CN117901881A - Vehicle speed planning method, device, computer equipment and storage medium - Google Patents
Vehicle speed planning method, device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a vehicle speed planning method, a vehicle speed planning device, computer equipment and a storage medium, wherein the method comprises the steps of obtaining vehicle road information; determining a traffic strategy of an intersection constrained by the signal lamp according to the vehicle-road information; determining constraint conditions for passing through the intersection according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps; and planning a speed sequence to be selected of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimum cost to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimum cost is at least the cost related to the energy consumption of the vehicle. The method can solve the problem of high energy consumption of the road section of the vehicle passing through the signal intersection in the prior art.
Description
Technical Field
The present application relates to the field of vehicle control technologies, and in particular, to a vehicle speed planning method, apparatus, computer device, and storage medium.
Background
Under the urban road signal intersection scene, because the signal lamp has a periodical blocking effect on traffic flow, the situation of rapid acceleration, rapid deceleration and idling of the vehicle can occur in the running process, and extra energy consumption is caused.
In the current automobile speed planning method, the blocking effect existing in the signalized intersection area is not considered, so that the energy consumption is higher when the automobile runs.
Disclosure of Invention
Based on the method, the device, the computer equipment and the storage medium for planning the vehicle speed are provided, and the problem that the energy consumption of the road section of the vehicle passing through the signal intersection is high in the prior art is solved.
In one aspect, a vehicle speed planning method is provided, including:
Obtaining vehicle road information, wherein the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
Determining a traffic strategy of an intersection constrained by the signal lamp according to the vehicle-road information;
Determining constraint conditions for passing through the intersection according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
and planning a speed sequence to be selected of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimum cost to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimum cost is at least the cost related to the energy consumption of the vehicle.
In one embodiment, the determining a traffic policy for the intersection according to the vehicle road information includes:
Determining a first traffic strategy, wherein the first traffic strategy comprises determining that the target driving distance of a vehicle is larger than or equal to the sum of the intersection distance and the intersection width in the duration time of the traffic state when the state of the signal lamp is the traffic state and the product of the average vehicle flow speed and the duration time of the traffic state is larger than or equal to the sum of the intersection distance and the intersection width;
Otherwise, determining a second traffic policy, where the second traffic policy includes determining that the target driving distance of the vehicle is less than the intersection distance before the signal lamp state is adjusted to the traffic state next time, and the target driving distance of the vehicle is greater than or equal to the sum of the intersection distance and the intersection width after the signal lamp state is adjusted to the traffic state next time.
In one embodiment, the determining the constraint condition of passing through the intersection according to the vehicle dynamics model and the traffic policy includes:
when the traffic policy is the first traffic policy, determining constraints on the vehicle torque is:
Wherein, con TL is signal lamp constraint, m is vehicle mass, T m is vehicle torque at time T, i t is transmission ratio, eta t is motor efficiency at time T, F is resistance, T is driving time, v init is initial speed, x init is intersection distance, x gap is intersection width, and v e is speed at the end of planning.
In one embodiment, the determining the constraint condition of passing through the intersection according to the vehicle dynamics model and the traffic policy further comprises:
When the traffic policy is the second traffic policy, determining constraints on the vehicle torque is:
wherein tgs is the time length for adjusting the signal lamp state distance to the traffic state at the next time.
In one embodiment, the constraints further include a front vehicle state constraint, and the determining the constraint of passing through the intersection according to the vehicle dynamics model and the traffic policy further includes:
Determining a relative distance constraint condition according to the relative distance between the vehicle and the front vehicle;
Determining displacement constraint conditions according to the displacement of the vehicle and the front vehicle;
And determining a speed constraint condition according to the road speed requirement.
In one embodiment, the controlling the vehicle to pass through the intersection with the signal lamp according to the target speed sequence comprises:
periodically updating the target speed sequence, outputting the first speed of the target speed sequence of each period, and combining to obtain an execution speed sequence;
and controlling the vehicle to run according to the execution speed sequence.
In one embodiment, before the periodically updating the target speed sequence, the method further comprises:
Determining the impact degree of the vehicle according to the estimated vehicle displacement sequence, wherein the estimated vehicle displacement sequence is determined according to the target speed sequence;
And based on the minimum impact degree, fitting to obtain a vehicle continuous displacement value so as to obtain a smoothed target speed sequence.
In yet another aspect, a vehicle speed planning apparatus is provided, the apparatus comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring vehicle road information, and the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
the traffic strategy determining module is used for determining the traffic strategy of the intersection constrained by the signal lamp according to the vehicle-road information;
the constraint module is used for determining constraint conditions of crossing according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
And the planning module is used for planning a to-be-selected speed sequence of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimized cost so as to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimized cost is at least the cost about the energy consumption of the vehicle.
In yet another aspect, a computer apparatus is provided comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when the computer program is executed.
There is also provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method.
According to the vehicle speed planning method, the vehicle speed planning device, the computer equipment and the storage medium, the traffic strategy of the vehicle passing through the intersection with the signal lamp is planned according to the vehicle road information, so that the constraint condition of the vehicle passing through the intersection is determined, the constraint condition represents the vehicle torque limitation of the vehicle implementing the traffic strategy under the signal lamp state indication, the vehicle to-be-selected speed sequences are planned under the constraint condition, each to-be-selected speed sequence has corresponding vehicle energy consumption, the target speed sequence is determined according to the vehicle energy consumption minimization rule, and the vehicle can be controlled to pass through the intersection with the signal lamp under the condition of saving energy most according to the target speed sequence.
Drawings
FIG. 1 is a schematic illustration of an intersection constrained by signal lights in one embodiment;
FIG. 2 is a flow chart of a vehicle speed planning method in one embodiment;
FIG. 3 is an ST-chart of signal lamp constraints in one embodiment;
FIG. 4 is a schematic view of a traffic policy in one embodiment;
FIG. 5 is a schematic diagram of an alternate ST trajectory in one embodiment;
FIG. 6 is an ST view of a front truck restraint in one embodiment;
FIG. 7 is an ST diagram of a front truck and signal lamp co-restraint in one embodiment;
FIG. 8 is a schematic diagram of dynamic programming in one embodiment;
FIG. 9 is a flow diagram of dynamic programming in one embodiment;
FIG. 10 is a block diagram of a vehicle speed planner in one embodiment;
FIG. 11 is an internal block diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The signal lamp has a periodical blocking effect on traffic flow, and the situation of rapid acceleration, rapid deceleration and idling of the vehicle can occur in the running process, and extra energy consumption is caused. Poor driving habits also lead to unnecessary energy consumption, and the driver often lacks predictability resulting in sudden braking and sudden acceleration further increasing vehicle energy consumption. For urban road scenes, vehicle road communication provides technical support for vehicles to acquire accurate traffic states and traffic control, and brings great energy-saving potential for economical driving of vehicles.
The automobile can obtain the running conditions of the automobile and surrounding vehicles in the network environment, and can also receive road condition information and the like from road side equipment, so that a reasonable speed curve can be planned to improve the safety, energy conservation and comfort of the automobile in running. For intersections with signal lights as shown in fig. 1, the driver's lack of predictability often results in sudden braking and sudden acceleration that further increases vehicle energy consumption.
In one embodiment, the vehicle speed planning method is provided without considering the influence of other vehicles on the road and only considering the blocking effect caused by traffic lights, the strategy of passing through signal light intersections is planned in advance by using vehicle road information, constraint conditions are obtained, and the minimum energy consumption passing through is realized through a dynamic planning algorithm under the constraint conditions.
In this embodiment, the vehicle speed planning method is shown in fig. 2, and includes the following steps:
and 101, acquiring vehicle road information.
The road information may be obtained based on vehicle sensors, such as radar sensors, vision sensors, and signal lamp phase timing information is sent to the vehicle through DSRC (DEDICATED SHORT RANGE COMMUNICATIONS, dedicated short range communication technology) wireless communication technology, as in fig. 1, (TL 1,tleft) represents phase timing information of the 1 st signal lamp from the vehicle, TL is signal lamp state, tl=1 is red lamp state, tl=2 is green lamp state, tl=3 is yellow lamp state, wherein signal lamp yellow lamp phase is equivalent to green lamp phase, i.e. when signal lamp is yellow lamp, the vehicle is allowed to pass, thus green lamp state and yellow lamp state are passable, red lamp state is not passable, t left is duration of each state.
The vehicle road information also includes an initial speed v init of the own vehicle, an intersection distance x init of the own vehicle relative to an intersection, an intersection width x gap, an entire road speed limit, a distance x TL of adjacent signal lamps, an average vehicle flow speed v m, and the like.
And 102, determining a traffic strategy of the intersection constrained by the signal lamp according to the vehicle road information.
Illustratively, the current signal state is indicated at D as to whether the vehicle can pass through the intersection at the average traffic speed, if so, d=1, otherwise d=0:
where t gl is the remaining duration of the passable state.
It will be appreciated that the traffic policy may include the following:
Case 1: the signal lamp state tl=2 or tl=3, and d=1, when the vehicle needs to pass through the green lamp or yellow lamp in the current green lamp or yellow lamp state, namely the driving distance of the vehicle is required to be equal to or more than the intersection distance x init +the intersection width x gap;
Case 2: the signal lamp state tl=2 or tl=3, d=0, and the vehicle cannot pass in the current passable period, the vehicle is planned to pass in the next passable period, namely, before the signal lamp is adjusted to the passing state next time, the vehicle driving distance is less than the road-junction distance x init; after adjustment, the vehicle driving distance is more than or equal to the intersection distance x init +the intersection width x gap;
Case 3: signal lamp state tl=1, d=0, similar to case 2, in the red light state, it is necessary to plan the vehicle to pass in the time period when the signal lamp changes to the green light again, i.e. when the signal lamp is red light, the vehicle driving distance is less than the road-to-road distance x init; after the traffic light is changed into the green light, the driving distance of the vehicle is equal to or more than the intersection distance x init +the intersection width x gap.
And step 103, determining constraint conditions of crossing according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps.
In the scene of an intersection, the constraint of the signal lamp can be equivalent to an obstacle whose displacement state is unchanged from the starting point in the ST graph, as shown in fig. 3. The vehicles can pass through the traffic lights in the green light and yellow light states, and the green light and yellow light duration is a feasible area for the speed planning interval. In the red light state, the vehicle is prohibited from passing through the intersection. During this time, the signal light corresponds to an obstacle. Therefore, the timing information and the position information of the red light and the yellow light of the signal lamp are mainly converted into boundary constraint and added to the local path planning problem, the horizontal solid line part in fig. 3a is a red light period, the horizontal dotted line part is a green light period and a yellow light period, and p 1-p4 in fig. 3b is four vertexes of a non-feasible region. In the speed planning process, considering the constraint condition of the red light, firstly, the signal lamp state TL and the residual duration of the current passing intersection are determined. And determining the red light signal infeasible area in the ST diagram through the current vehicle-to-intersection distance x init, the planning duration t pla and the planning distance x pla. The signal lamp displacement is unchanged in the red light duration, so that the infeasible area is rectangular.
The ST map can project an obstacle to a two-dimensional plane, reflecting the relationship between vehicle displacement and time. Since only the longitudinal displacement is considered in this embodiment, the ST map can directly reflect the travel displacement trajectory of the vehicle.
In the ST diagram, an ST track which is not overlapped with the obstacle area is planned in an iteration mode, the vehicle obtains speed-time data according to displacement-time data indicated by the ST track, and traffic of intersections constrained by the signal lamps can be completed, but the vehicle can travel on the basis of different ST tracks with huge difference in energy consumption.
Specifically, the embodiment uses the motor energy consumption consumed in the process of the vehicle passing through the intersection as an objective function, and simultaneously combines longitudinal dynamics equation constraint, road speed limit, vehicle performance limit, initial condition and signal lamp constraint to establish the optimal planning problem of economic running of the vehicle. The establishment process based on the optimization method is described from an objective function, constraint conditions and intersection traffic strategies respectively, and the energy consumption of the motor is used as the objective function:
Wherein E m is the energy consumed in the Δt time period, P m is the motor power, eta m is the working efficiency of the motor at the moment i when the torque is T m and the rotating speed is n m, P m is more than or equal to 0 and is the power when the motor is driven, and P m is less than 0 and is the power when the motor is recovered.
The energy consumption objective function can be a torque objective function based on the relation between the energy consumption, the torque and the rotating speed, and an optimal torque sequence with minimum energy consumption can be obtainedThe discrete form of the objective function is:
Illustratively, the relationship between tire size, gear ratio i t, vehicle speed v, motor speed n m: n m＝30vit/pi r.
The different states and the remaining time lengths of the signal lamps are used for restraining the displacement of the vehicle running, as in the three cases, the displacement of the vehicle running can be determined through a vehicle dynamics equation based on the torque, and in particular,
In case 1 above, the traffic light state tl=2 or tl=3, and d=1, then:
Wherein, con TL represents signal lamp constraint, m is vehicle mass, F is resistance, and in the vehicle dynamics equation, the resistance is divided into rolling resistance, air resistance, gradient resistance and acceleration resistance. v e program the speed at the end.
In the mathematical expression of signal lamp constraint, the integral part is the vehicle driving distance in the planning time, and the speed at the end is defined to be consistent with the initial speed.
In case 2 above, the traffic light state tl=2 or tl=3, d=0, then:
t gs is the time length for the signal lamp state distance to be adjusted to the traffic state next time, namely the time length for the signal lamp to be changed to the green lamp next time, and the constraint indicates that before the signal lamp is turned on, the displacement of the automobile is required to be before a stop line; when the signal lamp is green, the vehicle passes through the intersection in the time period, and the running accumulated displacement is larger than x init+xgap.
In case 3 above, the traffic light state tl=1, d=0, then similar to case 2:
When the signal lamp is in a red light state, the displacement of the vehicle when the vehicle runs is smaller than the position of the parking line within the residual time of the red light (namely, the starting time of the green light); when the signal lamp turns green, the vehicle passes through the intersection during the period of time, and the displacement of the traveling should be greater than the position of the intersection.
Under the different traffic strategies, corresponding constraint conditions are adopted.
The essence of the design of the signal light constraints con TL for vehicles to pass through each intersection is that the vehicles pass through the intersection during the pass period. At a time before the signal lamp turns green, the vehicle travel displacement should be not more than the stop line to be passed through the intersection; in the green and yellow time periods, the vehicle travel displacement should be greater than the sum of the distance from the intersection to be passed and the width of the intersection.
In one embodiment, for the traffic policy of successive intersections, the traffic decision flow is shown in fig. 4.
In fig. 4, the current signal lamp state tl=j and the current state remaining time period t j are obtained through vehicle-to-road communication, and whether the current signal lamp is a red lamp is determined; if the vehicle is a red light, the green light starting time t gr_str(j) is the residual duration of the red light, and the planned vehicle meets the constraint condition of fas TL and passes in the green light time period; if the traffic light is a green light or a yellow light, further judging whether the current green light or the yellow light can pass within the maximum speed limit of the road or pass under the average traffic flow speed, namely passing the shortest time t min of the signal intersection; otherwise, the traffic light passes in the green light time period of the next green light lighting time t gr_str(j)＝tj+tyellow+tred.
In further embodiments, limiting to motor torque capacity and intersection speed limit, further determining the constraint further comprises:
Tmin≤Tm≤Tmax
(ΔTm)min＜ΔTm＜(ΔTm)max
vmin≤v≤vmax
amin≤a≤amax
Wherein T min、Tmax is the minimum and maximum torque provided by the motor, (delta T m)min、(ΔTm)max is the minimum and maximum of the motor torque increment amplitude, v min、vmax is the minimum and maximum vehicle speed limited, and a min、amax is the limited range of the acceleration a.
Step 104, planning a candidate speed sequence of the vehicle based on the constraint condition, and determining a target speed sequence according to a minimum cost, wherein the minimum cost is at least a cost related to the energy consumption of the vehicle.
In the ST graph, there is one or even a plurality of ST trajectories satisfying the constraint conditions, as in fig. 5, when the vehicle controls the running speed based on the ST trajectories, the parameters related to energy consumption such as torque, vehicle speed and the like at each moment are determined values, so that the energy consumption corresponding to each trajectory can be obtained, and the ST trajectories satisfying the energy consumption objective function are selected to guide the vehicle to run, thereby saving the intersections where the vehicle is constrained by the signal lamps.
In one embodiment, a vehicle speed planning method of simultaneously restraining a front vehicle and restraining a signal lamp is further provided, a main vehicle is set as a planned coordinate origin, the front vehicle can be expressed as an obstacle which can linearly travel at a constant speed in one planning duration, and position information and speed information of the front vehicle are converted into boundary constraints and added to a local path planning optimization problem, as shown in fig. 6.
In fig. 6, a hatched portion is a tabu search region, and x 1、x2、x3、x4 is four vertexes of the tabu search region. The host vehicle does not exceed the preceding vehicle in the same lane, and is not available for the search area in front of the preceding vehicle, and is therefore a tabu search area. The initial position of the front vehicle relative to the vehicle is x rel, the final position is determined according to each planning time and displacement, and the average time t un＝(xpla-xrel)/vp0 required in the remaining planning displacement x pla is calculated by using the initial speed v p0 of the front vehicle.
According to the rolling-based dynamic programming speed planning method, the ST diagram of the vehicle is discretized, and meanwhile, the ST diagrams of the signal lamp and the front vehicle are considered. Fig. 7 is a discrete schematic diagram, where t pla is a speed planning time and s pla is a planning displacement. The shaded portion in the figure represents a tabu search region. Dynamic planning requires determining whether discrete points are within the region during planning. If the discrete point is within the area, the discrete point state quantity is not calculated, thereby reducing the planning calculation quantity.
In the speed planning process for a vehicle passing through an intersection, the speed profile of each stage is continuously changed and the current displacement and the vehicle speed are not affected by the previous stage, so the displacement s (k) and the speed v (k) of the vehicle are selected as state variables. Meanwhile, in order to ensure the comfort of passing through the intersection, the acceleration a (k) and the impact degree j (k) are also used as state variables, and the state quantity of each discrete point is dynamically planned to be expressed as:
sk＝[s(k),v(k),a(k),j(k)]
When solving the optimal path, the dynamic programming traverses each stage from the initial stage, then traverses each state of each stage, and simultaneously calculates a cost function in the state of the stage, wherein the state transfer function is as follows:
The cost value from t (0) to t (k+1) is the sum of the optimal cost value from t (0) to t (k) and the state transition cost value from t (k) to t (k+1). And traversing the cost value of each state in the k-1 stages, selecting an optimal value, and obtaining an optimal path through reverse optimization. In the ST graph, each discrete point meets the following conditions:
consTL
Tmin≤Tm≤Tmax
(ΔTm)min＜ΔTm＜(ΔTm)max
vmin≤v≤vmax
amin≤a≤amax
0≤s(i)≤s(i+1)
sh(i)≤sp(i)
xsaft≤xrel≤xrel_max
adding constraint conditions influenced by the front vehicle in the constraint conditions, wherein s p (i) is the displacement of the front vehicle, and the vehicle does not consider overtaking, so that the displacement s h (i) of the vehicle is smaller than the displacement of the front vehicle; the relative distance is constrained in view of the safety of driving, i.e., the relative distance is greater than the safety distance x saft. However, too far a relative distance would reduce the traffic efficiency, and the upper limit x rel_max should be limited, and at the same time, the vehicle is prohibited from running backwards, and the vehicle running displacement is 0.ltoreq.s (i). Ltoreq.s (i+1).
In this embodiment, the ST graph speed curve dynamic programming cost function is defined as:
Wherein ω a、ωj、ωacc、ωm is a vehicle acceleration coefficient, an impact coefficient, an acceleration passing intersection weight and a motor energy consumption coefficient, and P 4y is a numerical value of a coordinate P 4 in the signal lamp ST diagram on the S axis.
In the speed planning process of the vehicle passing through the continuous intersection, a dynamic planning method is adopted to continuously roll and update the planning result in a time domain, so that the optimal performance of the planning vehicle speed is ensured, and the principle is shown in fig. 8. The update time interval is defined as Δr=1, i.e. the planning result is updated every 1 s. The time of single planning is 23s, and the planning distance is 80m. The distance of the whole course is defined as L, which is an accumulated quantity, and the planned intersection distance is a final value. According to the displacement length Li of each update, the subscript i represents the planned distance of the ith update, and the problem in the ith update can be discretized into N k steps according to the distance domain of dynamic planning.
And selecting the first speed (namely the first speed) of the target speed sequence output by adopting the dynamic programming method at the ith moment as the current execution speed. The optimal state quantity of each stage is solved in turn, and fig. 9 depicts a dynamic programming speed solving flow based on scrolling, which comprises a speed solving part and a scrolling part.
In fig. 9, when the solution is performed by the dynamic programming method, the programming result is updated every 1s, and the first speed of the current programmed speed sequence is selected as the execution speed. The time of single planning is 23s, and the planning distance is 80m. Forward calculation and reverse deduction are carried out, the target (cost) function at each moment is calculated according to a state transfer equation through time and distance dispersion, and MATLAB is used for solving.
In the embodiment, the planning result is updated every 1s, each time, two adjacent discrete points are connected and smoothed by adopting a method of polynomial fitting of five times, and in vehicle motion planning, comfort is a very important index, and the more gradual the impact jerk is, the more comfortable the impact is.
In the ST graph, the optimal vehicle displacement sequence estimated by each planning is represented by a vehicle displacement track s=f (t), and the optimal vehicle displacement sequence corresponds to the target speed sequence which is suboptimal, so that the impact degree is highIf jerk is small in absolute value during the time of the [0, t ] interval, then the trajectory between two discrete points is more comfortable, so the smooth objective function is:
According to a fifth order polynomial fitting method, the fifth order polynomial expression which satisfies the optimum objective function is:
Knowing the vehicle start point position s (0) =s 0, speed Acceleration/>End position s (T), end speed/>Endpoint acceleration/>The vehicle continuous displacement curve is solved so that the discrete velocity sequences are smoothly connected.
The embodiment adopts a dynamic programming method based on rolling, updates programming conditions in real time and improves programming precision.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
In one embodiment, as shown in fig. 10, there is provided a vehicle speed planning apparatus including: an acquisition module 201, a traffic policy determination module 202, a constraint module 203 and a planning module 204, wherein:
The acquisition module 201 is configured to acquire vehicle road information, where the vehicle road information includes at least an initial speed of a vehicle, an intersection distance of the vehicle relative to an intersection, an intersection width, a signal lamp state of the intersection, a state duration of the signal lamp, and an average vehicle flow speed;
A traffic policy determining module 202, configured to determine a traffic policy of an intersection for signal lamp constraint according to the vehicle road information;
A constraint module 203, configured to determine constraint conditions for passing through an intersection according to a vehicle dynamics model and the traffic policy, where the constraint conditions at least include a vehicle torque condition constrained by a signal lamp;
A planning module 204, configured to plan a candidate speed sequence of the vehicle based on the constraint condition, and determine a target speed sequence according to a minimum cost, so as to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, where the minimum cost is at least a cost related to energy consumption of the vehicle.
In one embodiment, the traffic policy determining module 202 determines whether to adopt the first traffic policy or the second traffic policy based on the vehicle road information, and when the signal lamp state is the traffic state and the product of the average vehicle flow speed and the duration of the passable state is greater than or equal to the sum of the intersection distance and the intersection width, determines to adopt the first traffic policy, that is, plan to be within the duration of the passable state, the target driving distance of the vehicle is greater than or equal to the sum of the intersection distance and the intersection width;
Otherwise, a second traffic strategy is adopted, namely planning that the target running distance of the vehicle is smaller than the intersection distance before the signal lamp state is adjusted to the traffic state next time, and the target running distance of the vehicle is larger than or equal to the sum of the intersection distance and the intersection width after the signal lamp state is adjusted to the traffic state next time.
In one embodiment, the constraint module 203 determines the constraint based on the determined traffic policy, and when the traffic policy is the first traffic policy, determines the constraint as to the vehicle torque as:
Wherein, con TL is signal lamp constraint, m is vehicle mass, T m is vehicle torque at time T, i t is transmission ratio, eta t is motor efficiency at time T, F is resistance, T is driving time, v init is initial speed, x init is intersection distance, x gap is intersection width, and v e is speed at the end of planning.
When the traffic policy is the second traffic policy, determining constraints on the vehicle torque is:
Wherein t gs is the time length for adjusting the signal lamp state distance to the traffic state at the next time.
In one embodiment, the obtaining module 201 is further configured to obtain a front vehicle state, including a relative distance between the host vehicle and the front vehicle, a vehicle position and a front vehicle displacement, a road speed requirement, and the like, and the constraint module 203 is further configured to determine a relative distance constraint condition according to the relative distance between the host vehicle and the front vehicle; determining displacement constraint conditions according to the displacement of the vehicle and the front vehicle; and determining a speed constraint condition according to the road speed requirement.
The planning module 204 updates the target speed sequence periodically, outputs the first speed of the target speed sequence of each period, and combines the first speed and the first speed to obtain an execution speed sequence; and controlling the vehicle to run according to the execution speed sequence.
In one embodiment, before periodically updating the target speed sequence, the planning module 204 further determines the impact of the vehicle according to a predicted vehicle displacement sequence, wherein the predicted vehicle displacement sequence is determined according to the target speed sequence; and based on the minimum impact degree, fitting to obtain a vehicle continuous displacement value so as to obtain a smoothed target speed sequence.
According to the vehicle speed planning device, the traffic strategy of the vehicle passing through the intersection with the signal lamp is planned according to the vehicle road information, so that the constraint condition of the vehicle passing through the intersection is determined, the constraint condition indicates the vehicle torque limitation of the vehicle implementing the traffic strategy under the signal lamp state indication, the speed sequence to be selected of the vehicle is planned under the constraint condition, each speed sequence to be selected has corresponding vehicle energy consumption, the target speed sequence is determined according to the vehicle energy consumption minimization rule, and the vehicle can be controlled to pass through the intersection with the signal lamp under the condition of saving the most energy according to the target speed sequence.
For specific limitations on the vehicle speed planning apparatus, reference may be made to the above limitations on the vehicle speed planning method, and no further description is given here. The various modules in the vehicle speed planning apparatus described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 11. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a vehicle speed planning method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 11 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
Obtaining vehicle road information, wherein the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
Determining a traffic strategy of an intersection constrained by the signal lamp according to the vehicle-road information;
Determining constraint conditions for passing through the intersection according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
and planning a speed sequence to be selected of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimum cost to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimum cost is at least the cost related to the energy consumption of the vehicle.
In one embodiment, the processor when executing the computer program further performs the steps of:
Determining a first traffic strategy, wherein the first traffic strategy comprises determining that the target driving distance of a vehicle is larger than or equal to the sum of the intersection distance and the intersection width in the duration time of the traffic state when the state of the signal lamp is the traffic state and the product of the average vehicle flow speed and the duration time of the traffic state is larger than or equal to the sum of the intersection distance and the intersection width;
Otherwise, determining a second traffic policy, where the second traffic policy includes determining that the target driving distance of the vehicle is less than the intersection distance before the signal lamp state is adjusted to the traffic state next time, and the target driving distance of the vehicle is greater than or equal to the sum of the intersection distance and the intersection width after the signal lamp state is adjusted to the traffic state next time.
In one embodiment, the processor when executing the computer program further performs the steps of:
when the traffic policy is the first traffic policy, determining constraints on the vehicle torque is:
Wherein, con TL is signal lamp constraint, m is vehicle mass, T m is vehicle torque at time T, i t is transmission ratio, eta t is motor efficiency at time T, F is resistance, T is driving time, v init is initial speed, x init is intersection distance, x gap is intersection width, and v e is speed at the end of planning.
In one embodiment, the processor when executing the computer program further performs the steps of:
When the traffic policy is the second traffic policy, determining constraints on the vehicle torque is:
Wherein t gs is the time length for adjusting the signal lamp state distance to the traffic state at the next time.
In one embodiment, the processor when executing the computer program further performs the steps of:
Determining a relative distance constraint condition according to the relative distance between the vehicle and the front vehicle;
Determining displacement constraint conditions according to the displacement of the vehicle and the front vehicle;
And determining a speed constraint condition according to the road speed requirement.
In one embodiment, the processor when executing the computer program further performs the steps of:
periodically updating the target speed sequence, outputting the first speed of the target speed sequence of each period, and combining to obtain an execution speed sequence;
and controlling the vehicle to run according to the execution speed sequence.
In one embodiment, the processor when executing the computer program further performs the steps of:
Determining the impact degree of the vehicle according to the estimated vehicle displacement sequence, wherein the estimated vehicle displacement sequence is determined according to the target speed sequence;
And based on the minimum impact degree, fitting to obtain a vehicle continuous displacement value so as to obtain a smoothed target speed sequence.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Obtaining vehicle road information, wherein the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
Determining a traffic strategy of an intersection constrained by the signal lamp according to the vehicle-road information;
Determining constraint conditions for passing through the intersection according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
and planning a speed sequence to be selected of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimum cost to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimum cost is at least the cost related to the energy consumption of the vehicle.
In one embodiment, the computer program when executed by the processor further performs the steps of:
Determining a first traffic strategy, wherein the first traffic strategy comprises determining that the target driving distance of a vehicle is larger than or equal to the sum of the intersection distance and the intersection width in the duration time of the traffic state when the state of the signal lamp is the traffic state and the product of the average vehicle flow speed and the duration time of the traffic state is larger than or equal to the sum of the intersection distance and the intersection width;
Otherwise, determining a second traffic policy, where the second traffic policy includes determining that the target driving distance of the vehicle is less than the intersection distance before the signal lamp state is adjusted to the traffic state next time, and the target driving distance of the vehicle is greater than or equal to the sum of the intersection distance and the intersection width after the signal lamp state is adjusted to the traffic state next time.
In one embodiment, the computer program when executed by the processor further performs the steps of:
when the traffic policy is the first traffic policy, determining constraints on the vehicle torque is:
Wherein, con TL is signal lamp constraint, m is vehicle mass, T m is vehicle torque at time T, i t is transmission ratio, eta t is motor efficiency at time T, F is resistance, T is driving time, v init is initial speed, x init is intersection distance, x gap is intersection width, and v e is speed at the end of planning.
When the traffic policy is the second traffic policy, determining constraints on the vehicle torque is:
Wherein t gs is the time length for adjusting the signal lamp state distance to the traffic state at the next time.
In one embodiment, the computer program when executed by the processor further performs the steps of:
Determining a relative distance constraint condition according to the relative distance between the vehicle and the front vehicle;
Determining displacement constraint conditions according to the displacement of the vehicle and the front vehicle;
And determining a speed constraint condition according to the road speed requirement.
In one embodiment, the computer program when executed by the processor further performs the steps of:
periodically updating the target speed sequence, outputting the first speed of the target speed sequence of each period, and combining to obtain an execution speed sequence;
and controlling the vehicle to run according to the execution speed sequence.
Before the periodically updating the target speed sequence, the method further comprises:
Determining the impact degree of the vehicle according to the estimated vehicle displacement sequence, wherein the estimated vehicle displacement sequence is determined according to the target speed sequence;
And based on the minimum impact degree, fitting to obtain a vehicle continuous displacement value so as to obtain a smoothed target speed sequence.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A vehicle speed planning method, characterized by comprising:
Obtaining vehicle road information, wherein the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
Determining a traffic strategy of an intersection constrained by the signal lamp according to the vehicle-road information;
Determining constraint conditions for passing through the intersection according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
and planning a speed sequence to be selected of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimum cost to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimum cost is at least the cost related to the energy consumption of the vehicle.
2. The vehicle speed planning method according to claim 1, wherein the determining a traffic policy for an intersection from the road information includes:
Determining a first traffic strategy, wherein the first traffic strategy comprises determining that the target driving distance of a vehicle is larger than or equal to the sum of the intersection distance and the intersection width in the duration time of the traffic state when the state of the signal lamp is the traffic state and the product of the average vehicle flow speed and the duration time of the traffic state is larger than or equal to the sum of the intersection distance and the intersection width;
Otherwise, determining a second traffic policy, where the second traffic policy includes determining that the target driving distance of the vehicle is less than the intersection distance before the signal lamp state is adjusted to the traffic state next time, and the target driving distance of the vehicle is greater than or equal to the sum of the intersection distance and the intersection width after the signal lamp state is adjusted to the traffic state next time.
3. The vehicle speed planning method according to claim 2, wherein the determining the constraint condition of passing through the intersection according to the vehicle dynamics model and the traffic policy includes:
when the traffic policy is the first traffic policy, determining constraints on the vehicle torque is:
Wherein, con TL is signal lamp constraint, m is vehicle mass, T m is vehicle torque at time T, i t is transmission ratio, eta t is motor efficiency at time T, F is resistance, T is driving time, v init is initial speed, x init is intersection distance, x gap is intersection width, and v e is speed at the end of planning.
4. The vehicle speed planning method according to claim 2, wherein the determining constraint conditions for passing through an intersection according to a vehicle dynamics model and the traffic policy further comprises:
When the traffic policy is the second traffic policy, determining constraints on the vehicle torque is:
wherein tgs is the time length for adjusting the signal lamp state distance to the traffic state at the next time.
5. The vehicle speed planning method according to any one of claims 1-4, wherein the constraints further include a front vehicle state constraint, the determining a constraint of passing through an intersection according to a vehicle dynamics model and the traffic policy further includes:
Determining a relative distance constraint condition according to the relative distance between the vehicle and the front vehicle;
Determining displacement constraint conditions according to the displacement of the vehicle and the front vehicle;
And determining a speed constraint condition according to the road speed requirement.
6. The vehicle speed planning method according to claim 5, wherein the controlling the vehicle to pass through the intersection with the signal lamp according to the target speed sequence comprises:
periodically updating the target speed sequence, outputting the first speed of the target speed sequence of each period, and combining to obtain an execution speed sequence;
and controlling the vehicle to run according to the execution speed sequence.
7. The vehicle speed planning method of claim 6, wherein before periodically updating the target speed sequence, further comprising:
Determining the impact degree of the vehicle according to the estimated vehicle displacement sequence, wherein the estimated vehicle displacement sequence is determined according to the target speed sequence;
And based on the minimum impact degree, fitting to obtain a vehicle continuous displacement value so as to obtain a smoothed target speed sequence.
8. A vehicle speed planning apparatus, characterized in that the apparatus comprises:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring vehicle road information, and the vehicle road information at least comprises the initial speed of a vehicle, the intersection distance of the vehicle relative to an intersection, the intersection width, the signal lamp state of the intersection, the state duration time of the signal lamp and the average vehicle flow speed;
the traffic strategy determining module is used for determining the traffic strategy of the intersection constrained by the signal lamp according to the vehicle-road information;
the constraint module is used for determining constraint conditions of crossing according to the vehicle dynamics model and the traffic strategy, wherein the constraint conditions at least comprise vehicle torque conditions constrained by signal lamps;
And the planning module is used for planning a to-be-selected speed sequence of the vehicle based on the constraint condition, and determining a target speed sequence according to the minimized cost so as to control the vehicle to pass through the intersection with the signal lamp according to the target speed sequence, wherein the minimized cost is at least the cost about the energy consumption of the vehicle.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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| CN113359719A (en) * | 2021-05-28 | 2021-09-07 | 江苏大学 | Economic speed planning system and method for ACC vehicle to continuously pass through multiple intersections |
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