1. Field of the Invention
The invention relates to a vehicle navigation system, and more particularly to systems having a database that stores map data and methods for estimating energy consumption of a vehicle for a link of a route.
2. Related Art
Navigation systems are used in vehicles to calculate a route from a present vehicle position to a predetermined destination using map data. Navigation systems typically calculate the fastest or the shortest route to the destination using corresponding cost factors associated with the links of the route. With the costs of energy (such as fuel, gas or electricity) continuing to rise, it is desirable to reach the destination by a route that minimizes the energy consumption.
The determination of an energy efficient route may involve the use of static parameters, such as parameters associated with a speed category or a road size, and dynamic parameters, such as the driving behaviour of the driver of the vehicle. The static and dynamic parameters may be used to indicate characteristics of a link corresponding to a road segment. Although the use of these parameters may provide a good approximation of the energy consumption for a given route, it would be desirable to further improve the accuracy with which energy consumption is estimated.
Advanced driver assistance systems (ADAS) may also be used to provide assistance to the driver of the vehicle. ADAS systems acquire information about the current driving situation or the vehicle's surroundings using sensors. The information is evaluated in order to control various systems or components of the vehicle (such as for example the electronic stability program, or ESP, and the anti-lock brake system, or ABS) or to provide feedback to the driver. Modern assistance systems may combine the use of information retrieved from sensors with static parameters obtained from a database of a navigation system. Such static parameters are generally stored in an ADAS attribute layer of the navigation database. This layer generally corresponds to the lowest map data layer (layer 13), which includes the data generally associated with the shape points of links provided at the lowest layer. In order to retrieve this data, additional access to the ADAS layer is required, resulting in slow access times. The data is associated with shape points and used for a higher level route determination, which uses higher layer links. The use of the ADAS layer data for navigation purposes is thus generally difficult and costly in terms of computing time and computing power. Accordingly, the use of the ADAS layer data for route determination in a navigation system is at least associated with a number of drawbacks.
Accordingly, there is a need for improvements in the determination of an energy efficient route.
A vehicle navigation system having a database configured to store map data. The database includes links corresponding to road segments and attributes associated with the links. The map data includes at least some links associated with a curvature attribute. A mean absolute curvature (
Other devices, apparatus, systems, methods, features and advantages of the invention will be or will become apparent to one with skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the accompanying claims.
The invention may be better understood by reference to the following figures. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. In the figures, like reference numerals designate corresponding parts throughout the different views.
The processing unit 101 includes an interface to a position sensor 104 adapted to determine the current position of the vehicle in which navigation system 100 is located. The position sensor 104 may be any suitable position sensor, such as for example, a GPS (Global Positioning System) sensor, a Galileo sensor, a position sensor based on mobile telecommunication networks and other sensors.
The navigation system 100 includes a user interface 105 that may include a display and control elements, such as keys, buttons, rotary knobs and rotary/push knobs provided on a faceplate of the navigation device 100 or in any other suitable location inside the vehicle. The processing unit 101 may obtain information from other vehicle systems. For example, the current vehicle status information may be obtained via a vehicle interface 106. The vehicle interface 106 may include, for example, a CAN (controller area network) interface or a MOST (Media Oriented Systems Transport) interface. Information relating to the driving behavior of the driver of the vehicle, the current user of the vehicle, current operation conditions of the engine, current energy levels (such as for example, the status of batteries or the level of fuel in the fuel tank), and other similar information may be obtained by the processing unit 101 via the vehicle interface 106.
The memory 102 may include a database 103 having map data. The database 103 may be referred to as a navigation database or a map database in this specification. The database 103 may be stored in a storage system or device, such as a hard drive or a flash memory, or on a CD or DVD, or on other storage devices. The map database 103 may include a data representation of a road network of a particular region. The representation may include nodes representing points on a map, such as cities or other settlements, intersections, highway entrances or exits, or points placed along roads. The map database 103 may also include links between these nodes, where a link corresponds to a road segment between two nodes. The links may be provided for different layers corresponding to different map scales. As an example, at a lower layer, a link may be provided between two neighbouring highway entrances, whereas at a higher layer a link may be provided between two adjacent settlements.
The route building block 202 may include a curvature attribute 206, a rolling resistance attribute 208 and a grade resistance attribute 210 in addition to other attributes. Each of a plurality of links of the map data may be associated with a value of each of the attributes. If no attribute value is provided for a link, a default value may be used. Attribute values may also be stored only for the links for which they are provided. When determining a cost factor or energy consumption for the link, the database 103 may be queried for the availability of the attribute for the link. If the attribute is not available, the contribution to the cost factor corresponding to the attribute is neglected. A more compact database may be achieved when links have attributes only when specifically provided attribute values since space is not allocated for empty or default attribute values.
The curvature attribute 206 is provided to store an absolute mean curvature
In order to determine a curvature value for the entire link 300, the absolute values of curvature κ may be integrated along the course of the road segment or, when provided in discrete form, can be summed up and normalized with the length of the road segment 310. The mean absolute curvature
The integration may be performed numerically. In particular, the curvature values may be provided at discrete points along the road segment 310. The road segment 310 may for example be described with discrete points placed along or in proximity to the road segment, and for each of these points, a curvature value can be provided. The mean absolute curvature for the link 300 may then be calculated as a mean of the absolute curvatures provided at each discrete point.
It is also possible to weight the curvature values in the integral or sum when determining the mean absolute curvature,
When determining a route from a starting point to a destination, cost factors are generally provided for the links of the map and the route having the lowest total cost for reaching the destination is selected. The mean absolute curvature can be used for determining a cost factor for a link. It can also be used to estimate the energy required for travelling along the link. The additional required energy ΔB is generally proportional to the mean absolute curvature
ΔB=cC·
More complex models may also be employed. A more complex model may for example consider an estimate of the velocity of the vehicle while on the link, which may be a factor in a change in additional energy consumption due to curvature. Other factors include the braking of the vehicle that may be deemed likely in order to maintain vehicle control between curves in different directions such as, for example, a curve to the left going over into a curve to the right. Such braking may result in increased energy usage. The increased energy usage may be factored into the analysis in either the mean absolute curvature,
The route building block section 202 shown in
ΔB˜∫0L(FR(s)+F0(s))ds (4)
A rolling resistance coefficient CR and the grade resistance coefficient cG may be defined for the vehicle. The additional fuel consumption may be expressed as:
ΔB=∫0L(cR·f(δ(s))·cos(δ(s))+cG·g(δ(s))·sin(δ(s)))ds (5)
The cR and cG are generally vehicle-dependent. The weighting factors f(δ(s)) and g(δ(s)) are not vehicle-dependent, but can be made to be vehicle-independent. The weighting coefficients f(δ(s)) and g(δ(s)) may also be based on the type of vehicle. The performance of the vehicle with regards to energy consumption when travelling uphill or downhill may be modelled by using these weighting coefficients, f(δ(s)) and g(δ(s)). As shown in
From the above equation, a rolling resistance attribute and a grade resistance attribute may be determined from equations 6 and 7, respectively:
gcos=∫0Lf(δ(s))·cos(δ(s))ds (6)
gsin=∫0Lg(δ(s))·sin(δ(s))ds (7)
These rolling resistance attribute 208 and the grade resistance attribute and 210 as shown in
The attributes, curvature attribute 206, rolling resistance attribute 208 and the grade resistance attribute 210, may be associated with a single link as shown in map database 103 in
If the weighting factor is chosen to be a constant, as in for example, g(δ(s))=1, or is vehicle independent, then equation 5 may not accurately yield the desired results. For example, a link may have the starting point and the end point at the same elevation, yet include sections in-between that are at a higher or lower elevation. Referring to equation 5, the integral over sin (δ) may yield a value of zero despite the consumption of additional energy while on the incline and decline portions of the link. Such a result would only be valid if the vehicle regains all energy consumed during uphill driving when driving downhill, which is clearly not possible, at least for gasoline powered vehicles. Some vehicles, such as vehicles equipped with conventional combustion engines, consume energy when driving uphill and downhill, while other vehicle, such as hybrid vehicles or electric vehicles, may regain part of the consumed energy when travelling downhill.
With a constant or vehicle independent weighting factor, two values may be provided in the grade resistance attribute. For example, the term gsin+ may be defined as the sum or integral over the length of the link over the sine of all positive angles of elevations. The term gsin− may also be defined as the sum or integral over the sine of all negative angles of elevation. The uphill and downhill sections of the link may thus be considered separately when estimating the additional energy consumption for the link on the basis of the grade resistance attribute. For a combustion engine powered vehicle, a larger cG may be used for determining ΔB from gsin+, while a negative and smaller coefficient cG may be used for determining ΔB from gsin− (downhill sections). The model accounts for fuel consumption both on uphill and downhill sections. For hybrid or electric vehicles, the coefficient cG for the downhill sections gsin− may be positive and smaller, corresponding to a generated fraction of the energy.
Other ways of determining the grade resistance attribute gsin may also be used. For example, the weighting factor g(δ(s)) may be a triangular function having weighting for the sine term in accordance with the type of vehicle used. It is also possible to provide a vehicle-specific g(δ(s)) that precisely models the additional energy consumption or regained energy when driving uphill or downhill, respectively. In such applications, the map database 103 may be provided as a vehicle-specific map database.
It is noted that the attribute values may be either calculated by integration if the angle δ is provided as a continuous function of the distance s over the link, or by summation if discrete values of δ are provided at discrete points s along the road segment. The angle δ(s) may for example be the angle of elevation provided at particular discrete points along the road segment. When using a discrete sum, corresponding weighting factors may be determined by using the discrete values for δ(s) in the weighting factor functions g(δ(s)) and f(δ(s)).
The map database 103 in an example implementation may be configured as follows. For some of the links of the map data, information relating to curvature and angles of elevation may be available, for example by association with discrete points or shape points. The information may also be provided by a data source, such as for example, a map data provider or publisher. For the links having such information available, the corresponding attributes, curvature attribute 206, rolling resistance attribute 208 and the grade resistance attribute 210, may be determined as described above. The determined attributes may then be stored as associated with the corresponding link in a route building block such as, for example, the route building block 202 of the database 103 in
If a link corresponds to a road segment which has both a steep incline and high curvatures in both directions, for example, the determination of an estimate of the energy consumption based on the attributes described above may not be as precise as desired. The database may then be configured to include links that may be split up into link segments, each having a predetermined size. The link segments will have fewer curves, or fewer uphill/downhill sections. For each of the link segments, the curvature, rolling resistance and/or drag resistance attributes may be determined as described above with respect to the full links. The link segments may be stored in the database as an individual link having the attribute(s) determined for the respective link segment associated with it. These new and smaller links and their attributes may then be considered in determining a route or the estimation of an energy consumption.
Storing the attributes in the route building block 202 in
The attributes, curvature attribute 206, rolling resistance attribute 208 and the grade resistance attribute 210, may be stored in association with the links of the lowest layer of the map data, such as for example layer 13. The attributes may then be easily abstracted from lower layers to higher layers using the following equation:
The number M is the number of lower layer links that are summarized into the corresponding higher layer link. The term Lhigher/lower layer is the link length of the higher/lower layer link. The term xn is the respective attribute:
xε{
If the grade resistance attribute includes values for positive and negative angles of elevation, the term xn becomes the respective attribute:
xε[
Determining an attribute for a higher layer link is thus simplified, which may result in performance enhancement. Higher layer links quite frequently correspond to road segments having a number of curves in both directions and having uphill and downhill sections. Using the attributes xn for estimating energy consumption for the link simplifies the process.
In another example implementation, the attributes xn may be stored for the links of each layer. This would require more storage space, but may preclude the need for an abstraction of the attributes from lower to higher layers.
The processing unit 101 of vehicle navigation system 100 may retrieve the attributes mentioned above from the map database 103 and use these attributes for different purposes. For example, the attributes may be used to improve the determination of an estimate of the energy consumption for a particular link. This may be used to estimate the total energy consumption required for travelling a particular route, or to estimate the remaining distance that can be travelled with the energy reserves available in the vehicle. The processing unit 101 may also retrieve the current charging status of batteries of the vehicle or the current fuel level in the tank of a vehicle via the vehicle interface 106 in
The processing unit 101 may also estimate the energy consumption for the link in order to determine a cost factor for the link. The processing unit 101 may use such cost factors to determine a route from a starting point to a destination that minimizes the required energy consumption. Route determination may be performed using any suitable method known in the art. For example, route determination may involve the use of algorithms such as the A* or Dijkstra search algorithm.
The static parameters provided by the map database 103 may also be used for determining the cost for a particular link with the cost model. Such static parameters may include:
The grade resistance attribute and the curvature attribute may also be used in the cost model for estimating the energy consumption/cost of the link.
In step 602, the data corresponding to a link in a road segment is retrieved from the map database 103 (in
The above steps 602-610 is repeated at step 612 for the remaining links, so that total cost factors are available for all links relevant to the route determination. It is noted that for some links, not all attributes are provided in the map database and that accordingly, the corresponding factors are either neglected or default values are used. An energy efficient route can be determined in step 614 using the links associated with the total cost factors.
Referring back to
With these measures, energy consumption for particular links can be precisely calculated, and accordingly, the determination of an energy efficient route may be improved. It is noted that it is not necessary to calculate the energy consumption in actual physical terms, that is, for example in liters of fuel for a particular link, or ampere hours of electrical energy for a particular link. It is sufficient to provide a value proportional and representative of the energy consumption, which can be used as a cost factor.
It will be understood, and is appreciated by persons skilled in the art, that one or more processes, sub-processes, or process steps described in connection with
The foregoing description of implementations has been presented for purposes of illustration and description. It is not exhaustive and does not limit the claimed inventions to the precise form disclosed. Modifications and variations are possible in light of the above description or may be acquired from practicing the invention. The claims and their equivalents define the scope of the invention.
Number | Date | Country | Kind |
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10175871 | Sep 2010 | EP | regional |
This application is a divisional of the co-pending U.S. patent application titled, “VEHICLE NAVIGATION SYSTEM,” filed on Sep. 8, 2011 and having Ser. No. 13/228,294, which claims priority of European patent application titled, “VEHICLE NAVIGATION SYSTEM,” filed on Sep. 8, 2010, and having Serial No. 10 175 871.2. The subject matter of these related applications is hereby incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
6085137 | Aruga et al. | Jul 2000 | A |
6278928 | Aruga et al. | Aug 2001 | B1 |
6377741 | Lentink | Apr 2002 | B1 |
6798376 | Shioda et al. | Sep 2004 | B2 |
7103460 | Breed | Sep 2006 | B1 |
7336078 | Merewether | Feb 2008 | B1 |
7443154 | Merewether | Oct 2008 | B1 |
20030130779 | Shilmado et al. | Jul 2003 | A1 |
20040049339 | Kober et al. | Mar 2004 | A1 |
20050192727 | Shostak | Sep 2005 | A1 |
20060095195 | Nishimura et al. | May 2006 | A1 |
20060212222 | Miyoshi et al. | Sep 2006 | A1 |
20080071472 | Yamada | Mar 2008 | A1 |
20080280625 | Larsen | Nov 2008 | A1 |
20090222198 | Raynaud | Sep 2009 | A1 |
20090319139 | Kondou et al. | Dec 2009 | A1 |
20140350836 | Stettner | Nov 2014 | A1 |
Number | Date | Country |
---|---|---|
10122872 | May 1998 | JP |
2001-183150 | Jun 2001 | JP |
2005091083 | Apr 2005 | JP |
2005098749 | Apr 2005 | JP |
2009-067350 | Feb 2009 | JP |
2010052652 | Mar 2010 | JP |
2010115100 | May 2010 | JP |
Entry |
---|
JP Office Action dated Jan. 19, 2015. |
Extended European Search Report for Application No. 10 17 5871, dated Mar. 9, 2011. |
Number | Date | Country | |
---|---|---|---|
20160084665 A1 | Mar 2016 | US |
Number | Date | Country | |
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Parent | 13228294 | Sep 2011 | US |
Child | 14961804 | US |