CN103699717A - Complex road automobile traveling track predication method based on foresight cross section point selection - Google Patents

Abstract

The invention provides a complex road automobile traveling track predication method based on foresight cross section point selection. The method comprises the following steps: analyzing and simulating a track decision behavior of a driver; abstracting a track selection behavior of the driver and evoluting a calculation strategy, namely a ''foresight point selection'' calculation strategy; researching hidden motivations of five typical driving modes and performing mathematic representation, so as to finally obtain an automobile travelling track decision method which can adapt to complex roads with any mileage length and is capable of simulating the typical driving modes. By applying the technology provided by the invention, aiming at mountain highways and complex racing roads, expected tracks of the following five driving modes can be obtained: respectively a shortest track length mode, a minimum track curvature mode (a racing road mode), a minimum curvature change rate mode (a most comfortable driving mode), a centered track mode (a centered travelling mode) and a mixed mode which is a combination of the above four typical modes.

Description

Complicated road traval trace Forecasting Methodology based on the reconnaissance of forward sight section

Technical field

What the present invention relates to is a kind of complicated road traval trace Forecasting Methodology based on the reconnaissance of forward sight section.

Background technology

When the closed loop of carrying out " vehicle-driver-road " system is travelled emulation, or when automatic driving, need within the scope of the wheeled of road surface, decision-making in advance go out a desired trajectory (target trajectory), for vehicle, follow in the process of moving, thereby realize automatically advancing of vehicle.

Existing technological means normally, using center line of road or runway center line as desired trajectory, supposes that driver adopts the driving model (direction control model) travelling between two parties.But in actual road running, driver freely selects driving trace can use in width of roadway, take two-lane highway as example, can use width of roadway except comprising a track, also comprises the hardened verge on right side, and the subtend runway in part left side.Therefore compare with body width, can use width of roadway to have very large surplus, particularly all the more so for minibus.Therefore, driver selects there is very large freedom in track selection and speed, such as observing polytype direction and control custom in the curve section at mountain highway: cut and curvedly (enter when curved from tangential inner side, curve outside, go out when curved switchback outside again), runway is placed in the middle, extra curvature skidding is sailed, the inner side of curve travels and occupy curb, etc.For this reason, carrying out the travelling during emulation of mountain highway or racing track, the prediction (decision-making) of track need to be carried out for above driving model, to obtain target trajectory.

According to the difference of research means, existing trajectory predictions technology can be divided three classes, be respectively forecasting techniques, the forecasting techniques based on mathematical optimization and the forecasting techniques based on polynomial regression method based on fuzzy rule.The shortcoming of existing trajectory predictions (decision-making) technology is as follows:

With reference to figure 1, by fuzzy rule means, carrying out in the technology of trajectory predictions, the Forecasting Methodology of Lauffanburgar is representative, he is by the actual negotiation of bends track of observation, obtained between track and road boundary in bend import, song and the lateral distance of the feature locations such as outlet, then the turning radius of take has been set up 6 degree of membership subsets as variable, in order to determine the TRAJECTORY CONTROL parameter d 1～d3 corresponding with given bend curvature, then approach to obtain continuous desired trajectory with 4 polar polynomials battens.Shortcoming is that d1～d3 has obvious dependence to having a lot of social connections, and while occurring significantly to change when having a lot of social connections, track can run off border, road surface or too placed in the middle.And because research object is the driver of preference inscribe, the method can not meet portrays requirement to driving behavior is diversified.

Gao Zhenhai and Guan Xin etc. are used particle swarm optimization algorithm prediction traval trace, their method is poor at aspects such as stability, convergence, global optimization abilities, only can carry out track decision to the road of tens meters of length, surpass this length and cannot obtain stablizing effective result of calculation, therefore can not meet the requirement of long distance travel emulation.And, aspect applicable situation, their research be mainly for vehicle lane-changing and urban road with the car occasion of travelling, and road running track decision under non-complex alignment condition.

Ren Yuanyuan changes according to the lateral attitude between track within the scope of bend and runway center line, by track be divided into ideal, normal, wave, correct, drift about and cut curved 6 classes, for each class driving trace, use regression analysis to set up the polar equation based on peak excursion value and spring of curve off-set value, use these equations can access the geometric locus of single bend, run into continuous bend and there will be prediction failure phenomenon.Due to actual mountain highway, to be all that continuous bend accounts for leading, and this kind of technology cannot be for the emulation of travelling of mountain highway.

Summary of the invention

Technical matters to be solved by this invention is to provide a kind of complicated road traval trace Forecasting Methodology based on the reconnaissance of forward sight section for the deficiencies in the prior art.

Technical scheme of the present invention is as follows:

A complicated road traval trace Forecasting Methodology based on the reconnaissance of forward sight section, comprises the following steps:

(1) from electronic map of automobile navigation, online transportation database, extract the geometry linear data of road, by geometry analytical Calculation, solve the planimetric coordinates of road geometrical boundary;

(2) according to driving habits, determine the spendable width of roadway of driver, set a width of roadway usage factor λ, then carry out coordinate transform, determine the planimetric coordinates that can use road breadths circle;

(3) in the region, forward sight road surface of vehicle front, divide at a certain distance forward sight section, spacing is according to the trajectory predictions strategy of " reconnaissance of forward sight section " " arrange;

(4) from 5 kinds of driving models that pre-set, select a kind of, the optimization aim using its corresponding objective function during as iterative computation;

(5) read the current travel speed of vehicle, side acceleration parameter, there is clear in judgement the place ahead, if any barrier, calculate remaining width of roadway, according to these parameters again in conjunction with vehicle dimension parameter, complete constraint condition setting, described constraint condition comprise in border travel, obstacle keeps away around 4 kinds of, bend trafficability characteristic, riding stabilities;

(6) selection due to track is to carry out within the scope of driver's form, and form is with the travelling and move forward of vehicle, and therefore long mileage road is divided into some successive shorted segments; Then, adopt Optimization Solution device LINGO11.0 along travel direction iterative method, to solve the decision variable S of each shorted segment _ivalue;

(7) according to scale-up factor S _ivalue, by formula (1), along travel direction, calculate one by one the tracing point planimetric coordinates of each forward sight section;

x _pti＝x _pri+w _di·S _i·cos α _i，

y _pti＝y _pri-w _di·S _i·sin α _i (1)

α wherein _ifor forward sight section i is line segment P _lip _riwith the angle of earth coordinates X-axis, P _li, P _rirespectively the left and right sides end points of forward sight section i, candidate's tracing point P _tiat line segment P _lip _rion; x _pti, y _ptifor P _tiplanimetric coordinates; x _pri, y _prifor P _riplanimetric coordinates;

(8) connect adjacent track point, obtain continuous trajectory, i.e. the driving trace that decision-making obtains, requires high occasion for display precision, can obtain level and smooth geometric locus by cubic spline interpolation.

Described method, 5 kinds of described driving models comprise the mixed mode of pattern in the shortest pattern of driving trace, track curvature minimal mode, track curvature variation minimal mode, runway track pattern placed in the middle and aforementioned four.

Described method, described driving trace is the objective function of short pattern, as shown in the formula:

$\mathrm{Min}{f}_{01}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{P}_{\mathrm{ti}}{P}_{\mathrm{ti}+1}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{L}_{\mathrm{ti}}---\left(2\right)$

L wherein _ti=((x _pti-x _pti+1) ²+ (y _pti-y _pti+1) ²) ^0.5.

Described method, the objective function of described track curvature minimal mode is expressed as:

$\min f_{02}=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}{K}_i=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}\frac{{\mathrm{\α}}_i}{L_i}---\left(5\right);$

Trajectory deflection angle

l _i=((x _pti-x _pti+1) ²+ (y _pti-y _pti+1) ²) ^0.5.

Described method, the objective function of described track curvature variation minimal mode is expressed as:

$\min f_{03}=\underset{i=3}{\overset{n-2}{\mathrm{\Σ}}}|K_{i+1}-K_i|---\left(6\right)$

Point P _tithe curvature at place is K _i.

Described method, the objective function of described runway track pattern placed in the middle is:

$\min f_{04}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\left|\mathrm{\Δ}{w}_i\right|=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}|0.5w_{\mathrm{Li}}-w_{\mathrm{tri}}|---\left(7\right)$

W _trifor tracing point P _tiwith forward sight section right side end points P _ribetween distance, w _liit is lane width.

Described method, described mixed mode objective function is expressed as:

Min f ₀₅＝β ₁f′ ₀₁+β ₂f′ ₀₂+β ₃f′ ₀₃+β ₄f′ ₀₄ (9)

In formula, β 1～β 4 >=0, is weight coefficient, need meet β 1+ β 2+ β 3+ β 4=1.

The work that the present invention carries out is that driver's track decision behavior is analyzed and simulated; Abstract and EVOLUTIONARY COMPUTATION strategy is carried out in track selection behavior to driver, i.e. the calculative strategy of " forward sight reconnaissance "; The behind motivation of 5 kinds of typical driving models of research is also carried out mathematical notation, finally obtains adapting to complicated traval trace decision-making technique road, that can simulate typical driving model of any mileage length.Apply technology of the present invention, can obtain for mountain highway and complicated racing track the desired trajectory of following 5 kinds of driving models, be respectively the shortest pattern of course length, track curvature minimal mode (racing track pattern), curvature variation minimal mode (driving the most comfortable pattern), track pattern placed in the middle (driving mode placed in the middle) and mixed mode, wherein mixed mode is the comprehensive of front 4 kinds of typical modules.

Accompanying drawing explanation

Fig. 1 is fuzzy rule method;

Fig. 2 is " forward sight reconnaissance " calculative strategy;

Fig. 3 is that the coordinate of forward sight section both sides end points calculates;

Fig. 4 is one of direction control model: course length is the shortest;

Fig. 5 is two of direction control model: track curvature is minimum;

Fig. 6 is four of direction control model: in runway, travel between two parties;

Fig. 7 is the computation process that traval trace is optimized;

Fig. 8 is the track optimizing result on Suzuka Circuit;

Embodiment

Below in conjunction with specific embodiment, the present invention is described in detail.

1. the trajectory predictions strategy of " reconnaissance of forward sight section "

In order to control vehicle safety, advance, driver takes situation that carve to note road ahead, to obtain the information such as used width, curvature of the passage that travels.Research early conventionally suppose that driver's sight line drops on vehicle front road surface certain a bit, but found afterwards, the result of using form model to obtain is more reasonable, and driver's sight line is to drop on the stretch face in the place ahead, along with travelling of vehicle, the region, road surface of dropping in form moves forward fast.On form hypothesis basis, the present invention has designed " reconnaissance of forward sight section " strategy, as Fig. 2.Although vehicle travelling in window area is a continuous process, but can be by its discretize in actual treatment, the present invention is cut apart form road surface by certain interval, each cross cut line (forward sight section) is regarded as to the set of candidate's tracing point, what driver will do is on each forward sight section, to select a some P _ti, the horizontal desired locations while crossing this section as vehicle.

The interval of forward sight section arranges will consider sighting distance, route mean curvature and the channel width factor of travelling, and these 3 factors are all closely related with highway layout speed.Concrete method to set up is as follows:

A. at design rate V _dwhen lower, such as V _d=20～30km/h, radius-of-curvature can be low to moderate 15～30m, and bend length also can be very short, higher than the section interval of 5m, could accurately not portray bend geometrical property.

When b. design rate is 100～120km/h, more than the general 600m of turning radius, curvature relaxes and bend long enough, and bend characteristic can fully be described in the interval of 20～30m.

C. as for straight way, can use the treating method identical with bend, this is that curved straight line conventionally can be very not long yet because mountain highway is linear more trifling.

In Fig. 2, P _li, P _rirespectively the left and right sides end points of forward sight section i, candidate's tracing point P _tiat line segment P _lip _rion.Therefore, can use P _tiat P _lip _rion slip describe different track and select behavior, such as P _tiin the middle of sliding to, can represent to travel between two parties, P _tislide into curve inner side and represent to cut negotiation of bends, etc.

Road geometry information as input can be used following several means to obtain: such as, with alignment elements form or with three-dimensional/two-dimensional coordinate form, be stored in online " Digital Highway storehouse ", electronic map of automobile navigation, navigation map or the road parameters approximating method based on GPS/IMU, these several means are comparative maturity, as Fig. 3.Thus, two end points P of arbitrary cross-section _liand P _riplanimetric coordinates can be calculated in conjunction with having a lot of social connections by alignment elements, or the boundary coordinate interpolation of satisfying the need obtains.

Therefore, P _tislip behavior and slide after position can use scale-up factor S _iunique decides, S _ibe expressed as S _i=w _tri/ w _di, w wherein _trifor tracing point P _tiwith forward sight section right side end points P _ribetween distance, w _difor the width of forward sight section i, i.e. the used Road width of this section position.Tracing point P so _tiplanimetric coordinates x _priand y _prican be calculated by following formula:

x _pti＝x _pri+w _di·S _i·cos α _i，

y _pti＝y _pri-w _di·S _i·sin α _i (1)

α wherein _ifor forward sight section i (is line segment P _lip _ri) with the angle of earth coordinates X-axis.Therefore, as long as the scale-up factor S of interior each section of form _idecide, desired trajectory is just decided thereupon.

The technical scheme of the typical driving model of 2 simulation

In driving procedure, first determining of tracing point be driver's decision behavior, and what arrange rearward this decision behavior must be to make its benefited target.A lot of drivers target when selecting track is single clear and definite, but also there are some drivers between a plurality of targets, to compromise, for this reason, the present invention has set up the objective function that can be described 4 kinds of typical driving behaviors (driving model), then be set forth in the method for normalizing of objective function when a plurality of targets are combined and determining of weight coefficient, thereby obtain mixed mode (last a kind).

2.1 driving traces the shortest (apart from optimization model)

" taking a short cut " is a kind of instinct performances of people under the principle of going after profit or gain is ordered about, and for the car steering on highway, copying is closely all to occur on bend, shows as track and is close to curve inner side, and formed " cutting curved " effect, as Fig. 4.According to Fig. 2 and Fig. 4, can access the shortest objective function of driving trace, as shown in the formula:

$\mathrm{Min}{f}_{01}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{P}_{\mathrm{ti}}{P}_{\mathrm{ti}+1}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{L}_{\mathrm{ti}}---\left(2\right)$

L wherein _ti=((x _pti-x _pti+1) ²+ (y _pti-y _pti+1) ²) ^0.5.

2.2 track curvature minimum (time optimal, braking is optimum, engine speed is optimum and acceleration optimization model)

For racing track operating mode, racing driver always attempts road geometrical property to use the limit, and when running into sharp turn, driver can significantly improve curved speed by track optimizing, shortens running time (time optimal).And commerial vehicle driver and a part are relatively treasured the common driver of vehicle, wish to reduce the wearing and tearing of vehicle component as far as possible, cross when curved if reduce the use that track curvature can reduce detent when curved, thereby extending the life-span (braking is optimum) of friction facing.Oversize vehicle is when excessively curved, flatting turn of vehicle body can increase extra power consumption, if therefore will maintain certain curved speed of mistake, must improve engine speed, increase the abrasion of engine components, reduced the effective rotation speed change of control engine (engine speed optimum) of track curvature.In addition, if driver selects a larger orbital radius, can reduce the curved retarded velocity of entering of curve driving, go out curved acceleration and side acceleration, can obviously improve driving comfort (acceleration is optimum).

Track curvature minimum is mainly that the orbital radius when slowing down negotiation of bends is realized, as Fig. 5.Curvature optimum is all that position is drawn close to curve inner side in song with the track under the optimum two kinds of patterns of length, but when curvature is optimum, track is all as far as possible near outer rim at bend entrance point and endpiece, tangential curve inner side just while only closing in song, and the track of length when optimum is directly tangential curve inner side entering when curved, the process of not drawing close laterally.Any tracing point P _ticorresponding curvature, the method in available Fig. 5 calculates.First, by following formula, obtain tracing point P _tithe trajectory deflection angle α of position _i:

${\mathrm{\α}}_i=\frac{L_{i-1}^2+L_i^2-L_{i-1,i}^2}{2\×L_{i-1}\×L_i}---\left(3\right)$

L _i＝((x _pti-x _pti+1) ²+(y _Pti-y _Pti+1) ²) ^0.5，

L _i-1，i＝((x _pti-1-x _pti+1) ²+(y _pti-1-y _pti+1) ²) ^0.5 (4)

Due to α _ithat track is at P _tithe deflection at place is caused, P _tithe curvature K at some place _i=d θ/dL=α _i/ L ₂therefore, the objective function of track total curvature minimum can be expressed as:

$\min f_{02}=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}{K}_i=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}\frac{{\mathrm{\α}}_i}{L_i}---\left(5\right)$

2.3 track curvature variations minimum (handling maneuver optimization model)

Within steering wheel rotation is controlled at the width of roadway of wheeled by vehicle, be the working contents of driver when driving.If can maintain motionless or few rotation of bearing circle, obviously can reduce driver workload as far as possible.The object of driver's steering wheel rotation is to adjust track curvature, therefore, the curvature of adjacent track point is changed and is controlled at minimum, and nature can reduce the demand of bearing circle angle input (handling maneuver is optimum).Before provided the computing method of any tracing point curvature, therefore, the objective function of curvature variation minimum can be expressed as:

$\min f_{03}=\underset{i=3}{\overset{n-2}{\mathrm{\Σ}}}|K_{i+1}-K_i|---\left(6\right)$

2.4 runway tracks (safe optimization model) placed in the middle

Therefore for a part of driver, safety is primary at any time, and while travelling on highway, they are ready vehicle to be controlled in the middle of runway most, can keep like this side direction safe distance of sending a car with right side curb and left side subtend simultaneously.According to Fig. 6, when vehicle travels between two parties, tracing point is positioned at the centre of road center line and right side kerb line, and while departing from this position, formula Δ w _i=0.5 (w _li-w _tri) inevitable non-vanishing, w in formula _litherefore be lane width, available following formula is as the objective function of driving mode in the middle of track:

$\min f_{04}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\left|\mathrm{\Δ}{w}_i\right|=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}|0.5w_{\mathrm{Li}}-w_{\mathrm{tri}}|---\left(7\right)$

It should be noted that, during 4 kinds of driving models, the width of roadway that driver can take can arrange voluntarily according to actual conditions before use.On the mountain highway of wagon flow rareness, can round width width of roadway; Also can get lane width and add that a side hardened verge width adds a part of subtend lane width (0.5～1m); Certainly, can be also lane width.

2.5 objective function normalization and multiple goal combined strategy

In actual driving behavior observation, driving trace during some driver's maneuver vehicle has composite character, and multiobjectives decision just in time can be described this behavior.The functional value obtaining during due to each target of execution has different dimensions, before combination, should be normalized, and makes desired value within the same order of magnitude.Use following formula to f ₀₁～f ₀₄normalization, obtains afterwards

$f_{01}^n=\frac{f_{01}}{\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{L}_{\mathrm{ci}}},f_{02}^n=\frac{f_{02}}{\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}{K}_{\mathrm{ci}}},f_{03}^n=\frac{f_{03}}{\underset{i=2}{\overset{n-2}{\mathrm{\Σ}}}|K_{\mathrm{ci}}-K_{\mathrm{ci}+1}|},f_{04}^n=\frac{f_{04}}{0.1\×N}---\left(8\right)$

L in formula _cifor the center line of road length between adjacent forward sight section, as shown in Fig. 3 above; K _cifor center line of road and forward sight section P _lip _rithe curvature of intersection location; N is forward sight section quantity.In formula, the implication of 0.1N is, driver exists the error of 0.2m left and right when judgement centre position, track, gets its intermediate value, and the total error on N forward sight section is roughly 0.1N.To the objective function after normalization, give certain weight, multi-target track optimization problem can be expressed as:

Min f ₀₅＝β ₁f′ ₀₁+β ₂f′ ₀₂+β ₃f′ ₀₃+β ₄f′ ₀₄ (9)

In formula, β ₁～β ₄>=0, be weight coefficient, need meet β ₁+ β ₂+ β ₃+ β ₄=1.

The workflow of 3 trajectory predictions

The key link one of whole track decision has four, is respectively " reconnaissance of forward sight section " strategy, typical driving behavior simulation (setting up the optimization aim function corresponding with typical driving model), constraint condition setting and derivation algorithm.Emphasis involved in the present invention is that the simulation of " reconnaissance of forward sight section " methods and strategies and typical driving behavior realizes.Fig. 7 is the prediction flow process of driving trace, and concrete step is as follows:

(1) from electronic map of automobile navigation, online transportation database, extract the geometry linear data of road, by geometry analytical Calculation, solve the planimetric coordinates of road geometrical boundary;

(2) according to driving habits, determine the spendable width of roadway of driver, set a width of roadway usage factor λ, then carry out coordinate transform, determine the planimetric coordinates that can use road breadths circle;

(3) in the region, forward sight road surface of vehicle front, divide at a certain distance forward sight section, spacing setting is referring to the content in " the 1. trajectory predictions strategy of " reconnaissance of forward sight section " ";

(4) from 5 kinds of driving models setting above, select a kind of, the optimization aim using its corresponding objective function during as iterative computation;

(5) read the current travel speed of vehicle, side acceleration parameter, there is clear in judgement the place ahead, if any barrier, calculate remaining width of roadway, according to these parameters, again in conjunction with vehicle dimension parameter, complete constraint condition setting (travel in border, obstacle keep away around 4 kinds of, bend trafficability characteristic, riding stabilities etc.);

(6) selection due to track is to carry out within the scope of driver's form, and form is with the travelling and move forward of vehicle, and therefore long mileage road is divided into some successive shorted segments.Then, adopt Optimization Solution device LINGO11.0 along travel direction iterative method, to solve the decision variable S of each shorted segment _ivalue;

(7) according to S _ivalue, by formula (1), along travel direction, calculate one by one the tracing point planimetric coordinates of each forward sight section;

(8) connect adjacent track point, obtain continuous trajectory, i.e. the driving trace that decision-making obtains, requires high occasion for display precision, can obtain level and smooth geometric locus by cubic spline interpolation.

4 calculated examples

Use technology of the present invention, carry out the traval trace emulation of Suzuka Circuit (being positioned at the F1 racing track in Ling Lu city, Mie Prefecture, Japan).For F1 racing driver, the regulation that finishes within the shortest time number of turns is its unique target, it is excessively curved at a high speed shortening the most effective means of running time, and player only has bend width is used to the limit, farthest reduce track curvature, could reduce the speed that bend causes and lose, therefore, the track curvature minimal mode in the present invention (2.2 joint) optimum is used for describing driver's this behavior.Using objective function corresponding to track curvature minimal mode as decision objective, use trajectory predictions flow process of the present invention to carry out trajectory predictions, result of calculation is (C2-C20 in figure is bend numbering) as shown in Figure 8.If often watch Formula 1, can find that the track in Fig. 8 is very consistent with the racing car track in true match, take driving trace as intermediary, can understand racing driver's driving behavior, and then to understand driver be How to choose driving trace in order to obtain maximum by radius, this can provide scientific evidence for racing driver's training, driving model and racing track design.

Should be understood that, for those of ordinary skills, can be improved according to the above description or convert, and all these improvement and conversion all should belong to the protection domain of claims of the present invention.

Claims (7)

1. the complicated road traval trace Forecasting Methodology based on the reconnaissance of forward sight section, is characterized in that, comprises the following steps:

(1) from electronic map of automobile navigation, online transportation database, extract the geometry linear data of road, by geometry analytical Calculation, solve the planimetric coordinates of road geometrical boundary;

(2) according to driving habits, determine the spendable width of roadway of driver, set a width of roadway usage factor λ, then carry out coordinate transform, determine the planimetric coordinates that can use road breadths circle;

(3) in the region, forward sight road surface of vehicle front, divide at a certain distance forward sight section, spacing is according to the trajectory predictions strategy of " reconnaissance of forward sight section " " arrange;

(4) from 5 kinds of driving models that pre-set, select a kind of, the optimization aim using its corresponding objective function during as iterative computation;

(5) read the current travel speed of vehicle, side acceleration parameter, there is clear in judgement the place ahead, if any barrier, calculate remaining width of roadway, according to these parameters again in conjunction with vehicle dimension parameter, complete constraint condition setting, described constraint condition comprise in border travel, obstacle keeps away around 4 kinds of, bend trafficability characteristic, riding stabilities;

(6) selection due to track is to carry out within the scope of driver's form, and form is with the travelling and move forward of vehicle, and therefore long mileage road is divided into some successive shorted segments; Then, adopt Optimization Solution device LINGO11.0 along travel direction iterative method, to solve the decision variable S of each shorted segment _ivalue;

(7) according to scale-up factor S _ivalue, by formula (1), along travel direction, calculate one by one the tracing point planimetric coordinates of each forward sight section;

x _pti＝x _pri+w _di·S _i·cos α _i，

y _pti＝y _pri-w _di·S _i·sin α _i (1)

α wherein _ifor forward sight section i is line segment P _lip _riwith the angle of earth coordinates X-axis, P _li, P _rirespectively the left and right sides end points of forward sight section i, candidate's tracing point P _tiat line segment P _lip _rion; x _pti, y _ptifor P _tiplanimetric coordinates; x _pri, y _prtfor P _riplanimetric coordinates;

(8) connect adjacent track point, obtain continuous trajectory, i.e. the driving trace that decision-making obtains, requires high occasion for display precision, can obtain level and smooth geometric locus by cubic spline interpolation.

2. method according to claim 1, it is characterized in that, 5 kinds of described driving models comprise the mixed mode of pattern in the shortest pattern of driving trace, track curvature minimal mode, track curvature variation minimal mode, runway track pattern placed in the middle and aforementioned four.

3. method according to claim 2, is characterized in that, described driving trace is the objective function of short pattern, as shown in the formula:

$\mathrm{Min}{f}_{01}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{P}_{\mathrm{ti}}{P}_{\mathrm{ti}+1}=\underset{i=1}{\overset{n-1}{\mathrm{\Σ}}}{L}_{\mathrm{ti}}---\left(2\right)$

L wherein _ti=((x _pti-x _pti+1) ²+ (y _pti-y _pti+1) ²) ^0.5.

4. method according to claim 2, is characterized in that, the objective function of described track curvature minimal mode is expressed as:

$\min f_{02}=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}{K}_i=\underset{i=2}{\overset{n-1}{\mathrm{\Σ}}}\frac{{\mathrm{\α}}_i}{L_i}---\left(5\right);$

Trajectory deflection angle

l _i=((x _pti-x _pti+1) ²+ (y _pti-y _pti+1) ²) ^0.5.

5. method according to claim 2, is characterized in that, the objective function of described track curvature variation minimal mode is expressed as:

$\min f_{03}=\underset{i=3}{\overset{n-2}{\mathrm{\Σ}}}|K_{i+1}-K_i|---\left(6\right)$

Point P _tithe curvature at place is K _i.

6. method according to claim 2, is characterized in that, the objective function of described runway track pattern placed in the middle is:

$\min f_{04}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\left|\mathrm{\Δ}{w}_i\right|=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}|0.5w_{\mathrm{Li}}-w_{\mathrm{tri}}|---\left(7\right)$

W _trifor tracing point P _tiwith forward sight section right side end points P _ribetween distance, w _liit is lane width.

7. method according to claim 2, is characterized in that, described mixed mode objective function is expressed as:

Minf ₀₅＝β ₁f′ ₀₁+β ₂f′ ₀₂+β ₃f′ ₀₃+β ₄f′ ₀₄ (9)

In formula, β 1～β 4 >=0, is weight coefficient, need meet β 1+ β 2+ β 3+ β 4=1.

Images