WO2019037662A1 - 行驶速度控制方法、装置、计算机设备和存储介质 - Google Patents

行驶速度控制方法、装置、计算机设备和存储介质 Download PDF

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WO2019037662A1
WO2019037662A1 PCT/CN2018/101038 CN2018101038W WO2019037662A1 WO 2019037662 A1 WO2019037662 A1 WO 2019037662A1 CN 2018101038 W CN2018101038 W CN 2018101038W WO 2019037662 A1 WO2019037662 A1 WO 2019037662A1
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curvature
target
sampling
current
point
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PCT/CN2018/101038
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English (en)
French (fr)
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王斌
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腾讯科技（深圳）有限公司
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Priority to JP2020510587A priority Critical patent/JP6906690B2/ja
Priority to EP18847584.2A priority patent/EP3604069B1/en
Priority to KR1020197031001A priority patent/KR102282753B1/ko
Publication of WO2019037662A1 publication Critical patent/WO2019037662A1/zh
Priority to US16/558,057 priority patent/US11318942B2/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14—Adaptive cruise control
    • B60W30/143—Speed control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K31/00—Vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18145—Cornering
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/072—Curvature of the road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B60W2050/005—Sampling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/20—Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/30—Road curve radius
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2720/00—Output or target parameters relating to overall vehicle dynamics
    • B60W2720/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2720/00—Output or target parameters relating to overall vehicle dynamics
    • B60W2720/10—Longitudinal speed
    • B60W2720/103—Speed profile
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2720/00—Output or target parameters relating to overall vehicle dynamics
    • B60W2720/10—Longitudinal speed
    • B60W2720/106—Longitudinal acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Y—INDEXING SCHEME RELATING TO ASPECTS CROSS-CUTTING VEHICLE TECHNOLOGY
    • B60Y2300/00—Purposes or special features of road vehicle drive control systems
    • B60Y2300/14—Cruise control
    • B60Y2300/143—Speed control

Definitions

  • the present application relates to the field of driving control technologies, and in particular, to a driving speed control method, apparatus, computer device, and storage medium.
  • the curve is segmented, and the speed limit value is calculated in advance for each segment and recorded on the map.
  • the speed limit of the segment record on the map is queried. In this way, it is easy to cause obvious acceleration or deceleration at the boundary of the two speed limits, resulting in a sudden change in speed. For example, if the speed limit of this section is 100, the next section is relatively curved, and the speed limit is 60, a sudden change in speed will occur at the boundary between the two sections.
  • the application example provides a driving speed control method, and the method includes:
  • the traveling speed is controlled according to the speed limit.
  • the application example also provides a driving speed control device, the device comprising:
  • a sampling interval determining module for determining a sampling interval that matches a current traveling speed
  • a sampling point selection module configured to select a sampling point on the expected driving route according to the sampling interval from the current position
  • a target curvature determining module configured to determine a target curvature according to a curvature of the expected driving route at each of the sampling points;
  • a speed limit determining module configured to determine a speed limit on the expected driving route according to the target curvature
  • a travel speed control module is configured to control the travel speed according to the speed limit.
  • the application examples also provide a computer device comprising a memory and a processor, the memory storing a computer program, the computer program being executed by the processor, causing the processor to perform the method.
  • the present application examples also provide a storage medium storing a computer program that, when executed by one or more processors, causes one or more processors to perform the methods described above.
  • FIG. 1A is a schematic structural diagram of a system involved in some examples of the present application.
  • FIG. 1B is a schematic structural diagram of a system involved in another example of the present application.
  • 1C is a schematic flow chart of a driving speed control method in an example of the present application.
  • FIG. 2 is a schematic flow chart of a step of determining a curvature of a sampling point in an example of the present application
  • FIG. 3 is a schematic diagram of curvature calculation in an example of the present application.
  • FIG. 4 is a schematic flow chart of a step of obtaining a target curvature in an example of the present application
  • FIG. 5 is a schematic flowchart of a historical reference curvature obtaining step in an example of the present application.
  • FIG. 6 is a schematic flow chart of a target curvature generating step in an example of the present application.
  • FIG. 7 is a schematic flow chart of a driving speed control method in another example of the present application.
  • Figure 8 is a block diagram of a travel speed control device in an example of the present application.
  • Figure 9 is a block diagram of a travel speed control device in another example of the present application.
  • FIG. 10 is a schematic diagram showing the internal structure of a computer device in an example of the present application.
  • the present application proposes a travel speed control method that can be applied to the system architecture as shown in FIGS. 1A and 1B.
  • the system architecture includes: a vehicle 101 and a computing device 102, wherein the computer device 102 can be a terminal or a server, and when the computing device 102 is a terminal, the computing device 102 can be located in the vehicle 101, wherein The computing device 102 can be integrated into the vehicle 101, such as the operating system of the vehicle 101 itself, or it can be a device independent of the vehicle 101.
  • vehicle 101 and computing device 102 can be connected through network 103, as shown in FIG. 1B.
  • the computing device 102 can determine a sampling interval that matches the current traveling speed; from the current position, select sampling points on the expected driving route according to the sampling interval; Determining the curvature of the expected travel route at each of the sampling points, determining a target curvature; determining a speed limit on the expected travel route according to the target curvature; controlling the travel speed of the vehicle 101 according to the speed limit, The safe driving of the vehicle 101 is ensured.
  • FIG. 1C is a schematic flow chart of a driving speed control method in an example of the present application. This example is mainly illustrated by the application of the driving speed control method to a computer device, which may be a terminal or a server. Referring to FIG. 1C, the method specifically includes the following steps:
  • the sampling interval matching the current driving speed indicates that the current driving speed affects the sampling interval.
  • the sampling interval is positively correlated with the current travel speed. Specifically, the larger the current traveling speed, the larger the sampling pitch; the smaller the current traveling speed, the smaller the sampling pitch.
  • step S102 includes: obtaining a current travel speed and a preset duration; determining a sampling interval according to a product of a current travel speed and a preset duration.
  • the computer device can directly use the product of the current travel speed and the preset duration as the sampling interval.
  • determining the sampling interval according to the product of the current driving speed and the preset duration includes: determining a product of the current driving speed and the preset duration; acquiring a preset sampling interval; taking the current driving speed and the preset duration. The minimum of the product and the preset sampling interval is used as the sampling interval.
  • the computer device can obtain the sampling spacing according to the following formula:
  • d is the sampling interval
  • d 0 is the preset sampling interval
  • V is the current driving speed
  • t 0 is the preset duration.
  • d 0 can be 10 m and t 0 can be 0.5 s.
  • the current driving speed V is 15m/s
  • d 0 is 10m
  • t 0 is 0.5s
  • V*t 0 7.5m
  • step S102 includes: determining a preset travel speed range interval in which the current travel speed is located, and searching for the preset travel speed according to a correspondence between the preset travel speed range interval and the sampling interval. The sampling interval corresponding to the range interval.
  • a correspondence relationship between the travel speed range section and the sampling pitch is set in advance in the computer device.
  • the computer device can determine a range of travel speed ranges in which the current travel speed is located, and according to the correspondence, find a sampling interval corresponding to the determined difference in the travel range, that is, determine a sampling interval that matches the current travel speed.
  • the corresponding sampling interval is 10 m
  • the traveling speed is in the range of 26 to 30 m/s
  • the corresponding sampling interval is 15 m
  • the traveling speed is 31 to 35 m.
  • the corresponding sampling interval is 30m. If the current driving speed is 28 m/s, the range of the range is 31 to 35 m/s, and the matched sampling pitch is 30 m.
  • S104 Select a sampling point on the expected driving route according to the sampling interval from the current position.
  • the expected driving route refers to the route that is predicted to be driven.
  • the expected travel route may be a route formed by the road ahead in the current direction of travel of the vehicle.
  • the computer device may select a preset number of sampling points on the expected driving route according to the sampling interval from the current position.
  • the preset number can be 5.
  • the computer device can also determine the number of samples that match the current travel speed. Based on the determined number of samples, the corresponding sample points are selected on the expected travel route according to the sampling interval from the current position. In one example, the number of samples is positively correlated with the current travel speed.
  • the curvature of the expected travel route at a sampling point is a value indicating a degree to which the expected travel route deviates from the tangent of the sampling point, that is, a value of the degree of bending of the expected travel route at the sampling point, and the curvature is larger, the expected travel
  • the target curvature is the curvature that is ultimately used to determine the speed limit (ie, the maximum speed) that travels on the intended route of travel.
  • the computer device may select a maximum value from the curvatures at the respective sampling points, and determine the target curvature according to the selected maximum value of the curvature.
  • the computer device can directly take the selected maximum curvature as the target curvature.
  • the computer device can also average the selected curvature maximum and the curvature at the auxiliary point, and determine the target curvature based on the curvature average.
  • the speed limit on the expected driving route refers to the maximum speed of driving on the expected driving route.
  • step S108 includes: acquiring a preset lateral force coefficient; taking an absolute value of the target curvature; dividing the product of the lateral force coefficient and the gravity acceleration by an absolute value, and then opening the square to obtain a limit on the expected driving route. speed.
  • the lateral force coefficient is used to measure the stability of the driving object when driving on the driving route.
  • the computer device can obtain a speed limit on the expected travel route according to the following formula:
  • Vmax sqrt(u*g/fabs(k A ));
  • Vmax is the speed limit on the expected driving route
  • u is the lateral force coefficient
  • g is the gravitational acceleration
  • k A is the target curvature
  • sqrt(u*g/fabs(k A )) is for u*g/fabs (k A ) performs square root calculation
  • fabs(k A ) represents the absolute value of k A .
  • the lateral force coefficient u can be 0.2.
  • the computer device can perform speed planning according to the speed limit to determine the speed of traveling on the expected driving route.
  • the sampling interval is matched with the current traveling speed, and selecting the sampling point on the expected driving route according to the sampling interval will make the sampling point more reflect the demand of the driving speed control at the current driving speed.
  • the curvature of the target determined by the curvature at the selected sampling point the bending condition of the expected driving route can be better reflected, and the curve can be found in advance, and then the speed limit is determined according to the curvature of the curve to achieve accurate control of the traveling speed. Reduced speed mutations.
  • the method further includes a sampling point curvature determining step, which specifically includes the following steps:
  • the preset reference length is smaller than the sampling interval. It can be understood that, since the two first auxiliary points are continuously selected on the expected driving route with the preset reference length from the sampling point, the arc length between the sampling point and the first first auxiliary point, and two The arc lengths between the first auxiliary points are preset reference lengths.
  • the preset reference length can be the vehicle axle length.
  • the vehicle axle length refers to the distance from the center of the front axle of the vehicle to the center of the rear axle.
  • an angle may be formed between the sampling points and the respective first auxiliary points.
  • the linear distance between the two first auxiliary points refers to the length of the line segment between the two first auxiliary points.
  • the computer device can determine the curvature at each sample point as follows:
  • K s is the curvature at the sampling point
  • ⁇ is the angle formed by the line connecting the sampling point and the corresponding first auxiliary point
  • L is the linear distance between the two first auxiliary points.
  • the preset reference length is the vehicle axle length
  • the arc length between the two first auxiliary points is approximately equal to the linear distance between the two first auxiliary points, so The vehicle shaft length is substituted as L into the above formula for calculation.
  • Figure 3 is a schematic diagram of curvature calculation in one example.
  • P1, P2, P3, and P4 are sampling points
  • points A and B are first auxiliary points corresponding to P1 on the expected traveling route w, wherein the first auxiliary point and the sampling point P1 are
  • the preset reference length is less than the sampling interval between the two sampling points
  • ⁇ is the angle formed by the connection of the sampling point P1 and the corresponding first auxiliary point A and point B.
  • two first auxiliary points are continuously selected at intervals of a preset reference length smaller than the sampling interval.
  • the curvature at each sampling point is determined by the angle formed by the line connecting the two first auxiliary points and the sampling point and the linear distance between the two first auxiliary points.
  • step S106 (referred to as the target curvature obtaining step) specifically includes the following steps:
  • the target sampling point is the sampling point with the largest curvature among the sampling points.
  • the computer device can determine the curvature at each sampling point, and select the sampling point with the largest curvature as the target sampling point.
  • S404 on the expected driving route, select a second auxiliary point before and after the target sampling point according to a preset spacing smaller than the sampling interval.
  • the preset spacing is smaller than the sampling interval. It can be understood that the arc length between the second auxiliary point and the target sampling point in front of the target sampling point, and the arc length between the second auxiliary point and the target sampling point behind the target sampling point are equal to the preset spacing.
  • the second auxiliary point in front of the target sampling point refers to the point selected from the target sampling point on the expected driving route back to the driving direction according to the preset spacing.
  • the second auxiliary point after the target sampling point refers to a point selected from the target sampling point according to the driving direction along the driving direction on the expected driving route.
  • the second auxiliary point selected before or after the target sampling point is at least one.
  • the number of second auxiliary points selected before the target sampling point and after the target sampling point may be the same. It can be understood that when there are multiple second auxiliary points selected before or after the target sampling point, the arc length between the two adjacent second auxiliary points is equal to the preset spacing.
  • the computer device can average the curvature at the target sampling point and the curvature at the second auxiliary point, and determine the target curvature based on the average obtained.
  • the computer device can sum the curvature at the target sampling point and the curvature at the second auxiliary point and divide by the number of curvatures to be summed to obtain the curvature at the target sampling point and the curvature at the second auxiliary point. average value.
  • the computer device can obtain an average of the curvature at the target sampling point and the curvature at the second auxiliary point according to the following formula:
  • K R (K F_pre +K s +K F_next )/n;
  • K R is the average of the curvature at the target sampling point and the curvature at the second auxiliary point
  • K F — pre is the curvature at the second auxiliary point in front of the target sampling point
  • K s is the curvature at the target sampling point
  • K F_next is the curvature at the second auxiliary point behind the target sampling point
  • n is the number of curvatures to be summed. In one example, when the target sample points before and after the K s are selected only one second auxiliary point, then n is 3.
  • the computer device can directly take the average of the curvature at the target sampling point and the curvature at the second auxiliary point as the target curvature.
  • the computer device may also use the average of the curvature at the target sampling point and the curvature at the second auxiliary point as the current reference curvature, and combine the historical reference curvature to obtain the target curvature.
  • the sampling point with the largest curvature is first determined, and the second auxiliary point is selected at a preset interval before and after the sampling point with the largest curvature, and the target curvature is obtained according to the curvature at the target sampling point and the curvature at the second auxiliary point.
  • the target curvature obtained by combining the curvature considerations at the two auxiliary points before and after is more stable.
  • the curvature of the driving route can be accurately reflected, and the curvature can be accurately advanced.
  • the curve is found, and then the speed limit is determined according to the curvature of the curve to achieve accurate control of the traveling speed, which reduces the sudden change of speed and reduces the interference caused by the speed planning.
  • step S406 includes: generating a current reference curvature based on an average of the curvature at the target sampling point and the curvature at the second auxiliary point; acquiring a historical reference curvature; and averaging the current reference curvature and the acquired historical reference curvature , as the target curvature.
  • the historical reference curvature is the reference curvature generated before the current reference curvature is generated. It can be understood that the reference curvature is generated each time the speed limit calculation is performed, and the historical reference curvature is the reference curvature generated when the speed limit calculation is performed before the current time.
  • the computer device can directly use the curvature at the target sampling point and the average of the curvature at the second auxiliary point as the current reference curvature.
  • the computer device can obtain all or part of the historical reference curvature.
  • the computer device may average the current reference curvature and the acquired historical reference curvature, and take the average obtained as the target curvature.
  • the current reference curvature is combined with the historical reference curvature, and the target curvature is determined by the mean of the current reference curvature and the historical reference curvature, so that the determined target curvature is more stable, compared to a single According to the limitation of the current reference curvature, it is more accurate to accurately reflect the bending of the driving route.
  • obtaining a historical reference curvature (referred to as a historical reference curvature acquisition step) specifically includes the following steps:
  • S502 Acquire a speed limit calculation frequency and a preset selection duration.
  • the speed limit calculation frequency refers to the frequency at which the speed limit calculation is performed.
  • the rate limiting calculation frequency can be consistent with the speed planning frequency.
  • the speed planning frequency refers to the frequency at which the speed planning is performed.
  • the rate limit calculation frequency can be 10 hz, that is, 10 speed limit calculations are performed in one second.
  • the preset selection duration is used to determine the selection range of the historical reference curvature.
  • the computer device may select a historical reference curvature generated within a preset selection duration before the generation time of the current reference curvature. For example, if the preset selection duration is 1 s, the computer device can select the historical reference curvature generated within 1 s before the current reference curvature generation time.
  • S504 Calculate the product of the frequency according to the speed limit and the preset selection duration to obtain the target quantity.
  • the number of targets is the number of historical reference curvatures to be selected.
  • the computer device can directly use the product of the rate-limiting calculation frequency and the preset selection duration as the target number. It can be understood that, in this example, the target number is also the number of historical reference curvatures generated within a preset selection duration before the current reference curvature generation time.
  • the speed limit calculation frequency is 10hz
  • the preset selection time is 1s
  • the computer device may select the historical reference curvature generated by the previous target number of times before the current reference curvature is generated from the historical reference curvature generated before the current reference curvature is generated. For example, if the number of targets is 10, the computer device can select the historical reference curvature generated by the previous time, the first 2 times, and the first 10 times before the current reference curvature is generated.
  • the product of the speed limit and the preset selection duration is obtained according to the speed limit, and the target number is obtained, and the historical reference curvature of the number of targets generated recently before the current reference curvature is generated is obtained.
  • the target curvature is then determined based on the mean of the historical reference curvature and the current reference curvature. It is equivalent to calculating the mean value of the reference curvature in the time dimension by calculating the frequency of the speed limit, so that the final target curvature is the mean result in the time dimension, and further improves the stability of the target curvature in the time dimension.
  • the speed limit determined according to the target curvature is more accurate, thereby avoiding a sudden change in speed.
  • S406 (referred to as a target curvature generating step) specifically includes the following steps:
  • the computer device can directly take the curvature at the target sampling point and the average of the curvature at the second auxiliary point as the current reference curvature.
  • the computer device may add the curvature at the target sampling point and the curvature at the second auxiliary point and divide by the added amount of curvature to obtain the current reference curvature.
  • the target curvature generated last time refers to the target curvature generated in the previous time, that is, the target curvature generated when the current speed limit calculation is performed.
  • S606 Perform weighted averaging on the current reference curvature and the previously generated target curvature according to the corresponding weights to generate a current target curvature.
  • the computer device can generate the current target curvature according to the following formula:
  • K A_now (1-a) * K A_pre + a * K R_now ;
  • K A_now represents the current target curvature
  • K A_pre represents the previously generated target curvature
  • K R — now represents the current reference curvature
  • a is the weight of the current reference curvature
  • a 1/H/T.
  • H the speed limit calculation frequency
  • T the preset selection duration. It can be understood that as the number of iterations increases, the influence of the historical target curvature on the generation of the current target curvature is smaller, and finally the historical target generated within the preset selection time length T is approximated. Curvature can have a substantial impact on the generation of the target curvature.
  • 1/H is the length of time corresponding to the curvature of the target. The time corresponding to the curvature of the current target can be reflected by 1/H/T.
  • the iterative calculation method by the iterative calculation method, the previously generated target curvature is taken as an input, combined with the current reference curvature, and the weighted average is performed according to the corresponding weight to generate the current target curvature. It is equivalent to combining the mean value of the target curvature in the time dimension, so that the final target curvature is the mean result in the time dimension, and further improves the stability of the target curvature in the time dimension, so that the limit determined according to the target curvature is determined.
  • the speed is more accurate, which avoids sudden changes in speed.
  • another travel speed control method comprising the following steps:
  • S702 Determine a product of a current traveling speed and a preset duration, and acquire a preset sampling interval.
  • S704 Take a product of a current driving speed and a preset duration and a minimum value of the preset sampling interval as a sampling interval.
  • S706 Select a sampling point on the expected driving route according to the sampling interval from the current position.
  • S710 Determine a curvature at the sampling point according to an angle formed by a line connecting the sampling point and each first auxiliary point, and a linear distance between the two first auxiliary points.
  • S714 on the expected driving route, select a second auxiliary point before and after the target sampling point according to a preset spacing smaller than the sampling interval.
  • S718 obtain a speed limit calculation frequency and a preset selection duration, and calculate a target quantity according to a product of the speed limit calculation frequency and the preset selection duration.
  • S722 Acquire a preset lateral force coefficient, and take an absolute value of the target curvature.
  • the driving speed is controlled according to the speed limit.
  • the sampling interval is matched with the current traveling speed, and selecting the sampling point on the expected driving route according to the sampling interval will make the sampling point more reflect the demand of the driving speed control at the current driving speed.
  • the curvature of the target determined by the curvature at the selected sampling point the bending condition of the expected driving route can be better reflected, and the curve can be found in advance, and then the speed limit is determined according to the curvature of the curve to achieve accurate control of the traveling speed. Reduced speed mutations.
  • the target curvature obtained by combining the curvature considerations at the two auxiliary points before and after is more stable, and it is more able to reflect the overall bending of the driving route than the limitation of the curvature at a single sampling point.
  • the curve can be found in advance, and the speed limit is determined according to the curvature of the curve to achieve accurate control of the traveling speed and reduce the sudden change in speed.
  • the current reference curvature is combined with the historical reference curvature, and the target curvature is determined by the mean of the current reference curvature and the historical reference curvature, so that the determined target curvature is more stable, compared to a single basis. In terms of the limitations of the current reference curvature, it is more accurate to accurately reflect the bending of the driving route.
  • the mean value of the reference curvature is calculated in the time dimension by the speed limit calculation frequency, so that the final target curvature is the mean result in the time dimension, and the stability of the target curvature is further improved in the time dimension.
  • the speed limit determined according to the target curvature is more accurate, thereby avoiding a sudden change in speed.
  • a driving speed control device 800 includes a sampling interval determining module 802, a sampling point selection module 804, a target curvature determining module 808, a speed limit determining module 810, and Travel speed control module 812, wherein:
  • the sampling interval determining module 802 is configured to determine a sampling interval that matches the current traveling speed.
  • the sampling point selection module 804 is configured to select a sampling point on the expected driving route according to the sampling interval from the current position.
  • a target curvature determining module 808, configured to determine a target curvature according to a curvature of the expected driving route at each of the sampling points;
  • the speed limit determining module 810 is configured to determine a speed limit for traveling on the expected driving route according to the target curvature.
  • the driving speed control module 812 is configured to control the traveling speed according to the speed limit.
  • the sampling interval determining module 802 is further configured to acquire a current traveling speed and a preset duration; and determine a sampling interval according to a product of the current traveling speed and the preset duration.
  • the sampling interval determining module 802 is further configured to determine a product of the current traveling speed and the preset duration; acquire a preset sampling interval; and take a product of the current driving speed and the preset duration The minimum value among the preset sampling intervals is used as the sampling interval.
  • a travel speed control device 900 comprising:
  • sampling interval determining module 902 the sampling point selecting module 904, the target curvature determining module 908, the speed limit determining module 910, and the traveling speed control module 912, wherein:
  • the sampling interval determining module 902 is configured to determine a sampling interval that matches the current traveling speed.
  • the sampling point selection module 904 is configured to select a sampling point on the expected driving route according to the sampling interval from the current position.
  • a target curvature determining module 908 configured to determine a target curvature according to a curvature of the expected driving route at each of the sampling points;
  • the speed limit determination module 910 is configured to determine a speed limit for traveling on the expected travel route according to the target curvature.
  • the driving speed control module 912 is configured to control the traveling speed according to the speed limit.
  • the sampling interval determining module 902 is further configured to acquire a current driving speed and a preset duration; and determine a sampling interval according to a product of the current driving speed and the preset duration.
  • the sampling interval determining module 902 is further configured to determine a product of the current traveling speed and the preset duration; acquire a preset sampling interval; and take a product of the current driving speed and the preset duration The minimum value among the preset sampling intervals is used as the sampling interval.
  • apparatus 900 further includes:
  • the auxiliary point selection module 905 is configured to continuously select two first auxiliary points from the sampling point on the expected driving route with a preset reference length smaller than the sampling interval as an interval for each sampling point. ;
  • a sampling point curvature determining module 906 configured to determine the sampling point according to an angle formed by a line connecting the sampling point and each of the first auxiliary points, and a linear distance between the two first auxiliary points The curvature at the place.
  • the target curvature determining module 908 is further configured to determine a target sampling point having the largest curvature among the sampling points; and on the expected driving route, the predetermined spacing is less than the sampling spacing.
  • a second auxiliary point is respectively selected before and after the target sampling point; and the target curvature is obtained according to the curvature at the target sampling point and the curvature at the second auxiliary point.
  • the target curvature determination module 908 is further configured to generate a current reference curvature according to an average of a curvature at the target sampling point and a curvature at the second auxiliary point; acquire a historical reference curvature; The reference curvature and the mean of the obtained historical reference curvature are taken as the target curvature.
  • the target curvature determining module 908 is further configured to obtain a speed limit calculation frequency and a preset selection duration; and calculate a target quantity according to the product of the speed limit calculation frequency and the preset selection duration; The historical reference curvature of the target number that was recently generated before the reference curvature.
  • the target curvature determining module 908 is further configured to obtain a current reference curvature according to an average of a curvature at the target sampling point and a curvature at the second auxiliary point; and obtain a target curvature generated last time
  • the weight of the current reference curvature and the previously generated target curvature are weighted and averaged according to the corresponding weights to generate the current target curvature.
  • the target curvature determination module 908 is further configured to generate a current target curvature according to the following formula:
  • K A_now (1-a) * K A_pre + a * K R_now ;
  • K A_now represents the current target curvature
  • K A_pre represents the previously generated target curvature
  • K R — now represents the current reference curvature
  • a is the weight of the current reference curvature
  • the speed limit determination module 910 is further configured to acquire a preset lateral force coefficient; take an absolute value of the target curvature; divide the product of the lateral force coefficient and the gravity acceleration by the absolute value, and then square the square , obtaining a speed limit on the expected driving route.
  • FIG. 10 is a schematic diagram showing the internal structure of a computer device in an example.
  • the computer device can be a terminal or a server.
  • the terminal may be a personal computer or a mobile electronic device including at least one of a mobile phone, a tablet, a personal digital assistant, or a wearable device.
  • the server can be implemented as a stand-alone server or a server cluster consisting of multiple physical servers.
  • the computer device 1000 includes a processor 1002, a non-volatile storage medium 1004, an internal memory 1006, and a network interface 1008 that are connected by a system bus.
  • the non-volatile storage medium 1004 of the computer device can store the operating system 1010 and the computer program 1012, and when the computer program 1012 is executed, the processor can be caused to execute a driving speed control method.
  • the processor 1002 of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device.
  • the internal memory 1006 can store a computer program 1012 that, when executed by the processor 1002, can cause the processor 1002 to perform a travel speed control method.
  • a network interface 1008 of the computer device is used for network communication.
  • FIG. 10 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • the travel speed control device provided herein can be implemented in the form of a computer program that can be run on a computer device 1000 as shown in FIG. 10, the non-volatile nature of the computer device
  • the storage medium can store various program modules constituting the traveling speed control device, for example, the sampling interval determining module 802, the sampling point selecting module 804, the target curvature determining module 808, the speed limit determining module 810, and the traveling speed control module shown in FIG. 812.
  • Each of the program modules includes a computer program for causing the computer device to perform the steps in the travel speed control method of the various examples of the present application described in the present specification, for example, the computer device may pass through FIG.
  • the sampling interval determining module 802 in the illustrated driving speed control device 800 determines the sampling interval that matches the current traveling speed, and selects the sampling point on the expected driving route according to the sampling interval from the current position by the sampling point selection module 804. .
  • the target curvature determining module 808 determines the target curvature according to the curvature at each of the sampling points, and determines, by the speed limit determining module 810, the speed limit on the expected driving route according to the target curvature, and the passing speed.
  • the control module 812 controls the travel speed according to the speed limit.
  • a computer apparatus comprising a memory and a processor, wherein the memory stores a computer program, the computer program being executed by the processor, causing the processor to perform the following steps:
  • the traveling speed is controlled according to the speed limit.
  • the determining a sampling interval that matches the current travel speed includes:
  • the sampling interval is determined according to the product of the current traveling speed and the preset duration.
  • determining the sampling interval according to the product of the current driving speed and the preset duration includes:
  • the computer program prior to determining the target curvature based on the curvature at each of the sample points, the computer program further causes the processor to perform the following steps:
  • two first auxiliary points are continuously selected at intervals of a preset reference length smaller than the sampling interval;
  • determining the target curvature according to the curvature at each of the sampling points includes:
  • a target curvature is obtained based on the curvature at the target sampling point and the curvature at the second auxiliary point.
  • the obtaining the target curvature according to the curvature at the target sampling point and the curvature at the second auxiliary point includes:
  • the current reference curvature and the obtained mean value of the historical reference curvature are taken as the target curvature.
  • the obtaining a historical reference curvature includes:
  • a historical reference curvature of the number of targets recently generated prior to generating the current reference curvature is obtained.
  • the obtaining the target curvature according to the curvature at the target sampling point and the curvature at the second auxiliary point includes:
  • the current reference curvature and the previously generated target curvature are weighted and averaged according to the corresponding weights to generate the current target curvature.
  • the current reference curvature and the previously generated target curvature are weighted and averaged according to corresponding weights, and the current target curvature includes:
  • K A_now (1-a) * K A_pre + a * K R_now ;
  • K A_now represents the current target curvature
  • K A_pre represents the previously generated target curvature
  • K R — now represents the current reference curvature
  • a is the weight of the current reference curvature
  • determining the speed limit to travel on the expected travel route according to the target curvature includes:
  • the product of the lateral force coefficient and the gravitational acceleration is divided by the absolute value and then squared to obtain a speed limit for traveling on the expected travel route.
  • a storage medium storing a computer program, when executed by one or more processors, causes one or more processors to perform the following steps:
  • the traveling speed is controlled according to the speed limit.
  • the determining a sampling interval that matches the current travel speed includes:
  • the sampling interval is determined according to the product of the current traveling speed and the preset duration.
  • determining the sampling interval according to the product of the current driving speed and the preset duration includes:
  • the computer program prior to determining the target curvature based on the curvature at each of the sample points, the computer program further causes the processor to perform the following steps:
  • two first auxiliary points are continuously selected at intervals of a preset reference length smaller than the sampling interval;
  • determining the target curvature according to the curvature at each of the sampling points includes:
  • a target curvature is obtained based on the curvature at the target sampling point and the curvature at the second auxiliary point.
  • the obtaining the target curvature according to the curvature at the target sampling point and the curvature at the second auxiliary point includes:
  • the current reference curvature and the obtained mean value of the historical reference curvature are taken as the target curvature.
  • the obtaining a historical reference curvature includes:
  • a historical reference curvature of the number of targets recently generated prior to generating the current reference curvature is obtained.
  • the obtaining the target curvature according to the curvature at the target sampling point and the curvature at the second auxiliary point includes:
  • the current reference curvature and the previously generated target curvature are weighted and averaged according to the corresponding weights to generate the current target curvature.
  • the current reference curvature and the previously generated target curvature are weighted and averaged according to corresponding weights, and the current target curvature includes:
  • K A_now (1-a) * K A_pre + a * K R_now ;
  • K A_now represents the current target curvature
  • K A_pre represents the previously generated target curvature
  • K R — now represents the current reference curvature
  • a is the weight of the current reference curvature
  • determining the speed limit to travel on the expected travel route according to the target curvature includes:
  • the product of the lateral force coefficient and the gravitational acceleration is divided by the absolute value and then squared to obtain a speed limit for traveling on the expected travel route.
  • the storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

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Abstract

一种行驶速度控制方法、装置、计算机设备和存储介质，该方法包括：确定与当前的行驶速度相匹配的采样间距；从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；根据所述限速控制行驶速度。

Description

行驶速度控制方法、装置、计算机设备和存储介质
本申请要求于2017年08月22日提交中国专利局、申请号为201710725387.0、发明名称为“行驶速度控制方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及驾驶控制技术领域，特别是涉及一种行驶速度控制方法、装置、计算机设备和存储介质。
背景
随着科学技术的飞速发展，驾驶控制方面的技术也越来越先进，自动驾驶越来越受大家的关注。为了保证驾驶的安全性，在自动驾驶时，会确定前方道路的限速，以进行速度规划，保证安全驾驶。
目前，是对弯道进行分段处理，预先对各个分段计算限速值并记录在地图上。实际行驶时，会查询地图上的分段记录的限速。这样一来，就容易在两段限速的分界处造成明显的加速或减速现象，产生速度突变。比如，这段路限速100，下一段比较弯，限速60，则就会在两段分界处产生速度突变。
技术内容
本申请实例提供了一种行驶速度控制方法，所述方法包括：
确定与当前的行驶速度相匹配的采样间距；
从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
根据所述限速控制行驶速度。
本申请实例还提供了一种行驶速度控制装置，所述装置包括：
采样间距确定模块，用于确定与当前的行驶速度相匹配的采样间距；
采样点选取模块，用于从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
目标曲率确定模块，用于根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
限速确定模块，用于按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
行驶速度控制模块，用于根据所述限速控制行驶速度。
本申请实例还提供了一种计算机设备，包括存储器和处理器，所述存储器中存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行上述方法。
本申请实例还提供了一种存储有计算机程序的存储介质，所述计算机程序被一个或多个处理器执行时，使得一个或多个处理器执行上述方法。
附图简要说明
图1A为本申请一些实例涉及的一种系统构架示意图；
图1B为本申请另一些实例涉及的一种系统构架示意图；
图1C为本申请一个实例中行驶速度控制方法的流程示意图；
图2为本申请一个实例中采样点曲率确定步骤的流程示意图；
图3为本申请一个实例中曲率计算示意图；
图4为本申请一个实例中目标曲率得到步骤的流程示意图；
图5为本申请一个实例中历史参考曲率获取步骤的流程示意图；
图6为本申请一个实例中目标曲率生成步骤的流程示意图；
图7为本申请另一个实例中行驶速度控制方法的流程示意图；
图8为本申请一个实例中行驶速度控制装置的框图；
图9为本申请另一个实例中行驶速度控制装置的框图；
图10为本申请一个实例中计算机设备的内部结构示意图。
实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实例仅仅用以解释本申请，并不用于限定本申请。
本申请提出一种行驶速度控制方法，可应用于如图1A和1B所示的系统构架中。如图1A和1B所示，该系统构架包括：车辆101和计算设备102，其中，计算机设备102可以是终端或服务器，当计算设备102为终端时，计算设备102可以位于车辆101中，其中，计算设备102可以集成在车辆101中，例如是车辆101自身的操作系统，也可以是与车辆101独立的设备。如图1A所示；当计算设备102为服务器时，车辆101和计算设备102可以通过网络103相连，如图1B所示。在一些实例中，车辆101为自动驾驶模式时，计算设备102可以确定与当前的行驶速度相匹配的采样间距；从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；根据所述限速控制车辆101的行驶速度，以保证车辆101的安全驾驶。
图1C为本申请一个实例中行驶速度控制方法的流程示意图。本实例主要以该行驶速度控制方法应用于计算机设备来举例说明，该计算机设备可以是终端或服务器。参照图1C，该方法具体包括如下步骤：
S102，确定与当前的行驶速度相匹配的采样间距。
其中，与当前的行驶速度相匹配的采样间距，说明当前的行驶速度影响采样间距的大小。
在一个实例中，采样间距与当前的行驶速度正相关。具体地，当前的行驶速度越大，采样间距越大；当前的行驶速度越小，采样间距越小。
在一个实例中，步骤S102包括：获取当前的行驶速度和预设时长；按照当前的行驶速度和预设时长的乘积确定采样间距。
具体地，在一个实例中，计算机设备可以直接将当前的行驶速度和预设时长的乘积作为采样间距。在另一个实例中，按照当前的行驶速度和预设时长的乘积确定 采样间距包括：确定当前的行驶速度和预设时长的乘积；获取预设采样间距；取当前的行驶速度和预设时长的乘积与预设采样间距中的最小值作为采样间距。
在一个实例中，计算机设备可以按照以下公式得到采样间距：
d＝MIN(d 0，V*t 0)；
其中，d为采样间距，d 0为预设采样间距，V为当前的行驶速度，t 0为预设时长。在一个实例中，d 0可以为10m，t 0可以为0.5s。
比如，当前的行驶速度V为15m/s，d 0为10m，t 0为0.5s，那么，V*t 0＝7.5m，则d＝MIN(d 0，V*t 0)＝MIN(10,7.5)＝7.5m。
在另一个实例中，步骤S102包括：确定当前的行驶速度所处于的预设行驶速度范围区间，根据预先设置的行驶速度范围区间和采样间距之间的对应关系，查找所处于的预设行驶速度范围区间所对应的采样间距。
具体地，计算机设备中预先设置了行驶速度范围区间与采样间距间的对应关系。计算机设备可以确定当前的行驶速度所处于的行驶速度范围区间，根据该对应关系，查找与所确定的行驶范围区别对应的采样间距，即为确定出与当前的行驶速度相匹配的采样间距。
比如，行驶速度在20～25m/s的范围区间内时，对应的采样间距为10m，行驶速度在26～30m/s的范围区间内时，对应的采样间距为15m，行驶速度在31～35m/s的范围区间内时，对应的采样间距为30m。如果当前的行驶速度为28m/s，则所处于的范围区间为31～35m/s，进而所匹配的采样间距为30m。
S104，从当前位置起，按照采样间距在预期行驶路线上选取采样点。
其中，预期行驶路线，是指预测将要行驶的路线。预期行驶路线可以是车辆当前行驶方向的前方道路所构成的路线。
具体地，计算机设备可以从当前位置起，按照采样间距在预期行驶路线上选取预设数量的采样点。比如，预设数量可以为5。
计算机设备也可以确定与当前的行驶速度相匹配的采样数量，根据所确定的采样数量，从当前位置起，按照采样间距在预期行驶路线上选取相应的采样点。在一个实例中，采样数量与当前的行驶速度正相关。
S106，根据所述预期行驶路线在各采样点处的曲率，确定目标曲率。
其中，预期行驶路线在一采样点处的曲率，是表示预期行驶路线偏离该采样点 的切线的程度的数值，即预期行驶路线在该采样点上的弯曲程度的数值，曲率越大，预期行驶路线偏离该采样点的切线的程度越大，即预期行驶路线在该点处的弯曲程度越大。目标曲率，是最终用于确定在预期行驶路线上行驶的限速(即最大速度)的曲率。
具体地，计算机设备可以从各采样点处的曲率中选取最大值，根据选取的曲率最大值来确定目标曲率。在一个实例中，计算机设备可以直接将选取的曲率最大值作为目标曲率。在另一个实例中，计算机设备还可以对选取的曲率最大值与辅助点处的曲率取平均值，根据该曲率平均值来确定目标曲率。
S108，按照目标曲率，确定在预期行驶路线上行驶的限速。
其中，在预期行驶路线上行驶的限速，是指在预期行驶路线上行驶的最大速度。
在一个实例中，步骤S108包括：获取预设的横向力系数；对目标曲率取绝对值；将横向力系数与重力加速度的乘积除以绝对值后开平方，得到在预期行驶路线上行驶的限速。
其中，横向力系数，用于衡量行驶对象在行驶路线上行驶时的稳定程度。
具体地，计算机设备可以按照以下公式得到在预期行驶路线上行驶的限速：
Vmax＝sqrt(u*g/fabs(k A))；
其中，Vmax为在预期行驶路线上行驶的限速；u为横向力系数；g为重力加速度；k A为目标曲率；sqrt(u*g/fabs(k A))表示对u*g/fabs(k A)进行平方根计算；fabs(k A)表示取k A的绝对值。在一个实例中，横向力系数u可以为0.2。
S110，根据限速控制行驶速度。
具体地，计算机设备可以根据限速进行速度规划，确定出在预期行驶路线上行驶的速度。
上述行驶速度控制方法，采样间距与当前的行驶速度相匹配，按照该采样间距在预期行驶路线上选取采样点，将使得采样点更加能够反映当前的行驶速度下行驶速度控制的需求。根据选取的采样点处的曲率确定的目标曲率，可以更好地反映预期行驶路线的弯曲情况，就可以提前发现弯道，进而根据弯道的曲率确定限速以实现对行驶速度的准确控制，减少了速度突变。
如图2所示，在一个实例中，在步骤S106之前，该方法还包括采样点曲率确定 步骤，具体包括以下步骤：
S202，针对每个采样点，从所述采样点起，在所述预期行驶路线上，以小于采样间距的预设参照长度为间隔连续选取两个第一辅助点。
其中，预设参照长度小于采样间距。可以理解，因为是从所述采样点起，在预期行驶路线上以预设参照长度连续选取两个第一辅助点，所以采样点与第一个第一辅助点之间的弧长，以及两个第一辅助点之间的弧长均为预设参照长度。
在一个实例中，预设参照长度可以是车辆轴长。其中，车辆轴长，是指车辆前轴中心到后轴中心的距离。
S204，根据所述采样点与相应各第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定所述采样点处的曲率。
其中，采样点分别与相应的各第一辅助点的连线之间可以形成夹角。两个第一辅助点间的直线距离，是指两个第一辅助点间的线段的长度。
在一个实例中，计算机设备可以按照以下步骤确定各采样点处的曲率：
K s＝2*sin(θ/2)/L；
其中，K s为采样点处的曲率，θ为采样点与相应各第一辅助点的连线所形成的夹角；L为两个第一辅助点间的直线距离。
可以理解，当预设参照长度为车辆轴长时，由于车辆轴长比较短，所以两个第一辅助点间的弧长与两个第一辅助点间的直线距离近似相等，因此，可以直接将车辆轴长作为L代入上述公式中进行计算。
图3为一个实例中曲率计算示意图。如图3所示，P1、P2、P3和P4为采样点，点A和点B为在预期行驶路线w上与P1相应的第一辅助点，其中，第一辅助点与采样点P1间的预设参照长度小于两个采样点间的采样间距，θ为采样点P1与相应第一辅助点点A和点B的连线所形成的夹角。
上述实例中，针对每个采样点，从所述采样点起，在所述预期行驶路线上，以小于采样间距的预设参照长度为间隔连续选取两个第一辅助点。通过两个第一辅助点与采样点间连线所形成的夹角以及两个第一辅助点间的直线距离，确定各采样点处的曲率。在计算曲率时，通过做两个第一辅助点，将比较复杂的微积分曲率计算方法转化为夹角与距离间的直观计算，简化了处理步骤，提高了得到采样点处的曲率的效率，从而提高了行驶速度控制效率。
如图4所示，在一个实例中，步骤S106(简称目标曲率得到步骤)，具体包括以下步骤：
S402，确定各采样点中曲率最大的目标采样点。
其中，目标采样点，是各采样点中曲率最大的采样点。
具体地，计算机设备可以确定出各采样点处的曲率，从中选取曲率最大的采样点作为目标采样点。
S404，在预期行驶路线上，按照小于采样间距的预设间距在目标采样点的前后分别选取第二辅助点。
其中，预设间距小于采样间距。可以理解，在目标采样点前面的第二辅助点与目标采样点间的弧长，以及在目标采样点后面的第二辅助点与目标采样点间的弧长皆等于预设间距。目标采样点前面的第二辅助点，是指从目标采样点起，在预期行驶路线上背向行驶方向按照预设间距所选取的点。目标采样点之后的第二辅助点，是指从目标采样点起，在预期行驶路线上顺着行驶方向按照预设间距所选取的点。
在一个实例中，在目标采样点前面或后面所选取的第二辅助点为至少一个。在目标采样点前面与在目标采样点后面所选取的第二辅助点数量可以相同。可以理解，当在目标采样点前面或后面所选取的第二辅助点为多个时，两两相邻的第二辅助点间的弧长等于预设间距。
S406，根据目标采样点处的曲率和第二辅助点处的曲率，得到目标曲率。
在一个实例中，计算机设备可以对目标采样点处的曲率和第二辅助点处的曲率求平均值，根据求取的平均值确定目标曲率。
具体地，计算机设备可以对目标采样点处的曲率和第二辅助点处的曲率求和，并除以进行求和的曲率数量，得到目标采样点处的曲率和第二辅助点处的曲率的平均值。
在一个实例中，计算机设备可以按照以下公式得到目标采样点处的曲率和第二辅助点处的曲率的平均值：
K R＝(K F_pre+K s+K F_next)/n；
其中，K R为目标采样点处的曲率和第二辅助点处的曲率的平均值；K F_pre为位于目标采样点前面的第二辅助点处的曲率；K s为目标采样点处的曲率；K F_next为位 于目标采样点后面的第二辅助点处的曲率；n为进行求和的曲率数量。在一个实例中，当目标采样点K s的前后分别只选取了一个第二辅助点，则n为3。
在一个实例中，计算机设备可以直接将对目标采样点处的曲率和第二辅助点处的曲率求取的平均值作为目标曲率。在另一个实例中，计算机设备也可以将对目标采样点处的曲率和第二辅助点处的曲率求取的平均值作为当前参考曲率，并结合历史参考曲率，得到目标曲率。
上述实例中，先确定曲率最大的采样点，并在曲率最大的采样点的前后以预设间距选取第二辅助点，根据目标采样点处的曲率和第二辅助点处的曲率，得到目标曲率。通过结合了前后的两个辅助点处的曲率考量得到的目标曲率，更加的稳定，相较于单一采样点处的曲率的局限性而言，更能够准确反映行驶路线的弯曲情况，就可以提前发现弯道，进而根据弯道的曲率确定限速以实现对行驶速度的准确控制，减少了速度突变，减少对速度规划造成的干扰。
在一个实例中，步骤S406包括：根据目标采样点处的曲率和第二辅助点处的曲率的平均值，生成当前参考曲率；获取历史参考曲率；将当前参考曲率和获取的历史参考曲率的均值，作为目标曲率。
其中，历史参考曲率，是在当前参考曲率生成之前生成的参考曲率。可以理解，每次进行限速计算时会生成参考曲率，则历史参考曲率是当次之前进行的限速计算时所生成的参考曲率。
在一个实例中，计算机设备可以直接将目标采样点处的曲率和第二辅助点处的曲率的平均值作为当前参考曲率。计算机设备可以获取全部或部分历史参考曲率。计算机设备可以对当前参考曲率和获取的历史参考曲率求均值，将求取的均值作为目标曲率。
上述实例中，在进行目标曲率计算时，将当前参考曲率与历史参考曲率结合起来，通过当前参考曲率和历史参考曲率的均值来确定目标曲率，使得确定的目标曲率更加的稳定，相较于单一的根据当前参考曲率的局限性而言，更能够准确反映出行驶路线的弯曲情况。
如图5所示，在一个实例中，获取历史参考曲率(简称历史参考曲率获取步骤)， 具体包括以下步骤：
S502，获取限速计算频率和预设选取时长。
其中，限速计算频率，是指进行限速计算的频率。在一个实例中，限速计算频率可以与速度规划频率一致。速度规划频率是指进行速度规划的频率。在一个实例中，限速计算频率可以为10hz，即一秒钟进行10次限速计算。
预设选取时长，用于确定历史参考曲率的选取范围。计算机设备可以选取在当前参考曲率的生成时间前预设选取时长内生成的历史参考曲率。比如，预设选取时长为1s，则计算机设备可以选取在当前参考曲率生成时间前1s内所生成的历史参考曲率。
S504，根据限速计算频率和预设选取时长的乘积，得到目标数量。
其中，目标数量，是所要选取的历史参考曲率的数量。
在一个实例中，计算机设备可以直接将限速计算频率和预设选取时长的乘积，作为目标数量。可以理解，本实例中，目标数量也是在当前参考曲率的生成时间前预设选取时长内生成的历史参考曲率的数量。
比如，限速计算频率为10hz，预设选取时长为1s，则目标数量＝10*1＝10个。
S506，获取生成当前参考曲率之前最近生成的目标数量的历史参考曲率。
具体地，计算机设备可以从在生成当前参考曲率之前所生成的历史参考曲率中，选取此次生成当前参考曲率之前的前目标数量次生成的历史参考曲率。比如，目标数量为10个，则计算机设备可以选取此次生成当前参考曲率之前的前1次、前2次……直至前10次所生成的历史参考曲率。
上述实例中，根据限速计算频率和预设选取时长的乘积，得到目标数量，获取生成当前参考曲率之前最近生成的目标数量的历史参考曲率。然后根据历史参考曲率和当前参考曲率的均值来确定目标曲率。相当于通过限速计算频率在时间维度上来对参考曲率进行均值计算，使得最终得到的目标曲率为时间维度上的均值结果，进一步在时间维度上提高了目标曲率的稳定性。从而使得根据目标曲率确定的限速更加的准确，进而避免了速度突变。
如图6所示，在另一个实例中，S406(简称目标曲率生成步骤)，具体包括以下步骤：
S602，根据目标采样点处的曲率和第二辅助点处的曲率的平均值，得到当前参考曲率。
在一个实例中，计算机设备可以直接将目标采样点处的曲率和第二辅助点处的曲率的平均值，作为当前参考曲率。
具体地，计算机设备可以将目标采样点处的曲率和第二辅助点处的曲率相加，并除以相加的曲率数量，得到当前参考曲率。
S604，获取前次生成的目标曲率。
其中，前次生成的目标曲率，是指在当次的前一次所生成的目标曲率，即在当次的前一次进行限速计算时所生成的目标曲率。
S606，将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率。
在一个实例中，计算机设备可以按照以下公式生成当次的目标曲率：
K A_now＝(1-a)*K A_pre+a*K R_now；
其中，K A_now表示当次的目标曲率，K A_pre表示前次生成的目标曲率，K R_now表示当前参考曲率，a为当前参考曲率的权重。
在一个实例中，a＝1/H/T。其中，H为限速计算频率，T为预设选取时长。可以理解，随着迭代次数的增多，生成时间距当次越远的历史目标曲率对当次的目标曲率的生成的影响越小，最后近似在距当次预设选取时长T内生成的历史目标曲率对当次的目标曲率的生成能产生实质性的影响，1/H为当次生成目标曲率所对应的时长，通过1/H/T能够反映当次生成目标曲率所对应的时长在对当次的目标曲率的生成有影响作用的历史目标曲率的近似总时长中所占的比例，从而确定当前参考曲率的权重，在一个实例中，H＝10hz，T＝1s。
上述实例中，通过迭代计算的方式，将前次生成的目标曲率作为输入，结合当前参考曲率，按照相应的权重进行加权平均，生成当次的目标曲率。相当于结合了在时间维度上来对目标曲率进行均值计算，使得最终得到的目标曲率为时间维度上的均值结果，进一步在时间维度上提高了目标曲率的稳定性，从而使得根据目标曲率确定的限速更加的准确，进而避免了速度突变。
如图7所示，在一个实例中，提供了另一种行驶速度控制方法，该方法包括以 下步骤：
S702，确定当前的行驶速度和预设时长的乘积，以及获取预设采样间距。
S704，取当前的行驶速度和预设时长的乘积与预设采样间距中的最小值作为采样间距。
S706，从当前位置起，按照采样间距在预期行驶路线上选取采样点。
S708，针对每个采样点，从所述采样点起，在所述预期行驶路线上，以小于采样间距的预设参照长度为间隔连续选取两个第一辅助点。
S710，根据所述采样点与各第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定所述采样点处的曲率。
S712，确定各采样点中曲率最大的目标采样点。
S714，在预期行驶路线上，按照小于采样间距的预设间距在目标采样点的前后分别选取第二辅助点。
S716，根据目标采样点处的曲率和第二辅助点处的曲率的平均值，生成当前参考曲率。
S718，获取限速计算频率和预设选取时长，根据限速计算频率和预设选取时长的乘积，得到目标数量。
S720，获取生成当前参考曲率之前最近生成的目标数量的历史参考曲率，将当前参考曲率和获取的历史参考曲率的均值，作为目标曲率。
S722，获取预设的横向力系数，对目标曲率取绝对值。
S724，将横向力系数与重力加速度的乘积除以绝对值后开平方，得到在预期行驶路线上行驶的限速。
S726，根据限速控制行驶速度。
上述行驶速度控制方法，采样间距与当前的行驶速度相匹配，按照该采样间距在预期行驶路线上选取采样点，将使得采样点更加能够反映当前的行驶速度下行驶速度控制的需求。根据选取的采样点处的曲率确定的目标曲率，可以更好地反映预期行驶路线的弯曲情况，就可以提前发现弯道，进而根据弯道的曲率确定限速以实现对行驶速度的准确控制，减少了速度突变。
其次，通过做两个第一辅助点，将比较复杂的微积分曲率计算方法转化为夹角与距离间的直观计算，简化了处理步骤，提高了得到采样点曲率的效率，从而提高 了行驶速度控制效率。
然后，通过结合了前后的两个辅助点处的曲率考量得到的目标曲率，更加的稳定，相较于单一采样点处的曲率的局限性而言，更能够反映行驶路线的整体弯曲情况，就可以提前发现弯道，进而根据弯道的曲率确定限速以实现对行驶速度的准确控制，减少了速度突变。
此外，在进行目标曲率计算时，将当前参考曲率与历史参考曲率结合起来，通过当前参考曲率和历史参考曲率的均值来确定目标曲率，使得确定的目标曲率更加的稳定，相较于单一的根据当前参考曲率的局限性而言，更能够准确反映出行驶路线的弯曲情况。
最后，通过限速计算频率在时间维度上来对参考曲率进行均值计算，使得最终得到的目标曲率为时间维度上的均值结果，进一步在时间维度上提高了目标曲率的稳定性。从而使得根据目标曲率确定的限速更加的准确，进而避免了速度突变。
如图8所示，在一个实例中，提供了一种行驶速度控制装置800，该装置800包括：采样间距确定模块802、采样点选取模块804、目标曲率确定模块808、限速确定模块810以及行驶速度控制模块812，其中：
采样间距确定模块802，用于确定与当前的行驶速度相匹配的采样间距。
采样点选取模块804，用于从当前位置起，按照所述采样间距在预期行驶路线上选取采样点。
目标曲率确定模块808，用于根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
限速确定模块810，用于按照所述目标曲率，确定在所述预期行驶路线上行驶的限速。
行驶速度控制模块812，用于根据所述限速控制行驶速度。
在一个实例中，采样间距确定模块802还用于获取当前的行驶速度和预设时长；按照所述当前的行驶速度和所述预设时长的乘积确定采样间距。
在一个实例中，采样间距确定模块802还用于确定所述当前的行驶速度和所述预设时长的乘积；获取预设采样间距；取所述当前的行驶速度和所述预设时长的乘积与所述预设采样间距中的最小值作为采样间距。
如图9所示，在一个实例中，提供了一种行驶速度控制装置900，该装置900包括：
采样间距确定模块902、采样点选取模块904、目标曲率确定模块908、限速确定模块910以及行驶速度控制模块912，其中：
采样间距确定模块902，用于确定与当前的行驶速度相匹配的采样间距。
采样点选取模块904，用于从当前位置起，按照所述采样间距在预期行驶路线上选取采样点。
目标曲率确定模块908，用于根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
限速确定模块910，用于按照所述目标曲率，确定在所述预期行驶路线上行驶的限速。
行驶速度控制模块912，用于根据所述限速控制行驶速度。
在一个实例中，采样间距确定模块902还用于获取当前的行驶速度和预设时长；按照所述当前的行驶速度和所述预设时长的乘积确定采样间距。
在一个实例中，采样间距确定模块902还用于确定所述当前的行驶速度和所述预设时长的乘积；获取预设采样间距；取所述当前的行驶速度和所述预设时长的乘积与所述预设采样间距中的最小值作为采样间距。
在一些实例中，装置900还包括：
辅助点选取模块905，用于针对每个采样点，从所述采样点起，在所述预期行驶路线上，以小于所述采样间距的预设参照长度为间隔连续选取两个第一辅助点；
采样点曲率确定模块906，用于根据所述采样点与各所述第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定所述采样点处的曲率。
在一个实例中，所述目标曲率确定模块908还用于确定各所述采样点中曲率最大的目标采样点；在所述预期行驶路线上，按照小于所述采样间距的预设间距在所述目标采样点的前后分别选取第二辅助点；根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率。
在一个实例中，所述目标曲率确定模块908还用于根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，生成当前参考曲率；获取历史参考曲率；将当前参考曲率和获取的所述历史参考曲率的均值，作为目标曲率。
在一个实例中，所述目标曲率确定模块908还用于获取限速计算频率和预设选取时长；根据所述限速计算频率和所述预设选取时长的乘积，得到目标数量；获取生成当前参考曲率之前最近生成的所述目标数量的历史参考曲率。
在一个实例中，所述目标曲率确定模块908还用于根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，得到当前参考曲率；获取前次生成的目标曲率；将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率。
在一个实例中，所述目标曲率确定模块908还用于按照以下公式生成当次的目标曲率：
K A_now＝(1-a)*K A_pre+a*K R_now；
其中，K A_now表示当次的目标曲率，K A_pre表示前次生成的目标曲率，K R_now表示当前参考曲率，a为当前参考曲率的权重。
在一个实例中，限速确定模块910还用于获取预设的横向力系数；对所述目标曲率取绝对值；将所述横向力系数与重力加速度的乘积除以所述绝对值后开平方，得到在所述预期行驶路线上行驶的限速。
图10为一个实例中计算机设备的内部结构示意图。该计算机设备可以是终端或服务器。终端可以是个人计算机或者移动电子设备，移动电子设备包括手机、平板电脑、个人数字助理或者穿戴式设备等中的至少一种。服务器可以用独立的服务器或者是多个物理服务器组成的服务器集群来实现。参照图10，该计算机设备1000包括通过系统总线连接的处理器1002、非易失性存储介质1004、内存储器1006和网络接口1008。其中，该计算机设备的非易失性存储介质1004可存储操作系统1010和计算机程序1012，该计算机程序1012被执行时，可使得处理器执行一种行驶速度控制方法。该计算机设备的处理器1002用于提供计算和控制能力，支撑整个计算机设备的运行。该内存储器1006中可储存有计算机程序1012，该计算机程序1012被处理器1002执行时，可使得处理器1002执行一种行驶速度控制方法。计算机设备的网络接口1008用于进行网络通信。
本领域技术人员可以理解，图10中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的 计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一个实例中，本申请提供的行驶速度控制装置可以实现为一种计算机程序的形式，所述计算机程序可在如图10所示的计算机设备1000上运行，所述计算机设备的非易失性存储介质可存储组成该行驶速度控制装置的各个程序模块，比如，图8所示的采样间距确定模块802、采样点选取模块804、目标曲率确定模块808、限速确定模块810以及行驶速度控制模块812。各个程序模块中包括计算机程序，所述计算机程序用于使所述计算机设备执行本说明书中描述的本申请各个实例的行驶速度控制方法中的步骤，例如，所述计算机设备可以通过如图8所示的行驶速度控制装置800中的采样间距确定模块802确定与当前的行驶速度相匹配的采样间距，通过采样点选取模块804从当前位置起，按照所述采样间距在预期行驶路线上选取采样点。通过目标曲率确定模块808根据各所述采样点处的曲率，确定目标曲率，并通过限速确定模块810按照所述目标曲率，确定在所述预期行驶路线上行驶的限速，以及通过行驶速度控制模块812根据所述限速控制行驶速度。
在一些实例中，还提供了一种计算机设备，包括存储器和处理器，所述存储器中存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行如下步骤：
确定与当前的行驶速度相匹配的采样间距；
从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
根据所述限速控制行驶速度。
在一个实例中，所述确定与当前的行驶速度相匹配的采样间距包括：
获取当前的行驶速度和预设时长；
按照所述当前的行驶速度和所述预设时长的乘积确定采样间距。
在一个实例中，所述按照所述当前的行驶速度和所述预设时长的乘积确定采样间距包括：
确定所述当前的行驶速度和所述预设时长的乘积；
获取预设采样间距；
取所述当前的行驶速度和所述预设时长的乘积与所述预设采样间距中的最小值作为采样间距。
在一个实例中，在所述根据各所述采样点处的曲率，确定目标曲率之前，计算机程序还使得处理器执行以下步骤：
针对每个采样点，
从所述采样点起，在所述预期行驶路线上，以小于所述采样间距的预设参照长度为间隔连续选取两个第一辅助点；
根据所述采样点与各所述第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定各所述采样点处的曲率。
在一个实例中，所述根据各所述采样点处的曲率，确定目标曲率包括：
确定各所述采样点中曲率最大的目标采样点；
在所述预期行驶路线上，按照小于所述采样间距的预设间距在所述目标采样点的前后分别选取第二辅助点；
根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率。
在一个实例中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，生成当前参考曲率；
获取历史参考曲率；
将当前参考曲率和获取的所述历史参考曲率的均值，作为目标曲率。
在一个实例中，所述获取历史参考曲率包括：
获取限速计算频率和预设选取时长；
根据所述限速计算频率和所述预设选取时长的乘积，得到目标数量；
获取生成当前参考曲率之前最近生成的所述目标数量的历史参考曲率。
在一个实例中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，得到当前参考曲率；
获取前次生成的目标曲率；
将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率。
在一个实例中，所述将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率包括：
按照以下公式生成当次的目标曲率：
K A_now＝(1-a)*K A_pre+a*K R_now；
其中，K A_now表示当次的目标曲率，K A_pre表示前次生成的目标曲率，K R_now表示当前参考曲率，a为当前参考曲率的权重。
在一个实例中，所述按照所述目标曲率，确定在所述预期行驶路线上行驶的限速包括：
获取预设的横向力系数；
对所述目标曲率取绝对值；
将所述横向力系数与重力加速度的乘积除以所述绝对值后开平方，得到在所述预期行驶路线上行驶的限速。
在一些实例中，还提供了一种存储有计算机程序的存储介质，所述计算机程序被一个或多个处理器执行时，使得一个或多个处理器执行如下步骤：
确定与当前的行驶速度相匹配的采样间距；
从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
根据所述限速控制行驶速度。
在一个实例中，所述确定与当前的行驶速度相匹配的采样间距包括：
获取当前的行驶速度和预设时长；
按照所述当前的行驶速度和所述预设时长的乘积确定采样间距。
在一个实例中，所述按照所述当前的行驶速度和所述预设时长的乘积确定采样间距包括：
确定所述当前的行驶速度和所述预设时长的乘积；
获取预设采样间距；
取所述当前的行驶速度和所述预设时长的乘积与所述预设采样间距中的最小值作为采样间距。
在一个实例中，在所述根据各所述采样点处的曲率，确定目标曲率之前，计算机程序还使得处理器执行以下步骤：
针对每个采样点，
从所述采样点起，在所述预期行驶路线上，以小于所述采样间距的预设参照长度为间隔连续选取两个第一辅助点；
根据所述采样点与各所述第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定各所述采样点处的曲率。
在一个实例中，所述根据各所述采样点处的曲率，确定目标曲率包括：
确定各所述采样点中曲率最大的目标采样点；
在所述预期行驶路线上，按照小于所述采样间距的预设间距在所述目标采样点的前后分别选取第二辅助点；
根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率。
在一个实例中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，生成当前参考曲率；
获取历史参考曲率；
将当前参考曲率和获取的所述历史参考曲率的均值，作为目标曲率。
在一个实例中，所述获取历史参考曲率包括：
获取限速计算频率和预设选取时长；
根据所述限速计算频率和所述预设选取时长的乘积，得到目标数量；
获取生成当前参考曲率之前最近生成的所述目标数量的历史参考曲率。
在一个实例中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，得到当前参考曲率；
获取前次生成的目标曲率；
将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率。
在一个实例中，所述将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率包括：
按照以下公式生成当次的目标曲率：
K A_now＝(1-a)*K A_pre+a*K R_now；
其中，K A_now表示当次的目标曲率，K A_pre表示前次生成的目标曲率，K R_now表示当前参考曲率，a为当前参考曲率的权重。
在一个实例中，所述按照所述目标曲率，确定在所述预期行驶路线上行驶的限速包括：
获取预设的横向力系数；
对所述目标曲率取绝对值；
将所述横向力系数与重力加速度的乘积除以所述绝对值后开平方，得到在所述预期行驶路线上行驶的限速。
本领域普通技术人员可以理解实现上述实例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，该计算机程序可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实例的流程。其中，前述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)等非易失性存储介质，或随机存储记忆体(Random Access Memory，RAM)等。
以上实例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上实例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (15)

  1. 一种行驶速度控制方法，应用于计算机设备，所述方法包括：
    确定与当前的行驶速度相匹配的采样间距；
    从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
    根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
    按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
    根据所述限速控制行驶速度。
  2. 根据权利要求1所述的方法，其中，所述确定与当前的行驶速度相匹配的采样间距包括：
    获取当前的行驶速度和预设时长；
    按照所述当前的行驶速度和所述预设时长的乘积确定采样间距。
  3. 根据权利要求2所述的方法，其中，所述按照所述当前的行驶速度和所述预设时长的乘积确定采样间距包括：
    确定所述当前的行驶速度和所述预设时长的乘积；
    获取预设采样间距；
    取所述当前的行驶速度和所述预设时长的乘积与所述预设采样间距中的最小值作为采样间距。
  4. 根据权利要求1所述的方法，其中，在所述根据各所述采样点处的曲率，确定目标曲率之前，所述方法还包括：
    针对每个采样点，
    从所述采样点起，在所述预期行驶路线上，以小于所述采样间距的预设参照长度为间隔连续选取两个第一辅助点；
    根据所述采样点与各所述第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定所述采样点处的曲率。
  5. 根据权利要求1所述的方法，其中，所述根据各所述采样点处的曲率，确定目标曲率包括：
    确定各所述采样点中曲率最大的目标采样点；
    在所述预期行驶路线上，按照小于所述采样间距的预设间距在所述目标采样点 的前后分别选取第二辅助点；
    根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率。
  6. 根据权利要求5所述的方法，其中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
    根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，生成当前参考曲率；
    获取历史参考曲率；
    将当前参考曲率和获取的所述历史参考曲率的均值，作为目标曲率。
  7. 根据权利要求6所述的方法，其中，所述获取历史参考曲率包括：
    获取限速计算频率和预设选取时长；
    根据所述限速计算频率和所述预设选取时长的乘积，得到目标数量；
    获取生成当前参考曲率之前最近生成的所述目标数量的历史参考曲率。
  8. 根据权利要求5所述的方法，其中，所述根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率包括：
    根据所述目标采样点处的曲率和所述第二辅助点处的曲率的平均值，得到当前参考曲率；
    获取前次生成的目标曲率；
    将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率。
  9. 根据权利要求8所述的方法，其中，所述将当前参考曲率和前次生成的目标曲率，按照相应的权重进行加权平均，生成当次的目标曲率包括：
    按照以下公式生成当次的目标曲率：
    KA_now＝(1-a)*KA_pre+a*KR_now；
    其中，KA_now表示当次的目标曲率，KA_pre表示前次生成的目标曲率，KR_now表示当前参考曲率，a为当前参考曲率的权重。
  10. 根据权利要求1至9中任一项所述的方法，其中，所述按照所述目标曲率，确定在所述预期行驶路线上行驶的限速包括：
    获取预设的横向力系数；
    对所述目标曲率取绝对值；
    将所述横向力系数与重力加速度的乘积除以所述绝对值后开平方，得到在所述预期行驶路线上行驶的限速。
  11. 一种行驶速度控制装置，所述装置包括：
    采样间距确定模块，用于确定与当前的行驶速度相匹配的采样间距；
    采样点选取模块，用于从当前位置起，按照所述采样间距在预期行驶路线上选取采样点；
    目标曲率确定模块，用于根据所述预期行驶路线在各所述采样点处的曲率，确定目标曲率；
    限速确定模块，用于按照所述目标曲率，确定在所述预期行驶路线上行驶的限速；
    行驶速度控制模块，用于根据所述限速控制行驶速度。
  12. 根据权利要求11所述的装置，其中，所述装置还包括：
    辅助点选取模块，用于针对每个采样点，从所述采样点起，在所述预期行驶路线上，以小于所述采样间距的预设参照长度为间隔连续选取两个第一辅助点；
    采样点曲率确定模块，用于根据所述采样点与各所述第一辅助点的连线所形成的夹角，以及所述两个第一辅助点间的直线距离，确定各所述采样点处的曲率。
  13. 根据权利要求11或12所述的装置，其中，所述目标曲率确定模块还用于确定各所述采样点中曲率最大的目标采样点；在所述预期行驶路线上，按照小于所述采样间距的预设间距在所述目标采样点的前后分别选取第二辅助点；根据所述目标采样点处的曲率和所述第二辅助点处的曲率，得到目标曲率。
  14. 一种计算机设备，包括存储器和处理器，所述存储器中存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行如权利要求1至10中任一项所述方法的步骤。
  15. 一种存储有计算机程序的存储介质，所述计算机程序被一个或多个处理器执行时，使得一个或多个处理器执行如权利要求1至10中任一项所述方法的步骤。
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