CN110509922B - Vehicle forecasting and cruising control method based on high-precision map - Google Patents
Vehicle forecasting and cruising control method based on high-precision map Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/143—Speed control
- B60W30/146—Speed limiting
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/105—Speed
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- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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Abstract
The invention relates to a vehicle forecasting and cruising control method based on a high-precision map, which comprises the following steps: positioning the vehicle; transmitting a map; reconstructing a map; forecasting a cruise vehicle speed plan; the invention predicts the front road condition information in real time based on the GPS and the high-precision map, adaptively adjusts the cruising speed under different working conditions, balances the relation between low oil consumption and high timeliness, saves the transportation cost, improves the transportation efficiency, and greatly improves the fuel economy of the vehicle on the basis of ensuring the timeliness of the vehicle compared with the common cruise at constant speed.
Description
Technical Field
The invention relates to the technical field of vehicle control, in particular to a vehicle forecasting and cruising control method based on a GPS and a high-precision map.
Background
With the increasing demand of automobiles, the market of automobiles increasingly presents unprecedented vitality, and the huge automobile holding amount brings serious problems of environmental pollution and energy safety. Taking energy consumption as an example, in 2012, the total petroleum consumption in China is about 4.9 hundred million tons, the import dependence is as high as 57.8%, and the automobile consumption is about 1.86 hundred million tons, accounting for 37.8% of the total amount. No matter exogenous mandatory laws and regulations or endogenous product active innovation, further development of automobile energy-saving and emission-reducing technologies is required. Due to the high fuel consumption of the vehicle itself, if an effective fuel saving management technique is applied thereto, the effect thereof will be very remarkable. The rapid development of the expressway provides a wide application space for the cruise system, and research on the cruise system is also gradually hot. However, under the situation of energy shortage and serious environmental pollution, how to further improve the fuel economy of the automobile and achieve the purposes of energy conservation and emission reduction has great significance.
At present, many automobile manufacturers abroad such as Benz, Scandiana, DAF, IVECO and the like have successively provided oil-saving prediction cruise technologies, and Scandiana firstly provides an active prediction cruise control system, uses a GPS to position a vehicle and predict a road ahead, optimizes the optimal cruise speed in real time, improves the oil consumption rate in the whole driving process and reduces the transportation cost. In addition, the typical automatic cruise technology of "I-See" that Volvo company promoted still utilizes the backstage to store a large amount of real car data and optimizes the best mode of cruising under typical road conditions, and this kind of technology needs powerful backstage to support, and is comparatively complicated to the emergent reaction and the processing of special operating mode.
The automatic cruise technology is mainly designed aiming at the landform of foreign countries, does not necessarily have a good oil-saving effect aiming at the complex landform of China, but the automatic cruise technology is not developed aiming at different landforms at present, and the automatic cruise technology is designed based on the background.
Disclosure of Invention
The invention aims to provide a vehicle forecasting and cruising control method based on a high-precision map, which fully utilizes the terrain advantages to optimize the vehicle speed and can achieve the aim of dual guarantee of oil saving and time effectiveness.
In order to solve the technical problem, the vehicle forecasting and cruising control method based on the high-precision map comprises the following steps:
step one, positioning a vehicle
Accurately positioning the current position of the vehicle through a GPS, and acquiring map data information within X meters ahead according to a high-precision map;
step two, map transmission
Transmitting the map data information to a controller according to an ADASIS protocol; the map data information comprises the current node position and the node gradient within X meters ahead, intersection position information, a speed limiting position and a mark; x is 1000-3000 m, and the distance between adjacent nodes in X m is 10-100 m;
step three, map reconstruction
The controller effectively reconstructs the map ahead according to the received map data information to obtain reconstructed map data information which can identify the current slope section, the information of the front slope section and the position and speed limit identification information of the front intersection;
step four, forecasting cruise vehicle speed planning
4.1, the cruising speed is limited according to the following three conditions:
a. a speed limit mark in a certain distance in front and the speed of the vehicle is limited to Vlim1；
b. The intersection information exists in a certain distance ahead, and the vehicle speed is limited to Vlim2；
c. The cruising speed set by the driver is VrefAcceptable cruise speed deviation is VincWith a lower deviation of Vdec(ii) a The lower limit of the cruise vehicle speed is finally set to (V)ref-Vdec) Upper limit of Vlim1、Vlim2、(Vref+Vinc) Minimum value of (1);
4.2 cruise speed optimization
4.2.1 estimating the velocity ranges of the nodes ahead
Suppose the maximum velocity of node i is VimaxThe maximum torque that the whole vehicle can provide is TmaxThe mass of the whole vehicle is m, and the gradient value of the node i +1 is Slope(i+1)，The distance from node i to node i +1 is Δs(i_i+1)Then, according to the vehicle dynamics equation (1), the maximum acceleration ACC which can be reached when the vehicle runs from the node i to the node i +1 is calculated(i+1)max：
ACC(i+1)max＝facc(Tmax，Vimax，Slope(i+1)，m) (1)
If Vimax 2+2*Acc(i+1)max*Δs(i_i+1)<0, then node i +1 maximum vehicle speed V(i+1)max＝0；
If Vimax 2+2*Acc(i+1)max*Δs(i_i+1)If the speed is more than 0, the node i +1 has the maximum speed
V0max＝V0The vehicle speed at the current position of the vehicle;
suppose the minimum velocity of node i is ViminThe maximum negative torque that the whole vehicle can provide is TminWhen the vehicle runs at the maximum brake, the maximum deceleration Dec which can be reached when the vehicle runs from the node i to the node i +1 is calculated according to the vehicle dynamics equation (2)(i+1)max：
Dec(i+1)max＝fdec(Tmin，Vimin，Slope(i+1)，m) (2)
If Vimin 2+2*Dec(i+1)max*Δs(i_i+1)<0, then node i +1 minimum vehicle speed V(i+1)min＝0；
If Vimin 2+2*Dec(i+1)max*Δs(i_i+1)The node i +1 minimum vehicle speed is larger than or equal to 0
V0min＝V0The vehicle speed at the current position of the vehicle;
4.2.2. the optimal speed V of the end node NNPlanned as cruising speed V of vehiclerefI.e. VN＝Vref；
4.2.3 optimization of speeds of other nodes
(1) Discretizing the speed range of each node according to the speed range of each node obtained by prediction in the step 4.2.1 and set intervals; discretization of the designated node i-1n(i-1)Speed node
The optimal speed of node i is Vi；
(2) Assuming that the maximum speed and the minimum speed of the node N-1 are both equal to a certain speed node of the node N-1, the calculated speed range of the end node N does not include the optimal vehicle speed V of the end node NNIf the speed node does not meet the condition, the speed node is considered to be not in accordance with the condition; excluding all speed nodes of the node N-1 which do not meet the condition;
(3) speed of attempting to link node N and node N-1 with neutral
Assume that the Slope between node N and node N-1 is SlopeN-(N-1)A distance of SN-(N-1)(ii) a For any eligible speed node V(N-1)_xFrom which velocity node V is calculated(N-1)_xStarting from, running in neutral SN-(N-1)The final velocity obtained after the distance; if the final speed is equal to the optimal speed V of the final node NNIf the speed difference is more than 3km/h, directly jumping to the next step (4); otherwise, directly jumping to the step (6);
(4) attempting to link node N and node N-1 speed with positive torque
Calculating slave velocity node V(N-1)_xStarting from node N-1 to node N the required positive torque T(N-1)_xIf a positive torque T is obtained(N-1)_xIf the torque is larger than the maximum torque of the vehicle engine, directly jumping to the step (5); otherwise, directly jumping to the step (6);
(5) attempting to link node N and node N-1 speed with negative torque
Calculating slave velocity node V(N-1)_xStarting with available auxiliary braking torque from node N-1 to node N and vehicle speed at the final node N at Vnext(N-1)_x(ii) a If Vnext(N-1)_xAnd VNIf the speed difference is within 3km/h, turning to the step (6); otherwise, the speed node V is abandoned(N-1)_x；
(6) Saving velocity and objective function values for each available node
All eligible speed nodes are calculated asAt an initial speed, driving from the node N-1 to the objective function value of the node N; for velocity node V(N-1)_xValue of objective function J(N-1)_x_NThe following were used:
J(N-1)_x_N＝Q(N-1)B*(B(N-1)_x_N/B(N-1)_Nref+Q(N-1)T*Time(N-1)_x_N/Time(N-1)_N ref(6)
wherein, B(N-1)_x_N，Time(N-1)_x_NRespectively is an initial velocity V(N-1)_xThe amount and time of fuel consumed to travel to node N; q(N-1)BAnd Q(N-1)TThe weight coefficients of fuel economy and instantaneity of driving from the node N-1 to the node N are respectively; b is(N-1)_x_NObtaining the fuel consumption map of the vehicle engine through pre-calibration; time(N-1)_x_N＝S(N-1)_N/V(N-1)_x；B(N-1)_N refThe vehicle speed is cruising speed V(N-1)_N refReference fuel consumption, Time, from node N-1 to node N(N-1)_N refThe vehicle speed is cruising speed V(N-1)_N refA reference time from node N-1 to node N;
Time(N-1)_Nref＝SN-(N-1)/V(N-1)_Nref；
saving the state of each speed node, namely the speed and the corresponding objective function value; selecting a speed node corresponding to a smaller objective function value as an optimal vehicle speed VN-1And storing;
(7) repeating iteration to calculate optimal speed
After the state of the node N-1 is calculated, sequentially calculating the states of the following nodes N-2 and N-3 … according to the methods of the steps (2) to (6); aiming at any node, calculating a total objective function value when all nodes in front X meters are respectively linked by each speed node, selecting a speed chain with a smaller objective function value, and taking the speed node corresponding to the speed chain as the optimal speed of the node;
(8) if the speeds in any two non-first nodes can not be linked together through the steps (3), (4) and (5), the latter node is taken as a final state point, and then the speed of each node is carried out again according to the steps (1) to (7)Optimizing; if the velocity of the head node 1 cannot be linked with the velocity of the node 2, V of the node 1 is linked1As the optimal speed for node 2.
In conclusion, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the invention can realize accurate positioning of the vehicle and receive effective map data in a distance ahead in real time;
2. the method can effectively reconstruct the road ahead by effectively processing the received map data, and identify various road conditions;
3. under the condition that a driver drives normally, the driver can be prompted according to the recognized front road condition;
4. aiming at the cruising working condition, the requirements of oil saving and timeliness are integrated, the cruising speed can be adaptively adjusted within the acceptable range of a driver, and the advantage is brought into full play on the routes with rugged and uneven terrain and fluctuated road surfaces;
the invention can recognize the speed limit sign and the intersection in advance and realize effective vehicle speed control according to different conditions;
6. the invention simulates adaptive driving of experienced drivers based on knowledge of the road ahead, keeping fuel consumption as low as possible.
The invention predicts the front road condition information in real time based on the GPS and the high-precision map, adaptively adjusts the cruising speed under different working conditions, balances the relation between low oil consumption and high timeliness, saves the transportation cost, improves the transportation efficiency, and greatly improves the fuel economy of the vehicle on the basis of ensuring the timeliness of the vehicle compared with the common cruise at constant speed.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flow chart of the present invention for anticipatory cruise vehicle speed planning.
Fig. 2 is a schematic diagram of information of each node of the road ahead.
FIG. 3 is a schematic diagram of speed range prediction.
Fig. 4 is a schematic diagram of a speed planning process.
Detailed Description
The invention aims at the function of forecasting and cruising of the vehicle, identifies the current position of the vehicle and the road information X meters ahead according to a global positioning system and a high-precision map, and optimizes the optimal vehicle speed within the acceptable range of a driver on the basis of constant-speed cruising according to the real-time road condition information.
As shown in fig. 1, the vehicle predictive cruise control method based on a high-precision map of the present invention includes the steps of:
step one, positioning a vehicle
Firstly, the current position of the vehicle is accurately positioned through a GPS (global positioning system), and map data information of X meters ahead is obtained according to a high-precision map.
Step two, map transmission
And effectively transmitting the map information according to the ADASIS protocol and sending the map information to the controller. The map data comprises current road information and road information X meters ahead, and specifically comprises data such as ahead intersections, speed limits, gradients and the like; x is 1000-3000 m, and the distance between adjacent nodes in X m is 10-100 m; here, X is 2000 m, and the distance between adjacent nodes is 25 m.
Step three, map reconstruction
The controller receives the map data in real time and then effectively reconstructs the map in front. The reconstruction mainly comprises the following steps:
3.1 Signal input
The road data received by the controller comprises information such as node position, node gradient, intersection position information, speed limiting position and identification.
3.2 Signal processing
In order to ensure the continuity and the validity of the data, a series of singular point processing is required to be performed on the received data, for example, abrupt gradient points or a certain section of unreasonable data in the data are removed, so as to ensure the validity of subsequent road reconstruction.
3.3 road reconstruction
After the signal processing in step 3.2, the controller needs to reconstruct the map data X meters ahead, and as in navigation, the road condition ahead is summarized and arranged into a recognizable characteristic map. The method is divided into the following aspects:
3.3.1 recognizing road characteristics ahead
The controller receives the road information X meters ahead, and firstly stores the position and gradient information of each node of the road ahead. Then classifying and sorting the road information according to different gradients, and setting the gradient range of different typical road sections, for example, the gradient range of a flat road is S0—S1. According to the current position of the vehicle and the position of a front slope, the road condition of the vehicle is divided into the following conditions, including level roads, uphill slopes, downhill slopes, mountains, valleys and the like, and the conditions can be opened for a driver to serve as prompt information of the front road condition and also serve as the basis of a vehicle speed control strategy.
3.3.2 identifying the current road characteristics:
the map data information within the range of X meters of the vehicle is regarded as a known map, the current road characteristics including the current position, the gradient and other information are analyzed by searching in the map according to the current positioning information of the vehicle, and the maximum limit is made to the construction specification of the expressway according to the state.
3.3.3 identifying intersection location information
And the controller receives the position information of the intersection within X meters ahead and stores the position information in the array.
3.3.4 recognizing speed limit sign information
The controller receives the speed limit identification information within X meters ahead, and stores the speed limit position and the speed limit value into an array, so that the speed limit information can be accurately identified, and the corresponding limiting treatment is carried out on the vehicle speed.
Step four, forecasting cruise vehicle speed planning
The basic idea of the invention is to increase the vehicle speed as much as possible before going uphill, reduce the vehicle speed before going downhill, fully utilize the advantages of terrain, and achieve double optimization of driving efficiency and cost.
The invention relates to a method for planning a cruise forecasting vehicle speed, which comprises the following steps:
4.1. anticipatory cruise vehicle speed limit strategy
Based on the identification of the road, the controller firstly limits the maximum value of the finally set cruising speed according to the cruising working condition. The following three speed limit situations are specific:
(1) a speed limit mark in a certain distance in front and the speed of the vehicle is limited to Vlim1；
(2) The intersection information exists in a certain distance ahead, and the vehicle speed is limited to Vlim2(can be calibrated by oneself);
(3) the cruising speed set by the driver is VrefAcceptable cruise speed deviation is VincWith a lower deviation of Vdec(ii) a The lower limit of the cruise vehicle speed is finally set to (V)ref-Vdec) Upper limit of Vlim1、Vlim2、(Vref+Vinc) Minimum value of (1).
4.2. Anticipatory cruise vehicle speed control strategy
Information such as position and gradient within X meters ahead is stored according to the introduction of step 3.3.1, and how to optimize the cruising speed according to the stored map information is described in detail below.
4.2.1 estimating the velocity ranges of the nodes ahead
On the premise that the current vehicle speed is known, the speed range of each node in front is predicted according to the requirement.
The description will be made taking a node B as an example.
Maximum velocity calculation
Suppose the maximum velocity of the node B is VBmaxThe maximum torque that the whole vehicle can provide is TmaxM is the mass of the whole vehicle, and the gradient value of the node C is SlopeCThe distance from node B to node C is deltasBCThen the maximum acceleration ACC that can be reached for driving from node B to node C according to the vehicle dynamics equation (1) known in the artCmaxComprises the following steps:
ACCCmax＝facc(Tmax，VBmax，SlopeC，m) (1)
if VBmax 2+2*AccCmax*ΔsBC<0, then node C maximum speed VCmax＝0。
If VBmax 2+2*AccCmax*ΔsBCIf the speed is more than 0, the maximum speed of the node C is
Note: according to the above rule VBmaxCalculated from the speed of the node A, VAmax＝VAI.e. the speed of the vehicle at the current location of the vehicle.
Minimum velocity calculation
Suppose the minimum velocity of the node B is VBminThe maximum negative torque that the whole vehicle can provide is TminThen, as is known in the art, the maximum deceleration Dec that can be achieved from node B to node C assuming that the vehicle is traveling with maximum braking, according to vehicle dynamics equation (2)CmaxComprises the following steps:
DecCmax＝fdec(Tmin，VBmin，SlopeC，m) (2)
if VBmin 2+2*DecCmax*ΔsBC<0, node C minimum vehicle speed VCmin＝0。
If VBmin 2+2*DecCmax*ΔsBCNot less than 0, the minimum speed of the node C
Note: according to the above rule VBminCalculated from the speed of the node A, VAmin＝VAI.e. the speed of the vehicle at the current location of the vehicle. The speed ranges of the nodes are stored, and a specific schematic diagram is shown in FIG. 3.
4.2.2. End node velocity planning
After obtaining the speed ranges of the nodes, firstly planning the speed of the end node, wherein the speed of the end node is planned to be the cruising speed of the vehicle, and if the end node is F, the optimal speed of the end node F is VF；
VF＝Vref(3)
4.2.3 optimization of speeds of other nodes
Discretizing node speed and selecting available nodes
The speed planning of the invention is based on the idea of dynamic planning, and the speed of the tail node is advanced. Planning the optimal speed V of the node F according to the step 4.2.2FThen planning the speed of the E point; suppose the maximum velocity of node E obtained according to step 4.2.1 is VEaMinimum velocity is VEcDiscretizing the speed of the node E by a set speed interval delta V to obtain a speed node VEa、VEbAnd VEc. According to the method for calculating the speed range in the step 4.2.1, the initial speeds of the calculation nodes E are respectively VEa、VEbAnd VEcThe velocity range of node F. As shown in FIG. 4, assume that when node E has both a maximum speed and a minimum speed equal to VEaThe speed range of the node F obtained by time calculation does not contain the optimal vehicle speed V of the node FFThen, the velocity V is consideredEaThe condition is not met. So node E can program the speed node to be VEbAnd VEcNext with velocity node VEbThe description is given for the sake of example.
(2) Calculating a reference state
Firstly, calculating the vehicle maintenance cruising speed V in the road section EFrefThe respective reference state quantities at runtime, for example:
analyzing according to a map of the oil consumption of the vehicle engine calibrated in advance, wherein the vehicle speed is a cruising vehicle speed VrefReference fuel consumption B running from node E to node FerefIs composed of Vref，SlopeFM, determined by a four-dimensional map table of m components:
Beref＝MAP(Vref，SlopeF，m) (4)
the speed is cruising speed VrefReference Time of TimerefThe following were used:
Timeref＝SEF/Vref(5)
wherein SEFThe gradient value of the node F is SlopeF；
(3) Speed of attempting to link two nodes with neutral
Assume a Slope between EFFA distance of SEF，Calculating the slave velocity VEbStarting from, running in neutral SEFFinal velocity V obtained after distanceG0. If VFAnd VG0And (4) if the speed difference is more than 3km/h, determining that the two nodes cannot be connected by utilizing neutral gear sliding, and directly jumping to the step (4). Otherwise, if it is considered that the vehicle can coast from the node E to the node F by the neutral drive, the following steps (4) and (5) are omitted, and the process proceeds to the step (6).
(4) Attempting to link speeds of two nodes with positive torque
If the speed of linking two nodes cannot be used with neutral coasting, an attempt is made to calculate the positive torque T required from node E to node FEbIf the final torque T isEbAnd if the speed is not in a reasonable range (namely, the speed is larger than the maximum torque of the vehicle engine), the speed of the two nodes cannot be connected through the positive torque, and the step (5) is directly skipped. Otherwise, the speed of the two nodes can be linked through the positive torque, and the step (6) is directly skipped.
(5) Attempting to link speeds of two nodes with negative torque
If the speeds of the two nodes cannot be linked in the two modes of the steps (3) and (4), the auxiliary brake is tried to be used for linking, and the auxiliary brake driving S is calculatedEFFinal velocity V obtained after distancenextbIf V isnextbAnd VFIf the speed difference is within 3km/h, the speed of linking the two nodes can be achieved by using the auxiliary brake, and the step (6) is directly skipped; otherwise, the speed node V is abandonedEb。
(6) Saving velocity and objective function values for each available node
Calculating the objective function value of the node N from the node N-1 when all speed nodes meeting the conditions are used as initial speeds; for example, for velocity node VEbCalculating the objective function value J using equation (6)Eb(ii) a The formula (6) specifically considers the fuel economy, real-time performance and other performances of the whole vehicle, and can be defined by a user.
JEb＝QB*(BEbF/Beref)+QT*TimeEF/Timeref(6)
Wherein, BEbF，TimeEbFRespectively at an initial velocity VEbTravel to node F (node V)EbThe amount of fuel consumed and the time to travel from node E neutral to node F, positive torque to node F, or negative torque to node F) as the initial speed. QBAnd QTWeight factor, Q, for fuel economy and real-timeBAnd QTCan be obtained by simulation or real vehicle test debugging (the test debugging method is a known technology in the field); b isEbFThe method can be obtained through a map of the oil consumption of the vehicle engine calibrated in advance; timeEbF＝SEF/VEb；BEFrefThe vehicle speed is cruising speed VEFrefReference fuel consumption, Time, from node E to node FEFrefThe vehicle speed is cruising speed VEFrefA reference time from node E to node F; timeEFref＝SEF/VEFref；
Saving the state of speed nodes Eb and Ec, including speed VEb，VEcAnd the objective function value JEb，JEcSelecting a speed node corresponding to a smaller objective function value as the optimal vehicle speed VESaving the optimal vehicle speed V of the node EE；
If none of steps (3) - (5) links the speeds of the two nodes, the objective function value J is set to the maximum value (the maximum value is set, and may be set to infinity).
(7) Repeating iteration to calculate optimal speed
Similarly, after the optimal speed of the node E is calculated, the state of the node D, C, B is sequentially calculated, for example, the point D has three speed nodes, taking Da as an example, the total objective function value of Da- - -Eb- - -F and Da- - -Ec- - -F needs to be calculated, the speed chain (assuming Da- - -Eb- - -F) where the smaller total objective function is located is selected, and the other chain is discarded. And in the same way, the optimal speed chain where the Db and Dc points are located is sequentially calculated, and the optimal speed of each node and the corresponding optimal total objective function value are sequentially stored.
When the second node B is calculated, as can be seen from fig. 4, the Ba and Bd points will be discarded due to the speed range mismatch, the node B will store the two nodes Bb and Bc, and select the node with the minimum total objective function value (for example, Bc) from the two nodes Bb and Bc, and finally, V will be calculatedBcAs the optimized optimal vehicle speed. And when the vehicle continues to drive forwards, repeating the steps and updating the optimal vehicle speed at the next moment in real time.
(8) Special case handling
And (4) if the speeds in any two non-first nodes cannot be linked together through the steps (3), (4) and (5), for example, the speed node of the D point cannot be linked to the E point by any means, taking the D point as a final state point, and then replanning. If the speed of the first node A cannot be linked with the speed of the node B, the final speed of the node B is planned to be VA。
Claims (1)
1. A vehicle forecasting and cruising control method based on a high-precision map is characterized by comprising the following steps:
step one, positioning a vehicle
Accurately positioning the current position of the vehicle through a GPS, and acquiring map data information within X meters ahead according to a high-precision map;
step two, map transmission
Transmitting the map data information to a controller according to an ADASIS protocol; the map data information comprises the current node position and the node gradient within X meters ahead, intersection position information, a speed limiting position and a mark; x is 1000-3000 m, and the distance between adjacent nodes in X m is 10-100 m;
step three, map reconstruction
The controller effectively reconstructs the map ahead according to the received map data information to obtain reconstructed map data information which can identify the current slope section, the information of the front slope section and the position and speed limit identification information of the front intersection;
step four, forecasting cruise vehicle speed planning
4.1, the cruising speed is limited according to the following three conditions:
a. a speed limit mark in a certain distance in front and the speed of the vehicle is limited to Vlim1；
b. The intersection information exists in a certain distance ahead, and the vehicle speed is limited to Vlim2；
c. The cruising speed set by the driver is VrefAcceptable cruise speed deviation is VincWith a lower deviation of Vdec(ii) a The lower limit of the cruise vehicle speed is finally set to (V)ref-Vdec) Upper limit of Vlim1、Vlim2、(Vref+Vinc) Minimum value of (1);
4.2 cruise speed optimization
4.2.1 estimating the velocity ranges of the nodes ahead
Suppose the maximum velocity of node i is VimaxThe maximum torque that the whole vehicle can provide is TmaxThe mass of the whole vehicle is m, and the gradient value of the node i +1 is Slope(i+1)The distance from node i to node i +1 is Deltas(i_i+1)Then, according to the vehicle dynamics equation (1), the maximum acceleration ACC which can be reached when the vehicle runs from the node i to the node i +1 is calculated(i+1)max：
ACC(i+1)max＝facc(Tmax，Vimax，Slope(i+1)，m) (1)
If Vimax 2+2*Acc(i+1)max*Δs(i_i+1)<0, then node i +1 maximum vehicle speed V(i+1)max＝0；
If Vimax 2+2*Acc(i+1)max*Δs(i_i+1)If the speed is more than 0, the node i +1 has the maximum speed
V0max＝V0The vehicle speed at the current position of the vehicle;
suppose the minimum velocity of node i is ViminThe maximum negative torque that the whole vehicle can provide is TminWhen the vehicle is travelling with maximum braking, according to the vehicle dynamicsRange (2) calculates the maximum deceleration Dec that can be achieved by traveling from node i to node i +1(i+1)max：
Dec(i+1)max＝fdec(Tmin，Vimin，Slope(i+1)，m) (2)
If Vimin 2+2*Dec(i+1)max*Δs(i_i+1)<0, then node i +1 minimum vehicle speed V(i+1)min＝0；
If Vimin 2+2*Dec(i+1)max*Δs(i_i+1)The node i +1 minimum vehicle speed is larger than or equal to 0
V0min＝V0The vehicle speed at the current position of the vehicle;
4.2.2. the optimal speed V of the end node NNPlanned as cruising speed V of vehiclerefI.e. VN＝Vref；
4.2.3 optimization of speeds of other nodes
(1) Discretizing the speed range of each node according to the speed range of each node obtained by prediction in the step 4.2.1 and set intervals; discretization of the point to the node i-1 to obtain n(i-1)Speed node
The optimal speed of node i is Vi；
(2) Assuming that the maximum speed and the minimum speed of the node N-1 are both equal to a certain speed node of the node N-1, the calculated speed range of the end node N does not include the optimal vehicle speed V of the end node NNIf the speed node does not meet the condition, the speed node is considered to be not in accordance with the condition; excluding all speed nodes of the node N-1 which do not meet the condition;
(3) speed of attempting to link node N and node N-1 with neutral
Assume that the Slope between node N and node N-1 is SlopeN-(N-1)A distance of SN-(N-1)(ii) a For any characterConditional velocity node V(N-1)_xFrom which velocity node V is calculated(N-1)_xStarting from, running in neutral SN-(N-1)The final velocity obtained after the distance; if the final speed is equal to the optimal speed V of the final node NNIf the speed difference is more than 3km/h, directly jumping to the next step (4); otherwise, directly jumping to the step (6);
(4) attempting to link node N and node N-1 speed with positive torque
Calculating slave velocity node V(N-1)_xStarting from node N-1 to node N the required positive torque T(N-1)_xIf a positive torque T is obtained(N-1)_xIf the torque is larger than the maximum torque of the vehicle engine, directly jumping to the step (5); otherwise, directly jumping to the step (6);
(5) attempting to link node N and node N-1 speed with negative torque
Calculating slave velocity node V(N-1)_xStarting with available auxiliary braking torque from node N-1 to node N and vehicle speed at the final node N at Vnext(N-1)_x(ii) a If Vnext(N-1)_xAnd VNIf the speed difference is within 3km/h, turning to the step (6); otherwise, the speed node V is abandoned(N-1)_x；
(6) Saving velocity and objective function values for each available node
Calculating the objective function value of the node N from the node N-1 when all speed nodes meeting the conditions are used as initial speeds; for velocity node V(N-1)_xValue of objective function J(N-1)_x_NThe following were used:
J(N-1)_x_N＝Q(N-1)B*(B(N-1)_x_N/B(N-1)_Nref+Q(N-1)T*Time(N-1)_x_N/Time(N-1)_N ref(6)
wherein, B(N-1)_x_N，Time(N-1)_x_NRespectively is an initial velocity V(N-1)_xThe amount and time of fuel consumed to travel to node N; q(N-1)BAnd Q(N-1)TThe weight coefficients of fuel economy and instantaneity of driving from the node N-1 to the node N are respectively; b is(N-1)_x_NObtaining the fuel consumption map of the vehicle engine through pre-calibration; time(N-1)_x_N＝S(N-1)_N/V(N-1)_x；B(N-1)_N refThe vehicle speed is cruising speed V(N-1)_N refReference fuel consumption, Time, from node N-1 to node N(N-1)_N refThe vehicle speed is cruising speed V(N-1)_N refA reference time from node N-1 to node N;
Time(N-1)_Nref＝SN-(N-1)/V(N-1)_Nref
saving the state of each speed node, namely the speed and the corresponding objective function value; selecting a speed node corresponding to a smaller objective function value as an optimal vehicle speed VN-1And storing;
(7) repeating iteration to calculate optimal speed
After the state of the node N-1 is calculated, sequentially calculating the states of the following nodes N-2 and N-3 … according to the methods of the steps (2) to (6); aiming at any node, calculating a total objective function value when all nodes in front X meters are respectively linked by each speed node, selecting a speed chain with a smaller objective function value, and taking the speed node corresponding to the speed chain as the optimal speed of the node;
(8) if the speeds in any two non-first nodes cannot be linked together through the steps (3), (4) and (5), taking the latter node as a final state point, and then optimizing the speeds of the nodes again according to the steps (1) to (7); if the velocity of the head node 1 cannot be linked with the velocity of the node 2, V of the node 1 is linked1As the optimal speed for node 2.
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| CN112046480A (en) * | 2020-09-21 | 2020-12-08 | 广州小鹏汽车科技有限公司 | Control method and device for vehicle speed limit |
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