CN110509922A - A kind of vehicle prediction cruise control method based on high-precision map - Google Patents

Abstract

The present invention relates to a kind of, and the vehicle based on high-precision map predicts cruise control method, and this method includes the following steps: vehicle location；Map transmission；Map reconstruct；Prediction cruise speed planning；The present invention is based on GPS and high-precision maps to predict front traffic information in real time, and automatic adjusument is carried out to cruise speed under different operating conditions, balance the relationship between low oil consumption and high timeliness, transportation cost is saved, improve conevying efficiency, compared with common cruise, on the basis of guaranteeing vehicle timeliness, the fuel economy of vehicle is greatly improved.

Description

A kind of vehicle prediction cruise control method based on high-precision map

Technical field

The present invention relates to technical field of vehicle control more particularly to it is a kind of based on the vehicle of GPS and high-precision map predict Cruise control method.

Background technique

Growing with automobile demand, automobile market increasingly shows unprecedented vigor, and huge automobile is protected The amount of having brings serious environmental pollution and energy security problem.By taking energy consumption as an example, China Petroleum wastage in bulk or weight about 4.9 in 2012 Hundred million tons, import dependency degree is up to 57.8%, and about 1.86 hundred million tons of automobile consumption amount, account for the 37.8% of total amount.It is no matter exogenous Mandatory rules of law or endogenic product are actively reformed, and the further development of vehicle energy saving, emission-reduction technology is required to.Due to vehicle The high fuel consumption of itself, if implementing effective fuel-economizing administrative skill to it, effect can highly significant.Highway Rapid development provides wide application space for cruise system, and the research for cruise system has gradually become a hot spot.It is close Emerge much research achievements about cruise system year both at home and abroad, these achievements are concentrated mainly on comfort, safety and move On state tracking performance however under the energy shortage situation that environmental pollution is serious, how to further increase the fuel-economy of automobile Property, achieving energy-saving and emission reduction purposes will be of great significance.

Many automobile vendors external at present such as run quickly, Scania, DAF, IVECO etc. have had launched prediction Fuel-economizing cruise technology, Scania take the lead in being proposed active predicting cruise control system, using GPS positioning vehicle and predict front Road, real-time optimization go out optimal cruise speed, and fuel consumption rate is improved in whole driving process, reduce transportation cost.Separately Outside, more representational there are also " I-See " automatic cruising technologies that Volvo AB releases, and are stored using backstage a large amount of real Car data simultaneously preferably goes out optimal cruising manner under typical road conditions, and this technology needs powerful background support, for special The emergency reaction of operating condition and processing are complex.

Above-mentioned automatic cruising technology is designed primarily directed to foreign landform, for Chinese complicated topography, There might not be preferable oil-saving effect, and the domestic automatic cruising function of designing not yet for different terrain pushes away at present Out, the present invention is based under this background and designs.

Summary of the invention

The technical problem to be solved in the present invention is to provide a kind of, and the vehicle based on high-precision map predicts cruise control method, This method makes full use of geographical advantage to optimize speed, can achieve the purpose that fuel-economizing and timeliness double shield.

In order to solve the above-mentioned technical problem, the vehicle prediction cruise control method of the invention based on high-precision map includes Following step:

Step 1: vehicle location

Vehicle present position is accurately positioned by GPS, and is obtained in X meters of front according to high-precision map Map data information；

Step 2: map transmission

Map data information is transferred to controller according to ADASIS agreement；The map data information include it is current and Node location, the node gradient in front X meters, intersection location information, speed limiting position and mark；X=1000~3000 meter, X Adjacent node spacing is 10~100 meters in rice；

Step 3: map reconstructs

Map data information effectively reconstructs front map to controller based on the received, and obtaining, which can recognize, works as scarp slope road The reconstruct map data information of section, front slope road section information and front cross mouth position and speed limit identification information；

Step 4: prediction cruise speed planning

4.1, cruise speed does the limitation of most value according to following three kinds of situations:

A, there are speed limit mark, restricted speed V in a distance of front_lim1；

B, there are intersection information, restricted speed V in a distance of front_lim2；

C, the cruise speed that driver sets is V_ref, the acceptable cruise speed upper deviation is V_inc, lower deviation is V_dec；The cruise speed lower limit finally set is (V_ref-V_dec), upper limit V_lim1、V_lim2、(V_ref+V_inc) in minimum value；

4.2, cruise speed optimization

4.2.1 each node speed range in estimation front

Assuming that the maximum speed of node i is V_imax, the peak torque that vehicle is capable of providing is T_max, complete vehicle quality m, section The value of slope of point i+1 is Slope_(i+1), the distance of node i to node i+1 is Δ_{s(i_i+1)}, then according to dynamics of vehicle equation (1) it is calculated from node i and drives to the peak acceleration ACC that node i+1 can reach_(i+1)max:

ACC_(i+1)max=f_acc(T_max, V_imax, Slope_(i+1), m) and (1)

If V_imax ²+2*Acc_(i+1)max*Δ_{s(i_i+1)}< 0, then+1 the max speed V of node i_(i+1)max=0.

If V_imax ²+2*Acc_(i+1)max*Δ_{s(i_i+1)}> 0, then+1 the max speed of node i

V_0max=V₀That is the speed of current vehicle position；

Assuming that the minimum speed of node i is V_imin, the maximum negative torque that vehicle is capable of providing is T_min, vehicle is with maximum system Dynamic traveling, then be calculated from node i according to dynamics of vehicle equation (2) and drive to the maximum deceleration that node i+1 can reach Spend Dec_(i+1)max:

Dec_(i+1)max=f_dec(T_min, V_imin, Slope_(i+1), m) and (2)

If V_imin ²+2*Dec_(i+1)max*Δ_{s(i_i+1)}< 0, then the minimum vehicle velocity V of node i+1_(i+1)min=0；

If V_imin ²+2*Dec_(i+1)max*Δ_{s(i_i+1)}>=0, then the minimum speed of node i+1

V_0min=V₀That is the speed of current vehicle position；

4.2.2. by the optimal velocity V of end-node N_NIt is planned to the cruise vehicle velocity V of vehicle_ref, i.e. V_F=V_ref；

4.2.3 other each node speed optimizations

(1) each node speed range predicted according to step 4.2.1, according to setting interval to each node speed model Enclose carry out discretization；If obtaining n for -1 discretization of node i_(i-1)A velocity nodeThe optimal velocity of node i is V_i；

(2) it when assuming that the maximum speed of node N-1 and minimum speed are equal to a certain velocity node of node N-1, calculates The velocity interval of obtained end-node N does not include the optimal vehicle velocity V of end-node N_N, then it is assumed that the velocity node is ineligible； Exclude ineligible all velocity nodes of node N-1；

(3) speed with neutral gear hinged node N and node N-1 is attempted

Assuming that the gradient between node N and node N-1 is Slope_N-(N-1), distance is S_N-(N-1)；For any eligible Velocity node V_{(N-1)_x}, calculate from velocity node V_{(N-1)_x}It sets out, S is travelled using neutral gear_N-(N-1)The end speed obtained after distance Degree；If the optimal vehicle velocity V of end speed and end-node N_NSpeed differs 3km/h or more, then leaps to next step (4)；Instead Then jump directly to step (6)；

(4) speed with positive-torque hinged node N and node N-1 is attempted

It calculates from velocity node V_{(N-1)_x}It sets out, from positive-torque T required for node N-1 to node N_{(N-1)_x}If obtained Positive-torque T_{(N-1)_x}Greater than vehicle motor peak torque, then step (5) are jumped directly to；It is on the contrary then jump directly to step (6)；

(5) speed with negative torque hinged node N and node N-1 is attempted

It calculates from velocity node V_{(N-1)_x}It sets out, available auxiliary braking torque and end-node N from node N-1 to node N Speed be V_{next(N-1)_x}；If V_{next(N-1)_x}With V_NSpeed differs within 3km/h, then goes to step (6)；Otherwise give up the speed Spend node V_{(N-1)_x}；

(6) speed and target function value of each enabled node are saved

When calculating all qualified velocity nodes as initial velocity, the objective function of node N is driven to from node N-1 Value；For velocity node V_{(N-1)_x}, target function value J_{(N-1)_x_N}It is as follows:

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_N}Respectively initial velocity V_{(N-1)_x}Drive to amount of fuel consumed by node N and Time；Q_(N-1)BAnd Q_(N-1)TThe fuel economy of node N and the weight coefficient of real-time are respectively driven to from node N-1； B_{(N-1)_x_N}It is obtained by the vehicle startup engine oil consumption map figure demarcated in advance；Time_{(N-1)_x_N}=S_{(N-1)_N}/V_{(N-1)_x}；B_{(N-1)_N ref}It is cruise vehicle velocity V for speed_{(N-1)_N ref}When reference oil consumption from node N-1 to node N, Time_{(N-1)_N ref}It is to patrol for speed Boat vehicle velocity V_{(N-1)_N ref}When from node N-1 to the reference time of node N；

Time_{(N-1)_Nref}=S_N-(N-1)/V_{(N-1)_Nref}；

Save the state of each velocity node, i.e. speed and corresponding target function value；Selection is wherein compared with Small object letter The corresponding velocity node of numerical value is as optimal vehicle velocity V_N-1And it saves；

(7) it iterates, calculates optimal velocity

After the state that node N-1 has been calculated, each node N-2, N- below are successively calculated according to step (2)-(6) method The state of 3 ...；For any node, general objective when linking all nodes in X meters of front respectively with its each velocity node is calculated Functional value selects the wherein Speed Chain where lesser target function value, using the corresponding velocity node of the Speed Chain as the section The optimal velocity of point；

(8) if the speed in any two non-first node can not be linked together by step (3), (4), (5), Then using latter node as final state point, then each node speed is optimized again according to step (1)-(7)；If The speed of first node 1 can not be linked together with the speed of node 2, then by the V of node 1₁Optimal velocity as node 2.

To sum up, by adopting the above-described technical solution, the beneficial effects of the present invention are:

1. the accurate positionin to vehicle, effective map number in front of real-time reception in a distance may be implemented in the present invention According to；

2. the present invention by carrying out validity processing to received map datum, can carry out the road in front effectively heavy Structure identifies different kinds of roads operating condition；

3. can be prompted according to the front road conditions identified driver in driver's normal driving；

4. it is directed to cruising condition, comprehensive fuel-economizing and timeliness requirement, the adaptability in the range that driver is subjected to Adjust cruise speed, this advantage be even more on the route that landform is rugged and rough, road surface rises and falls performed to it is ultimate attainment；

5 present invention can identify speed limit mark and intersection in advance, and realize that effective speed controls according to different situations；

6. imitating the drive automatically for having experience driver the present invention is based on the understanding to road ahead, keeping as far as possible Low fuel consumption.

The present invention is based on GPS and high-precision maps to predict front traffic information in real time, and to cruise vehicle under different operating conditions Speed carries out automatic adjusument, balances the relationship between low oil consumption and high timeliness, has saved transportation cost, improves conevying efficiency, Compared with common cruise, on the basis of guaranteeing vehicle timeliness, the fuel economy of vehicle is greatly improved.

Detailed description of the invention

Invention is further described in detail with reference to the accompanying drawings and detailed description.

Fig. 1 is present invention foresees that cruise speed planning flow chart.

Fig. 2 is each nodal information schematic diagram of road ahead.

Fig. 3 is that velocity interval predicts schematic diagram.

Fig. 4 is speed planning process schematic.

Specific embodiment

The present invention is directed to the prediction cruise function of vehicle, identifies that vehicle is worked as according to global positioning system and high-precision map Front position and front X meters of road information, and according to real-time road condition information on the basis of cruise, it is acceptable in driver The best speed of optimization in range.

As shown in Figure 1, the vehicle prediction cruise control method of the invention based on high-precision map includes the following steps:

Step 1: vehicle location

Vehicle present position is accurately positioned by GPS (global positioning system) first, and according to high-precision Map obtains the map data information in X meters of front.

Step 2: map transmission

It is effectively transmitted according to ADASIS agreement to map information and is sent to controller.Map datum includes current Road information, front X meters of road information specifically include the data such as front cross mouth, speed limit and the gradient；X=1000~3000 Meter, adjacent node spacing is 10~100 meters in X meters；Here X=2000 meters are chosen, adjacent node spacing chooses 25 meters.

Step 3: map reconstructs

Front map is effectively reconstructed after controller real-time reception map datum.It mainly includes following several for wherein reconstructing A step:

The input of 3.1 signals

The road data that controller receives includes node location, the node gradient, intersection location information, speed limiting position and The information such as mark.

3.2 signal processing

In order to guarantee the continuity and validity of data, for the data received, need to be handled by a series of singular points, Such as the grade point being mutated in data or a certain section of unreasonable data are removed, to guarantee the validity of subsequent road reconstruct.

The reconstruct of 3.3 roads

After step 3.2 signal processing, controller needs that front X meters of map datum is reconstructed, and is similar to Navigation is the same, by the road conditions induction-arrangement in front at the characteristics map that can be identified.It is divided into the following aspects:

3.3.1 identifying road ahead feature

Controller receives X meters of the road information in front, first the position to each node of road ahead and grade information into Row storage.Then taxonomic revision is carried out to road information according to gradient difference, sets the range of grade in different typical sections, it is such as flat The range of grade on road is S₀—S₁.According to current vehicle position and the front position Po Lu, road conditions locating for vehicle are divided into following several Situation, including level road, upward slope, descending, mountain peak, mountain valley etc. open to driver can be used as front road condition advisory information, can also make For the foundation of speed control strategy.

3.3.2 current roadway characteristic is identified:

Regard the map data information in X meters of ranges of vehicle as known map, according to the current location information of vehicle It is searched in map, parses current roadway characteristic, including current position, the information such as the gradient, and according to country to high speed The construction specification of highway does the limitation of most value.

3.3.3 identifying intersection location information

Controller receives intersection location information in X meters of front, and is stored in array.

3.3.4 identifying speed limit identification information

Controller receives speed limit identification information in X meters of front, by speed limiting position and speed limit value storage into array, convenient for standard Really identification speed-limiting messages do corresponding limitation to speed and handle.

Step 4: prediction cruise speed planning

Basic ideas of the invention are to go to improve speed as far as possible before upward slope, reduce speed before descending, make full use of landform Advantage reaches the dual optimization of running efficiency and cost.

Prediction cruise speed planing method according to the present invention including the following steps:

4.1. prediction cruise speed restriction strategy

Based on the above-mentioned identification to road, for cruising condition, controller first does most the cruise speed finally set Value limitation.Specifically there are following three kinds of speed limit situations:

(1) there are speed limit mark, restricted speed V in a distance of front_lim1；

(2) there are intersection information, restricted speed V in a distance of front_lim2(can self-calibration)；

(3) the cruise speed that driver sets is V_ref, the acceptable cruise speed upper deviation is V_inc, lower deviation is V_dec；The cruise speed lower limit finally set is (V_ref -V_dec), upper limit V_lim1、V_lim2、(V_ref +V_inc) in minimum value.

4.2. prediction cruise speed control strategy

Introduced according to step 3.3.1, in front X meters position and the information such as the gradient store, be specifically described below Once how cruise speed to be optimized according to the cartographic information of storage.

4.2.1 each node speed range in estimation front

Under the premise of known current vehicle speed, the velocity interval of each node in front is predicted using needs.

It is introduced by taking node B as an example.

Maximum speed calculates

Assuming that the maximum speed of node B is V_Bmax, the peak torque that vehicle is capable of providing is T_max, m is complete vehicle quality, section The value of slope of point C is Slope_C, the distance of node B to node C is Δ_sBC, then according to dynamics of vehicle side well known in the art Journey (1) drives to the peak acceleration ACC that node C can reach from node B_CmaxAre as follows:

ACC_Cmax=f_acc(T_max, V_Bmax, Slope_C, m) and (1)

If V_Bmax ²+2*Acc_Cmax*Δ_sBC< 0, then node C the max speed V_Cmax=0.

If V_Bmax ²+2*Acc_Cmax*Δ_sBC> 0, then node C the max speed

Note: according to above-mentioned rule V_BmaxIt is to be calculated according to node A speed, V_Amax=V_AThat is current vehicle position Speed.

Minimum speed calculates

Assuming that the minimum speed of node B is V_Bmin, the maximum negative torque that vehicle is capable of providing is T_min, then known in this field According to dynamics of vehicle equation (2), it is assumed that vehicle with maximum braking traveling, driving to node C from node B can reach most Big retarding degree Dec_CmaxAre as follows:

Dec_Cmax=f_dec(T_min, V_Bmin, Slope_C, m) and (2)

If V_Bmin ²+2*Dec_Cmax*Δ_sBC< 0, then node C minimum vehicle velocity V_Cmin=0.

If V_Bmin ²+2*Dec_Cmax*Δ_sBC>=0, then node C minimum speed

Note: according to above-mentioned rule V_BminIt is to be calculated according to node A speed, V_Amin=V_AThat is current vehicle position Speed.Each node speed range is stored, specific schematic diagram is as shown in Figure 3.

4.2.2. end-node speed planning

After obtaining each node speed range, the speed of end-node is planned first, herein by minor details spot speed Metric divides the cruise speed of vehicle into, it is assumed that end-node F, then the optimal speed of end-node F is V_F；

V_F=V_ref (3)

4.2.3 other each node speed optimizations

Node speed discretization chooses enabled node

The present invention is the thought based on Dynamic Programming for the planning of speed, from minor details spot speed forward impelling.According to step The optimal speed of rapid 4.2.2 elder generation plan node F is V_F, then plan the speed of E point；Assuming that the section obtained according to step 4.2.1 The maximum speed of point E is V_Ea, minimum speed V_Ec, the speed dispersion of node E is obtained by speed with setting speed interval delta v Node V_Ea、V_EbAnd V_Ec.According to the method for step 4.2.1 calculating speed range, calculate node E initial velocity is respectively V_Ea、V_Eb And V_EcThe velocity interval of Shi Jiedian F.It is assumed that the maximum speed and minimum speed as node E are equal to V_EaWhen count The velocity interval of obtained node F does not include the optimal vehicle velocity V of node F_F, then it is assumed that speed V_EaIt is ineligible.So section Point E can plan that velocity node is V_EbAnd V_Ec, below with velocity node V_EbFor be illustrated.

(2) reference state is calculated

Vehicle in the EF of section is calculated first maintains cruise vehicle velocity V_refEach reference state amount when operation, such as:

According to the vehicle startup engine oil consumption map map analysis demarcated in advance, speed is cruise vehicle velocity V_refWhen from node E run To the reference oil consumption B of node F_eref, it is by V_ref, Slope_F, it is fixed that the four-dimensional map of m composition decides by vote:

B_eref=MAP (V_ref, Slope_F, m) and (4)

Speed is cruise vehicle velocity V_refWhen reference time Time_refIt is as follows:

Time_ref=S_EF/V_ref (5)

Wherein S_EFDistance between EF, the value of slope of node F are Slope_F；

(3) trial links the speed of two nodes with neutral gear

Assuming that the gradient between EF is Slope_F, distance is S_EF, it calculates from speed V_EbIt sets out, S is travelled using neutral gear_EFDistance The end speed V obtained afterwards_G0.If V_FWith V_G0Speed differs 3km/h or more, then it is assumed that two sections can not be connected using neutral position sliding Point jumps directly to step (4).It is on the contrary then think to travel using neutral gear and from node E slide into node F, then omit step below Suddenly (4) and (5) leap to step (6).

(4) trial links the speed of two nodes with positive-torque

If the speed of two nodes can not be linked with neutral position sliding, attempt to calculate required for node E to node F just Torque T_EbIf final torque T_Eb(it is greater than vehicle motor peak torque) not in reasonable range, then it is assumed that can not The speed that two nodes are connected by positive-torque, jumps directly to step (5).It is on the contrary then think can by positive-torque link two The speed of node leaps to step (6).

(5) trial links the speed of two nodes with negative torque

If above-mentioned steps (3) (4) both of which can not link the speed of two nodes, attempt to use auxiliary braking chain It connects, calculates and S is travelled using auxiliary braking_EFThe end speed V obtained after distance_nextbIf V_nextbWith V_FSpeed is differed in 3km/h Within, then it is assumed that auxiliary braking can be used up to the speed of two nodes of link, leap to step (6)；Otherwise give up the speed Spend node V_Eb。

(6) speed and target function value of each enabled node are saved

When calculating all qualified velocity nodes as initial velocity, the objective function of node N is driven to from node N-1 Value；For example, being directed to velocity node V_Eb, utilize formula (6) calculating target function value J_Eb；Wherein formula (6) specifically considers vehicle Fuel economy, the performances such as real-time can also be by user's self-defining.

J_Eb=Q_B*(B_EbF/B_eref)+Q_T*Time_EF/Time_ref (6)

Wherein, B_EbF, Time_EbFRespectively with initial velocity V_EbNode F is driven to (by velocity node V_EbAs initial velocity from Node E neutral gear drives to node F, positive-torque drives to node F or negative torque drives to node F) consumed by amount of fuel and Time.Q_BAnd Q_TFor the weight coefficient of fuel economy and real-time, Q_BAnd Q_TIt is obtained using emulation or real train test debugging (test adjustment method is techniques well known)；B_EbFIt can be obtained by the vehicle startup engine oil consumption map figure demarcated in advance； Time_EbF=S_EF/V_Eb；B_EFrefIt is cruise vehicle velocity V for speed_EFrefWhen reference oil consumption from node E to node F, Time_EFrefFor Speed is cruise vehicle velocity V_EFrefWhen from node E to the reference time of node F；Time_EFref=S_EF/V_EFref；

Save the state of velocity node Eb and Ec, including speed V_Eb, V_EcWith target function value J_Eb, J_Ec, select wherein smaller The corresponding velocity node of target function value is as optimal vehicle velocity V_E, save the optimal vehicle velocity V of node E_E；

If step (3)-(5) can not link the speed of two nodes, maximum value is set by target function value J (maximum value is setting, can be set to infinity).

(7) it iterates, calculates optimal velocity

Similarly, after the optimal velocity that node E has been calculated, the successively state of calculate node D, C, B, such as there are three D points Velocity node, needs to calculate by taking Da as an example the general objective functional value of Da-----Eb-----F and Da----Ec-----F, selection compared with Speed Chain (assuming that being Da-----Eb-----F) where small catalogue scalar functions, then another chain can be rejected.Similarly successively The optimal velocity chain where Db and Dc point is calculated, the optimal velocity and corresponding optimal catalogue scalar functions of each node are successively saved Value.

When calculating to second node B, as shown in Figure 4, Ba and Bd point can be rejected since velocity interval is not met, In B node can save two nodes Bb and Bc, select the smallest node of general objective functional value (by taking Bc as an example) in the two, then finally will V_BcOptimal speed as optimization.When vehicle continues to move forward, repeat the above steps, real-time update subsequent time it is optimal Speed.

(8) treatment on special problems

If the speed in any two non-first node can not be linked together by step (3) (4) (5), such as D point When no matter velocity node can not all be linked to E point by which kind of mode, then using D point as final state point, then advise again It draws.If the speed of first node A can not be linked together with the speed of B node, it is by the final speed planning of B node V_A。

Claims (1)

1. a kind of vehicle based on high-precision map predicts cruise control method, it is characterised in that include the following steps:

Step 1: vehicle location

Vehicle present position is accurately positioned by GPS, and the map in X meters of front is obtained according to high-precision map Data information；

Step 2: map transmission

Map data information is transferred to controller according to ADASIS agreement；The map data information includes current and front Node location, the node gradient in X meters, intersection location information, speed limiting position and mark；X=1000~3000 meter, in X meters Adjacent node spacing is 10~100 meters；

Step 3: map reconstructs

Map data information effectively reconstructs front map to controller based on the received, obtain can recognize when scarp slope section, The reconstruct map data information of front slope road section information and front cross mouth position and speed limit identification information；

Step 4: prediction cruise speed planning

4.1, cruise speed does the limitation of most value according to following three kinds of situations:

A, there are speed limit mark, restricted speed V in a distance of front_lim1；

B, there are intersection information, restricted speed V in a distance of front_lim2；

C, the cruise speed that driver sets is V_ref, the acceptable cruise speed upper deviation is V_inc, lower deviation V_dec；Most The cruise speed lower limit set eventually is (V_ref-V_dec), upper limit V_lim1、V_lim2、(V_ref+V_inc) in minimum value；

4.2, cruise speed optimization

4.2.1 each node speed range in estimation front

Assuming that the maximum speed of node i is V_imax, the peak torque that vehicle is capable of providing is T_max, complete vehicle quality m, node i+1 Value of slope be Slope_(i+1), the distance of node i to node i+1 is Δ_{s(i_i+1)}, then calculated according to dynamics of vehicle equation (1) It obtains driving to the peak acceleration ACC that node i+1 can reach from node i_(i+1)max:

ACC_(i+1)max=f_acc(T_max, V_imax, Slope_(i+1), m) and (1)

If V_imax ²+2*Acc_(i+1)max*Δ_{s(i_i+1)}< 0, then+1 the max speed V of node i_(i+1)max=0.

If V_imax ²+2*Acc_(i+1)max*Δ_{s(i_i+1)}> 0, then+1 the max speed of node i

V_0max=V₀That is the speed of current vehicle position；

Assuming that the minimum speed of node i is V_imin, the maximum negative torque that vehicle is capable of providing is T_min, vehicle is with maximum braking row It sails, is then calculated according to dynamics of vehicle equation (2) from node i and drives to the maximum deceleration that node i+1 can reach Dec_(i+1)max:

Dec_(i+1)max=f_dec(T_min, V_imin, Slope_(i+1), m) and (2)

If V_imin ²+2*Dec_(i+1)max*Δ_{s(i_i+1)}< 0, then the minimum vehicle velocity V of node i+1_(i+1)min=0；

If V_imin ²+2*Dec_(i+1)max*Δ_{s(i_i+1)}>=0, then the minimum speed of node i+1

V_0min=V₀That is the speed of current vehicle position；

4.2.2. by the optimal velocity V of end-node N_NIt is planned to the cruise vehicle velocity V of vehicle_ref, i.e. V_F=V_ref；

4.2.3 other each node speed optimizations

(1) each node speed range predicted according to step 4.2.1, according to setting interval to each node speed range into Row discretization；If obtaining n for -1 discretization of node i_(i-1)A velocity nodeSection The optimal velocity of point i is V_i；

(2) it when assuming that the maximum speed of node N-1 and minimum speed are equal to a certain velocity node of node N-1, is calculated End-node N velocity interval do not include end-node N optimal vehicle velocity V_N, then it is assumed that the velocity node is ineligible；It excludes Ineligible all velocity nodes of node N-1；

(3) speed with neutral gear hinged node N and node N-1 is attempted

Assuming that the gradient between node N and node N-1 is Slope_N-(N-1), distance is S_N-(N-1)；For any qualified speed Spend node V_{(N-1)_x}, calculate from velocity node V_{(N-1)_x}It sets out, S is travelled using neutral gear_N-(N-1)The end speed obtained after distance； If the optimal vehicle velocity V of end speed and end-node N_NSpeed differs 3km/h or more, then leaps to next step (4)；It is on the contrary then Jump directly to step (6)；

(4) speed with positive-torque hinged node N and node N-1 is attempted

It calculates from velocity node V_{(N-1)_x}It sets out, from positive-torque T required for node N-1 to node N_{(N-1)_x}If obtained just Torque T_{(N-1)_x}Greater than vehicle motor peak torque, then step (5) are jumped directly to；It is on the contrary then jump directly to step (6)；

(5) speed with negative torque hinged node N and node N-1 is attempted

It calculates from velocity node V_{(N-1)_x}It sets out, the speed of available auxiliary braking torque and end-node N from node N-1 to node N For V_{next(N-1)_x}；If V_{next(N-1)_x}With V_NSpeed differs within 3km/h, then goes to step (6)；Otherwise give up the velocity node V_{(N-1)_x}；

(6) speed and target function value of each enabled node are saved

When calculating all qualified velocity nodes as initial velocity, the target function value of node N is driven to from node N-1； For velocity node V_{(N-1)_x}, target function value J_{(N-1)_x_N}It is as follows:

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)_Nref}(6)

Wherein, B_{(N-1)_x_N}, Time_{(N-1)_x_N}Respectively initial velocity V_{(N-1)_x}Drive to amount of fuel consumed by node N and time； Q_(N-1)BAnd Q_(N-1)TThe fuel economy of node N and the weight coefficient of real-time are respectively driven to from node N-1；B_{(N-1)_x_N} It is obtained by the vehicle startup engine oil consumption map figure demarcated in advance；Time_{(N-1)_x_N}=S_{(N-1)_N}/V_{(N-1)_x}；B_{(N-1)_Nref}For speed For vehicle velocity V of cruising_{(N-1)_Nref}When reference oil consumption from node N-1 to node N, Time_{(N-1)_Nref}It is cruise speed for speed V_{(N-1)_Nref}When from node N-1 to the reference time of node N；

Time_{(N-1)_Nref}=S_N-(N-1)/V_{(N-1)_Nref}

Save the state of each velocity node, i.e. speed and corresponding target function value；Selection is wherein compared with Small object functional value Corresponding velocity node is as optimal vehicle velocity V_N-1And it saves；

(7) it iterates, calculates optimal velocity

After the state that node N-1 has been calculated, each node N-2, N-3 ... below is successively calculated according to step (2)-(6) method State；For any node, catalogue scalar functions when linking all nodes in X meters of front respectively with its each velocity node are calculated Value selects the wherein Speed Chain where lesser target function value, using the corresponding velocity node of the Speed Chain as the node Optimal velocity；

It (8), will if the speed in any two non-first node can not be linked together by step (3), (4), (5) Then latter node again optimizes each node speed according to step (1)-(7) as final state point；If head section The speed of point 1 can not be linked together with the speed of node 2, then by the V of node 1₁Optimal velocity as node 2.