JPH0694470A - Vehicle position detecting device - Google Patents

Abstract

PURPOSE:To provide a vehicle position detecting device capable of detecting a road on which a vehicle is traveling without error. CONSTITUTION:The image of a road is taken by a video camera 6 set on a vehicle, and the road form is extracted from the image by an image analyzing part 7b. The extracted road form is collated with road forms in a map data to determine the road on which the vehicle is traveling or the present place.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle position detecting device, and particularly to a vehicle position suitable for use in an in-vehicle navigator which displays a vehicle position mark on a map image around the vehicle position so as to guide a vehicle. Regarding a detection device.

[0002]

2. Description of the Related Art There is a vehicle-mounted navigator which guides a vehicle so that a driver can easily reach a desired destination. In this in-vehicle navigator, the vehicle position is detected, the map data (background layer, character symbol layer, etc.) around the vehicle position is read from the CD-ROM, the map image is drawn in the V-RAM, and the vehicle position is displayed in the map image. The marks are overlaid and drawn, and the image in the V-RAM is converted into a video signal and output to the CRT display and displayed on the screen. Then, as the vehicle position changes due to the movement of the vehicle, the vehicle position mark on the screen is moved, or the vehicle position mark is fixed at a specific position on the screen and the map is scrolled to always display the current position around the current position. The map information can be seen at a glance.

The map stored in the CD-ROM is divided into regions of a longitude width and a latitude width of appropriate sizes according to the scale level, and roads and the like have vertices (nodes) expressed in longitude and latitude. It is represented by a coordinate set, and these renderings are performed by connecting each node in sequence with a straight line. A portion connecting two or more nodes is called a road link.

Vehicle position detection methods include dead-reckoning navigation (self-contained navigation) that cumulatively obtains the vehicle position from the starting point using an azimuth sensor and a distance sensor, and absolute measurement based on the principle of triangulation using satellites. There is a satellite navigation method that seeks the vehicle position. Of these, the former type of dead reckoning has a simple structure, and even if satellite navigation cannot be used in tunnels where satellite radio waves do not reach or in urban areas where satellite radio waves are blocked by buildings or multiple reflections, the vehicle position can be reliably achieved. However, the accuracy of detection is poor because the sensor error and the error due to the meandering of the vehicle are accumulated, and especially when the mileage becomes long, the error becomes too large and the vehicle is located at a point far from the actual position. There is a drawback that the position mark is displayed.

For this reason, in the vehicle-mounted navigator, the road data for map matching is included in the map data so that the vehicle position detected by dead reckoning can be corrected using the road data. Map matching includes a projection method that corrects the vehicle position mark on the correct road by projecting the vehicle position obtained by dead-reckoning to the nearest road in the road data, and the movement locus and road of the vehicle position obtained by dead-reckoning navigation. There are two pattern matching methods of comparing the road shapes in the data to find a correct road on which the vehicle is running and correcting it on the road.

FIG. 14 is an explanatory diagram of a vehicle position correcting method by pattern matching. When the vehicle moves on the road RD ₁ in the northeast direction, changes to the east when it comes out on the road RD ₂ , turns north at the point Px and reaches the point Pc on the road RD ₃ , the vehicle position mark CM is point P
It is assumed that it is displayed on c'and the traveling locus RDT is shown by the dotted line. In the pattern matching, every time the vehicle travels for a predetermined distance, (1) the map data is used to search for a road path having the same shape as the shape of the traveling locus RTD,
(2) Pay attention to the reference point, for example, the latest node Px,
A point Pc on the road path RD such that x′Pc ′ = PxPc is obtained, and (3) after that, the vehicle position mark C
M is moved from point Pc 'to point Pc. According to this map matching process, the vehicle position can be corrected to the correct position even if the sensor has an error or the vehicle meanders to cause an error in the traveling distance.

[0007]

However, if the vehicle is shown in FIG.
Roads RD ₃ and RD ₄ divided at small angles as shown in
When there is more than one road path that is the same shape as the travel path, such as when entering one of them, it is not possible to determine which road path should be used to correct the vehicle position, and There is a problem of displaying the vehicle position and the traveling locus. This problem also occurs when map matching is performed by the projection method. In view of the above, an object of the present invention is to provide a vehicle position detection device that can detect the current position of a vehicle or a road on which the vehicle is running without error.

[0008]

According to the present invention, there is provided the above-mentioned object, a video camera installed in a vehicle for capturing an image of a road, an image analyzing means for extracting a road shape from an image captured by the video camera, and map data. It is achieved by providing a map data storage means for storing the above, and a collating means for collating the road shape extracted by the image analyzing means with the road shape in the map data to determine the road on which the vehicle is traveling or the present location.

[0009]

According to the present invention, the video of the road is captured by the video camera installed in the vehicle, and the road shape is extracted from the video.
Then, the extracted road shape is collated with the road shape in the map data to determine the road on which the vehicle is traveling or the current location. As a result, it is possible to accurately detect the road on which the vehicle is traveling or the current position without being affected by the sensor error or the error in the traveling distance due to the meandering of the vehicle.

[0010]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Overall Configuration FIG. 1 is an overall configuration diagram of an in-vehicle navigator according to an embodiment of the present invention. In the figure, 1 is a CD-ROM that serves as map data storage means, 2 is an operation panel, and scroll keys for left, right, up, and down directions for scrolling a map with respect to a vehicle position mark, map search, and enlargement / reduction Equipped with various keys for use. 3 is a direction sensor that detects an absolute direction of the vehicle traveling direction and outputs a direction signal. 4 is a distance sensor that outputs a pulse each time the vehicle travels a unit distance. 5 is a position calculation CP.
At U, the current position (longitude, latitude) of the vehicle is calculated based on dead reckoning from the respective signals input from the azimuth sensor 3 and the distance sensor 4.

Reference numeral 6 denotes a TV camera installed on the front part of the roof of the vehicle so as to point slightly downward from the horizontal and captures an image of the road ahead of the vehicle. Reference numeral 7 denotes an image recognition device which is an image captured by the television camera. The road shape is extracted and the road shape is extracted and collated with the road data in the map data to determine the road on which the vehicle is running or the current position of the vehicle. Reference numeral 7a denotes a still image extraction unit that periodically extracts a still image from a video captured by a television camera, and 7b sequentially performs binarization, edge detection, thinning, and feature extraction on the still image extracted by the still image extraction unit. An image analysis unit 7c for performing road shape extraction performs a comparison between the road shape extracted by the image analysis unit and the road data in the map data to determine the road on which the vehicle is running and the current location of the vehicle (matching unit). Section).

A navigation processing device 8 has a system controller (CPU) 9, a map data buffer memory 10 and the like. The system controller 9 has a navigation processing unit 9a and a map matching processing unit 9b, and (1) CD-R maps data corresponding to the current vehicle position.
Read from OM1 to map data buffer memory 10,
The map data is input to a display device to draw a map, (2) the map read address (window-address) is changed according to the traveling of the vehicle to scroll the map, and (3) the passing position data of the vehicle is displayed. The data is discretely stored as a travel locus, the travel locus data is input to the display device to draw the travel locus, and (4) the vehicle's current position data and direction data are input to the display device to display the vehicle position mark on the map. Draw the direction of travel to the corresponding position of (the above navigation processing), and further perform (5) map matching (pattern matching) processing to correct the vehicle position, and (6) a road having the same shape as the shape of the traveling locus. 2 passes
Vehicle position correction processing and the like in the case where the above exists are performed.

A display device 11 has a CRT controller 12, a video RAM (V-RAM) 13, a read control unit 14, a CRT 15, etc., and displays a desired map and mark on the CRT screen. .

The map data stored in the map data CD-ROM 1 is (1)
Road layer consisting of road list, intersection configuration node list, node list, etc., (2) background layer for displaying objects on the map, (3) character symbol layer for displaying municipality names, national road names, etc. Etc.

The road layer has the data structure shown in FIG. 2, and the road list includes a road list for each road (one road is represented by a set of a plurality of vertices (nodes)) on the map. Data such as type (national road, highway, narrow road, toll road, main local road, other), total number of nodes on the road, number on node list of each node and width, etc. It is the one. The node list shows the position information (longitude / latitude) for each node on the map, the intersection identification flag whether or not it is an intersection, the number on the intersection constituent node list when the node is an intersection, and the road when it is not an intersection. It is a list of data such as pointers indicating numbers on the list in order. For each intersection on the map, the intersection configuration node list is the number of nodes (called intersection configuration nodes) that are closest to the intersection on the link connecting the intersections, and the set of the intersection configuration nodes (numbers on the node list Representation) is a list in order.

FIG. 3 is an explanatory view showing the traveling route of the vehicle together with surrounding roads, FIG. 4 is a flow chart of the image recognition processing by the image recognition device, FIG. 5 is an explanatory view of the image recognition operation, and FIG. 6 is a perspective graphic to a planar graphic. FIG. 7 is an explanatory view showing an intersection road shape after being converted into a planar figure, FIG. 8 is an explanatory view of image recognition operation, FIG. 9 is an explanatory view showing a road shape after being converted into a planar figure, FIG. 10 is a flow chart of the vehicle position correction processing of the system controller 9, and FIG. 11 is an explanatory diagram of the vehicle position correction processing, which will be described below with reference to these figures.

Image Recognition Operation In the image recognition device 7, the still image extraction section 7a is used in the television camera 6.
A still image is periodically extracted from the road image in front of the vehicle captured in (step 101 in FIG. 4). Then, every time one still image is extracted, the image analysis unit 7b performs binarization, edge detection, and thinning in order, and then the characteristic points at the intersections and end points,
The road shape is extracted by extracting a line segment (a line segment connecting the intersection and the end point or a line segment connecting the end points) (steps 102 to 105).

Next, the collation unit 7c checks whether the road shape extracted by the image analysis unit 7b is an intersection including an intersection (step 106) or is near an intersection including a plurality of line segments (step 107). ), Step 1
If YES in 06, it is collated with the road data around the vehicle position read in the map data buffer memory 10 of the navigation processing device 8 to find the same intersection (step 108), and the determined intersection is found. After temporarily storing the data (combination of the intersection node and the intersection constituent node) and the identification data of each road forming the intersection in the memory (step 109), the road on which the own vehicle position is located is determined and the own vehicle position is determined. It also determines itself and outputs these data to the system controller 9 (step 110). Then, after waiting for a fixed time in step 111, the process returns to step 101 again. It should be noted that, in step 111, the vehicle may wait for traveling for a certain distance.

Specifically, for example, a vehicle is traveling along a route shown by an arrow in FIG. 3, and an image obtained by edge detection is shown on a binarized image of a still image captured at a point A on the way. 5 (1), the thinning in step 104 produces the result shown in FIG. 5 (2).
As shown in (3), the feature of the road shape consisting of the intersection points cp, the end points ep _{1 to} ep ₅ , and the line segments ks _{1 to} ks ₅ is extracted. Since the road shape includes the intersection point cp, the matching unit 7
From step c, the road shape of the intersection is recognized in step 106.

The collation unit 7c is extracted by the image analysis unit 7b.
Since the intersection road shape is a perspective figure,
Before performing the processing of step 107, the intersection road shape
The shape is once converted into a plane figure by the method shown in Fig. 6, and the road
Make it easier to check the data. In FIG. 6, the XZ plane is
It is a horizontal plane equivalent to the ground, and the Y-axis is vertically upward.
ing. In the XY plane, the center of the figure in FIG. 5C is the Y axis.
Place it so that it is at the specified position on the positive side of
From the view point VP at a predetermined position, draw a figure on the XY plane.
Drawing on the XZ plane so that it looks like a flat figure
And By conversion to a plane figure, cp → cp ', e
p₁~ Ep_Five→ ep₁´ ～ ep _Five´, ks₁~ Ks_Five→
ks₁´ ～ ks_Five′ (See FIG. 7).

On the other hand, stored in the map data buffer memory 9
The road data around the determined vehicle position is as shown in Fig. 3.
Crossing point CP₁Is an intersection node N_TenAnd intersection configuration no
De N_Four, N₆~ N₉Expressed as a combination of
₂Is an intersection node N_FiveAnd intersection node N₁~ N_Fourof
Expressed as a combination, the intersection CP₃Is an intersection node N₁₃
And intersection node N₉, N₁₁, N₁₂Expressed as a combination of
Has been done. And road RD₁Is node N₁, N_Five，
N₃・ ・ The roads are represented by connecting them in order. ₂Is
Code N₂, N_Five, N_Four, N_Ten, N₉, N₁₃・ ・ Sequentially connect
The road RD₃Is node N₆, N_Ten，
N₈The road RD_FourIs a node
N_Ten, N₇,, ... are connected in order, and the road R
D_FiveIs node N₁₁, N₁₃, N₁₂・ ・ Expressed by connecting in order
Has been.

The collation unit 7c intersection road shape obtained by converting the plane figures _{(cp', ep 1'~ep 5 '} , ks 1'~ks
₅ ') is compared with each intersection shape represented by each intersection data (each combination of intersection node and intersection constituent node) in the road data around the vehicle position, and the one that is most similar is selected. By doing so, the intersection CP ₁ is determined. In order to determine the intersection, the intersection road shape converted into a planar figure is appropriately rotated, translated, reduced, or enlarged, and the degree of matching with each intersection shape represented by the intersection data in the road data is calculated. However, the vehicle direction detected by the direction sensor 3 is input, and the vehicle direction is set to the end point ep ₁ ′ (ep ₁ ′ corresponds to the vehicle position) and cp ′ at the bottom center of FIG. 7. Including line segment ks
₁ '(ks _1' vehicle corresponds to the road currently running)
Is fixed to the detected azimuth and compared, the collation process can be performed more easily.

After the intersection CP ₁ is determined, the collating unit 7c determines the intersection data (combination of the intersection node N ₁₀ and the intersection constituent nodes N ₄ , N _{6 to} N ₉ ) relating to the intersection CP ₁ and the intersection. Identification data of each road (R
(Road number on the road list for D ₂ , RD ₃ , and RD ₄ )
Is temporarily stored in the memory, the road RD ₂ corresponding to the line segment ks ₁ ′ is indexed as the road currently running, and the position on the road RD ₂ corresponding to the end point ep ₁ ′ is set as the current position of the vehicle. To do. The current position is determined on the road RD ₂ as a position in front of the intersection CP ₁ by the length of the line segment ks ₁ ′. And the determined road RD ₂
And the current location are output to the system controller 9.

After a lapse of a certain time, when the still image extracting unit 7a again extracts a still image from the road image ahead of the vehicle captured by the television camera 6 (step 10).
1) If the vehicle is turning north at the intersection CP ₁ and traveling along the road RD ₄ to the point B, the edge detection and thinning by the image analysis unit 7b are as shown in (1) and (2) of FIG. As shown in FIG.
As shown in (3), there is no intersection, but the end point ep ₁ ,
ep ₂ and line segments sk ₁ and sk ₂ are found as road shapes (step 105). Since there are a plurality of line segments, YES is obtained in step 107. At this time, the collation unit 7c uses the latest intersection data temporarily stored in the memory after making the plane figure by the method shown in FIG. Then, this time, it is checked whether the road shape extracted from the still image matches a part of the roads forming the intersection (step 112).

Here, the line segment ks ₁ ′ coincides with a part of the link connecting the intersection nodes N ₁₀ and N ₇ ,
The line segment ks ₂ ′ has intersection nodes N ₁₀ and N _8.
Since it coincides with a part of the link connecting the two, the RD ₄ corresponding to the line segment sk ₁ ′ including the end point ep ₁ ′ corresponding to the current vehicle position is selected from the road identification data temporarily stored in the memory. Then, the vehicle is indexed as the road on which the vehicle is currently traveling, and the position on the road RD ₄ corresponding to the end point ep ₁ ′ is indexed as the current position of the vehicle (step 110). Your location line segments ks ₁ 'and the line segment ks _2' intersections obtained by extending the end points ep ₁ 'intersections CP ₁ over the length amount corresponding road RD ₄ between (CP' see FIG. 9)
The position is determined as the position advanced from. Then, the determined road RD ₄ and the present location are output to the system controller 9.

It should be noted that the above-described image recognition device 7 determines the road in which the vehicle is traveling and the current location only when the vehicle is traveling near the intersection (step 106 or 1).
If YES at 07).

The operation system controller 9 of the navigation processor reads out predetermined map data from the CD-ROM 1 to the map data buffer memory 10 according to the traveling of the vehicle based on the vehicle position data input from the position calculation CPU 5, and The map data is input to the display device 11 to draw the map, and the map read address (window address) is changed to scroll the map. Further, the system controller 9 discretely stores some of the latest vehicle passing positions (longitude / latitude) in a built-in memory as traveling locus data, and inputs the traveling locus data into the display device 11 to drive the traveling locus RT.
D is displayed, and the current vehicle position data and vehicle azimuth data are input to the display device 11 to display the vehicle position mark CM on the CRT 14 (step 2 in FIG. 10).
01 and above navigation processing).

Every time the system controller 9 moves a predetermined distance, the system controller 9 compares the shape of the traveling locus RTD with the road shape of the map data to obtain a road path having the same shape as the traveling locus (map matching, step 202).

Then, it is checked whether there are two or more road paths having the same shape as the traveling locus RTD (step 203).
If only one road path of the same shape exists, the vehicle position mark CM is corrected to a position on the road path, and the CRT1
4 is displayed (step 205), the corrected vehicle position data is given to the position calculation CPU 5 as a new starting point, and then the process returns to step 201 to repeat the subsequent processing.

On the other hand, when the vehicle is traveling along the traveling route of FIG. 3 to a position past point B, R of FIG.
As shown in D ₃ and RD ₄ , if there are two or more road paths that are almost the same as the travel locus RTD, and it is not possible to correct which road path to correct only by comparing the travel locus and the road shape, the image Using the road path RD ₄ indicated by the identification data of the latest traveling road input from the recognition device 7 as a correct candidate, the vehicle position mark CM is corrected at a position above the road RD ₄ and displayed on the CRT 14, and the corrected vehicle is displayed. The position data is given to the position calculation CPU 5 to be a new starting point (steps 204, 205, see FIG. 11 (2)).

As a result, after passing through the intersection CP ₁ , even when traveling on one of the roads RD ₃ and RD ₄ which are close to each other and run substantially in parallel, the vehicle position mark is correctly placed on the traveling road RD ₄ . It is possible to adjust to.

In the above embodiment, the road path RD ₄ indicated by the latest identification data of the traveling road input from the image recognition device 7 is set as the correct candidate, but it is close to the latest current position data input from the image recognition device 7. Alternatively, the other road path may be set as a correct candidate. Although the case where the pattern matching is performed has been described as an example, the image recognition device 7 can also perform the map matching by the projection method when there is a plurality of projection target candidates and it is not possible to project the road. Can narrow down candidates based on information from. Further, the width of the road may be recognized from the image capturing the road, and may be used as a reference when comparing with the road shape of the map data.

FIG. 12 is a block diagram of a modification of the above-described embodiment, in which the television camera 60 is installed in the front part of the roof of the vehicle so as to face forward and slightly upward from the horizontal. The television camera 60 captures an image of the road guide sign 80 installed on the road. 70 is an image recognition device,
By analyzing the image captured by the TV camera, extracting the road shape displayed on the road sign and collating it with the road data in the map data, the running road and the current location of the vehicle can be found. .

Reference numeral 70a denotes a still image extracting section for periodically extracting a still image from the image captured by the television camera, and 70b denotes a road sign cut out (the background color of the sign is blue) for the still image extracted by the still image extracting section. Is performed),
An image analysis unit for extracting the road shape of the road by binarizing, cutting out the road portion in the road sign (hereinafter referred to as the road sign), and extracting features, and 70c is the map data of the road shape extracted by the image analysis unit. This is a collating unit (matching unit) that collates with the inside road data to determine the road on which the vehicle is running and also the present location of the vehicle.

FIG. 13 is a diagram for explaining the operation of the image recognition apparatus 70, which will be described below with reference to this figure. When a still image is extracted by the still image extraction unit 70a at a certain point in time when the vehicle is running, and the road sign is cut out and binarized by the image analysis unit 70b as shown in FIG. In Figure 13
An image is obtained as in (2). Then, as shown in FIG. 13 (3), the sign road shape including the intersections cp ₁ and cp ₂ , the end points ep _{1 to} ep ₄ , and the line segments ks _{1 to} sk ₅ is extracted from the image of FIG. 13 (2). In addition, the bottom end point ep
₁ corresponds to the current position of the vehicle, and the line segment ks ₁ including the end point ep ₁ corresponds to the road currently running.

The collating unit 70c compares the extracted sign road shape with the road shape represented by the road data, selects the most similar one, and selects the intersection point cp existing at one end of the line segment sk _1. After the intersection corresponding to ₁ is determined, the road corresponding to the line segment sk ₁ is determined as the currently running road, and the intersection corresponding to cp ₁ on the road is located in front of the intersection corresponding to the length of the line segment sk ₁ . The current location is calculated, and the roads and the current location that have been calculated are output to the outside.

As a result, it becomes possible to accurately detect the road on which the vehicle is traveling and the current location. Further, since the image of the road sign is simple, the image analysis can be easily performed. Note that the current location may be a certain distance (for example, 300 m) from the intersection corresponding to cp ₁ on the road currently being driven, and the current location may be drawn with a character indicating the distance on the road sign as shown in FIG. In many cases, the character may be recognized by template matching or the like to obtain the current position. Also, in most cases, road signs are displayed only for main roads.Therefore, only the roads whose type information is national road, highway, toll road, or main local road should be matched. May be.

[0038]

As described above, according to the present invention, a video camera installed in a vehicle for capturing an image of a road, an image analysis means for extracting a road shape from an image captured by the video camera, and map data storing map data. A storage means and a matching means for matching the road shape extracted by the image analysis means with the road shape in the map data to find the road on which the vehicle is traveling or the current location are provided, and the video of the road is captured by the video camera, The road shape is extracted from the map, and the extracted road shape is compared with the road shape in the map data to determine the road on which the vehicle is running or the current location. It is possible to accurately detect the road on which the vehicle is traveling or the current position without being affected.

Further, a video camera installed in the vehicle for capturing the image of the road guide sign, an image analysis means for extracting the shape of the labeled road from the image captured by the video camera, and a map data storage means for storing map data. , The sign road road shape extracted by the image analysis means is collated with the road shape in the map data to provide a collation means for determining the road on which the vehicle is traveling or the current location, and the video of the road is captured by the video camera. The sign road shape is extracted, and the extracted sign road shape is compared with the roads in the map data to determine the road on which the vehicle is running or the current location. It is possible to accurately detect the road on which the vehicle is traveling or the current location without being affected, and at this time, because the image of the road sign is simple, image analysis can be performed easily. Can.

[Brief description of drawings]

FIG. 1 is an overall configuration diagram of a vehicle-mounted navigator according to an embodiment of the present invention.

FIG. 2 is a configuration diagram of road layers in map data.

FIG. 3 is an explanatory diagram of a traveling route of a vehicle and surrounding roads.

FIG. 4 is a flowchart of image recognition processing by the image recognition device.

FIG. 5 is an explanatory diagram of an image recognition operation.

FIG. 6 is an explanatory diagram of a method of converting a perspective graphic into a planar graphic.

FIG. 7 is an explanatory diagram of an intersection road shape after conversion into a plane figure.

FIG. 8 is an explanatory diagram of an image recognition operation.

FIG. 9 is an explanatory diagram of a road shape after conversion into a plane figure.

FIG. 10 is a flowchart of vehicle position correction processing by the system controller.

FIG. 11 is an explanatory diagram of a vehicle position correcting operation.

FIG. 12 is a configuration diagram of a modified example of the present invention.

FIG. 13 is an explanatory diagram of an image recognition operation.

FIG. 14 is an explanatory diagram of general map matching processing.

FIG. 15 is an explanatory diagram showing a problem of a conventional map matching process.

[Explanation of symbols]

 1 CD-ROM 6,60 TV camera 7,70 Image recognition device 7a, 70a Still image extraction unit 7b, 70b Image analysis unit 7c, 70c Collation unit

Claims (2)

[Claims] 1. A video camera installed in a vehicle for capturing an image of a road, an image analysis unit for extracting a road shape from an image captured by the video camera, a map data storage unit for storing map data, and an image analysis unit. A vehicle position detecting device comprising: a matching unit that matches the road shape extracted in step 1 with the road shape in the map data to determine the road on which the vehicle is traveling or the current location. 2. A video camera installed on a vehicle for capturing an image of a road guide sign, an image analysis means for extracting a shape of a labeled road from the image captured by the video camera, and a map data storage means for storing map data. A vehicle position detecting device, comprising: a checking means for checking the sign road shape extracted by the image analyzing means with the road shape in the map data to find the road on which the vehicle is traveling or the current location.