JP7469424B1 - Method for automatic driving of articulated vehicles - Google Patents
Method for automatic driving of articulated vehicles Download PDFInfo
- Publication number
- JP7469424B1 JP7469424B1 JP2022159300A JP2022159300A JP7469424B1 JP 7469424 B1 JP7469424 B1 JP 7469424B1 JP 2022159300 A JP2022159300 A JP 2022159300A JP 2022159300 A JP2022159300 A JP 2022159300A JP 7469424 B1 JP7469424 B1 JP 7469424B1
- Authority
- JP
- Japan
- Prior art keywords
- vehicle
- articulated
- axle
- changes
- automatic driving
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 26
- 230000005484 gravity Effects 0.000 claims abstract description 37
- 230000007246 mechanism Effects 0.000 claims description 2
- 230000001133 acceleration Effects 0.000 abstract description 46
- 230000033001 locomotion Effects 0.000 abstract description 39
- 238000010586 diagram Methods 0.000 description 24
- 230000008859 change Effects 0.000 description 11
- 238000002474 experimental method Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 230000003044 adaptive effect Effects 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 239000002131 composite material Substances 0.000 description 2
- 238000009795 derivation Methods 0.000 description 2
- 230000007935 neutral effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000005096 rolling process Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 101150004141 Vcan gene Proteins 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000009347 mechanical transmission Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Abstract
【課題】連節バス及び単車バスが共用運行されるバス高速輸送システムのための、連節バス及び単車バスが共用可能運行経路の設定と自動運転連節バスの制御方法の必要に応える。【解決手段】単車・連節車両を問わず最後軸の軌跡を経路とする経路設定をして、その経路を車両諸元寸法が異なり乗客乗降に伴う車両重量が変化する連節車両が辿ることができる様にする。自重変化、重心位置変化、軸荷重変化を捉えるセンサを装備する。動力性能を自重変化、道路勾配変化と共に捉えて要求加速度に応え、制動性能を自重変化、道路勾配変化と共に捉えて要求減速度に応える。路面の湿潤に適応して前後横運動の安全制御の必要を満たす。【選択図】図３[Problem] To meet the need for setting a route that can be shared by articulated buses and single-vehicle buses, and a control method for an autonomous articulated bus, for a bus rapid transit system in which articulated buses and single-vehicle buses are operated together. [Solution] A route is set that follows the trajectory of the last axle, regardless of whether it is a single-vehicle or articulated vehicle, and the route can be followed by articulated vehicles whose vehicle dimensions differ and whose vehicle weight changes as passengers get on and off. The vehicle is equipped with sensors that detect changes in vehicle weight, center of gravity position, and axle load. The vehicle's power performance is detected along with changes in vehicle weight and road gradient to meet the required acceleration, and the vehicle's braking performance is detected along with changes in vehicle weight and road gradient to meet the required deceleration. The vehicle satisfies the need for safe control of longitudinal and lateral movement by adapting to wet road surfaces. [Selected drawing] Figure 3
Description
本発明は計画された経路を運行するバス高速輸送システム（Bus Rapid Transit, BRT）に供される自動運転連節車両（Articulated Vehicle）とその制御に関する。 The present invention relates to an autonomous articulated vehicle (AV) for use in a bus rapid transit (BRT) system that operates along a planned route, and its control.
専用道路を走行するバスによって、鉄道並みの大量輸送を可能にするシステムをバス高速輸送（BRT）システムと称する。鉄道車両は、複数の車両が連結して同じ軌道レールの上を人の操舵を必要とせず走る。
バス高速輸送システムは、連節バス或いは単車バスが、レールのない路面を“人が運転操舵”して走る。本発明は、その“人の運転”を“自動運転”にし、且つ、複数の連節バス或いは連節バスと単車バスが1つの路線を共有して混在し混合し、互いに加減速を等しくして、1つの路線内で車間距離を詰めて、運行するシステムである。
A system that enables mass transportation on a par with railroads by using buses that run on dedicated roads is called a Bus Rapid Transit (BRT) system. Railroad cars are made up of multiple cars that are linked together and run on the same track rails without the need for human steering.
In a bus rapid transit system, articulated buses or single-vehicle buses run on a road surface without rails, driven and steered by a human. This invention is a system that changes this "human driving" to "automated driving," and allows multiple articulated buses or articulated buses and single-vehicle buses to share a single route and coexist, accelerating and decelerating equally to each other, and shortening the distance between vehicles on the route.
尚、ここで言う連節バスは、前側と後側の間に関節機構を有する二両編成のバスであり、エンジン（ガソリン・ディーゼル・水素エンジン、ハイブリッドエンジン、電動モータなどの動力源を総称）を搭載する後側車両が、エンジンを搭載しない前側車両を押して前進する。後から押されるため増加傾向になる連節角を抑制しての進路制御が必要になる。その点、エンジンを搭載する前側車両（トラクタ）がエンジンを搭載しない後側車両（トレーラ）を引くため前後車両の相対角が減少傾向になる牽引車と異なる。 Note that an articulated bus here is a two-car bus with a joint mechanism between the front and rear, in which the rear car, which is equipped with an engine (a general term for power sources such as gasoline, diesel, or hydrogen engines, hybrid engines, and electric motors), pushes the front car, which does not have an engine, to move forward. Because it is pushed from behind, it is necessary to control the course by suppressing the articulation angle, which tends to increase. In this respect, it differs from a towing vehicle, in which the front car (tractor) with an engine pulls the rear car (trailer) without an engine, so the relative angle between the front and rear cars tends to decrease.
人の運転によってレールのない路面で、鉄道がレールの上を走る様に、バスが「同じ軌跡を描き」走行してきて、駅・バス停のプラットホーム・縁石に横づけして（接弦して・正着して）停車することは簡単ではない。
特に、後車両が前車両を押して前進する連節車両には、その押す力（駆動力）によって生じる連節角の増加を抑制しつつ経路を辿る運転技量、連節する前車両と同じ軌道を辿らない後車両の軌道を見込みながら車線を辿り且つ正着する運転技量が求められる。
Just as a train runs on rails, it is not easy for a bus to "follow the same trajectory" as a train driven by a human driver on a road surface without rails and pull up alongside (attach directly to) the platform or curb at a station or bus stop.
In particular, articulated vehicles, in which the rear vehicle pushes the front vehicle forward, require driving skills to follow a route while suppressing the increase in articulation angle caused by the pushing force (driving force), and to follow the lane and arrive correctly while anticipating the trajectory of the rear vehicle, which does not follow the same trajectory as the articulated front vehicle.
同じ軌跡を描く自動運転には、「経路の曲率乃至経路方位角と操舵角の関係式」が必要である。「後車両の軌道を見込む」の自動運転には「後車両の方位角乃至後車両の経路方位角と操舵角の関係式」が必要である。 For autonomous driving to trace the same trajectory, "the relationship between the curvature of the route or the route azimuth and the steering angle" is required. For autonomous driving to "predict the trajectory of the rear vehicle", "the relationship between the azimuth of the rear vehicle or the route azimuth of the rear vehicle and the steering angle" is required.
特許文献１は、その図１に単車の場合と連節車両の場合のバス停正着軌跡を図示して、単車及び連節車両いずれの場合にも「最後軸の軌跡が車両全体の動きの根幹になる」としているが、その図４に「後軸が描く軌跡を辿るハンドル角を算出する方法」を、単車のみを例に示し、連節車両については示していない。
特許文献２は、連節車両の前部に走行レーンの画像を取得するカメラを備え、走行レーンの画像から経路と推奨速度を読み取って、前車両の前輪の操舵及び速度制御を支援する
運転支援システムと運転支援方法について示しているが、その走行レーンは「前車両の前輪が辿る経路」であり、特許文献１が述べる「単車及び連節車両いずれの場合にも最後軸の軌跡が車両全体の動きの根幹になる」ところを押さえていないので、この経路での運行は同じ仕様の連節車両の運行に限られる。仕様が異なる車両の運行はできない。
バスが駅・バス停のプラットホーム・縁石に横づけして停車する。乗降口が開き、乗客が乗降して、乗降口が閉まりバスが発進する。この間の乗客乗降に伴い車両総重量とその重心位置が変化するので、出発時の車両の加速特性（動力性能）・減速特性（制動性能）・操舵特性（横運動性能）は、到着時と異なる。加速特性は、車両総重量と道路勾配の変化に影響されるので、その変化を推定ないし検出して適応する適応制御が求められる。減速特性は、加速特性同様に車両総重量と道路勾配の変化に影響されるが、装備するEBS（電子制御ブレーキシステム）によって対処される。操舵特性は、車両総重量の変化に加えて重心位置の変化及び路面摩擦（各車軸のコーナリング係数）の変化に影響されるので、その変化を推定ないし検出して適応する適応制御が求められる。 A bus stops alongside the platform or curb at a station or bus stop. The boarding and alighting door opens, passengers get on and off, the door closes, and the bus departs. During this time, the total vehicle weight and the position of the center of gravity change, so the acceleration characteristics (power performance), deceleration characteristics (braking performance), and steering characteristics (lateral movement performance) of the vehicle at the time of departure are different from those at the time of arrival. Acceleration characteristics are affected by changes in total vehicle weight and road gradient, so adaptive control is required to estimate or detect these changes and adapt to them. Deceleration characteristics are also affected by changes in total vehicle weight and road gradient, like acceleration characteristics, but are handled by the EBS (electronic brake system) installed. Steering characteristics are affected by changes in total vehicle weight as well as changes in center of gravity and road friction (cornering coefficient of each axle), so adaptive control is required to estimate or detect these changes and adapt to them.
特許文献３は、その図６において車両重量と軸重を推定する方法を説明している。車速とエンジン回転からギヤ比を判別してピークトルク点における空車加速度を把握して照合用空車加速度データとし、その空車加速度と道路勾配を含む実稼働加速度から算出する平坦路実稼働換算値との比から積車重量を推定する。更に、後軸の空気ばねの空気圧から後軸荷重を検出して、車両重量から後軸荷重を引算して前軸荷重を求めること、即ち、重心位置を求める方法を示している。しかし、それは、単車についてであり、連節車両については示しておらず、運行中の加速度から検出する方法であり、駅・バス停における停車時の乗客乗降によって生じる自重・軸重変化を求める必要までは満たせていない。
更に、特許文献３は、その図３において操舵特性（横運動性能）の指標であるスタビリティファクタの式（４）と横すべり係数の式（５）を実験同定する方法を説明している。
実験同定されたスタビリティファクタ及び横すべり係数を制御に適用することにより、2軸車、3軸車、4軸車に適用する車両操舵装置の提供が可能になるとしているが、その実験同定されたスタビリティファクタおよび横すべり係数に含まれる各車軸のコーナリング係数を求めて制御モデルに反映する方法、更に連節車両への適用については示していない。
Furthermore, in FIG. 3 of
It is said that by applying the experimentally identified stability factor and sideslip coefficient to control, it is possible to provide a vehicle steering device applicable to two-axle, three-axle, and four-axle vehicles. However, it does not show a method for determining the cornering coefficient of each axle contained in the experimentally identified stability factor and sideslip coefficient and reflecting it in a control model, nor does it show how to apply it to articulated vehicles.
上述した従来技術にあっては、単車バスと連節バスが、同じ経路を、バス停における乗客乗降に伴う自重など自車の状態が変化しても、それに適応して、同じ軌跡を描き、加減速を等しくして、車間距離を詰めて、自動運行するBRTシステムのための連節車両の自動運転方法を示していない。 The above-mentioned conventional technologies do not disclose an automatic driving method for articulated vehicles for a BRT system in which single-vehicle and articulated buses travel the same route, adapting to changes in the state of their own vehicles, such as their own weight, as passengers get on and off at bus stops, while tracing the same trajectory, equalizing acceleration and deceleration, and reducing the distance between vehicles.
本発明は、同じ経路を同じ軌跡を描き辿るについては、特許文献１が述べるところの、単車及び連節車両いずれの場合にも「最後軸の軌跡が車両全体の動きの根幹になる」を踏まえて「後軸が描く軌跡を辿るハンドル角を算出する方法」を、連節車両について示し、自重などの自車の状態の変化を検出する方法を示し、検出した自車の状態を諸元とする進路制御式、加速度制御式、減速度制御式を示して、乗客数の変化に伴う車両状態量の変化、路面摩擦変化に適応しての混成BRTシステムのための自動運転制御法を示す。
Regarding tracing and following the same trajectory along the same route, the present invention shows, for articulated vehicles, a "method of calculating the steering angle that traces the trajectory of the rear axle" based on the fact that, as stated in
上記課題を解消するため本発明は、単車・連節車両を問わず“最後軸の軌跡”を経路とする経路設定をして、車両諸元寸法が異なる単車・連節車両が辿ることができる様にする。その“最後軸の軌跡”とは、連節バスの場合は、連節後車両の重心の運動に対応するので、連節車両全体の車両運動を連節後車両の運動に集約した横運動モデルを導出して、後車の後軸の軌跡に対応する前車の前軸実舵角制御式、後車の後軸の軌跡に対応した連節角制御式を示す。その制御式に含まれる自重変化、路面摩擦変化に適応するタイヤ特性式を示す。自重変化、勾配変化に適応する加速度制御式及び減速度制御式を示す。 In order to solve the above problems, the present invention sets a route that follows the "path of the last axle" regardless of whether the vehicle is a single vehicle or an articulated vehicle, allowing single vehicles and articulated vehicles with different vehicle dimensions to follow it. In the case of an articulated bus, the "path of the last axle" corresponds to the movement of the center of gravity of the rear articulated vehicle, so a lateral movement model is derived that aggregates the vehicle movement of the entire articulated vehicle into the movement of the rear articulated vehicle, and a front axle actual steering angle control equation for the front vehicle that corresponds to the path of the rear axle of the rear vehicle and an articulation angle control equation that corresponds to the path of the rear axle of the rear vehicle are shown. Tire characteristic equations that adapt to changes in vehicle weight and road surface friction included in the control equations are shown. Acceleration control equations and deceleration control equations that adapt to changes in vehicle weight and gradient are shown.
本発明によれば、単車・連節車両共用経路でのバス高速輸送システムが成立し、乗客数の変化に伴う自重・重心位置などの車両内部状態変化、道路の勾配・路面の湿潤などの車両外部状態変化（環境変化）に適応してのバス高速輸送システムが成立する。 According to the present invention, a bus rapid transit system can be established on a route shared by single vehicles and articulated vehicles, and the system can be established that can adapt to changes in the internal conditions of the vehicle, such as its own weight and center of gravity position, that accompany changes in the number of passengers, and changes in the external conditions of the vehicle (environmental changes), such as the gradient of the road and wetness of the road surface.
本発明の実施の形態を図１から図１１にもとづいて説明する。
図１に鉄道の軌道と自動車の軌道の相違を示す。図の左側に鉄道の軌道を示し、右側に自動車の軌道を示す。鉄道が前軸の左右輪と後軸の左右輪が同じ轍を通る同轍軌道であるのに対して、自動車は前軸の旋回内輪と後軸の旋回内輪の轍に内輪差、前軸の旋回外輪と後軸の旋回外輪の轍に外輪差が生じ同じ轍を通らない。そのため、バス高速輸送システム（BRT）の軌道を定めて、そこで自動車を自動運転制御するについて、前軸又は後軸いずれの軌道を基軸にするかの配慮が必要になる。
An embodiment of the present invention will be described with reference to FIGS.
Figure 1 shows the difference between railroad tracks and automobile tracks. The left side of the figure shows railroad tracks, and the right side shows automobile tracks. Railroad tracks are the same track, where the left and right wheels of the front axle and the left and right wheels of the rear axle follow the same track, whereas automobiles have an inner wheel difference between the track of the inner wheel of the front axle and the inner wheel of the rear axle, and an outer wheel difference between the track of the outer wheel of the front axle and the outer wheel of the rear axle, so they do not follow the same track. Therefore, when determining the track of a bus rapid transit (BRT) system and controlling the automatic driving of automobiles on it, it is necessary to consider whether the track of the front axle or the rear axle should be used as the base.
図２に、単車と連節車両の最後軸の軌道が共通することを示す。図の左側に単車の軌道を示し、右側に連節車両の軌道を示す。点線で示す単車の後車軸中心の軌跡と連節車両の後車両の後車軸中心の軌跡が共通していることが判る。このことから、バス高速輸送システム（BRT）の軌道は、最後車軸の軌跡で定める必要がある。 Figure 2 shows that the track of the last axle of a single car and an articulated car is the same. The track of a single car is shown on the left side of the figure, and the track of an articulated car is shown on the right side. It can be seen that the trajectory of the center of the rear axle of the single car, shown by the dotted line, is the same as the trajectory of the center of the rear axle of the rear car of the articulated car. For this reason, the track of a bus rapid transit (BRT) system needs to be determined by the trajectory of the last axle.
図３に、連節車両の横運動モデルを説明する。図の左側に車両平面図、右側に車両モデル図を示す。車両平面図は、図の上部から下部へ前車両、連節機、後車両が示され、その下部に連節機が示され、更にその下に後車両が示され、連節角（δ12）が生じた状態の前車両外形が点線で示される。前車両には、ハンドル、前軸（操舵輪）、重心、後軸（非駆動軸）が図示され、後車両には、重心、後軸（駆動軸）が図示されている。これら図示されているものは、乗客乗降に伴う車両総重量変化、軸荷重変化、タイヤ特性変化と、ハンドル操作に伴う車両の横運動（進路変化）に関係する車両状態量である。これら車両状態量を記号で表現すると右側の車両モデル図になる。 FIG. 3 illustrates the lateral motion model of an articulated vehicle. The left side of the figure shows a vehicle plan view, and the right side shows a vehicle model view. In the vehicle plan view, the front vehicle, the articulated machine, and the rear vehicle are shown from top to bottom, with the articulated machine shown below, and the rear vehicle shown further below that, and the front vehicle outline with the articulated angle (δ 12 ) being generated is shown in dotted lines. The front vehicle shows the steering wheel, front axle (steered wheels), center of gravity, and rear axle (non-driven axle), and the rear vehicle shows the center of gravity and rear axle (driven axle). These figures show vehicle state quantities related to the change in total vehicle weight, axle load, and tire characteristic changes associated with passengers getting on and off, and the lateral motion (course change) of the vehicle associated with steering operation. These vehicle state quantities are expressed by symbols to form the vehicle model view on the right.
前車両の重心を原点とするx1y1座標と、後車両の重心を原点とするx2y2座標を定め、連節点pcでx1y1座標とx2y2座標を連節させ、連節角をδ12とする。前車両と後車両それぞれに重心位置に質量m1,m2、慣性モーメントI1,I2を置き、それら重心点の速度v1,v2としその車体横すべり角をβ１，β２とし、それら重心点回りのヨーレイトをr1,r2とする。前車両の重心点から前方ｌf1に前軸左右輪を中央に集約した前車両前軸タイヤを置き、タイヤ速度をvf1、タイヤ切れ角をδ、タイヤ横すべり角をβf1、そのタイヤが発生するコーナリングフォースをCF1とする。前車両の重心点から後方ｌr1に後軸左右輪を中央に集約した前車後軸タイヤを置き、タイヤ速度をvr1、タイヤ横すべり角をβr1、そのタイヤが発生するコーナリングフォースをCR1とする。後車両の重心点から後方ｌf2に後軸左右輪を中央に集約した後車後軸タイヤを置き、タイヤ速度をvr2、タイヤ横すべり角をβr2、そのタイヤが発生するコーナリングフォースをCR2とする。前車両の重心から後方ｌc1の位置且つ後車両の重心から前方ｌf2の位置に連節点pcを置いて、その連節点に作用する前後荷重をFx,横荷重をFyとし、その連節点における前車両の横すべり角をβp1、前車両の横すべり角をβp2とする。 Define the x1y1 coordinate with the center of gravity of the front vehicle as the origin, and the x2y2 coordinate with the center of gravity of the rear vehicle as the origin, and articulate the x1y1 and x2y2 coordinates at articulation point pc , with the articulation angle being δ12 . Place masses m1 , m2 and moments of inertia I1 , I2 at the center of gravity of the front and rear vehicles, respectively, and take the velocities v1 , v2 of these center of gravity points, the vehicle body sideslip angles β1 , β2 , and the yaw rates r1 , r2 about these center of gravity points. Place the front vehicle front axle tires, with the left and right front axle wheels gathered in the center, lf1 forward of the center of gravity of the front vehicle, and take the tire speed vf1 , tire turning angle δ, tire sideslip angle βf1 , and cornering force generated by the tire CF1 . A front vehicle rear axle tire with the left and right rear wheels gathered in the center is placed lr1 rearward from the center of gravity of the front vehicle, and the tire speed is vr1, the tire side slip angle is βr1 , and the cornering force generated by the tire is CR1 . A rear vehicle rear axle tire with the left and right rear wheels gathered in the center is placed lf2 rearward from the center of gravity of the rear vehicle, and the tire speed is vr2 , the tire side slip angle is βr2 , and the cornering force generated by the tire is CR2 . A joint point pc is placed at a position lc1 rearward from the center of gravity of the front vehicle and lf2 forward from the center of gravity of the rear vehicle, and the front/rear load acting on the joint point is Fx, the lateral load is Fy, the lateral slip angle of the front vehicle at the joint point is βp1, and the lateral slip angle of the front vehicle is βp2.
図４に、連節車両の横運動モデルの状態方程式導出について説明する。連節点ｐcで連節される前車両と後車両との、連節分離状態を左側に、連節状態を右側に示して、連節部における拘束条件の説明に供する。先に、右側図により、前車両の前後運動のつり合い式、横運動のつり合い式、回転運動のつり合い式、及び後車両の前後運動のつり合い式、横運動のつり合い式、回転運動のつり合い式について説明した後に、左側図により連節部の拘束条件式について説明する。 The derivation of the state equation for the lateral motion model of an articulated vehicle will be explained in Fig. 4. The articulated separated state of the front and rear vehicles articulated at articulation point p c is shown on the left, and the articulated state is shown on the right, to explain the constraint conditions at the articulation section. First, the balance equations for the longitudinal motion, lateral motion, and rotational motion of the front vehicle, and the balance equations for the longitudinal motion, lateral motion, and rotational motion of the rear vehicle will be explained using the right-hand diagram, and then the constraint condition equations for the articulation section will be explained using the left-hand diagram.
先の段落（００１４）で述べた「連節車両全体の車両運動を連節後車両の運動に集約した横運動モデル」を導出するためには、前車両のヨー角（ω１）及び横すべり角（β１）を、後車両のヨー角（ω２）及び横すべり角（β２）で表現する必要がある。その対応について以下に述べる。 In order to derive the "lateral motion model in which the vehicle motion of the entire articulated vehicle is integrated into the motion of the rear articulated vehicle" mentioned in paragraph (0014) above, the yaw angle ( ω1 ) and sideslip angle ( β1 ) of the front vehicle must be expressed in terms of the yaw angle ( ω2 ) and sideslip angle ( β2 ) of the rear vehicle. The correspondence therebetween will be described below.
・連節点の横すべり角は、前車両の重心点横すべり角（β１）から展開すると式（14）、後車両の重心点横すべり角（β２）から展開すると式（15）になる。 The side slip angle of the joint is expressed as equation (14) when expanded from the side slip angle of the center of gravity of the front vehicle (β 1 ), and as equation (15) when expanded from the side slip angle of the center of gravity of the rear vehicle (β 2 ).
・前車両の重心点横すべり角は、式（14）から式（14a）に展開して、βp1に式（10）のβp1を代入すると式（14b）になる。 - The front vehicle's center of gravity side slip angle is calculated by expanding equation (14) to equation (14a) and substituting βp1 from equation (10) for βp1, resulting in equation (14b).
・式（14c）に前側車両のヨーレイトr1が含まれる。これを後車両の状態量で表現する。式（１４ｃ）における前車両のヨーレイトr1と後車両のヨーレイトr2は、式（９a）から次の様に展開してr1＝r2と見做し、式（14ｄ）の様に整理する。 The yaw rate r1 of the front vehicle is included in equation (14c). This is expressed as a state quantity of the rear vehicle. The yaw rate r1 of the front vehicle and the yaw rate r2 of the rear vehicle in equation (14c) are expanded from equation (9a) as follows, and are rearranged as in equation (14d), assuming that r1 = r2 .
連節車両全体の車両運動を連節後車両の運動に集約した横運動モデルの制御式は、各軸のコーナリングフォース（CF1、CR1、CR2）を各軸の荷重（Nf1、Nr1、Nr2）と各軸の路面摩擦係数に相当するコーナリング係数（前車両前軸をCcf、前車両後軸及び後車後軸をCcr）の積で表現すると、次の様になる。 The control equation for the lateral motion model, which aggregates the vehicle motion of the entire articulated vehicle into the motion of the post-articulated vehicle, is as follows, expressing the cornering force of each axle (CF1, CR1, CR2) as the product of the load of each axle (Nf1, Nr1, Nr2) and the cornering coefficient equivalent to the road friction coefficient of each axle (Ccf for the front axle of the front vehicle, Ccr for the rear axle of the front vehicle and the rear axle of the rear vehicle).
導出した式（16）、式（17）について、実験同定を可能にするために、横すべり係数とスタビリティファクタで表現する式に展開する。 The derived equations (16) and (17) are expanded into equations expressed in terms of the sideslip coefficient and stability factor to enable experimental identification.
横すべり係数ｋβ0の式（16i）と、スタビリティファクタKSFの式（17i）の一次の連立方程式を解くと、前車両の前軸コーナリング係数Ccfの式（18）、前車両の後軸および後車両の後軸コーナリング係数Ccrの式（19）が得られる。 By solving the linear simultaneous equations of equation (16i) for the sideslip coefficient kβ0 and equation (17i) for the stability factor KSF, equation (18) for the front axle cornering coefficient Ccf of the front vehicle and equation (19) for the rear axle cornering coefficients Ccr of the front vehicle and the rear axle of the rear vehicle can be obtained.
図５に連節車両の横運動モデルの同定実験について説明する。図の左側に、前車両前軸の実舵角δを固定（保持）して定常円旋回する連節車両図を示し、その定常円旋回によって得られる後車両の重心点における横すべり角βの車速依存特性（式16ｈ））及び後車両の重心点の旋回半径の車速依存特性（式（17h））を示している。左図において、後車両の重心の旋回半径は極低速時後車両後車軸の延長線上の点“Ov0”から、車速上昇時の“Ovup”へ移動する。この変化を右側の図の横すべり係数Ｋβ0及びスタビリティファクタKSFを式（16i）及び式（17i）の実験同定値として取得する。即ち、この変化は、前出の式（０）の静的旋回半径Rr2=1/ρ2rが、車速上昇に依存し式（17h）の動的変化をして、式（２０）になることを意味する。 Figure 5 explains the identification experiment of the lateral motion model of an articulated vehicle. The left side of the figure shows an articulated vehicle making a steady circular turn with the actual steering angle δ of the front axle of the front vehicle fixed (maintained), and shows the vehicle speed dependency characteristic of the side slip angle β at the center of gravity of the rear vehicle obtained by the steady circular turn (Equation 16h)) and the vehicle speed dependency characteristic of the turning radius of the center of gravity of the rear vehicle (Equation (17h)). In the left figure, the turning radius of the center of gravity of the rear vehicle moves from a point "O v0 " on the extension line of the rear axle of the rear vehicle at a very low speed to "O vup " when the vehicle speed increases. This change is obtained as the side slip coefficient K β0 and stability factor K SF in the right side figure as experimental identification values of Equation (16i) and Equation (17i). That is, this change means that the static turning radius R r2 =1/ρ 2r in the above equation (0) depends on the increase in vehicle speed and undergoes a dynamic change of equation (17h) to become equation (20).
そして、式（１８）により前車両の前軸のタイヤコーナリング係数の実験同定値を取得し、式（１９）により前車両の後軸及び後車両の後軸のタイヤコーナリング係数の実験同定値を取得する。 Then, the experimentally identified value of the tire cornering coefficient of the front axle of the front vehicle is obtained using equation (18), and the experimentally identified value of the tire cornering coefficient of the rear axle of the front vehicle and the rear axle of the rear vehicle is obtained using equation (19).
図６に、車両重量変化・重心位置変化・軸重変化を検出するセンサ装備を説明する。図の左側に連節車両の平面図と側面図を示す。図の右側の枠内に前車両と後車両を連節する連節機を示す。連節機には、Ｙ軸ジョイントとＺ軸ジョイントがある。Y軸ジョイント部にて前後車両間の前後荷重、横荷重及び上下荷重の伝搬がされると共に、前後車両間のピッチ角変化が吸収されて、Z軸ジョイント部にて前後車両間のヨー角変化（方位角変化）が吸収される。このY軸ジョイント部に上下荷重を検出するロードセル（上下荷重センサ）を装備し、前車両と後車両の各車軸の空気ばねのエア配管部に空気圧センサを装備して、乗客数などの変化に伴う車両総重量の変化を検出する。Z軸ジョイント部には、連節角変化を検出する角度センサが、自動運転に限らず標準装備される。 Figure 6 explains the sensor equipment that detects changes in vehicle weight, center of gravity, and axle load. The left side of the figure shows a plan view and a side view of an articulated vehicle. The right side of the figure shows the articulation machine that articulates the front and rear vehicles in the frame. The articulation machine has a Y-axis joint and a Z-axis joint. The Y-axis joint transmits the front-rear load, lateral load, and vertical load between the front and rear vehicles, and absorbs pitch angle changes between the front and rear vehicles, while the Z-axis joint absorbs yaw angle changes (azimuth angle changes) between the front and rear vehicles. This Y-axis joint is equipped with a load cell (vertical load sensor) that detects vertical loads, and air pressure sensors are installed in the air piping of the air springs of each axle of the front and rear vehicles to detect changes in total vehicle weight due to changes in the number of passengers, etc. The Z-axis joint is equipped with an angle sensor that detects articulation angle changes as standard, not just in autonomous driving.
図７に、図６に照合して進めるところの車両総重量変化、重心位置変化、軸重変化の検出フローを説明する。
工程（１）にて、連節前に前車両の前軸/後軸荷重、後車両のYジョイント及び後軸の荷重（Nf1,Nr1,Nf2,Nr2）を計測する。工程（２）にて、空車の前車両重心位置、及び後車両重心位置（ｌf1v,ｌf2v）を式（２１）式（２２）により計算する。ここまでは、車両製造工程での検査管理項目として記録されることが望ましい。
FIG. 7 illustrates a flow of detecting changes in the total vehicle weight, the center of gravity position, and the axle load, which is carried out in conjunction with FIG.
In process (1), the loads of the front and rear axles of the front vehicle and the loads of the Y-joint and rear axles of the rear vehicle are measured before articulation. In process (2), the position of the empty front vehicle center of gravity and the position of the rear vehicle center of gravity (lf1v, lf2v) are calculated using equations (21) and (22). It is desirable that the above information be recorded as an inspection and management item in the vehicle manufacturing process.
工程（３）にて、空車連節状態での各軸の空気ばね荷重（△Nf1,△Nr1，△Nr2）及びジョイント荷重（△Nf2）を把握して、この荷重をゼロ点とする。工程（４）にて、乗車状態での各軸空気ばね荷重及び連節ジョイント荷重のゼロ点補正後値（△Nf1w,△Nf2w,△Nr2w,及び、△Nf2w）を把握する。工程（５）にて、後車の乗客荷重（△Nr2w,及び△Nf2w）とその合力点（ｌf2p）を式（23）により計算する。 In step (3), the air spring loads (△Nf1, △Nr1, △Nr2) and joint loads (△Nf2) of each axle in the empty articulated state are determined, and these loads are set as the zero point. In step (4), the zero point corrected values (△Nf1w, △Nf2w, △Nr2w, and △Nf2w) of the air spring loads of each axle and articulated joint loads in the occupant state are determined. In step (5), the passenger loads of the rear car (△Nr2w, and △Nf2w) and their resultant force point (lf2p) are calculated using formula (23).
工程（６）にて、前車の乗客荷重（△Nr1w、及び△Nf1w）とその合力点（ｌf1p）を式（24）式（25）及び式（26）により計算する。 In step (6), calculate the passenger load of the front car (△Nr1w and △Nf1w) and its resultant force point (lf1p) using equations (24), (25), and (26).
工程（７）にて、後車の車両重量と乗客重量の合計の車両総重量（w1+△W2）とその合重心点（ｌf2vp）を式（２7）式（２8）により計算する。 In step (7), the total vehicle weight (w1+△W2), which is the sum of the rear vehicle weight and passenger weight, and its combined center of gravity point (lf2vp) are calculated using equations (27) and (28).
工程（８）にて、前車の車両重量と乗客重量の合計の車両総重量（W1＋△W１）とその合重心点（ｌf1vp）を式（２9）式（30）により計算する。 In step (8), the total vehicle weight (W1 + △W1), which is the sum of the vehicle weight of the front vehicle and the passenger weight, and its combined center of gravity point (lf1vp) are calculated using equations (29) and (30).
工程（９）にて、乗車状態での各軸荷重（Nf1w,Nr1w,Nr2w）を式（31）式（32）及び式（33）により計算する。 In step (9), calculate the loads on each axle (Nf1w, Nr1w, Nr2w) in the riding state using equations (31), (32), and (33).
以上の様にして、求められた乗客の乗降に伴う車両総重量、重心位置及び軸荷重の変化は、前後運動モデル及び横運動モデルの諸元に反映されて、その変化への適応制御に用いられる。 The changes in total vehicle weight, center of gravity, and axle loads resulting from passengers getting on and off in this way are reflected in the specifications of the longitudinal motion model and lateral motion model, and are used for adaptive control to those changes.
図８に、加速度表現での走行性能曲線図と加速制御式を説明する。図の上段の左から右へ順に、エンジントルク図、ギヤ変速図、走行性能曲線図に並べ、その右側下段に加速度表現での走行性能曲線図を示す。そして、加速度表現での走行性能曲線式（３４）、下段の右から左へ移動して、要求加速度の式（３５）、その下に要求加速度に応えるアクセル開度式（３６）、更にその下に発生加速度から乗車時車両質量を算出する式（３７）を示す。 Figure 8 explains the driving performance curve diagram and acceleration control formula expressed in acceleration. From left to right in the upper part of the figure, the engine torque diagram, gear shift diagram, and driving performance curve diagram are arranged, and the driving performance curve diagram expressed in acceleration is shown in the lower right part. Then, moving from right to left in the lower part, the driving performance curve diagram expressed in acceleration (34) is shown, and below that, the equation for the required acceleration (35), the accelerator opening equation (36) that responds to the required acceleration, and further below that, the equation (37) for calculating the vehicle mass when riding from the generated acceleration are shown.
エンジントルク図はピークトルク点(np)を持ちそのピーク点より低回転側を使用する。エンジントルクは、AMT（Automated Mechanical Transmission）を経てギヤ変速されて走行性能線図になる。この図の4段のギヤ比の例では、四つの山（駆動力）が描かれる。その山に接して点線で描かれる二次曲線は双曲線になる。その駆動力は、ころがり抵抗と空気抵抗の和の速度依存の二次曲線で表現される惰行抵抗に坂路勾配に重力加速度を乗じた勾配抵抗を加えた走行抵抗に消費される。その双曲線からその走行抵抗を差引いた駆動力が余剰牽引力になる。 The engine torque diagram has a peak torque point (n p ), and the lower revolution side than the peak point is used. The engine torque is changed through the AMT (Automated Mechanical Transmission) and becomes the driving performance diagram. In the example of a four-speed gear ratio in this diagram, four peaks (driving force) are drawn. The quadratic curve drawn with dotted lines tangent to the peaks becomes a hyperbola. The driving force is consumed by the running resistance, which is the coasting resistance expressed by a speed-dependent quadratic curve of the sum of rolling resistance and air resistance, plus the gradient resistance, which is the slope of the hill multiplied by the acceleration of gravity. The driving force subtracted by the running resistance from the hyperbola becomes the surplus traction force.
車速に対する駆動力で表現される走行性能曲線図の駆動力に代え加速度と減速度で表現すると加速度表現での走行性能曲線図になる。平坦なテストコースにおいてアクセル開度全開で加速実験をして（2）の実線で示す発生加速度曲線を得て、高速域からギヤを中立にしてアクセルを放して減速度を記録して（3）の惰行抵抗減速度の2次曲線を得て、それを（2）の発生加速度曲線に加えると（1）の点線で示す双曲線の式（34）になる。 If you express the driving performance curve in terms of acceleration and deceleration instead of driving force, which is expressed as a function of vehicle speed, you get a driving performance curve expressed in terms of acceleration. An acceleration experiment is conducted with the accelerator fully open on a flat test course to obtain the generated acceleration curve shown by the solid line in (2). From high speed range, the gear is put into neutral and the accelerator is released, and the deceleration is recorded to obtain the quadratic curve of coasting resistance deceleration in (3). Adding this to the generated acceleration curve in (2) results in the hyperbolic equation (34) shown by the dotted line in (1).
左辺のｙは、要求加速度（乃至、発生加速度）である。右辺のaが双曲線定数、ｘが車速、m0が空車質量、ｍLが乗車質量、Acc%がアクセル開度、Drがころがり抵抗相当加速度、Daが空気抵抗相当加速度、Dθは勾配抵抗相当加速度である。a、m0、Dr、Daは図の右下の「加速度表現での走行性能曲線図」を作成する際の実験によって既知であり、ｍLは図6，図7によって既知であるから、現在走行中の道路勾配Dθ、車速ｘ、アクセル開度Acc%に応じた加速度ｙが算出できる。尚、道路勾配Dθは、後述図9により取得できる。 y on the left side is the required acceleration (or generated acceleration). a on the right side is the hyperbolic constant, x is the vehicle speed, m0 is the unladen vehicle mass, mL is the occupant mass, Acc% is the accelerator pedal stroke, Dr is the acceleration equivalent to rolling resistance, Da is the acceleration equivalent to air resistance, and Dθ is the acceleration equivalent to gradient resistance. a, m0 , Dr, and Da are known from experiments conducted when creating the "Driving performance curve diagram in acceleration expression" shown in the lower right of the figure, and mL is known from Figures 6 and 7, so that the acceleration y corresponding to the road gradient Dθ , vehicle speed x, and accelerator pedal stroke Acc% on the current road can be calculated. The road gradient Dθ can be obtained from Figure 9, which will be described later.
式（３５）から式（３６）の要求加速度に対するアクセル開度の式が得られる。この式（３６）から、現在走行中の道路勾配Dθ、車速ｘにおいて、要求加速度ｙを受けて、アクセル開度Acc%を決める制御ができる。 From equation (35), an equation for the accelerator opening degree with respect to the required acceleration can be obtained as equation (36). From this equation (36), control can be performed to determine the accelerator opening degree Acc% in response to the required acceleration y at the current road gradient D θ and vehicle speed x.
式（３５）式（３６）から式（３７）の乗車時車両質量の式が得られる。搭載されている加速度計によって検出される発生加速度ｙ、車速ｘ、アクセル開度、道路勾配を入力することにより乗車時車両質量ｍLが判り、図６図７による検出値と照合しての検証ができる。自動運転は、アクセル開度Acc%相対の状態量を制御して行われる。 From equations (35) and (36), the equation for the vehicle mass at the time of riding can be obtained as equation (37). The vehicle mass at the time of riding m L can be determined by inputting the generated acceleration y detected by the on-board accelerometer, the vehicle speed x, the accelerator opening, and the road gradient, and can be verified by comparing it with the detection values shown in Figures 6 and 7. Autonomous driving is performed by controlling the state quantity relative to the accelerator opening Acc %.
図９に、道路勾配の推定方法を説明する。車両に搭載される重力加速度計（G計）の読み値（Gx(static)）は、坂道で静止乃至定速状態では式（３８）になる。 A method for estimating the road gradient is explained with reference to Fig. 9. The reading (G x(static) ) of a gravitational accelerometer (G meter) mounted on a vehicle is expressed by equation (38) when the vehicle is stationary or moving at a constant speed on a slope.
図１０に、減速度制御の方法を説明する。乗客数の変化、道路勾配の変化に適応してブレーキペダルストロークに比例する減速度を発生させる電子制御ブレーキシステム（EBS）が装備されていることを前提とする。図の右側にブレーキペダルストローク（％）に対する発生減速度（ｍ/ｓ２）例を示す。減速度制御式は式（４１）になる。 The method of deceleration control is explained in Figure 10. It is assumed that the vehicle is equipped with an electronic brake system (EBS) that generates deceleration proportional to the brake pedal stroke in response to changes in the number of passengers and road gradient. An example of generated deceleration (m/ s2 ) versus brake pedal stroke (%) is shown on the right side of the figure. The deceleration control formula is given by formula (41).
図１１に、GPSと磁気マーカと慣性計測との整合をとり機能する車両（力学）モデルを説明する。図の上部太線の上側に前後運動を示し、太線の下側に横運動を示す。先ず、前後運動の部分について説明する。車速（車輪速）と前後加速度（Gx）から道路勾配（図９参照）を推定し、アクセル％と車速と道路勾配から自重（図７，８）を推定して、計画車速に対する要求加減速度に対応するアクセル％、或いはブレーキ％を算出して計画車速、或いは運行事情に合わせて車速制御する。車両運動には車体横すべり角を伴うため車輪速（前後速度）と車体横すべり角の影響を受けないGPSによる車速（前後と横の合成速度）との相違が生じるので、「車載する加速度計による横加速度を積分しての横速度と前後加速度を積分しての前後速度の比から求める横すべり角」及び「車両モデルから得られる車体横すべり角」の余弦で除し、GPS車速と照合して誤差補正する。 Figure 11 explains the vehicle (mechanical) model that functions by matching the GPS, magnetic markers, and inertial measurements. The upper part of the figure shows the longitudinal movement above the thick line, and the lower part shows the lateral movement below the thick line. First, the longitudinal movement part will be explained. The road gradient (see Figure 9) is estimated from the vehicle speed (wheel speed) and longitudinal acceleration (Gx), and the vehicle weight (Figures 7 and 8) is estimated from the accelerator %, vehicle speed, and road gradient, and the accelerator % or brake % corresponding to the required acceleration/deceleration for the planned vehicle speed is calculated, and the vehicle speed is controlled according to the planned vehicle speed or driving conditions. Since the vehicle motion involves the vehicle body side slip angle, there is a difference between the wheel speed (longitudinal speed) and the vehicle speed (combined longitudinal and lateral speed) by GPS that is not affected by the vehicle body side slip angle. Therefore, the vehicle body side slip angle is divided by the cosine of "the side slip angle obtained from the ratio of the lateral speed obtained by integrating the lateral acceleration by the accelerometer mounted on the vehicle and the longitudinal speed obtained by integrating the longitudinal acceleration" and "the vehicle body side slip angle obtained from the vehicle model", and the error is corrected by comparing with the GPS vehicle speed.
次に、横運動部分について説明する。GPSベースでの目標経路座標を備えて現在位置から目標経路へ流入する曲線式を作成してその曲率計算をする。並行して、視覚センサによる目標点に至る経路曲率を計算もして備えて待機する。視覚センサが障害検出すると、その障害を回避するための前後距離と横距離をパラメータとする進路変更式に検出した前後距離と横距離を代入して進路変更の曲率を算出して、その曲率を計画経路曲率へ加えて合成曲率を得てハンドル角の式に代入すると共に、「その合成曲率と車速から求められる横加速度」と「車輪速と横加速度とヨーレイトによって検出される道路カント」との和になる「相対カント角（ξ）」をハンドル角の式へ代入する。ハンドル角の式（２０）には、積載により変化する軸重が代入され車両或いは車両モデルへの入力舵角を算出する。その入力操舵は操舵モータによって行われる。その際に、操舵モータのゼロ点位置と実車ハンドル中立位置との偏差が車両制御量に入力され、それを受けて車両運動が生じ、生じた横すべり角（β）、ヨー角（φ）から移動座標とその方位角がGPS,磁気センサ、及びIMUから出力される。並行してハンドル角に操舵ヒステリシス補正が加えられた実舵角が式（16）式（１７）の車両モデルに入力され、横すべり角（β）、ヨー角（φ）から移動座標とその方位角の計算値が出力される。 Next, the lateral movement part will be explained. A curve equation flowing from the current position to the target route is created with GPS-based target route coordinates, and its curvature is calculated. In parallel, the route curvature to the target point is calculated using the visual sensor and is on standby. When the visual sensor detects an obstacle, the detected longitudinal and lateral distances are substituted into a route change equation with the longitudinal and lateral distances as parameters to avoid the obstacle to calculate the curvature of the route change, and this curvature is added to the planned route curvature to obtain a composite curvature, which is substituted into the steering angle equation. At the same time, the "relative cant angle (ξ)", which is the sum of the "composite curvature and lateral acceleration calculated from the vehicle speed" and the "road cant detected from the wheel speed, lateral acceleration, and yaw rate", is substituted into the steering angle equation. The axle load, which changes due to loading, is substituted into the steering angle equation (20) to calculate the input steering angle to the vehicle or vehicle model. The input steering is performed by the steering motor. At that time, the deviation between the zero point position of the steering motor and the neutral position of the actual vehicle steering wheel is input to the vehicle control amount, which causes vehicle motion, and the resulting sideslip angle (β) and yaw angle (φ) are used to output the movement coordinates and their azimuth from the GPS, magnetic sensor, and IMU. In parallel, the actual steering angle, which is the steering wheel angle to which steering hysteresis correction has been applied, is input to the vehicle model of equations (16) and (17), and the calculated values of the movement coordinates and their azimuth from the sideslip angle (β) and yaw angle (φ) are output.
図の中央部の縦長枠に実車、その下の太線の縦長枠に車両モデルを示す。実車に搭載されるIMU（慣性計測装置inertial measurement unit）によって横加速度Gy_imu、前後加速度Gx_imu,ヨーレイトγ_imuが検出され、GPSからはX座標X_GPS、Y座標Y_GPS、方位角λ_GPSが検出され、磁気センサからはX座標Xmk、Y座標Ymk、方位角λmkが検出される。Gy_imuとGx_imu,からIMU検出横すべり角βimuが計算され、GPS検出の車速VGPSと車両CAN検出の前後車速Vcanから横すべり角βGPSが検出され、車両モデルの式（１６）から算出されるβcalの三つのβが、システム診断状況によって待機冗長構造を構成する。このβとIMU検出のヨーレイトγ_imuから、IMUによるX座標Ximu、Y座標Yimu、方位角λimuが算出され、GPS検出のX座標XGPS、Y座標YGPS、方位角λGPS及び磁気センサ検出のX座標Xmk、Y座標Ymk、方位角λmk、更に車両モデルから計算出力されるX座標Xcal、Y座標Ycal、方位角λcal、の四つが、システム診断状況によって待機冗長構造を構成する。待機冗長構造からシステム診断状況により出力された自己位置（X,Y）と進行方向（λ）の現在位置をフィードフォワード項である目標経路座標に照らし、現在位置から目標経路へ流入する曲線式を作成し、その曲率から舵角決める。GPSが使用できない環境下では、視覚センサによって目標経路を定め、舵角を決める。この様に、GPSと磁気マーカと慣性計測および車両モデルとの整合をとり機能する冗長システムを構成する。 The vertical frame in the center of the figure shows an actual vehicle, and the thick vertical frame below it shows a vehicle model. The IMU (inertial measurement unit) installed in the actual vehicle detects lateral acceleration Gy_imu, longitudinal acceleration Gx_imu, and yaw rate γ_imu, the GPS detects X coordinate X_GPS , Y coordinate Y_GPS , and azimuth angle λ_GPS , and the magnetic sensor detects X coordinate Xmk, Y coordinate Ymk, and azimuth angle λmk. The IMU-detected sideslip angle βimu is calculated from Gy_imu and Gx_imu, and the sideslip angle βGPS is detected from the GPS-detected vehicle speed VGPS and the vehicle CAN-detected longitudinal vehicle speed Vcan, and the three βs of βcal calculated from equation (16) of the vehicle model form a standby redundant structure depending on the system diagnosis situation. From this β and the yaw rate γ_imu detected by the IMU, the X coordinate Ximu, Y coordinate Yimu, and azimuth λimu are calculated by the IMU, and the X coordinate X GPS , Y coordinate Y GPS , and azimuth λ detected by the GPS are calculated. The X coordinate Xmk, Y coordinate Ymk, and azimuth λmk detected by the GPS and magnetic sensor, as well as the X coordinate Xcal, Y coordinate Ycal, and azimuth λcal calculated and output from the vehicle model, form a standby redundant structure according to the system diagnostic situation. The current position of the self-position (X, Y) and the direction of travel (λ) output from the standby redundant structure according to the system diagnostic situation are referenced to the target route coordinates, which are the feedforward terms, to create a curve equation that flows from the current position to the target route, and the steering angle is determined from the curvature. In an environment where GPS cannot be used, the target route is determined by the visual sensor, and the steering angle is determined. In this way, a redundant system that functions by matching the GPS, magnetic markers, inertial measurement, and vehicle model is formed.
以上述べた様に、本発明は、単車・連節車両を問わず最後軸の軌跡を経路とする経路設定をし、車両諸元寸法が異なる単車・連節車両が辿ることができる様にして、その経路曲率から操舵角を算出する式、即ち軸距と連節点位置をパラメータとする幾何寸法とそのスタビリティファクタで構成する制御式を備える。レールのない路面を“人の運転”に依らず自動運転するバス高速輸送システムに運用される自動運転連節車両およびその制御方法を実現する。 As described above, the present invention sets a route that follows the trajectory of the last axle regardless of whether the vehicle is a single vehicle or an articulated vehicle, and allows single vehicles and articulated vehicles with different vehicle dimensions to follow the route. It also provides a formula for calculating the steering angle from the curvature of the route, i.e., a control formula composed of geometric dimensions with the wheelbase and articulation point positions as parameters, and their stability factors. This realizes an autonomous articulated vehicle and its control method for use in a bus rapid transit system that operates autonomously on roads without rails without relying on "human driving."
そして、その“スタビリティファクタで構成する制御式”を、車両総重量とその重心位置及び軸荷重とタイヤコーナリング係数を変数とする式で表現し、車両総重量、重心位置、軸荷重の変化は、装備するセンサで検出し、タイヤコーナリング係数は、実験同定値を持つことによって進路制御にかかわる自車両の状態変化、道路の湿潤への適応を可能にする。更に、加減速制御にかかわる自車両の状態変化、道路勾配への適応を可能にする。
かくして、レールのない路面を“人の運転”に依らず自動運転するバス高速輸送システムに運用される自動運転連節車両およびその制御方法を実現する。
The "control formula consisting of stability factors" is expressed as a formula with the total vehicle weight, its center of gravity position, axle load, and tire cornering coefficient as variables, and changes in the total vehicle weight, center of gravity position, and axle load are detected by the installed sensors, and the tire cornering coefficient has an experimentally identified value, making it possible to adapt to changes in the vehicle's state related to route control and to wet roads.Furthermore, it makes it possible to adapt to changes in the vehicle's state related to acceleration/deceleration control and to road gradients.
Thus, an autonomous articulated vehicle and its control method are realized for use in a bus rapid transit system that operates autonomously on roads without rails without relying on "human driving."
Claims (5)
連節車両の後車両の最後軸（最後軸の中心点）の軌道が予め決められた単車（単一車両）の最後軸（最後軸の中心点）と共通する目標経路を辿るように目標経路の曲率から連節車両の前車両と後車両との連節角を換算するにあたり、
車両重量変化、前車両の前軸コーナリング係数（Ｃｃｆ）変化および後車両の後軸コーナリング係数（Ｃｃｒ）変化に対応するスタビリティファクタ（Ksf）を用いて以下の式（20）から前車両の前輪実舵角（δ）を換算し、換算した操舵角に応じたあて舵を前車両の操舵軸に加えることを特徴とする連節車両によって実行される自動運転方法。
When converting the articulation angle between the front vehicle and the rear vehicle of the articulated vehicle from the curvature of the target path so that the trajectory of the last axle (center point of the last axle) of the rear vehicle of the articulated vehicle follows a common target path with the last axle (center point of the last axle) of a predetermined single vehicle (single vehicle) ,
An automatic driving method performed by an articulated vehicle, characterized in that the actual front wheel steering angle (δ) of the front vehicle is converted from the following equation (20) using a stability factor (Ksf) corresponding to changes in vehicle weight, changes in the front axle cornering coefficient (Ccf) of the front vehicle, and changes in the rear axle cornering coefficient (Ccr) of the rear vehicle, and a counter steering angle corresponding to the converted steering angle is added to the steering axle of the front vehicle .
ここに、ｖ2は後車両の重心点の速度、Ｖx1は前車両の前後速度、Ｖx2は後車両の前後速度
An automatic driving method executed by an articulated vehicle as described in claim 1, characterized in that the sideslip angle (β2) and yaw rate (r2) of the rear vehicle relative to the actual steering angle of the front vehicle are calculated using the following equations (16) and (17).
Here, v2 is the velocity of the center of gravity of the rear vehicle, Vx1 is the longitudinal velocity of the front vehicle, and Vx2 is the longitudinal velocity of the rear vehicle.
An automatic driving method performed by an articulated vehicle as described in claim 1, characterized in that the articulated machine is equipped with a load cell (upper and lower load sensor) for detecting upper and lower loads, and air pressure sensors are equipped in the air piping sections of the air springs on the rear axles of the front and rear vehicles, to detect changes in vehicle weight due to changes in the number of passengers.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2022159300A JP7469424B1 (en) | 2022-10-03 | 2022-10-03 | Method for automatic driving of articulated vehicles |
| PCT/JP2023/019981 WO2023234271A1 (en) | 2022-05-31 | 2023-05-29 | Automated driving method executed by articulated vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2022159300A JP7469424B1 (en) | 2022-10-03 | 2022-10-03 | Method for automatic driving of articulated vehicles |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JP7469424B1 true JP7469424B1 (en) | 2024-04-16 |
| JP2024057120A JP2024057120A (en) | 2024-04-24 |
Family
ID=90667748
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2022159300A Active JP7469424B1 (en) | 2022-05-31 | 2022-10-03 | Method for automatic driving of articulated vehicles |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP7469424B1 (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001310651A (en) | 2000-02-24 | 2001-11-06 | Toyota Motor Corp | Automatic travel joint vehicle and method of travel direction change |
| JP2002144832A (en) | 2000-11-10 | 2002-05-22 | Mitsubishi Automob Eng Co Ltd | Connection advancing equipment device of guideway bus |
| JP2006089970A (en) | 2004-09-22 | 2006-04-06 | Railway Technical Res Inst | Compound transportation system maintaining environment of commuter belt |
| JP2017065454A (en) | 2015-09-30 | 2017-04-06 | 先進モビリティ株式会社 | Vehicle stop system |
| JP2019156066A (en) | 2018-03-09 | 2019-09-19 | 株式会社Ｓｕｂａｒｕ | Travel control device for vehicle |
| CN110550023A (en) | 2019-09-02 | 2019-12-10 | 厦门理工学院 | running stability control method for pure electric multi-section articulated automobile train |
-
2022
- 2022-10-03 JP JP2022159300A patent/JP7469424B1/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001310651A (en) | 2000-02-24 | 2001-11-06 | Toyota Motor Corp | Automatic travel joint vehicle and method of travel direction change |
| JP2002144832A (en) | 2000-11-10 | 2002-05-22 | Mitsubishi Automob Eng Co Ltd | Connection advancing equipment device of guideway bus |
| JP2006089970A (en) | 2004-09-22 | 2006-04-06 | Railway Technical Res Inst | Compound transportation system maintaining environment of commuter belt |
| JP2017065454A (en) | 2015-09-30 | 2017-04-06 | 先進モビリティ株式会社 | Vehicle stop system |
| JP2019156066A (en) | 2018-03-09 | 2019-09-19 | 株式会社Ｓｕｂａｒｕ | Travel control device for vehicle |
| CN110550023A (en) | 2019-09-02 | 2019-12-10 | 厦门理工学院 | running stability control method for pure electric multi-section articulated automobile train |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2024057120A (en) | 2024-04-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Rajamani et al. | Tire-road friction-coefficient estimation | |
| JP4048176B2 (en) | Method for calculating the mass of a motor vehicle taking into account different driving situations | |
| US9199639B2 (en) | Motion control system of vehicle | |
| Tseng et al. | The development of vehicle stability control at Ford | |
| US9296374B2 (en) | Motion controlling apparatus for a vehicle | |
| US8311706B2 (en) | Integrated vehicle control system using dynamically determined vehicle conditions | |
| CN102402644B (en) | Dynamical model modeling method of vehicle driven on mountainous road | |
| CN101939202B (en) | Device for measuring the movement of a self-guided vehicle | |
| GB2547304A (en) | Deceleration determination of a vehicle | |
| GB2546869A (en) | Vehicle curvature determination | |
| CN105416294A (en) | Heavy-duty combination vehicle parameter estimation method | |
| CN103608229A (en) | Device and method for controlling the driving dynamics of a vehicle and vehicle having such a device | |
| Kharrazi | Steering based lateral performance control of long heavy vehicle combinations | |
| CA3121250A1 (en) | System for smart coupling between a road implement and a tractor vehicle, system and method for managing the actuation of auxiliary traction on road implements | |
| CN114379540B (en) | Rollover-prevention driving decision method for large-sized operation vehicle considering influence of front obstacle | |
| CN113359457A (en) | High-dimensional dynamic model resolving device and method for intelligent vehicle chassis area controller | |
| CN116457270A (en) | Predictive energy and motion management for multi-trailer heavy vehicles | |
| Buggaveeti et al. | Longitudinal vehicle dynamics modeling and parameter estimation for plug-in hybrid electric vehicle | |
| JP7469424B1 (en) | Method for automatic driving of articulated vehicles | |
| WO2023234271A1 (en) | Automated driving method executed by articulated vehicle | |
| Kanellakopoulos et al. | Commercial trucks and buses in automated highway systems | |
| Guvenc | Preventive and Active Safety Applications | |
| Albinsson | Online and offline identification of Tyre model parameters | |
| Park et al. | A Research on Autonomous Vehicle Control in Track Beyond Its Limits of Handling | |
| Pyun et al. | Development of a real-time autonomous driving lateral control algorithm for an articulated bus using a model predictive control algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20230802 |
|
| A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20240118 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20240220 |
|
| TRDD | Decision of grant or rejection written | ||
| A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20240315 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20240404 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 7469424 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |