approximate region shown in  FIG. 4 , 
         FIG. 8  a multi-modal three-dimensional map of a section of the region shown in  FIG. 4 , 
         FIG. 9  the multi-modal three-dimensional map of  FIG. 8  with a path that is generated according to the invention and 
         FIG. 10  a flow chart roughly depicting a method of localizing a user of the system. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       FIG. 1  shows an urban scene  1  with a pavement  2 , a building  3  that is built closer to the street, a building  4  that is built more distant from the street, a flower bed  5 , lamp posts  6  and parked cars  7 .  FIG. 1  also shows an exemplary route  8  as it might be calculated by a conventional navigational system. It can be clearly seen, that the actual route taken by a pedestrian normally would deviate from the shown straight line and take the flower bed  5  and the building  3  closer to the street into consideration. However, this action requires the pedestrian to know about the flower bed  5  or the irregularly placed houses  3 ,  4 . This information can be easily acquired by simply being at the scene and seeing the placement of the aforementioned urban elements. But with the lack of visual information to assess the scene the given route  8  is insufficient and can even be dangerous, for example by causing a blind person to stumble over the edge of the flower bed  5  which occasionally cannot even be detected by a white cane. 
     The scene shown in  FIG. 2  is the same as shown in  FIG. 1  with an improved path  9 , that—if followed by a pedestrian—requires no adjustment due to obstacles. The flower bed  5  and the differently placed buildings  3 ,  4  are no longer a danger. 
     Two other problems are illustrated in  FIG. 3 . Firstly, there is the problem that arises when a visually impaired pedestrian wants to cross a street  10 . Given that safety is of paramount importance, any route that requires the crossing of streets must be built so that zebra crossings  11  are always prioritized over other routes. Secondly, especially in urban surroundings, stationary installations like bollards  12 , lamp posts  6  (see  FIG. 1 ), trash bins  13 , street signs  14  and the like are safety hazards that have to be circumvented. An optimized path  15  that meets these requirements is also shown in  FIG. 3 . 
     To create and efficiently use such an optimized path  9 ,  15  three major properties of the system are highly advantageous. Firstly, a route as precise and fine-granular as possible is to be defined on a map. Secondly, the location of the user ought to be known with very high accuracy and within very fine measurements, approximately within only a few centimeters, in order for a user to be able to follow the route. The usual “couple of meters”—accuracy provided by current technology such as GPS or magnetic sensors (mobile device compasses) are not sufficient. Thirdly, in order for a blind or visually impaired person to make use of the path information, it is to be conveyed in a way such that such a person can use it. 
     To accomplish this task, a guiding system for visually impaired or blind people according to the invention must include carrying out the Steps:
         A. providing a multi-modal three-dimensional map,   B. calculating a route based on the multi-modal three-dimensional map connecting the at least two places over at least one intermediate waypoint,   C. determining a precise location of the traffic participant, preferably by using the multi-modal three-dimensional map and   D. setting beacons along the path at the waypoints.       

     A multi-modal three-dimensional map as it is provided in step A is derived from two or more different sources whereby each source adds another layer of information. A precise but conventional map may contain information on where the pavements and streets are, but it probably does not discern between pavement and flowerbeds. A (municipal) tree inventory can provide information on the location of trees; this is often combined with a garden and parks department where the precise location of public flower beds is charted. Municipal utilities can provide information on electricity (street lamps) and water (hydrants, manholes). The department responsible for traffic can provide plans where traffic lights, zebra crossings and the like are located. 
     Next to the aforementioned cartographic and geodetic information other sources can be added to a multi-modal three-dimensional map, such as: areal views, satellite pictures, surface texture data or conventional 3D-data. The latter being plain geometric information on three-dimensional objects like for example the shape and location of houses. 
     The list of possible sources to create a multi-modal three-dimensional map is not exhaustive and can be expanded to reflect the distinctive peculiarities of a city or region, for example cycling tracks on the pavements, spaces reserved for horse carriages, tramway tracks, stairs, the type of paving (especially cobble stones), monuments, (park) benches, drinking fountains, trash bins, bicycle stands, outdoor dining areas of restaurants or defibrillators. 
       FIG. 4  to  FIG. 6  show different examples for freely available maps and information that can be combined into a multi-modal three-dimensional map.  FIG. 4  shows a two-dimensional map.  FIG. 5  shows a reconstructed areal view, that is derived from satellite pictures with many different datasets from different satellites with different sensors.  FIG. 6  shows a three-dimensional model of the region depicted in  FIG. 4  and  FIG. 5 .  FIG. 7  shows a so called “depth image” of the region shown in  FIG. 4  to  FIG. 6 . A depth image shows distances along a defined axis, with more distant surfaces usually being depicted darker and closer surfaces being depicted lighter. In the example shown the defined axis is the vertical. Brighter parts of the depth image are in conclusion higher and darker parts flatter or lower. In the case of the urban scene the depth image in  FIG. 7  hence shows the height of buildings and other structures. 
     All the data layers can be obtained from a multitude of available sources. A preferred way of obtaining data is through open sources. For example, the two-dimensional map data, the aerial view/map and conventional three-dimensional map data are available, in many cases without any usage limitation, e.g. from the OpenStreetMap Foundation. Moreover, other sources such as government institutions have publicly available geographic data about cities. 
     For example, the city of Vienna has the three previously mentioned sources as well as the aforementioned surface model from which one can extract the height of objects present at each of the points in the map. In total the city of Vienna has over 50 different datasets with several levels of detail that can be used to create a multi-modal three-dimensional map. 
     In a preferred embodiment of the invention the different layers of the multi-modal three-dimensional map are combined in a spatially coherent way. Spatial coherence can for example be achieved by defining objects and features, like houses, in a common coordinate system. By taking this step alone the layers are already aligned to some extent. Moreover, a more precise alignment can be obtained by using image registration methods, based on features present in both map layers (for example buildings in aerial view and two-dimensional layer) which are well known in the art. With this alignment, the location of objects which are only present in some layers (for example road limits or fire hydrants) can be correlated with all the other map features in the multi-modal map. 
     If combined the following information can be extracted from the different exemplary types of datasets shown in  FIG. 4  to  FIG. 7 : 
     The three-dimensional layer, for example, can yield the information on the precise location of buildings&#39; walls  19  (see  FIG. 8 ) or edges  20  (see  FIG. 8 ). A border  22  (see  FIG. 9 ) between pavement  2  and street  10  can be extracted from the aerial view. A combination between the depth image and three-dimensional map yields very good estimations on the correct location of trees (see obstacles  21  in  FIG. 8 ) for example. All sources of information mentioned in this example that is located in the city of Vienna are freely available open data from the city government and other non-governmental sources. A multi-modal three-dimensional map can also be very useful independently of the invention, for example when automatically guiding autonomous vehicles or planning the transport of large objects on the street. 
     According to a further embodiment of the invention, at least one walkable space is defined within the multi-modal three-dimensional map. The walkable space can be according to a very simple example every pavement minus everything that is not pavement, for example pavement minus every bench, trash bin, sing post, lamp post, bollard, flower bed, etc. In this case the walkable spaces can be defined automatically. Of course, the walkable spaces can also be defined manually. 
     Next to the essentially stationary, aforementioned objects other aspects can also be taken into consideration. For example, the entrance area of a very busy shop can be excluded from the walkable space and circumvented. 
     Accordingly step B is preferably carried out based on the multi-modal three-dimensional map especially based on the walkable space. 
     Also, when carrying out step B (calculating a path) two walkable spaces can be connected via at least one waypoint. Furthermore, if two or more walkable spaces are not bordering each other within the multi-modal three-dimensional map, at least one transitioning space is defined and a transitioning space bridges a gap between said two or more walkable spaces. 
     This is illustrated in  FIG. 3 . The pavement  2  is not directly bordering the other remote pavement  16 . They are connected via two waypoints  17 ,  18 . Between them there is a zebra crossing  11 . In this case the zebra crossing  11  is the transitioning space that bridges the gap between the two pavements  2 ,  16 . Other types of transitioning spaces can for example be traffic lights and way between them. However, even stairs or spaces with difficult pavement like cobble stones can be transitioning spaces, if they are not considered to be a safe walking space. 
     Another aspect of the invention is illustrated in  FIG. 8  and  FIG. 9 . They show a very simplified example of a two-dimensional view of a multi-modal three-dimensional map. 
     The multi-modal three-dimensional map shows the building  3 , the street  10  and the pavement  2  just as a normal map would show. However, grace to the additional layers of information the correct location of the building&#39;s  3  walls  19  and edges  20  are correctly noted with their actual location. Trees  21  have been registered and placed accordingly. The same applies for the now correctly noted border  22  between pavement  2  and street  10 . 
     According to one preferred embodiment of the invention at least one obstacle is identified and marked in the multimodal three-dimensional map and at least one waypoint is set to circumvent said obstacle. 
     As can be seen in  FIG. 9  a path  15  has been created along several waypoints  23  that are circumventing obstacles, such as walls  19 , corners  20 , trees  21 , and avoiding the border  23  between street  10  and pavement  2 . 
     When setting the waypoints  23  automatically or manually it is important to try to be at a maximum distance to any spaces that are not walkable spaces. An easy way to find suitable places for waypoints could be to identify any bottleneck and to place the waypoints essentially in the middle of the bottleneck to achieve a maximum distance to all spaces that are not walkable spaces. 
     In order to follow the now created path, the precise location of the person (or vehicle/drone) has to be known. This can preferably be done by locating a device that is used to carry out the computer implemented method, for example a smartphone. However, the methods to locate devices are not precise enough to safely tell where along a path the device is located or if on or near the path at all. 
     One possible method to determine the precise location of the traffic participant during step C of the invention is shown in the flow-chart in  FIG. 10 . 
     The depicted preferred embodiment includes the following sub-steps:
         a. acquiring a real view by processing at least one digital picture of the surrounding,   b. generating at least one possible artificial view based on a raw location, the raw location providing a scene that is part of the multi-modal three-dimensional map and that is being depicted to provide the artificial view,   c. comparing the artificial view and the real view,   d. if the artificial view and the real view are essentially the same, providing location as the point of view the artificial view was generated from, and completing the subprocess,   e. if the artificial view and the real view are not essentially the same repeating the subprocess with at least one different artificial view.       

     Step a. can be simply carried out by photographing the scene in front of the device that is used to carry out the process. If the device is a smartphone, the smartphone camera can be used. 
     Filming a scene is also considered taking photographs since filming basically is taking photographs with a (higher) frame rate. 
     A succession of pictures that is strung together to create a lager real view is also considered to be within the scope of the invention. 
     Then at least one artificial view is created. This can be done for example by using a ray-caster as it is well known to those skilled in the art. A simple ray-caster casts rays from a certain point of view through a 3D-surface and renders the first surface the ray(s) meet. More sophisticated ray-casters can take material into consideration and for example even render a view as if it has passed through glass. However, for this embodiment of the invention a very simple ray-caster is sufficient. Other methods of rendering 3D-images may also be employed. In case of this embodiment the 3D-surface is the multi-modal three-dimensional map. 
     The point of view is a raw location. The raw location can be obtained by any known locating means, for example GPS, magnetic sensors or an inertial navigation system that uses motion sensors like accelerometers and gyroscopes. The raw location estimation can also be improved by considering part or all of the previous known precise locations in the map. This information can be used, together with geometrical constraints (like walls) of the map, to reduce uncertainty in current raw location estimated from the sensor. For example, a person cannot stand where there are buildings or trees. 
     The artificial view and the real view are then being compared. If they are essentially the same, the point of view of the artificial view is considered the traffic participant&#39;s location. If they are not the same, further artificial views are compared to the real view until a location has been determined. 
     One problem that can impede the aforementioned method to determine a location is that the view of the camera that takes the picture that is used to create the real view is obstructed. These obstructions can be any objects that are between the surfaces and objects of the multi-modal three-dimensional map and the camera. Usual causes for such an obstruction are dynamic objects that can be part of the scenery but are not captured by the multi-modal three-dimensional map, such as cars  24 , pedestrians  25  (see  FIG. 3  for both), non-permanent art installations or advertisements such as A-frames. 
     Even if the threshold to consider the real view and the artificial view is set very coarse, a high number of dynamic objects can lead to false negatives when comparing views. To avoid this problem, when processing the digital picture to create the real view a sub-step “i. Removing of dynamic objects from the picture” is carried out. One possible means to remove dynamic objects is by identifying them with an artificial intelligence, for example a convolutional neural network that is trained to identify pedestrians, cars, bicycles and the like in pictures. 
     The described method of determining a location can be advantageously implemented independent of the invention. It can be used in combination with the aforementioned other characteristics of the invention or on its own. 
     Once the precise location has been determined the relation between a user and its surroundings is known and an augmented reality that precisely fits reality can be created. 
     The user in this case does not need to be known in the art. It suffices if he is simply capable of operating the device on which the method is carried out, e.g. using a smartphone. 
     According to a preferred embodiment of the invention the beacons from step D are perceptible within said augmented reality. 
     For example, the perceptible beacons can be superimposed into the field of vision of a pair of smart glasses, within the picture that was taken to determine the location or within a camera view of the aforementioned device. 
     However, these means are of little to no help to visually impaired or blind users. Therefore, according to a further preferred embodiment of the invention the method is characterized in that the augmented reality is acoustic and that the beacons are audible at their respective locations. This can be realized for example via headphones that simulate noises at certain locations. In a simpler exemplary embodiment, the device itself generates a sound that gets louder when pointed towards the nearest beacon and lower when pointed away. When a beacon/waypoint has been reached a sound can be played to indicate that the sound for the next beacon is now played. Using a stereo technique, the sound can also be heard louder in the left speaker when the waypoint is at the left of the user and louder in the right speaker when the waypoint is at the right of the user. In a preferred embodiment, binaural virtual audio (also known as spatial audio or 3D audio) can be used. In this case, the device processes an audio source to simulate to the user that the sound is coming from the actual spatial location of the waypoint. As this technique simulates the way humans perceive direction and distance of a sound source, it is ideal to guide users through the path since it is a true means to implement virtual audio sources in space (audio augmented reality). 
     It is also preferred that only one beacon is active at a time. Preferably only the closest beacon along the path is active and it is switched to the next when the user reaches the respective waypoint. 
     The described method to guide people can be implemented advantageously independent of the invention and used for guiding systems that are based on other methods, for example for guiding people within a building. A possible method to locate the user relative to his surrounding could then for example be the use of RFID transponders within the building and a corresponding RFID chip on the user. 
     The augmented reality can of course contain further indicators, for example when reaching or crossing transitioning spaces or what type of transitioning space there is (zebra crossing, traffic light, stairs, ramp, lift, escalators and so on . . . ). 
     In general, every element that is noted in the multi-modal three-dimensional map can be part of the augmented reality. 
     A traffic participant according to the invention can not only be a pedestrian but also a bicycle rider, a drone, a car or the like.
           1  urban scene  14  street sign     2  pavement  15  path     3  building  16  pavement (not     4  building connected)     5  flower bed  17  waypoint     6  lamp posts  18  waypoint     7  cars  19  wall     8  route  20  edge/corner     9  path  21  tree     10  street  22  border     11  zebra crossing  23  waypoints     12  bollard  24  cars     13  trash bin  25  pedestrians