JP2004037141A - Vehicular road surface altitude estimation device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a vehicular road surface altitude estimation device that precisely estimates the altitude of a travel route irrespective of vehicle travel routes. <P>SOLUTION: The vehicular road surface altitude estimation device comprises road information storing means 53 storing latitudes and longitudes of a plurality of points on roads, surface altitude storing means 53 storing surface altitude information about a plurality of points on maps, interpolated altitude value computing means 56 for computing road surface altitude values of the plurality of points on roads with the use of surface altitude data on a plurality of nearby points on maps, reliability computing means 56 for computing reliability of the computed altitude values of the plurality of points from the road information or the altitude value information, and filtering means 56 for capturing the interpolated altitude values and filtering them so that less reliable values in the altitude values less affect output values to estimate road surface altitude values. <P>COPYRIGHT: (C)2004,JPO

Description

【００４６】
係数ａ０、ａ１、ａ２、．．．、ａｎを次の評価関数Ｊが最小となるように推定し、
【００４７】
【数２】

【００４８】
ここで、ｘ１、ｘ２、ｘ３、．．．、ｘｎは各特徴点における出発点からの道のり（λ（ｋ）≧０のとき）
誘導経路の標高を道のりの関数として記述することになる。本方法は一般的なものであるので詳細な記述は省略する。
【００４９】
続いて、前述のように算出した経路上の路面標高推定値を用いて経路の道路状況に適合した車両制御を実現する方法について説明する。
【００５０】
例えば特開平８−３２２１０７公報に示されたハイブリッド電気自動車のモータ制御装置に本発明の経路上の路面標高推定値を用いて経路の道路状況に適合した車両制御を実現するがことが可能である。この公報では、ナビゲーション装置よりこれから進む走行経路の勾配を検出し、上り坂がある場合は、バッテリの充電量が下限値を下回らないようモータ走行を制限し、下り坂がある場合には上限値を超えないようにモータ走行の比率を多くして、バッテリの充放電パターンを走行路の勾配状況に対応させ、充放電を効率的に行なう方法が開示されている。これらの演算は、車両コントローラ１６内で実現することになるが、詳細な実現形態については、特開平８−３２２１０７公報や特開２００１−２９８８０５公報などに開示されているので、説明を省略する。
【００５１】
ハイブリッド電気自動車を用いて車両制御を説明したが、このほか、例えばエンジン自動車のパワートレーンの制御において、下り坂を検出した場合は予めシフトアップを禁止してエンジンブレーキの量を増加させる準備をし、上り坂を検出した場合は電制スロットルのゲインを上げて走行に必要なトルクの増加に備えるよう制御特性を決定することもできる。この場合車両の運転性が向上する。他にも自動配光ランプや自動ブレーキシステムや前車追従のための制駆動力等の制御に本発明を適用してもよい。制御の演算は、車両コントローラ１６内で実現する。これらの実施形態に関しては、従来使用している路面標高データあるいは／および勾配データを、発明の方法で演算したもの路面標高データあるいは／および勾配データと置き換えることで実現できるので、説明は省略する。
【００５２】
したがって本実施形態では、推定される標高値あるいは／およびそれらから演算する勾配値に応じて、走行路状態に適合する車両の制御特性を決定するものとした。誘導経路の標高情報あるいは／および勾配の検出精度が高いため、これをもとに決定される車両の制御特性は、走行路状況に適合する車両走行特性をもたらす。例えば勾配が下り坂の場合は、ハイブリッド電気自動車の制御において、回生発電による充電に備え、バッテリが過充電とならないよう予めモータ走行の比例を多くし、上り坂の場合には、上り坂を走行するに必要な力行エネルギーからバッテリが過放電とならないようモータ走行の比例を減らしてバッテリの消費を抑えるように制御特性を決定することができる。
【００５３】
また、エンジン自動車のパワートレーンの制御においては、勾配が下り坂の場合には、予めシフトアップを禁止してエンジンブレーキ量を増加させる準備をし、上り坂の場合には電制スロットルのゲインを上げて走行に必要なトルクの増加に備えるように車両の制御特性を決定することもできる。誘導経路の標高情報あるいは／および勾配の検出精度が高いため、これらの制御により、実走行路状況に適合する車両特性を実現できる。
【００５４】
また、本発明を用いて、目的地までの燃料消費量を精度良く予測し、それを運転者に情報提供するものがある。この機能はナビゲーションシステム３３にて実現することが出来る。
【００５５】
まず、本発明の基づき算出した路面標高データを用いて、目的地までの誘導経路上に３次元誘導経路データを作成する。そして、市街地道路か、郊外の道路か、又は高速道路かにより燃料消費係数（平均的な条件に対する燃料消費量の比）を設定し、更に平坦路か、上り勾配か、又は下り勾配かにより燃料消費係数を補正する。それら燃料消費率と区間毎の燃料消費係数及び区間毎の走行距離とにより、目的地に到達するまでに必要な燃料の量を計算する。本方法の詳細な実現形態については説明を省略するが、特開平１０−１９７２７２公報に開示されている形態で実現できる。
【００５６】
したがって、推定された路面標高値あるいは推定された路面標高から演算される勾配推定値に応じて車両の未来情報を予測し運転者に提供することができる。目的地までの燃費は、例えば目的地までの経路の標高変化に依存するものである。目的地の標高が現在地より高い場合には、車両をより高い位置に運ぶためのポテンシャルエネルギーが必要なので目的地の標高が現在値と同じ場合に比べて、燃料消費量が多くなる傾向にある。このような情報を提供する場合にも、本発明を用いれば精度良く路面標高や勾配を推定できるので、より正確な情報を運転者にできるという効果がある。
【００５７】
これまで地表標高情報および道路情報を保有する地図データベース５３を車両に搭載する実施形態を示したが、本発明は必ずしもそのような形態に限定されるものではない。
【００５８】
例えば、地表標高情報および道路情報からあらかじめ全ての道路に関しで前述の路面推定処理を実施しておき、その結果を地図データベース５３に保有する形態もある。本形態を取れば、メッシュ標高データを地図データベース５３に保有する必要は無く、路面推定処理した結果のみを道路上の特徴点に関連付けて標高データとして保有するようにしておけば良い。この形態をとると、データベース５３の使用メモリを減らすことができる。また、車両コントローラ１６では路面推定処理のための演算が不要となるのでより低価格のマイクロコンピュータで実現可能となるメリットがある。
【００５９】
また、地表標高情報および道路情報からあらかじめ全ての道路に関して記述の路面推定処理を実施しておき、その結果をサービスプロバイダ（車両と無線通信を行なえる基地局）に保持しておく形態もある。この場合には、地表標高情報および道路情報を車両に保持しなくてもよい。ただしこの場合、車両はサービスプロバイダと通信機能を有する必要がある。乗員が設定した目的地情報および現在地情報は通信機能を利用してサービスプロバイダに送信し、サービスプロバイダ側で経路誘導探索およびその経路上の標高を演算し、それらのデータを車両が受信する。これによって車両側で誘導経路の路面標高を推定することができる。本形態によると、地図データベース５３が保有する情報量は少なくてよく、使用メモリを減らすことができる。また、ナビゲーションシステム３３では路面推定処理のための演算が不要となるので、より低価格のマイクロコンピュータで実現可能となるメリットがある。
【００６０】
本発明は、上記した実施形態に限定されるものではなく、本発明の技術的思想の範囲内でさまざまな変更がなしうることは明白である。
【図面の簡単な説明】
【図１】本発明の路面推定装置を搭載した車両の一実施形態の構成を示す図である。
【図２】路面推定装置の構成を示す図である。
【図３】路面標高推定部５６で行う制御内容について説明する図である。
【図４】本発明による路面標高推定方法を説明する図である。
【図５】本発明による路面標高推定方法を説明する別の図である。
【図６】確からしさを求める方法を説明する図である。
【図７】確からしさを求める方法を説明する別の図である。
【符号の説明】
１、４、１０　モータ
２　エンジン
３　クラッチ
５　無段変速機
６　減速機
１６　コントローラ[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a vehicular road surface altitude estimating device capable of highly accurately estimating a road surface altitude of a vehicle traveling route from a ground surface altitude data group associated with latitude and longitude.
[0002]
[Prior art]
Since currently available navigation devices do not include information on gradients in map data, it is necessary to estimate the road surface elevation of the travel route from the ground surface elevation data group and then estimate and detect the gradient from the estimated road surface elevation data. become. Japanese Patent Application Laid-Open No. 2000-123292 discloses an apparatus for estimating a road surface altitude of a traveling route from a ground surface altitude data group. Here, a method is shown in which ground surface elevation values of a plurality of point sequences on a road are obtained from contour data of a topographic map, and a filtering process for removing high spatial frequency components is performed on the elevation values of the plurality of point sequences. Have been. In the filtering process, the cutoff frequency is switched according to the type of road (expressway national road, city road, etc.) and the road environment, thereby realizing the removal performance suitable for the road surrounding environment.
[0003]
[Problems to be solved by the invention]
However, with this conventional road surface altitude estimating device, it is difficult to accurately estimate the road surface altitude when there is a tunnel on the traveling route of the vehicle or when there is a hairpin power line having an altitude difference such as a mountain road. There is a problem.
[0004]
In view of such a problem, an object of the present invention is to provide a vehicular road surface altitude estimating device that accurately estimates the altitude of a traveling route irrespective of the traveling route of the vehicle.
[0005]
[Means for Solving the Problems]
The present invention provides a road information storage unit that stores latitude and longitude of a plurality of points on a road, a surface elevation storage unit that stores surface elevation information of a plurality of points on a map, and a road surface of a plurality of points on the road. An interpolated altitude value calculating means for calculating altitude values by using ground surface altitude data of a plurality of points on a map in the vicinity, and the likelihood of the altitude values of the calculated plural points from the road information or the altitude value information. Estimating the road road surface elevation value by inputting the interpolation altitude value and inputting the interpolation altitude value, and performing a filtering process so that the value of the altitude value that is low in probability has a small effect on the output value. Filter processing means.
[0006]
【The invention's effect】
In the present invention, when estimating the altitude of the road surface based on the ground altitude data, in addition to the means for calculating the ground altitude value of the point on the road from the ground altitude data, there is provided a means for calculating the certainty of the value. Then, since the altitude of the road surface is estimated by performing a filter process that emphasizes more likely data, the road surface altitude can be estimated as a value close to the actual road surface altitude. Also, for example, at the entrance of a tunnel, since the surface elevation generally changes drastically, it is assumed that the value to be calculated by interpolation of the surface elevation data is low, and the weight of the point where the deviation of the estimated value is large is allowed to deviate. Filter processing can be performed smaller than a point having a small degree. As a result, the road surface elevation can be estimated as a value close to the actual road surface elevation, and the drivability can be improved for vehicles equipped with a vehicle control system using a road elevation or a road gradient. .
[0007]
BEST MODE FOR CARRYING OUT THE INVENTION
FIG. 1 shows a configuration of an embodiment of a hybrid vehicle to which the road surface elevation estimation device of the present invention is applied. In FIG. 1, a thick solid line indicates a transmission path of mechanical force, and a thick broken line indicates a power line. A thin solid line indicates a control line, and a double line indicates a hydraulic path.
[0008]
The power train of this hybrid vehicle includes a motor 1, an engine 2, a clutch 3, a motor 4, a continuously variable transmission 5, a reduction gear 6, and a differential gear 7, which are arranged on the same axis. An engine 2 is arranged between the motor 1 and the motor 2, and a clutch 3 is interposed between the engine 2 and the motor 4. Therefore, the output shaft of the motor 1, the output shaft of the engine 2, and the output shaft of the motor 4 are connected via the clutch 3.
[0009]
When the clutch 3 is engaged, the engine 2 and the motor 4 serve as propulsion sources for the vehicle. When the clutch 3 is released, only the motor 4 serves as a propulsion source for the vehicle. The motor 4 transmits power to drive wheels 8 via a continuously variable transmission 5, a reduction gear 6, and a differential 7. Pressure oil is supplied to the continuously variable transmission 5 from a hydraulic device 9. An oil pump (not shown) of the hydraulic device 9 is driven by a motor 10.
[0010]
The motors 1, 4, and 10 are AC machines such as a three-phase synchronous motor or a three-phase induction motor. The motor 1 is mainly used for engine start and power generation, and the motor 4 is mainly used for vehicle propulsion and braking. The motor 10 is for driving the oil pump of the hydraulic device 9. The motors 1, 4, and 10 are not limited to AC machines, and DC motors can be used. When the clutch 3 is engaged, the motor 1 can be used for propulsion and braking of the vehicle, and the motor 4 can be used for power generation.
[0011]
The clutch 3 has a function of adjusting the transmission torque, and for example, a powder clutch can be used. It should be noted that a dry single-plate clutch or a wet multi-plate clutch can be used as the clutch 3. The continuously variable transmission 5 is a continuously variable transmission of a belt type, a toroidal type, or the like, which can adjust a speed ratio in a stepless manner. The motors 1, 4, and 10 are driven by inverters 11, 12, and 13, respectively. The inverters 11 to 13 are connected to a main battery 15 via a common DC link 14, convert DC charging power of the main battery 15 into AC power and supply the AC power to the motors 1, 4, and 10, and 4 is converted into DC power to charge the main battery 15. Since the inverters 11 to 13 are connected to each other via the DC link 14, the electric power generated by the motor in the regenerative operation can be directly supplied to the motor in the power running operation without passing through the main battery 15. . As the main battery 15, various batteries such as a lithium-ion battery, a nickel-metal hydride battery, and a lead battery, and an electric double layer capacitor, a so-called power capacitor, can be used.
[0012]
As shown in FIG. 2, the road surface altitude estimating device includes a vehicle controller 16, a navigation system 32, various sensors 22 to 27, and the like.
[0013]
The vehicle controller 16 is composed of a microcomputer and peripheral parts such as a memory, the rotational speeds and output torques of the motors 1, 4 and 10, the rotational speed and output torque of the engine 2, the engagement and disengagement of the clutch 3, the continuously variable transmission 5 The gear ratio of the vehicle is controlled.
[0014]
As shown in FIG. 2, the vehicle controller 16 includes a key switch 20, a brake switch 21, an accelerator sensor 22, a vehicle speed sensor 23, a battery temperature sensor 24, a battery SOC detection device 25, an engine rotation sensor 26, a throttle sensor 27, and the like. Connected.
[0015]
The key switch 20 is turned on (closed) when the vehicle key is set to the ON position or the START position. The brake switch 21 detects the depression state of the brake pedal, and the accelerator sensor 22 detects the depression amount of the accelerator pedal (hereinafter, referred to as accelerator opening). The vehicle speed sensor 23 detects the running speed of the vehicle, and the battery temperature sensor 24 detects the temperature of the main battery 15. The battery SOC detection device 25 detects the state of charge (SOC) of the main battery 15, and the engine rotation sensor 26 detects the rotation speed of the engine 2. Further, the throttle sensor 27 detects a throttle valve opening of the engine 2.
[0016]
Further, a fuel injection device 30, an ignition device 31, a throttle valve control device 32, a navigation system 33, and the like of the engine 2 are connected to the vehicle controller 16. The controller 16 controls the fuel injection device 30 to supply and stop the fuel to the engine 2 and adjust the fuel injection amount, controls the ignition device 31 to ignite the engine 2, and controls the throttle valve adjustment device 32 Then, the output torque of the engine 2 is adjusted.
[0017]
Further, the vehicle controller 16 receives the altitude estimation data of the guidance route estimated in the navigation system 33 from the navigation system 33, and based on the altitude estimation data, the rotational speeds and output torques of the motors 1, 4, and 10, the engine 2 And the output torque, the engagement and disengagement of the clutch 3, and the speed ratio of the continuously variable transmission 5.
[0018]
As shown in FIG. 2, the navigation system 33 includes a GPS 51 for detecting the current position and the traveling direction, the type of road, the number of lanes, the radius of curvature of the road, the elevation or road gradient, the presence of an intersection, a tunnel, a bridge, an overpass, a railroad crossing, a tollgate, and the like. A map database 53 in the form of a DVD-ROM is provided which stores regulation information such as speed limit, area information such as urban roads and mountain roads, and ground elevation mesh data of a Japanese map.
[0019]
Here, the surface elevation mesh data on the Japan map is, for example, mesh elevation data provided by the Geographical Survey Institute. The mesh elevation data is obtained by finely dividing a map of the whole country into small square areas each having a side of about 50 m, and storing the elevation at the center of each area. This data may have a size of one side changed according to the capacity of information that can be stored in the DVD-ROM. For example, data of about 100 m per side may be obtained by thinning out every other mesh grid data. By doing so, the memory capacity required for storing information can be reduced to 1/4.
[0020]
The navigation system 33 includes a guidance device 55 that searches for a route to a destination set by the driver on the touch panel 54 and guides an occupant along the route. When the route is not guided, the guidance device 55 predicts the destination and the travel route of the vehicle from the information on the position and the traveling direction of the vehicle and the past travel route stored in the memory. For example, it detects that the vehicle is traveling on a commuting route or a route that travels frequently, and specifies a destination such as a commuting destination or a supermarket from information on past traveling to predict a traveling route.
[0021]
In addition, the navigation system 33 checks whether there has been a change in destination, a departure from the guidance route, or a change in traffic congestion, for each characteristic point on the route, for a given time, or for a given travel distance. If any of them is found, the route to the destination is searched again, and the occupant is guided to the destination.
[0022]
Further, the navigation system 33 estimates the road elevation of the guidance route to the destination by the road elevation estimation unit 56 based on the data of the map database 53 and the road information of the guidance route calculated by the guidance device 55. Send those estimates to the controller 16.
[0023]
Hereinafter, an embodiment of the road surface elevation estimating unit 56, which is a point of the present invention, will be described. First, two input data to the road surface elevation estimating unit 56 will be described. The first input data is the elevation mesh data of the database 53. Numerical altitude data (hgt, surface) of a square having a side of 50 m is associated with latitude (axis, lat) and longitude (axis, lng), and is stored in meters.
[0024]
The second input data is road information of the guidance route. The road information of the guidance route is provided to the guidance device 55 as a sequence of n point points on the guidance route (for example, points for displaying a curve shape or the like at an intersection, a tunnel entrance, both ends of a bridge, a sharp curve portion). Is calculated. Latitude information lat [k], longitude information lng [k], and information on the way to the next point way [k] are associated as numerical values with each point, and whether or not it is an entrance / exit of a tunnel is tunnel1 [k]. Inside or not, tunnel2 [k], presence / absence of a signal signal1 [k], whether or not it is an end point of a bridge, bridge1 [k], whether or not it is in the middle of a bridge, bridge2 [k], whether or not it is on an elevated road, etc. Are associated with each other as bit information and calculated. Here, n is the number of feature points from the current position to the destination, and k is an integer from 1 to n.
[0025]
The contents of control performed by the road surface elevation estimating unit 56 based on these two data will be described with reference to FIG.
[0026]
First, in step 1, altitude values hgt and step1 [k] of n feature points pnt [k] are calculated by lookup of mesh altitude data (hgt, surface). Step 1 is a table lookup operation. The altitude values hgt and step1 [k] are calculated by linear interpolation based on quadrangle vertex data having a side length of 50 m including the feature points. For example, the elevation values hgt and step1 [i] of the feature point B in FIG. 4A are calculated by linear interpolation of the elevation data of the points B1, B2, B3 and B4. Here, another method such as spline interpolation may be used as the interpolation method. FIG. 4B shows an example of an elevation value of a feature point calculated from the data of FIG.
[0027]
In step 2, for each of the n feature points pnt [k], m grid points of neighboring mesh elevation data are selected. These lattice points are set as pnts [k] [p] (p = 1, 2,... M). These grid points are used to calculate certainty. Here, the grid points used in the interpolation calculation in step 1 are selected as grid points pnts [k] [p] of the nearby mesh elevation data. For example, for point B in FIG. 4A, four points B1, B2, B3, and B4 are defined as pnts [i] [1], pnts [i] [2], pnts [i] [3], and pnts [ i] [4] (m = 4 at this time).
[0028]
In the following step 3, the elevation data hgt and pnts [k] [p] for the selected grid point pnts [k] [p] are calculated by lookup of the mesh elevation data (hgt, surface). For example, the calculated value for the point B in FIG. 4A is hgt, pnts [i] [1] = 33, hgt, pnts [i] [2] = 33, hgt, pnts [i] [3] = 35, hgt, pnts [i] [4] = 36. Therefore, the range of the elevation value for the point B is from the lower limit value 33 to the upper limit value 36.
[0029]
In step 4, for each of the n feature points pnt [k], based on the variation of the elevation data hgt, pnts [k] [p] and the bit information of the n feature points pnt [k], Calculate likeness. Here, the likelihood indicates the magnitude of the difference between the actual altitude value of the feature point pnt [k] and the altitude value calculated from the altitude data hgt and pnts [k] [p]. ], The likelihood of the feature point pnt [k] is indicated by the variation of the altitude data hgt and pnts [k] [p] for calculating the altitude value.
[0030]
Specifically, in the case of the point B in FIG. 4A, the calculation is performed with the width of 33 to 35 as the certainty. FIG. 4B shows an example of the likelihood of the points A to G calculated based on the data of FIG. 4A as the width of the elevation value. Here, the width value is corrected according to the bit information of each feature point. For example, since point D is inside the tunnel and has a very low correlation with the ground surface elevation value, the lower limit value of the width may be forcibly set to a sufficiently small value (for example, the lower limit correction value −20 m), or the point at the entrance and exit of the tunnel. You may set based on C and E. Since bridges and overpasses are usually located higher than the ground surface, the upper limit of the width may be corrected higher (for example, the upper limit correction value +10 m) based on the bit information. Therefore, by calculating assuming that the likelihood of the interpolated elevation value at the point in the tunnel, on the overpass, or on the bridge is low, appropriate likelihood can be set for the feature point according to the feature.
[0031]
In step 5, from the altitude values hgt and step1 [k] of the n feature points pnt [k] and the likelihood thereof, the road surface altitude of the guidance route to the destination is calculated. In doing so, a point with high probability (small elevation value width) is selected from the feature points. Here, as points to be selected, points A, B, F, and G are selected using a criterion that an altitude value width indicating certainty is 5 m or less. As another selection criterion, there is a criterion of selecting a criterion in which the altitude value width indicating the certainty falls within 50% from the smaller one. The feature points selected based on such criteria are connected by a polygonal line. Here, since the distance between the feature points is known as way [k] as described above, if the horizontal axis is the distance to the target point, a line such as LINE1 shown in FIG. Can be.
[0032]
Next, the feature points closest to the current location are extracted from those that do not pass through the range of certainty among the feature points. In the case of this example, point C corresponds. For this point, if LINE1 is below the lower limit of the likelihood width, the polygonal line is corrected so as to pass through the lower limit of the feature point (the altitude hgt, step1 [i] of the point B and the point If the value exceeds the upper limit value (connecting the lower limit value of C), the polygonal line is corrected so as to pass through the upper limit value of the feature point (LINE2 in the figure is corrected). This procedure is repeated until all the corrected broken lines fall within the range of the elevation width.
[0033]
In the case of FIG. 4, if the point E is corrected once again, the repetition ends. The result of the straight line repeatedly corrected is shown as LINE3 in FIG. By such control, the road surface altitude can be accurately estimated.
[0034]
Therefore, when estimating the altitude of the road surface based on the ground surface altitude data, in addition to calculating the ground surface altitude value of the point on the road from the ground surface altitude data, the likelihood of the value is calculated and the more probable data is emphasized. By performing the filtering process described above, the altitude of the road surface is estimated. For example, in a tunnel, it is assumed that the correlation between the ground elevation and the road elevation is extremely low.In other words, it is possible to calculate the probability to be extremely low and ignore it during the filtering process. As a result, the road surface can be calculated as a value close to the actual road elevation. Altitude can be estimated. In addition, for example, at the entrance of a tunnel, the surface elevation generally changes drastically, so that it is assumed that the value calculated by interpolation of the surface elevation data is low (for example, there is an error of ± 20 m), and the deviation of the estimated value Filtering can be performed with respect to a point having a large degree of tolerance with a smaller weight than a point having a small degree of deviation tolerance. As a result, the road surface altitude can be estimated as a value close to the actual road surface altitude, and the drivability of a vehicle equipped with a vehicle control system using a road altitude or a road gradient can be improved.
[0035]
In addition, the likelihood of the interpolation calculation value of the ground surface elevation data is calculated according to the degree of variation of the elevation values of the adjacent mesh grid points, and the greater the variation, the lower the likelihood is calculated. As a result, the likelihood of the interpolation calculation value can be appropriately set according to the altitude change in the vicinity of the point of interest.
[0036]
Various other similar calculation methods are conceivable for the calculation by the road surface elevation estimation unit 56, and these may be used. For example, while the method of calculating the likelihood in step 4 uses the ground elevation data, there is also a simpler method that uses only bit information of the feature points. At the entrance of the tunnel, the surface altitude generally changes drastically, so that the altitude width indicating the certainty is uniformly set to the altitude hgt, step 1 [k] ± 20 m. For a feature point in a tunnel, there is a method of setting an altitude width indicating certainty to a uniform infinite width, and consequently ignoring the point to estimate a road surface altitude.
[0037]
FIG. 6 shows another method of selecting grid points pnts [k] [p] of mesh elevation data in the vicinity of step 2 as the second embodiment.
[0038]
As shown in FIG. 6, a mesh region is formed from a rectangle to a triangle, and vertices (B1, B2, B3) of a triangle R1 including the point B are selected as lattice points near the point B. Alternatively, a plurality of triangular grid points along the road may be selected in consideration of the direction of the road. In the second embodiment shown in FIG. 6, grid points B1 to B5 are selected in consideration of, for example, three triangles R1, R2, and R3. However, in order to increase the grid points selected along the road, R1 to R5 are selected. The five grid points B1 to B7 may be selected in consideration of the above five triangle areas. Further, grid points may be further selected from the selected grid points. For example, among the elevation data B1 to B7, five points excluding the maximum value and the minimum value are set as grid points of the final selection, and based on them. You may ask for certainty.
[0039]
FIG. 5 shows an example of the result of performing Step 5 after determining the likelihood in consideration of the three triangular regions.
[0040]
In this case, the likelihood of the interpolated calculated value of the ground elevation data is calculated according to the degree of variation of the elevation value of the mesh grid point close to the point on the road along the direction of the road. The calculation is performed so that the likelihood is low. As a result, the likelihood of the interpolation calculation value can be appropriately set according to the altitude change in the vicinity of the point of interest and the altitude change along the direction of the road, and the road surface altitude can be estimated with high accuracy.
[0041]
As a third embodiment, FIG. 7 shows another method of calculating an altitude value width indicating certainty. This is an embodiment in which information of a plurality of roads is used when calculating the altitude value width, and the calculation can be performed more accurately (the altitude value width is reduced).
[0042]
As shown in FIG. 7, when the likelihood is determined along the directions of the guidance routes A to B to C, the value range of the grid points of the triangles R1 ′, R2 ′, R3 ′ is 33 to 40. On the other hand, another road intersecting at the point B is formed into a triangular area like R1, R2, and R3 in FIG. 6, and its grid points are taken to obtain the width of the altitude value. Taking the larger lower limit and the smaller upper limit as an altitude width indicating the certainty is 33 to 35, which can be smaller than the certainty determined along the guidance route (always). It is not always small, but not large). In this way, the altitude of the road surface can be more accurately estimated by reducing the altitude width of the certainty.
[0043]
Therefore, the likelihood of the interpolation calculation value of the ground surface elevation data at the intersection of the roads is calculated according to the degree of dispersion of the elevation values of the mesh grid points close to the points on the road along the directions of the multiple intersecting roads, In particular, since the likelihood is calculated based on the degree of variation of the road with the smallest variation among the elevation values of multiple roads, it is possible to estimate the road surface altitude using a more reliable altitude value, and the estimation accuracy of the road surface altitude Can be raised.
[0044]
In the fourth embodiment, the likelihood is represented in step 4 by the reciprocal of the maximum elevation difference between neighboring grid points (assumed to be λ (k)) or the like. In step 5, the elevation values hgt, This is a method in which step 1 [k] is weighted by the likelihood and then the least-squares approximation of the path road surface elevation function. In this case, the route of the guidance route is set as a variable x, and the route road surface elevation function y (x) is set as the following equation.
[0045]
(Equation 1)

[0046]
The coefficients a0, a1, a2,. . . , An such that the next evaluation function J is minimized,
[0047]
(Equation 2)

[0048]
Here, x1, x2, x3,. . . , Xn are the distances from the starting point at each feature point (when λ (k) ≧ 0)
The elevation of the guidance route will be described as a function of the distance. Since this method is a general one, detailed description is omitted.
[0049]
Next, a method of realizing vehicle control suitable for the road conditions of the route using the road surface estimated value on the route calculated as described above will be described.
[0050]
For example, a vehicle control adapted to the road conditions of the route can be realized by using the estimated value of the road surface elevation on the route in the motor control device of the hybrid electric vehicle disclosed in Japanese Patent Application Laid-Open No. 8-322107. . In this publication, the navigation device detects the gradient of a traveling route to be advanced from now on, and when there is an uphill, the motor traveling is limited so that the charged amount of the battery does not fall below a lower limit. A method is disclosed in which the ratio of the motor running is increased so as not to exceed, and the charge / discharge pattern of the battery is made to correspond to the gradient condition of the running road, and the charge / discharge is efficiently performed. These calculations are realized in the vehicle controller 16, but a detailed implementation form is disclosed in JP-A-8-322107, JP-A-2001-298805, and the like, and a description thereof will be omitted.
[0051]
Although vehicle control has been described using a hybrid electric vehicle, in addition, for example, in the control of a power train of an engine vehicle, if a downhill is detected, a shift-up is prohibited in advance to prepare for increasing the amount of engine braking. When an uphill is detected, the control characteristic can be determined so as to prepare for an increase in torque required for traveling by increasing the gain of the electronically controlled throttle. In this case, the drivability of the vehicle is improved. In addition, the present invention may be applied to control of an automatic light distribution lamp, an automatic brake system, a braking / driving force for following a front vehicle, and the like. The calculation of the control is realized in the vehicle controller 16. Since these embodiments can be realized by replacing conventionally used road surface elevation data or / and gradient data with road surface elevation data or / and gradient data calculated by the method of the present invention, description thereof will be omitted.
[0052]
Therefore, in the present embodiment, the control characteristics of the vehicle suitable for the traveling road condition are determined according to the estimated altitude value and / or the gradient value calculated from the altitude value. Since the detection accuracy of the altitude information and / or the gradient of the guidance route is high, the control characteristics of the vehicle determined based on the information provide the vehicle traveling characteristics suitable for the traveling road conditions. For example, when the gradient is downhill, in the control of the hybrid electric vehicle, the proportion of the motor traveling is increased in advance so that the battery is not overcharged in preparation for charging by regenerative power generation. The control characteristic can be determined so as to reduce the proportionality of the motor running so as to prevent the battery from being over-discharged from the powering energy required to reduce the battery consumption.
[0053]
In the control of the power train of an engine vehicle, when the gradient is downhill, the upshift is prohibited in advance to prepare for increasing the engine braking amount, and when the gradient is uphill, the electric throttle gain is increased. It is also possible to determine the control characteristics of the vehicle so as to prepare for an increase in the torque required for traveling. Since the accuracy of detecting the altitude information and / or the gradient of the guidance route is high, the vehicle characteristics suitable for the actual traveling road condition can be realized by these controls.
[0054]
In addition, there is one that accurately predicts fuel consumption to a destination using the present invention and provides the information to a driver. This function can be realized by the navigation system 33.
[0055]
First, using the road surface elevation data calculated based on the present invention, three-dimensional guidance route data is created on a guidance route to a destination. Then, a fuel consumption coefficient (ratio of fuel consumption to an average condition) is set depending on whether the road is an urban road, a suburban road, or a highway, and the fuel consumption is further determined depending on whether the road is flat, uphill, or downhill. Correct the consumption factor. The amount of fuel required to reach the destination is calculated from the fuel consumption rate, the fuel consumption coefficient for each section, and the travel distance for each section. Although a detailed description of the method of realizing the present method is omitted, it can be realized by the method disclosed in Japanese Patent Application Laid-Open No. H10-197272.
[0056]
Therefore, the future information of the vehicle can be predicted and provided to the driver according to the estimated road elevation value or the gradient estimation value calculated from the estimated road elevation. The fuel efficiency to the destination depends on, for example, altitude change of the route to the destination. When the altitude of the destination is higher than the current position, potential energy for transporting the vehicle to a higher position is required, so that the fuel consumption tends to be larger than when the altitude of the destination is the same as the current value. Also in the case of providing such information, the present invention can accurately estimate the road surface elevation and the gradient, so that there is an effect that more accurate information can be provided to the driver.
[0057]
Although the embodiment in which the map database 53 holding the ground surface elevation information and the road information is mounted on the vehicle has been described, the present invention is not necessarily limited to such an embodiment.
[0058]
For example, there is a form in which the above-described road surface estimation processing is performed in advance on all roads from the ground surface elevation information and the road information, and the result is stored in the map database 53. According to this embodiment, it is not necessary to hold the mesh elevation data in the map database 53, and only the result of the road surface estimation processing may be held as the elevation data in association with the feature point on the road. With this configuration, the memory used by the database 53 can be reduced. In addition, since the vehicle controller 16 does not need the calculation for the road surface estimation processing, there is an advantage that the vehicle controller 16 can be realized by a lower-cost microcomputer.
[0059]
There is also a form in which a road surface estimation process for all roads is preliminarily performed from ground surface elevation information and road information, and the result is stored in a service provider (a base station capable of wireless communication with a vehicle). In this case, the ground elevation information and the road information need not be stored in the vehicle. However, in this case, the vehicle needs to have a communication function with the service provider. The destination information and the current location information set by the occupant are transmitted to the service provider using the communication function, the route guidance search and the elevation on the route are calculated on the service provider side, and the vehicle receives the data. Thereby, the road surface altitude of the guidance route can be estimated on the vehicle side. According to this embodiment, the amount of information held by the map database 53 may be small, and the memory used can be reduced. Further, since the navigation system 33 does not need the calculation for the road surface estimation processing, there is a merit that the navigation system 33 can be realized by a lower-cost microcomputer.
[0060]
The present invention is not limited to the above-described embodiments, and it is apparent that various changes can be made within the scope of the technical idea of the present invention.
[Brief description of the drawings]
FIG. 1 is a diagram showing a configuration of an embodiment of a vehicle equipped with a road surface estimation device of the present invention.
FIG. 2 is a diagram illustrating a configuration of a road surface estimation device.
FIG. 3 is a diagram for describing control performed by a road surface elevation estimating unit 56;
FIG. 4 is a diagram illustrating a road surface elevation estimation method according to the present invention.
FIG. 5 is another diagram illustrating a road surface elevation estimation method according to the present invention.
FIG. 6 is a diagram for explaining a method of obtaining certainty.
FIG. 7 is another diagram for explaining a method of obtaining certainty.
[Explanation of symbols]
1, 4, 10 motor
2 Engine
3 clutch
5 continuously variable transmission
6 Reducer
16 Controller

Claims (8)

Road information storage means for storing the latitude and longitude of a plurality of points on the road;
Surface elevation storage means for storing surface elevation information of a plurality of points on the map,
Interpolated elevation value calculation means for calculating the road surface elevation values of the plurality of points on the road using the ground surface elevation data of the plurality of points on the map in the vicinity,
From the road information or the altitude value information, a certainty calculating means for calculating the certainty of the calculated altitude values of the plurality of points,
Filter processing means for inputting the interpolated elevation value and estimating a road surface elevation value by performing a filtering process so that a value with a low probability of the elevation value has a small effect on an output value.
Road altitude estimation device for vehicles. The likelihood calculating means calculates the likelihood in accordance with the degree of variation in the elevation values of the plurality of points on the map that are close to the plurality of points on the road, and the likelihood is calculated lower as the variation is larger. The road surface elevation estimating device for a vehicle according to claim 1, wherein: The likelihood calculating means calculates the likelihood according to the degree of variation in the elevation values of the plurality of points on the map that are close to each other along the direction of the road including the plurality of points on the road. 3. The vehicle altitude estimating device according to claim 2, wherein a lower value is calculated as the value is larger. The likelihood calculating means calculates, at a point where a plurality of roads intersect, the degree of dispersion of elevation values at a plurality of points on the map which are adjacent along each road, and calculates the calculated degree of dispersion at a predetermined condition. The vehicle altitude estimating device according to claim 3, wherein a probability is calculated according to the selected degree of variation based on the selected variation. 5. The vehicle road surface according to claim 4, wherein the predetermined condition for selecting the degree of variation is to calculate a degree of variation for each of the plurality of roads and select a degree of variation of a road having the smallest degree of variation. Elevation estimation device. The road information storage means also has information on the road shape (tunnel, viaduct, bridge), and the likelihood calculating means assumes that the likelihood of the interpolated elevation value at the point in the tunnel, on the overpass, or on the bridge is low. The apparatus for estimating a road surface elevation according to any one of claims 1 to 4, wherein the apparatus is a means for calculating. A control characteristic determining means for determining a control characteristic of the vehicle,
The control characteristic determining means is means for determining a control characteristic of the vehicle suitable for the traveling state according to the estimated road elevation value or the gradient estimation value calculated from the estimated road elevation. The road surface elevation estimating device for a vehicle according to any one of claims 1 to 6. 8. A future information providing means for predicting future information of a vehicle according to an estimated road elevation value or a gradient estimation value calculated from the estimated road elevation, and providing the predicted information to a driver. The road surface elevation estimation device for a vehicle according to any one of the above.

Images