CN113928372B - Virtual rail train, rail generation method, auxiliary driving method and system thereof - Google Patents
Virtual rail train, rail generation method, auxiliary driving method and system thereof Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/08—Control, warning or like safety means along the route or between vehicles or trains for controlling traffic in one direction only
- B61L23/14—Control, warning or like safety means along the route or between vehicles or trains for controlling traffic in one direction only automatically operated
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
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Abstract
The invention discloses a virtual rail train, a rail generation method, an auxiliary driving method and a system thereof, which sense the external environment in real time, control the automatic steering and the automatic acceleration and deceleration of a vehicle, solve the problem of driving blind areas brought to a driver by overlength flexible marshalling, improve the intellectualization and safety level of the whole vehicle and improve the comfort level of the whole vehicle.
Description
Technical Field
The invention relates to the field of rail transit, in particular to a virtual rail train and an auxiliary driving method and system thereof.
Background
The public traffic jam of large and medium cities has seriously affected the healthy development of China cities, and even the public traffic conditions of two-line and three-line cities are optimistic. The public transportation priority development is adhered to, and a multi-level integrated public passenger transportation system taking rapid rail transportation as a backbone, road buses as a main body and taxis as supplements is established to become the main stream of the current urban public transportation development. The rail transit network mainly comprising subways and light rails has long construction period and huge cost, can not cover all areas of large and medium cities, and cannot bear the construction cost of two-line and three-line cities. Therefore, the construction of a mass, low-cost and intelligent public transportation system is the first choice for solving the problem of partial urban public traffic jam. Tram and trolley are two important vehicles for solving urban road public transportation, and in recent years, modern tram and trolley are transited from the past high floor to 100% low floor and gradually transited from the past single marshalling to ultra-long flexible marshalling. In addition, "green" and "intelligent" are mainstream developments in future vehicles from the trend of vehicle technology.
Super virtual rail trains employ four consist, which are over 30 meters in length, have failed current road traffic vehicle standards requirements, and therefore their route of travel is typically either closed-type dedicated roads, or dedicated/priority roads, as well as small numbers of intersections. Because of the particularity of the super virtual rail train, a driver at the side of the tail part of the super virtual rail train cannot judge an obstacle or danger by visual observation, and the steering and acceleration/deceleration of the vehicle are controlled by the driver to hardly meet the control requirement of the vehicle, an auxiliary driving system for sensing the external environment in real time and controlling the automatic steering and automatic acceleration/deceleration of the vehicle is required.
The method in the prior art only controls a single vehicle (namely a single-section vehicle), or only controls the longitudinal traction and braking of a train, and cannot solve the problem of driving blind areas brought by overlength flexible grouping to a driver or the problem of transverse control (transverse control is steering control of tires of each axle of the vehicle) of a super virtual rail train.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a virtual rail train, a rail generation method, an auxiliary driving method and a system thereof, and the transverse control of the super virtual rail train is realized.
In order to solve the technical problems, the invention adopts the following technical scheme: an auxiliary driving method of a super virtual rail train comprises the following steps:
1) Lane lines are collected, a plan view of the lane lines is generated, and a discrete coordinate point set (P 1 ,P 2 ,...,P i ,...,P n ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein n is the number of discrete coordinate points; fitting discrete coordinate points in the discrete coordinate point set to obtain a running track curve C (u); benefit (benefit)Calculating road curvature information rho (u) of the virtual digital track by using the running track curve k )；
According to the maximum running speed V of the vehicle max Calculating the estimated distance deviation delta L of the driving target point in the next period according to the time period delta T p ：
ΔL p ＝ΔT*V max ；
2) According to the estimated distance deviation DeltaL p Calculating estimated arc length parametersThe arc length parameter +.>Substituting road curvature information ρ (u) k ) Expression of->Calculate the maximum speed allowed for the next cycle +.>
Wherein:l is a discrete coordinate point P 1 To discrete coordinate point P n Is a total arc length of a running track;
3) Comparing the maximum running speed V of the vehicle max And the maximum speed allowed by the curvature of the road, calculating the practically allowed distance deviation deltaL:
4) Calculating actual arc length parameters according to the actual allowable distance deviation delta LSubstituting the actual arc length parameter into the expression of the running track curve C (u), and obtaining the coordinates of the running target point of the vehicle in the next time period as follows:
5) According to the current position coordinates (x 0 ,y 0 ) And the coordinates (x (t), y (t)) of the vehicle running target point in the next time period are calculated to obtain the steering angle increment alpha of the steering wheel at the current moment:
the invention realizes the automatic steering function based on image recognition and guiding, and solves the problem of difficult transverse control of the vehicle caused by the super virtual rail train.
The expression of the running track curve C (u) is as follows:
wherein N is i,p (u) is a basis function of a p-th order B-spline curve; u (u) 0 ＝0，u m ＝1；m＝n-p+1。
The B spline curve has many excellent properties such as geometric invariance, convex hull property, degradation reducibility, local supportability and the like, so that the running track curve described by the mathematical expression can be maximally close to the actual track curve.
Basis function N of p-th order B spline curve i,p The calculation formula of (u) is:
p is the order of the curve, and the values of the subsequent p u are all 1.
The calculation formula of the road curvature information is as follows:
wherein, I II is European space norm, kappa (u) k ) And ρ (u) k ) Respectively curve parameters u k Lower curvature and radius of curvature, C' (u) k ) And C "(u) k ) The first-order derivative and the second-order derivative of the curve running track curve C (u) are respectively shown as u k Coordinate values at that location.
The method of the invention further comprises: and calculating the steering angles of the other shafts of the vehicle according to the steering angle value of the steering wheel at the current moment.
The invention also provides an auxiliary driving system of the super virtual rail train, which comprises computer equipment; the computer device is configured or programmed to perform the steps of the above-described method.
The computer device is in communication with the perception module; the sensing module comprises a plurality of cameras arranged on the vehicle head, the vehicle body and the vehicle tail. The lane line image is convenient to collect.
The computer equipment is also connected with a transmission module; the transmission module is used for sending the control instruction output by the computer equipment to the vehicle executing mechanism.
1. As an inventive concept, to facilitate calculation of a steering angle of a steering wheel, the present invention also provides a digital virtual track generation method, in which a running track curve C (u) of a vehicle on a digital virtual track is represented by the following formula:
wherein N is i,p (u) is a basis function of a p-th order B-spline curve; u (u) 0 ＝0，u m ＝1；m＝n-p+1；(P 1 ,P 2 ,...,P n ) For collecting vehicleThe lane line is used for generating a top view of the lane line, and a discrete coordinate point set on the lane line extracted by the top view is utilized; n is the number of discrete coordinate points, P i I=1, 2, … …, n for discrete coordinate points. The invention also provides a virtual rail train, which comprises the driving assisting system.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention realizes the automatic steering function based on image recognition and guiding, and solves the problem of difficult transverse control of the vehicle caused by the super virtual rail train;
2. the plurality of image acquisition devices are arranged, so that the problem of driving blind areas brought to a driver by overlength flexible grouping is solved;
3. compared with the traditional manual driving vehicle, the intelligent vehicle steering control system can sense the external environment in real time, control the automatic steering of the vehicle, solve the problem of driving blind areas brought to a driver by overlength flexible grouping, improve the intelligent and safety level of the whole vehicle and improve the comfort and safety of the whole vehicle.
Drawings
FIG. 1 is a block diagram of a driving assistance system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for generating a digital virtual track according to an embodiment of the present invention;
FIG. 3 is a graph of a digital virtual lane according to an embodiment of the present invention;
FIG. 4 is a schematic block diagram of a method for calculating steering angle of a steering wheel according to an embodiment of the present invention;
fig. 5 is a network architecture diagram of the whole vehicle steering system of the present invention.
Detailed Description
The embodiment of the invention provides an image recognition-based auxiliary driving system for a super virtual rail train capable of being flexibly grouped, which is shown in fig. 1.
The working principle of the embodiment of the invention is as follows: and identifying the road in front of the vehicle through the image identification system, detecting the surrounding traffic environment information in the driving process, and transmitting the information to the central processing module after the information is fused. The central processing module runs an image recognition algorithm and a steering angle generation algorithm which are built in the central processing unit, receives sensing information from the sensor layer, and outputs the sensing information to the vehicle executor layer through the internal main modules of the controllers such as the behavior prediction module, the processing module, the motion planning module, the vehicle control module and the like to form a control instruction. The power control unit is used as an actuator at the bottom layer to directly control the vehicle execution layer (namely a steering system, a traction system, a braking system and an alarm system).
As shown in fig. 1, the system of the embodiment of the present invention is mainly implemented by the following functional modules:
the sensing module is used for sensing the environment and recognizing lane lines through the binocular cameras arranged on the head of the vehicle, the lateral cameras around the vehicle body and the binocular cameras at the tail of the vehicle (the front and the rear of the vehicle body are symmetrically arranged), and accurately sensing the position of the train in the lane through image recognition. Meanwhile, due to overlong vehicles, a driver cannot judge obstacles or dangers at positions such as the side surfaces of the tail parts of the vehicles only by visual observation, and an auxiliary driving system with the vehicle-mounted image recognition device can recognize and sense surrounding environment information of the vehicles in time.
In the processing module, the image recognition central processing unit generates a high-precision digital track according to the road information and the surrounding environment information of the vehicle body obtained by the sensing module, then compares the current position information of the vehicle with the comparison result of the lane information and the digital track, generates a steering angle of the steering wheel, and sends the steering angle to the control module.
The method of generating the digital virtual track is shown in fig. 2.
The binocular camera of the vehicle head recognizes the lane lines, then generates a top view of the lane lines through image segmentation and top view transformation, and performs image algorithm processing on the top view to extract discrete coordinate points of the lane lines. Image segmentation and overlooking transformation and image algorithm processing are the prior art (see: gold and beautiful jade. Research and software implementation of an image segmentation method based on anti-perspective transformation [ D)]The power university of North China (Hebei, 2008), the travel track within the current vehicle visual field is obtained by processing, as shown in figure 3, the travel direction of the vehicle is the positive Y-axis direction, and is perpendicular to the travel direction of the vehicle by taking the first axis center of the super virtual track as the originThe right side of the direction is the X-axis positive direction (the Y-axis positive direction rotates 90 degrees anticlockwise, namely the X-axis positive direction) to establish a rectangular coordinate system, and a curve C (u) is a track of the vehicle running, wherein a point set (P) 1 ,P 2 ,...,P i ,...,P n ) The discrete points on the lane lines obtained by processing the image algorithm, and the coordinate points of the discrete points are known by the image algorithm and can be expressed as follows:
P i ＝(x i ,y i ),i＝1,...,n (1)
by using a spline curve fit to discrete coordinate points, a spline curve-based digital virtual lane is generated, providing input information for the travel of the vehicle (for calculation of the steering wheel steering angle). Wherein, the fitting of the spline curve to the discrete coordinate points uses p times NURBS spline curve fitting, and the specific process is as follows:
the definition of a p-th NURBS curve is as follows:
wherein w is i A weight for each control point; p (P) i All control points; n (N) i,p (U) is a basis function of a p-th order B-spline defined on an aperiodic (and non-uniform) node vector U. The node vector is:
wherein u is n-p+1 ＝u m And generally take u 0 ＝0，u m =1. The B-spline basis function of NURBS curve can be solved according to node vector and recurrence formula, specifically:
then, based on the positions of the control points and the weights at each control point, equation (2) can be solved if w in equation (2) is calculated i The class of curves is called B-spline curves, which are all special forms of NURBS curves, when the values are all taken as 1. The B-spline curve can flexibly express complex shape tracks, and is particularly suitable for expressing running track curves. The expression is
x (u), y (u) are the abscissa and ordinate of the point on the solution curve, which are vectors.
The road curvature information of the virtual digital track can be calculated according to the virtual digital track curve expression obtained in the formula (5), and the calculation expression is shown in the formula (6):
wherein, I II is European space norm, kappa (u) k ) And ρ (u) k ) Respectively for curve parameter u k Lower curvature and radius of curvature, C' (u) k ) And C "(u) k ) The first and second derivatives of curve C (u), respectively, are at u k Coordinate values at that location.
The calculation principle of the steering angle of the steering wheel is shown in fig. 4:
firstly, determining the estimated driving distance delta L of the next servo period of the vehicle according to the current vehicle speed and the calculated time period delta T p As shown in the figure:
ΔL p ＝V×ΔT (7)
the coordinate value P of the target point in the next servo period is estimated t (x t ,y t ) It can be determined that:
i.e.
Wherein the curve parametersL is point P 1 To P n Total arc length of driving track of (2),>andcalculating the abscissa and ordinate values of the target for the servo, u ΔL The arc length for the current cycle is accumulated.
Then according to the current coordinate value (x 0 ,y 0 ) Coordinate value of next point (x t ,y t ) The road curvature information obtained by the digital virtual track and the road information can be obtained, the distance deviation and the angle deviation of the current period are calculated, and the steering angle value increment of the current steering wheel is calculated in real time by the image recognition central processing unit and is used for transverse control of the vehicle.
The road curvature information is used for calculating the maximum speed of the road allowing the vehicle to run in the current movement period, and the calculation formula is as follows:
it is necessary to ensure the vehicle speedPreventing the vehicle from sideslip, etc. The running speed of the longitudinal control is therefore:
wherein V is max And limiting the speed of the road surface of the current driving track.
By maximum operating speed V of the vehicle max And the maximum speed allowed by the curvature of the road is compared, and the practically allowed distance deviation is calculated:
ΔL＝ΔT*V (11)
then calculate the actual arc length parameter according to the distance deviationNumber of digitsBy combining the running track curve C (u), the coordinates of the running target point of the vehicle in the next time period can be calculated as follows:
and then based on the current position coordinates (x 0 ,y 0 ) And the coordinates (x (t), y (t)) of the vehicle running target point in the next time period are calculated to obtain the steering angle increment alpha of the steering wheel at the current moment:
the invention has good applicability to the super virtual rail train driven in two directions, can sense the external environment in real time and control the automatic steering of the vehicle.
The following specifically describes functions implemented by the embodiments of the present invention.
The network architecture of the existing super virtual rail train steering system is shown in fig. 5, a A, F shaft is a power shaft, and electrohydraulic power-assisted steering is adopted; B. the C, D, E shaft is a non-power shaft, hydraulic power assisted steering is adopted, and six shafts are provided with independent active steering control. All the following axles follow the steering when the driver operates the a-axis steering wheel. Each carriage is provided with an independent steering controller, the independent steering controller is connected with the steering controller of the whole vehicle through a control network, and the steering controller of the whole vehicle is connected with the controller of the whole vehicle through the control network.
In the running process of the automobile, a driver can select an auxiliary driving mode through a human-computer interaction interface, and an auxiliary driving system carries out environment sensing and lane line recognition through a binocular camera arranged on the head of the automobile, a lateral camera around the automobile body and a binocular camera (symmetrically arranged on the front and the rear of the automobile body) at the tail of the automobile. In the processing module, the image recognition central processing unit generates a high-precision digital track according to the road information and the surrounding environment information of the vehicle body obtained by the sensing module, then compares the current position information of the vehicle with the comparison result of the lane information and the digital track, generates a steering angle of the steering wheel, transmits the steering angle to the steering main control unit through the control network, calculates the steering angles of other shafts according to the input of the steering angle, and sends the steering angle to the control unit to realize automatic steering of the vehicle.
According to the invention, a driver can perform man-machine interaction by additionally installing the tablet personal computer, and information required to be seen and heard by the driver and operation aiming at auxiliary driving are acquired from an additionally installed tablet personal computer screen, and the method comprises the following steps:
(1) Map information (overall position information of the vehicle in the map);
(2) Surrounding environment information of the vehicle (display simulated vehicle, simulated host vehicle, lane lines, surrounding vehicles, objects, etc.);
(3) Vehicle travel information (e.g., assisted driving state, set vehicle speed, current vehicle speed, steering angle);
(4) Displaying alarm reminding and requesting manual taking over information, wherein the alarm reminding and the manual taking over information comprise two modes of figure flashing and sound;
(5) The driver performs operations (including starting or stopping auxiliary driving, selecting a mode, setting a vehicle speed and the like) on the man-machine interaction display screen.
The super virtual rail train auxiliary driving scheme is not only suitable for the rail trolleybus, but also used for the trolley trolleybus, can flexibly group (single-section or multi-section carriages), flexibly adjust the auxiliary driving scheme according to the grouping condition, adjust the arrangement of satellite navigation antennas and sensors and the like.
Claims (8)
1. An auxiliary driving method of a virtual rail train is characterized by comprising the following steps:
1) Lane lines are collected, a plan view of the lane lines is generated, and a discrete coordinate point set (P 1 ,P 2 ,...,P n ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein n is the number of discrete coordinate points, P i I=1, 2, … …, n for discrete coordinate points; fitting the discrete coordinate points in the discrete coordinate point set to obtain a rowA travel track curve C (u); calculating road curvature information rho (u) of virtual digital track by using the running track curve k )；
According to the maximum running speed V of the vehicle max Calculating the estimated distance deviation delta L of the driving target point in the next period according to the time period delta T p ：
ΔL p ＝ΔT*V max ；
2) According to the estimated distance deviation DeltaL p Calculating estimated arc length parametersCombining road curvature information ρ (u) k ) Calculate the maximum speed allowed for the next cycle +.>
Wherein:u ΔL the arc length accumulated value of the current period is L, which is a discrete coordinate point P 1 To discrete coordinate point P n Is a total arc length of a running track;
3) Comparing the maximum running speed V of the vehicle max And the maximum speed allowed by the curvature of the road, calculating the practically allowed distance deviation deltaL:
4) Calculating actual arc length parameters according to the actual allowable distance deviation delta LSubstituting actual arc length parameters into the rowsIn the expression of the driving track curve C (u), the coordinates of the driving target point of the vehicle in the next time period are obtained as follows:
5) And then based on the current position coordinates (x 0 ,y 0 ) And the coordinates (x (t), y (t)) of the vehicle running target point in the next time period are calculated to obtain the steering angle increment alpha of the steering wheel at the current moment:
the expression of the running track curve C (u) of the virtual track is as follows:
wherein N is i,p (u) is a basis function of a p-th order B-spline curve; u (u) 0 ＝0，u m ＝1；m＝n-p+1；
The calculation formula of the road curvature information is as follows:
wherein, I II is European space norm, kappa (u) k ) And ρ (u) k ) Respectively curve parameters u k Lower curvature and radius of curvature, C' (u) k ) And C "(u) k ) The first-order derivative and the second-order derivative of the running track curve C (u) are respectively represented by u k Coordinate values at the position; k is an arc length parameter, and the value range is 0-L.
2. The aided driving method of a virtual rail train according to claim 1, characterized in that the basis function N of the p-th order B-spline curve i,p The calculation formula of (u) is:
3. the method for assisting driving of a virtual rail train according to claim 1, further comprising: and calculating the steering angles of the other shafts of the vehicle according to the steering angle value of the steering wheel at the current moment.
4. An auxiliary driving system of a virtual rail train is characterized by comprising computer equipment; the computer device being configured or programmed for performing the steps of the method of one of claims 1 to 3.
5. The virtual rail train auxiliary driving system of claim 4, wherein the computer device is in communication with a perception module; the sensing module comprises a plurality of cameras arranged on the vehicle head, the vehicle body and the vehicle tail.
6. The auxiliary driving system of a virtual rail train according to claim 4 or 5, wherein the computer device is further connected to a transmission module; the transmission module is used for sending the control instruction output by the computer equipment to the vehicle executing mechanism.
7. A digital virtual track generation method for the assisted driving system according to claim 4 or 5, characterized in that the travel track curve C (u) of the vehicle on the digital virtual track is characterized by the following formula:
wherein N is i,p (u) is a basis function of a p-th order B-spline curve; u (u) 0 ＝0，u m ＝1；m＝n-p+1；
(P 1 ,P 2 ,...,P n ) In order to collect lane lines and generate a top view of the lane lines, a discrete coordinate point set on the lane lines extracted by utilizing the top view is utilized; n is the number of discrete coordinate points, P i I=1, 2, … …, n for discrete coordinate points;
basis function N of p-th order B spline curve i,p The calculation formula of (u) is:
8. a virtual rail train comprising the driving assistance system according to any one of claims 4 to 6.
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