CN114148137A - Vehicle running stability control method, device, equipment and storage medium - Google Patents
Vehicle running stability control method, device, equipment and storage medium Download PDFInfo
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Abstract
本申请公开了一种车辆行驶平稳性控制方法、装置、设备和存储介质,涉及自动驾驶领域领域。具体实现方案为:获取所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息;根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息;根据所述策略信息,对所述车辆的悬挂系统进行调整。本申请实施例能够及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。
The present application discloses a vehicle driving stability control method, device, device and storage medium, which relate to the field of automatic driving. The specific implementation scheme is as follows: obtaining the forecast information of the road conditions ahead and the information of the current road conditions during the driving process of the vehicle; and determining the strategy information for adjusting the suspension system of the vehicle according to the forecast information of the road conditions ahead and the information of the current road conditions. ; Adjust the suspension system of the vehicle according to the strategy information. In the embodiment of the present application, policy information for adjusting the suspension system of the vehicle can be made in time, so that the suspension system of the vehicle can be adjusted in time to adapt to the road conditions ahead, the vehicle can run smoothly, and the ride comfort can be improved.
Description
本发明是2020年03月13日所提出的申请号为202010175377.6、发明名称为《车辆行驶平稳性控制方法、装置、设备和存储介质》的发明专利申请的分案申请。The present invention is a divisional application for an invention patent application filed on March 13, 2020 with the application number of 202010175377.6 and the invention title of "Vehicle Driving Stability Control Method, Device, Equipment and Storage Medium".
技术领域technical field
本申请涉及数据处理技术领域,具体涉及自动驾驶技术。The present application relates to the technical field of data processing, in particular to automatic driving technology.
背景技术Background technique
车辆行驶过程中,车辆平稳行驶对于车辆内乘坐者的舒适度来说,是很重要的因素。During the running of the vehicle, the smooth running of the vehicle is a very important factor for the comfort of the occupants in the vehicle.
目前,在车辆平稳行驶控制方面,是通过对车辆行驶速度进行监控来调整车辆的整体高度,例如,如果当前行驶速度过高,就会调低车辆的整体高度,以此来降低风阻。或者通过车载惯性测量单元监测并分析车辆行驶颠簸程度,来调整车辆悬挂系统的阻尼系数,例如,如果当前路段较为颠簸,则调低车辆悬挂系统的阻尼系数。At present, in terms of vehicle smooth driving control, the overall height of the vehicle is adjusted by monitoring the driving speed of the vehicle. For example, if the current driving speed is too high, the overall height of the vehicle will be lowered to reduce wind resistance. Alternatively, the on-board inertial measurement unit monitors and analyzes the bumpiness of the vehicle to adjust the damping coefficient of the vehicle suspension system. For example, if the current road section is bumpy, lower the damping coefficient of the vehicle suspension system.
然而,采用上述现有技术进行车辆平稳行驶控制时,时常出现调整滞后的现象,导致调整后的舒适度也时常不能满足乘客对于平稳性的要求。However, when the above-mentioned prior art is used to control the smooth running of the vehicle, the phenomenon of adjustment lag often occurs, resulting in that the adjusted comfort level often cannot meet the passengers' requirements for stability.
发明内容SUMMARY OF THE INVENTION
第一方面,本申请实施例提供了一种车辆行驶平稳性控制方法,包括:获取所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息;根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息;根据所述策略信息,对所述车辆的悬挂系统进行调整。In a first aspect, an embodiment of the present application provides a vehicle driving stability control method, including: acquiring forward road condition prediction information and current driving road condition information of the vehicle during driving; The road condition information is used to determine strategy information for adjusting the suspension system of the vehicle; and the suspension system of the vehicle is adjusted according to the strategy information.
本申请实施例通过获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息,并根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。In the embodiment of the present application, the vehicle's road condition prediction information and current driving road condition information are obtained during the driving process, and the strategy information for adjusting the suspension system of the vehicle is determined according to the forward road condition prediction information and the current driving road condition information, and according to the strategy information , Adjust the suspension system of the vehicle to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort.
可选的,所述获取所述车辆在行驶过程中的前方路况预测信息,包括:获取所述车辆上的图像采集设备采集的所述车辆周围环境的环境图像;将所述环境图像输入预先训练得到的路况预测模型,得到所述车辆在行驶过程中的前方路况预测信息。Optionally, the acquiring the prediction information of the road conditions ahead of the vehicle during driving includes: acquiring an environmental image of the surrounding environment of the vehicle collected by an image acquisition device on the vehicle; inputting the environmental image into pre-training. The obtained road condition prediction model obtains the forward road condition prediction information of the vehicle during the driving process.
可选的,所述路况预测模型是采用如下过程对神经网络的训练得到的:获取车辆行驶过程中周围环境的环境样本图像以及所述环境样本图像对应的路况预测标注信息;将所述环境样本图像作为神经网络的输入,将所述路况预测标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述路况预测模型。Optionally, the road condition prediction model is obtained by training a neural network by adopting the following process: obtaining an environmental sample image of the surrounding environment during the driving of the vehicle and road condition prediction label information corresponding to the environmental sample image; The image is used as the input of the neural network, the road condition prediction and annotation information is used as the output of the neural network, and the neural network is iteratively trained to obtain the road condition prediction model.
本申请实施例通过对神经网络进行训练得到路况预测模型,从而将车辆上的图像采集设备采集的所述车辆周围环境的环境图像输入路况预测模型,对前方路况进行预测,由于路况预测模型是对神经网络进行训练得到的,因此,路况预测模型能够得到更加丰富的图像语义信息,从而对前方路况进行更准确地预测。In the embodiment of the present application, a road condition prediction model is obtained by training a neural network, so that the environmental image of the surrounding environment of the vehicle collected by the image acquisition device on the vehicle is input into the road condition prediction model, and the road condition ahead is predicted. Therefore, the road condition prediction model can obtain richer image semantic information, so as to predict the road conditions ahead more accurately.
可选的,所述获取所述车辆的当前行驶路况信息,包括:获取所述车辆上的惯性测量单元采集的所述车辆的姿态信息;根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息。Optionally, the acquiring the current driving road condition information of the vehicle includes: acquiring the attitude information of the vehicle collected by the inertial measurement unit on the vehicle; and determining the current driving condition of the vehicle according to the attitude information of the vehicle. Driving traffic information.
可选的,所述根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息,包括:根据预设时间段内所述车辆的姿态信息,确定所述姿态信息的变化量;在所述姿态信息的变化量大于预设变化量的情况下,确定当前行驶路况信息为不平稳路段;在所述姿态信息的变化量小于或等于预设变化量的情况下,确定当前行驶路况信息为平稳路段。Optionally, the determining the current driving road condition information of the vehicle according to the attitude information of the vehicle includes: determining the change amount of the attitude information according to the attitude information of the vehicle within a preset time period; When the change amount of the attitude information is greater than the preset change amount, it is determined that the current driving road condition information is an unstable road section; when the change amount of the attitude information is less than or equal to the preset change amount, it is determined that the current driving road condition information is smooth road.
本申请实施例通过根据车辆在一段时间内的姿态信息的变化量,确定车辆当前所处的路况,姿态信息是用于表征车辆的倾角信息,若车辆当前所处路况为不平稳路段,那么倾角信息的变化量也会不稳定,根据此原理可以方便地确定车辆当前的路况信息,另外,姿态信息可以根据车辆上已有的惯性测量单元来获取,不需要增加额外的传感器。In the embodiment of the present application, the current road condition of the vehicle is determined according to the amount of change of the attitude information of the vehicle within a period of time. The attitude information is used to characterize the inclination angle information of the vehicle. If the current road condition of the vehicle is an unstable road section, then the inclination angle The change of information will also be unstable. According to this principle, the current road condition information of the vehicle can be easily determined. In addition, the attitude information can be obtained from the existing inertial measurement unit on the vehicle without adding additional sensors.
可选的,所述根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息,包括:将所述车辆的姿态信息输入预先训练得到的路况检测模型,得到所述车辆的当前行驶路况信息。Optionally, the determining the current driving road condition information of the vehicle according to the attitude information of the vehicle includes: inputting the attitude information of the vehicle into a road condition detection model obtained by pre-training to obtain the current driving road conditions of the vehicle. information.
可选的,所述路况检测模型是采用如下过程对神经网络的训练得到的:获取所述车辆行驶过程中的姿态样本数据以及所述姿态样本数据对应的当前行驶路况标注信息;将所述姿态样本数据作为神经网络的输入,将所述当前行驶路况标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述路况检测模型。Optionally, the road condition detection model is obtained by training a neural network by adopting the following process: acquiring attitude sample data during the driving of the vehicle and annotation information of the current driving road conditions corresponding to the attitude sample data; The sample data is used as the input of the neural network, the current driving road condition annotation information is used as the output of the neural network, and the neural network is iteratively trained to obtain the road condition detection model.
本申请实施例通过对神经网络进行训练得到路况检测模型,从而将车辆上的惯性测量单元采集的所述车辆的姿态信息输入路况检测模型,对前方路况进行预测,由于路况检测模型是对神经网络进行训练得到的,相较于直接根据姿态信息的变化量确定当前行驶路况,路况检测模型能够更加准确地检测当前行驶路况。In the embodiment of the present application, a road condition detection model is obtained by training a neural network, so that the attitude information of the vehicle collected by the inertial measurement unit on the vehicle is input into the road condition detection model, and the road condition ahead is predicted. Since the road condition detection model is a neural network After training, the road condition detection model can detect the current driving road condition more accurately than directly determining the current driving road condition according to the change of attitude information.
可选的,所述根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,包括:将所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息输入预先训练得到的策略确定模型,得到对所述车辆的悬挂系统进行调整的策略信息。Optionally, determining the strategy information for adjusting the suspension system of the vehicle according to the predicted information of the forward road conditions and the information of the current driving road conditions includes: The driving road condition information is input into a pre-trained strategy determination model to obtain strategy information for adjusting the suspension system of the vehicle.
可选的,所述策略确定模型是采用如下过程对神经网络的训练得到:获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据和当前行驶路况样本数据;将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述策略确定模型。Optionally, the strategy determination model is obtained by training a neural network by adopting the following process: obtaining training sample data and adjustment strategy annotation information corresponding to the training sample data, and the training sample data includes sample data of road conditions ahead and current driving. Road condition sample data; the training sample data is used as the input of the neural network, the adjustment strategy labeling information is used as the output of the neural network, and the neural network is iteratively trained to obtain the strategy determination model.
可选的,所述根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,包括:若所述前方路况预测信息指示路面湿滑且所述当前行驶路况信息指示为平稳路段,则确定调低所述车辆的悬挂系统的悬挂高度。Optionally, determining the strategy information for adjusting the suspension system of the vehicle according to the predicted information of the road ahead and the current driving road condition information includes: if the predicted information of the road ahead indicates that the road is slippery and the current road condition is slippery If the driving road condition information indicates a smooth road section, it is determined to lower the suspension height of the suspension system of the vehicle.
可选的,所述根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,包括:若所述前方路况预测信息指示路段颠簸且所述当前行驶路况信息指示当前路段的颠簸程度越来越大,则确定调低所述悬挂系统的阻尼系数并调高所述车辆的悬挂系统的悬挂高度。Optionally, determining the policy information for adjusting the suspension system of the vehicle according to the predicted information of the road ahead and the current driving road condition information includes: if the predicted information of the road ahead indicates that the road section is bumpy and the current driving When the road condition information indicates that the current road section has an increasingly bumpy degree, it is determined to lower the damping coefficient of the suspension system and increase the suspension height of the vehicle suspension system.
本申请实施例通过对神经网络进行训练得到策略确定模型,从而将获取的前方路况预测信息和当前行驶路况信息输入策略确定模型,确定对车辆的悬挂系统进行调整的策略信息,由于策略确定模型是对神经网络进行训练得到的,因此,确定的策略信息对车辆进行调整的效果更好。In the embodiment of the present application, a neural network is trained to obtain a strategy determination model, so that the acquired forward road condition prediction information and current driving road condition information are input into the strategy determination model, and the strategy information for adjusting the suspension system of the vehicle is determined. Since the strategy determination model is It is obtained by training the neural network, so the determined policy information is more effective in adjusting the vehicle.
可选的,所述方法还包括:获取所述车辆的风阻信息;根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息。Optionally, the method further includes: acquiring wind resistance information of the vehicle; and determining policy information for adjusting the suspension system of the vehicle according to the forward road condition prediction information, current driving road condition information and wind resistance information.
可选的,所述获取所述车辆的风阻信息,包括:获取所述车辆的速度信息和形状结构信息;将所述车辆的速度信息和形状结构信息输入预设的风阻模型,得到所述车辆的风阻信息。Optionally, the obtaining the wind resistance information of the vehicle includes: obtaining speed information and shape structure information of the vehicle; inputting the speed information and shape structure information of the vehicle into a preset wind resistance model to obtain the vehicle wind resistance information.
可选的,所述根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息,包括:将所述前方路况预测信息、当前行驶路况信息和风阻信息输入预先训练得到的策略确定模型,得到对所述车辆的悬挂系统进行调整的策略信息。Optionally, determining the strategy information for adjusting the suspension system of the vehicle according to the forward road condition prediction information, the current driving road condition information and the wind resistance information, including: combining the forward road condition prediction information, the current driving road condition information and wind resistance information is input into a pre-trained strategy determination model to obtain strategy information for adjusting the suspension system of the vehicle.
可选的,所述策略确定模型是采用如下过程对神经网络的训练得到:获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据、当前行驶路况样本数据、速度样本数据和车辆形状结构信息;将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述策略确定模型。Optionally, the strategy determination model is obtained by training a neural network by adopting the following process: acquiring training sample data and adjustment strategy labeling information corresponding to the training sample data, the training sample data including sample data of road conditions ahead, current driving Road condition sample data, speed sample data and vehicle shape and structure information; take the training sample data as the input of the neural network, take the adjustment strategy labeling information as the output of the neural network, and perform iterative training on the neural network to obtain The policy determines the model.
可选的,所述根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息,包括:若所述前方路况预测信息指示路段平稳、当前行驶路况信息指示路段平稳并且风阻信息指示风阻持续增大,则确定调高所述车辆的悬挂系统的阻尼系数和调低悬挂高度。Optionally, determining the strategy information for adjusting the suspension system of the vehicle according to the forecast information of road conditions ahead, current driving road condition information and wind resistance information, including: if the forecast information of road conditions ahead indicates that the road section is stable and the current If the driving road condition information indicates that the road section is stable and the wind resistance information indicates that the wind resistance continues to increase, it is determined to increase the damping coefficient of the suspension system of the vehicle and to lower the suspension height.
本申请实施例通过在姿态信息的基础上结合风阻信息能够从不同角度确定车辆当前的状态,再结合前方路况预测信息,可以对车辆做出更加适合当前场景的调整策略信息,以对车辆进行调整,调整后的舒适度能够更好地满足乘客对于平稳性的要求。In the embodiment of the present application, the current state of the vehicle can be determined from different angles by combining the wind resistance information on the basis of the attitude information, and then combined with the forward road condition prediction information, the adjustment strategy information more suitable for the current scene can be made for the vehicle to adjust the vehicle. , the adjusted comfort can better meet the passengers' requirements for stability.
第二方面,本申请实施例提供了一种车辆行驶平稳性控制装置,包括:获取模块,用于获取所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息;策略确定模块,根据所述前方路况预测信息和当前行驶路况信息,确定所述车辆的悬挂系统进行调整的策略信息;调整模块,用于根据所述策略信息,对所述车辆的悬挂系统进行调整。In a second aspect, an embodiment of the present application provides a vehicle driving stability control device, including: an acquisition module for acquiring forward road condition prediction information and current driving road condition information of the vehicle during driving; a strategy determination module, according to The forward road condition prediction information and the current driving road condition information determine strategy information for adjusting the suspension system of the vehicle; an adjustment module is used to adjust the suspension system of the vehicle according to the strategy information.
第三方面,本申请实施例提供了一种车辆行驶平稳性控制设备,包括:In a third aspect, an embodiment of the present application provides a vehicle driving stability control device, including:
至少一个处理器;以及at least one processor; and
与所述至少一个处理器通信连接的存储器;其中,a memory communicatively coupled to the at least one processor; wherein,
所述存储器存储有可被所述至少一个处理器执行的指令,所述指令被所述至少一个处理器执行,以使所述至少一个处理器能够执行第一方面所述的方法。The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.
第四方面,本申请实施例提供了一种车辆,包括第三方面所述的车辆行驶平稳性控制设备。In a fourth aspect, an embodiment of the present application provides a vehicle, including the vehicle driving stability control device described in the third aspect.
可选的,所述车辆还包括:图像采集单元,用于在车辆行驶过程中采集车辆周围环境的环境图像;惯性测量单元,用于在车辆行驶过程中采集所述车辆的姿态信息。Optionally, the vehicle further includes: an image acquisition unit for acquiring an environment image of the surrounding environment of the vehicle during the running of the vehicle; and an inertial measurement unit for acquiring the attitude information of the vehicle during the running of the vehicle.
可选的,所述车辆还包括:速度传感器,用于在车辆行驶过程中采集所述车辆的速度信息。Optionally, the vehicle further includes: a speed sensor, configured to collect speed information of the vehicle during the running process of the vehicle.
第五方面,本申请实施例提供了一种存储有计算机指令的非瞬时计算机可读存储介质,所述计算机指令用于使所述计算机执行第一方面所述的方法。In a fifth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause the computer to execute the method of the first aspect.
上述申请中的一个实施例具有如下优点或有益效果:通过获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息,并根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。因为采用获取能够指示车辆在行驶过程中的当前行驶路况信息,和对车辆行驶过程中前方路况的预测信息,以及根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整的技术手段,所以克服了现有技术进行车辆平稳行驶控制时,时常出现调整滞后的现象,导致调整后的舒适度也时常不能满足乘客对于平稳性的要求的技术问题,进而达到及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度的技术效果。An embodiment in the above application has the following advantages or beneficial effects: by acquiring the predicted information of the road conditions ahead and the information of the current road conditions during the driving process of the vehicle, and according to the predicted information of the road conditions ahead and the information of the current road conditions, the suspension system of the vehicle is determined. The adjusted strategy information, and according to the strategy information, the vehicle suspension system is adjusted to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort. Because it adopts the acquisition of information that can indicate the current driving conditions of the vehicle during driving, and the prediction information of the road conditions ahead during the driving process of the vehicle, and determines the strategy of adjusting the suspension system of the vehicle according to the forecast information of the road conditions ahead and the information of the current driving road conditions. information, and the technical means to adjust the suspension system of the vehicle according to the strategy information, so it overcomes the phenomenon that the adjustment lag often occurs when the existing technology controls the smooth running of the vehicle, resulting in the adjusted comfort level that often cannot satisfy the passengers' concern for the vehicle. The technical problem of the requirements of stability, and then achieve the strategy information to adjust the suspension system of the vehicle in time, so that the suspension system of the vehicle can be adjusted to the state of the road ahead in time, so that the vehicle can run smoothly and improve the technology of riding comfort. Effect.
上述可选方式所具有的其他效果将在下文中结合具体实施例加以说明。Other effects of the above-mentioned optional manners will be described below with reference to specific embodiments.
附图说明Description of drawings
附图用于更好地理解本方案,不构成对本申请的限定。其中:The accompanying drawings are used for better understanding of the present solution, and do not constitute a limitation to the present application. in:
图1是本申请实施例提供的车辆悬挂系统结构图;1 is a structural diagram of a vehicle suspension system provided by an embodiment of the present application;
图2是本申请实施例提供的车辆平稳行驶控制方法的流程图;FIG. 2 is a flowchart of a vehicle smooth running control method provided by an embodiment of the present application;
图3是本申请实施例提供的车辆的控制逻辑示意图;3 is a schematic diagram of a control logic of a vehicle provided by an embodiment of the present application;
图4是本申请一示例提供的车辆平稳行驶控制方法的示意图;FIG. 4 is a schematic diagram of a vehicle smooth running control method provided by an example of the present application;
图5是本申请一示例提供的车辆平稳行驶控制方法的示意图;FIG. 5 is a schematic diagram of a vehicle smooth running control method provided by an example of the present application;
图6是本申请另一实施例提供的车辆平稳行驶控制方法的流程图;FIG. 6 is a flowchart of a method for controlling a smooth running of a vehicle provided by another embodiment of the present application;
图7是本申请一示例提供的车辆平稳行驶控制方法的示意图;FIG. 7 is a schematic diagram of a vehicle smooth running control method provided by an example of the present application;
图8是本申请实施例提供的车辆平稳行驶控制装置的结构示意图;8 is a schematic structural diagram of a vehicle smooth running control device provided by an embodiment of the present application;
图9是本申请实施例提供的车辆平稳行驶控制设备的框图。FIG. 9 is a block diagram of a vehicle smooth running control device provided by an embodiment of the present application.
具体实施方式Detailed ways
图1是本申请实施例提供的车辆悬挂系统结构图。如图1所示,车辆10上设置有悬挂系统11,悬挂系统包括相应的控制参数,通过对悬挂系统的控制参数进行调节,可以改善乘坐的舒适度。悬挂系统的控制参数包括阻尼系数和悬挂高度。FIG. 1 is a structural diagram of a vehicle suspension system provided by an embodiment of the present application. As shown in FIG. 1 , the
其中,阻尼系数的调节可以通过对悬挂系统11中弹簧12的弹性系数进行调节来实现。例如高速行驶时悬挂系统的弹簧可以变硬,也就是调高阻尼系数,以提高车身稳定性,而长时间低速行驶时,车辆的控制单元会认为车辆正在经过颠簸路面,又可以将悬挂变软,也就是调低阻尼系数,来减震提高舒适性。The adjustment of the damping coefficient can be realized by adjusting the elastic coefficient of the
另外,悬挂系统的悬挂高度可以理解为车辆底盘与地面之间的距离,通过调节悬挂系统的悬挂高度可以使车辆底盘升高或降低。在不同的场景中,不同的悬挂高度可以带来不同的乘坐感受,例如,在崎岖山路上行驶时,可以调高悬挂高度,使车辆底盘与地面之间的距离增大,从而使乘客的乘坐感受不那么颠簸。而在高速公路上行驶时,可以调低悬挂高度,使车辆底盘与地面之间的距离减小,可以增加轮胎的抓地能力,并且减小风阻,有利于车辆行驶的安全和稳定性,并且油耗也会随着风阻的降低而减少。In addition, the suspension height of the suspension system can be understood as the distance between the vehicle chassis and the ground, and the vehicle chassis can be raised or lowered by adjusting the suspension height of the suspension system. In different scenarios, different suspension heights can bring different riding experiences. For example, when driving on rough mountain roads, the suspension height can be increased to increase the distance between the vehicle chassis and the ground, so that passengers can ride more comfortably. Feels less bumpy. When driving on the highway, the suspension height can be lowered to reduce the distance between the vehicle chassis and the ground, which can increase the grip ability of the tires and reduce the wind resistance, which is beneficial to the safety and stability of the vehicle. Fuel consumption also decreases with the reduction in wind resistance.
对于悬挂高度的调节,针对不同类型的悬挂系统,调节方式不同,以空气悬挂系统为例,空气悬挂系统一般采用空气弹簧,可以通过对空气弹簧进行充气或放气,来调整悬挂系统的悬挂高度。对于其他类型的悬挂系统的悬挂高度的调节,可以参见现有技术的介绍,此处不再一一介绍。For the adjustment of the suspension height, the adjustment methods are different for different types of suspension systems. Taking the air suspension system as an example, the air suspension system generally uses an air spring, and the suspension height of the suspension system can be adjusted by inflating or deflating the air spring. . For the adjustment of the suspension height of other types of suspension systems, reference may be made to the introduction of the prior art, which will not be introduced one by one here.
现有技术中,仅仅依赖速度或惯性测量单元采集的数据对车辆进行调整,而速度和惯性测量单元采集的数据只能表征车辆行驶的历史状态或当前状态,在根据车辆的历史状态和当前状态对车辆进行调整时,如果车辆当前行驶路段和前方路段的路况一致,这种调节方式就没有问题,而一旦前方路段的路况和当前行驶路段的路况不一致,就会出现调节滞后的现象,导致车辆平稳性较低,乘客乘坐体验不好,舒适度不高。本申请在车辆行驶过程中,对车辆平稳性进行控制的过程中,通过提前感知前方路况,增加对前方路况的预测信息,再结合当前行驶路况,确定出对车辆的悬挂系统在未来时刻的状态进行调整的策略信息,以使车辆根据该策略信息,对车辆的悬挂系统进行调整,从而对车辆及时调整,以使车辆的悬挂系统的设置参数能够适应前方路况,达到使车辆平稳行驶的效果。In the prior art, only the data collected by the speed or inertial measurement unit is used to adjust the vehicle, and the data collected by the speed and inertial measurement unit can only represent the historical state or current state of the vehicle. When adjusting the vehicle, if the road conditions of the current driving section of the vehicle and the road section ahead are the same, this adjustment method is no problem, but once the road conditions of the road section ahead and the road conditions of the current driving section are inconsistent, there will be a phenomenon of adjustment lag, resulting in the vehicle The stability is low, the passenger experience is not good, and the comfort is not high. In the process of controlling the stability of the vehicle during the driving process of the vehicle, the present application detects the road conditions ahead, increases the prediction information of the road conditions ahead, and then combines the current driving road conditions to determine the status of the suspension system of the vehicle at the future time. The adjusted policy information enables the vehicle to adjust the vehicle's suspension system according to the policy information, so as to adjust the vehicle in time so that the setting parameters of the vehicle's suspension system can adapt to the road conditions ahead and achieve the effect of making the vehicle run smoothly.
以下将结合附图对本申请的示范性实施例做出详细说明,其中包括本申请实施例的各种细节以助于理解,应当将它们认为仅仅是示范性的。因此,本领域普通技术人员应当认识到,可以对这里描述的实施例做出各种改变和修改,而不会背离本申请的范围和精神。同样,为了清楚和简明,以下的描述中省略了对公知功能和结构的描述。Exemplary embodiments of the present application will be described in detail below with reference to the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.
图2是本申请实施例提供的车辆行驶平稳性控制方法的流程图。FIG. 2 is a flowchart of a vehicle driving stability control method provided by an embodiment of the present application.
本申请实施例针对现有技术的如上技术问题,提供了车辆行驶平稳性控制方法,该方法具体步骤如下:In view of the above technical problems in the prior art, the embodiments of the present application provide a vehicle driving stability control method. The specific steps of the method are as follows:
步骤201、获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息。Step 201: Acquire forward road condition prediction information and current driving road condition information of the vehicle during driving.
如图3所示,本是实施例的车辆包括中控系统31,还包括多种类型的传感器:图像采集设备32、惯性测量单元(Inertial Measurement Unit,IMU)33和速度传感器34等。该车辆可以是无人驾驶车辆,也可以是安装有高级驾驶辅助系统(Advanced DrivingAssistance System,ADAS)的车辆,无论是无人驾驶车辆,还是安装有ADAS的车辆,都可以适用于图3所示的结构。As shown in FIG. 3 , the vehicle of this embodiment includes a
其中,图像采集设备可以是车载相机,用于对车辆行驶过程中的周围环境进行拍摄,得到环境图像,通过对环境图像进行分析处理,可以获得车辆前方路况预测信息。The image acquisition device may be a vehicle-mounted camera, which is used for photographing the surrounding environment during the driving of the vehicle to obtain an environmental image, and by analyzing and processing the environmental image, the prediction information of the road condition in front of the vehicle can be obtained.
惯性测量单元,用于采集车辆行驶过程中的姿态信息,其中,车辆的姿态信息可以理解为车辆的姿态角,包括车辆的横滚角(roll角)、俯仰角(pitch角)和航向角(yaw角)。车辆的姿态角可以表征车辆与路面之间的倾角,根据车辆的当前姿态角和历史姿态角,可以确定车辆当前所处的路况。例如,若车辆持续在平稳路段上行驶,车辆与路面之间的倾角的变化量应当为恒定值,而若车辆持续在颠簸路段上行驶,则车辆与路面之间的倾角的变化量就会发生变化。据此原理,可以根据姿态角确定当前路况信息。其中,对于横滚角(roll角)、俯仰角(pitch角)和航向角(yaw角)的具体定义可以参见现有技术的介绍,此处不再赘述。The inertial measurement unit is used to collect attitude information during the driving process of the vehicle, wherein the attitude information of the vehicle can be understood as the attitude angle of the vehicle, including the roll angle (roll angle), pitch angle (pitch angle) and heading angle ( yaw angle). The attitude angle of the vehicle can represent the inclination angle between the vehicle and the road surface, and the current road condition of the vehicle can be determined according to the current attitude angle and the historical attitude angle of the vehicle. For example, if the vehicle continues to drive on a smooth road section, the amount of change in the inclination angle between the vehicle and the road surface should be a constant value, while if the vehicle continues to drive on a bumpy road section, the amount of change in the inclination angle between the vehicle and the road surface will occur. Variety. According to this principle, the current road condition information can be determined according to the attitude angle. For the specific definitions of the roll angle (roll angle), the pitch angle (pitch angle) and the yaw angle (yaw angle), reference may be made to the introduction of the prior art, and details are not repeated here.
本实施例的执行主体可以是车辆的中控系统,在一种可选的实施方式中,可以由车辆的中控系统从图像采集设备和IMU分别获取环境图像和姿态角,并分别根据环境图像和姿态角确定车辆行驶过程中的前方路况预测信息和当前路况信息。The execution subject of this embodiment may be the central control system of the vehicle. In an optional implementation manner, the central control system of the vehicle may obtain the environmental image and the attitude angle from the image acquisition device and the IMU, respectively, and obtain the environmental image and attitude angle according to the environmental image. and attitude angle to determine the forward road condition prediction information and current road condition information during the driving process of the vehicle.
步骤202、根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息。Step 202: Determine strategy information for adjusting the suspension system of the vehicle according to the forecast information of the road conditions ahead and the current driving road condition information.
本实施例中,中控系统在获取到前方路况预测信息和当前行驶路况信息之后,可以根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统的阻尼系数和/或悬挂高度进行调整的策略信息。而根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统的阻尼系数和/或悬挂高度进行调整的策略信息,至少可以包括如下几种可选的场景:In this embodiment, after the central control system obtains the forward road condition prediction information and the current driving road condition information, it may determine to adjust the damping coefficient and/or the suspension height of the vehicle's suspension system according to the forward road condition prediction information and the current driving road condition information policy information. The strategy information for adjusting the damping coefficient and/or the suspension height of the suspension system of the vehicle is determined according to the forecast information of the road conditions ahead and the current driving road condition information, which may include at least the following optional scenarios:
在第一种可选的场景下,若前方路况预测信息指示路面湿滑且当前行驶路况信息指示为平稳路段,则确定调低车辆的悬挂系统的悬挂高度。示例性地,若根据车载相机采集的环境图像得到的预测结果指示路面湿滑,且根据IMU采集的姿态信息得到的检测结果指示当前路段为平稳路段,则中控系统就会确定调低车辆的悬挂系统的悬挂高度的策略信息。In the first optional scenario, if the road condition prediction information ahead indicates that the road is slippery and the current driving road condition information indicates a smooth road section, it is determined to lower the suspension height of the suspension system of the vehicle. Exemplarily, if the prediction result obtained according to the environmental image collected by the on-board camera indicates that the road is slippery, and the detection result obtained according to the attitude information collected by the IMU indicates that the current road section is a stable road section, the central control system will determine to lower the vehicle's speed. Policy information for the suspension height of the suspension system.
在第二种可选的场景下,若前方路况预测信息指示路段颠簸且所述当前行驶路况信息指示当前路段的颠簸程度越来越大,则确定调低所述悬挂系统的阻尼系数并调高所述车辆的悬挂系统的悬挂高度。示例性地,若根据车载相机采集的环境图像得到的预测结果指示路段颠簸,且根据IMU采集的姿态信息得到的检测结果指示当前路段颠簸程度越来越大,则中控系统就会确定调低所述悬挂系统的阻尼系数并调高所述车辆的悬挂系统的悬挂高度的策略信息。In the second optional scenario, if the road condition prediction information ahead indicates that the road section is bumpy and the current driving road condition information indicates that the current road section is increasingly bumpy, it is determined to lower the damping coefficient of the suspension system and increase it The suspension height of the vehicle's suspension system. Exemplarily, if the prediction result obtained according to the environmental image collected by the on-board camera indicates that the road section is bumpy, and the detection result obtained according to the attitude information collected by the IMU indicates that the current road section is increasingly bumpy, the central control system will determine to lower the bump. The damping coefficient of the suspension system and the strategy information to increase the suspension height of the vehicle's suspension system.
在第三种可选的场景下,若前方路况预测信息指示前方路段存在减速带且当前行驶路况信息指示为平稳路段,则确定调低车辆的悬挂系统的悬挂高度。示例性地,若根据车载相机采集的环境图像得到的预测结果指示前方路段存在减速带,且根据IMU采集的姿态信息得到的检测结果指示当前路段为平稳路段,则中控系统就会确定调低车辆的悬挂系统的悬挂高度的策略信息。In a third optional scenario, if the forward road condition prediction information indicates that there is a speed bump on the preceding road section and the current driving road condition information indicates a stable road section, it is determined to lower the suspension height of the vehicle's suspension system. Exemplarily, if the prediction result obtained according to the environmental image collected by the vehicle-mounted camera indicates that there is a speed bump on the road ahead, and the detection result obtained according to the attitude information collected by the IMU indicates that the current road is a stable road, the central control system will determine to lower the speed. Policy information for the suspension height of the vehicle's suspension system.
步骤203、根据策略信息,对车辆的悬挂系统进行调整。Step 203: Adjust the suspension system of the vehicle according to the policy information.
中控系统确定对车辆的悬挂系统的阻尼系数和/或悬挂高度进行调整的策略信息之后,将该策略调整信息发送至调整系统。车辆的调整系统,例如悬挂系统的控制系统,在接收到对车辆的悬挂系统进行调整的策略信息之后,就会根据策略信息,对车辆的悬挂系统的阻尼系数和/或悬挂高度进行调整,以使悬挂系统的参数适应前方路况,使车辆平稳行驶,提高乘客乘坐舒适度。下面分别以上述三种场景为例说明调整系统如何对悬挂系统进行调整:After the central control system determines the strategy information for adjusting the damping coefficient and/or the suspension height of the suspension system of the vehicle, the strategy adjustment information is sent to the adjustment system. The adjustment system of the vehicle, such as the control system of the suspension system, after receiving the policy information for adjusting the suspension system of the vehicle, will adjust the damping coefficient and/or the suspension height of the suspension system of the vehicle according to the policy information, so as to The parameters of the suspension system are adapted to the road conditions ahead, so that the vehicle can run smoothly and improve the riding comfort of passengers. The following three scenarios are used as examples to illustrate how the adjustment system adjusts the suspension system:
对应上述第一种可选的场景,调整系统就会调低车辆的悬挂系统的悬挂高度,以使车辆重心降低,车辆整体更加贴地,从而平稳地通过湿滑路段。Corresponding to the above-mentioned first optional scenario, the adjustment system will lower the suspension height of the vehicle's suspension system, so that the vehicle's center of gravity is lowered, and the vehicle as a whole is closer to the ground, so as to smoothly pass through the slippery road section.
对应上述第二种可选的场景,调整系统就会调低悬挂系统的阻尼系数并调高车辆的悬挂系统的悬挂高度,从而使悬挂系统的弹簧弹性系数更低,弹簧更加松软,车辆底盘距离地面的高度更大,这样车辆在通过颠簸路段时,乘坐者就不会感觉到那么颠簸。Corresponding to the second optional scenario above, the adjustment system will reduce the damping coefficient of the suspension system and increase the suspension height of the vehicle's suspension system, so that the spring elastic coefficient of the suspension system is lower, the spring is softer, and the distance between the vehicle chassis is reduced. The height of the ground is higher so that the occupants feel less bumpy when the vehicle is passing through bumpy roads.
对应上述第三种可选的场景,调整系统就会调低车辆的悬挂系统的悬挂高度,车辆的晃动程度就不会太大,车辆的平稳性更高,乘坐者也不会感觉到剧烈晃动,舒适度更高。Corresponding to the above-mentioned third optional scenario, the adjustment system will lower the suspension height of the vehicle's suspension system, so that the degree of shaking of the vehicle will not be too large, the stability of the vehicle will be higher, and the occupants will not feel violent shaking. , more comfortable.
由于本实施例是根据前方路况预测信息和当前行驶路况信息做出的对车辆的悬挂系统进行调整的策略,前方路况预测信息是对前方路况的预测,因此,为了避免提前调整,还可以在接收到策略信息之后,间隔预设时间再对车辆的悬挂系统进行调整。其中,预设时间可以根据车辆与前方路段的距离,数据的采集、获取和策略确定等时间来设置。Since this embodiment is a strategy for adjusting the suspension system of the vehicle based on the forecast information of the ahead road condition and the current driving road condition information, and the forecast information of the ahead road condition is the forecast of the road condition ahead, therefore, in order to avoid the adjustment in advance, it is also possible to receive After the strategy information is received, the suspension system of the vehicle is adjusted at preset time intervals. The preset time may be set according to the distance between the vehicle and the road section ahead, the time for data collection, acquisition, and strategy determination.
本申请实施例通过获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息,并根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。In the embodiment of the present application, the vehicle's road condition prediction information and current driving road condition information are obtained during the driving process, and the strategy information for adjusting the suspension system of the vehicle is determined according to the forward road condition prediction information and the current driving road condition information, and according to the strategy information , Adjust the suspension system of the vehicle to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort.
以上实施例中介绍了由车辆的中控系统从图像采集设备和IMU分别获取环境图像和姿态角,并分别根据环境图像和姿态角获取车辆行驶过程中的前方路况预测信息和当前路况信息的实施方式。In the above embodiments, the implementation of obtaining the environmental image and attitude angle from the image acquisition device and the IMU respectively by the central control system of the vehicle, and obtaining the forecast information of the road conditions ahead and the current road condition information during the driving process of the vehicle according to the environmental image and the attitude angle, respectively, is introduced. Way.
而为了减少中控系统的计算压力,使得车辆调整更加及时,在另一种可选的实施方式中,也可以是通过中控系统之外的其他模块单元来从图像采集设备获取环境图像,并根据环境图像确定车辆行驶过程中的前方路况预测信息,以及从IMU获取姿态信息,并根据姿态信息确定车辆行驶过程中的当前路况信息。具体实施过程请参见如下内容的介绍:In order to reduce the calculation pressure of the central control system and make the vehicle adjustment more timely, in another optional implementation, other module units other than the central control system can also be used to obtain environmental images from the image acquisition device, and Determine the forward road condition prediction information during the vehicle driving process according to the environment image, obtain the attitude information from the IMU, and determine the current road condition information during the vehicle driving process according to the attitude information. For the specific implementation process, please refer to the following introduction:
针对车辆在行驶过程中的前方路况预测信息,可以通过如下方式来获取:获取车辆上的图像采集设备采集的车辆周围环境的环境图像;将环境图像输入预先训练得到的路况预测模型,得到车辆在行驶过程中的前方路况预测信息。其中,路况预测模型是采用获取车辆行驶过程中周围环境的环境样本图像以及环境样本图像对应的路况预测标注信息,和将环境样本图像作为神经网络的输入,将路况预测标注信息作为神经网络的输出,对神经网络进行迭代训练的过程对神经网络的训练得到的。本实施例中对神经网络的迭代训练过程可以参见现有技术的介绍,此处不再赘述。The prediction information of the road conditions ahead of the vehicle during the driving process can be obtained by the following methods: acquiring the environmental image of the surrounding environment of the vehicle collected by the image acquisition device on the vehicle; inputting the environmental image into the road condition prediction model obtained by pre-training, and obtaining Predicted information about road conditions ahead while driving. Among them, the road condition prediction model adopts the environment sample image of the surrounding environment during the driving of the vehicle and the road condition prediction label information corresponding to the environment sample image, and uses the environment sample image as the input of the neural network, and uses the road condition prediction label information as the output of the neural network. , which is obtained from the training of the neural network in the iterative training process of the neural network. For the iterative training process of the neural network in this embodiment, reference may be made to the introduction of the prior art, which will not be repeated here.
以图像采集设备是车载相机为例,如图4所示,车载相机不断采集车辆周围环境的环境图像,该环境图像中包括车辆前方道路,并输入路况预测模型,路况预测模型就会根据该环境图像,提取该环境图像中的特征图,并根据提取的特征图确定车辆前方路况预测信息并输出至中控系统。Taking the image acquisition device as an on-board camera as an example, as shown in Figure 4, the on-board camera continuously collects environmental images of the surrounding environment of the vehicle, including the road in front of the vehicle, and input the road condition prediction model, the road condition prediction model will be based on the environment. image, extract the feature map in the environment image, and determine the prediction information of the road condition ahead of the vehicle according to the extracted feature map and output it to the central control system.
针对车辆在行驶过程中的当前路况信息,可以采用如下方式来获取:根据预设时间段内车辆的姿态信息,确定姿态信息的变化量;在姿态信息的变化量大于预设变化量的情况下,确定当前行驶路况信息为不平稳路段;在姿态信息的变化量小于或等于预设变化量的情况下,确定当前行驶路况信息为平稳路段。The current road condition information during the driving process of the vehicle can be obtained in the following ways: determine the change amount of the attitude information according to the attitude information of the vehicle within the preset time period; when the change amount of the attitude information is greater than the preset change amount , determine that the current driving road condition information is an unstable road section; when the change amount of the attitude information is less than or equal to the preset change amount, determine that the current driving road condition information is a stable road section.
本实施方式中,预设变化量可以设置为0,考虑到实际应用过程中,可能会存在一些误差,因此,预设变化量可以设置为比0大的值,具体的值本领域技术人员可以根据实际情况进行设置。In this embodiment, the preset change amount can be set to 0. Considering that there may be some errors in the actual application process, the preset change amount can be set to a value larger than 0. The specific value can be determined by those skilled in the art. Set according to the actual situation.
以预设变化量是0为例,在T时间段内,T时间段按照时间先后顺序依次包括t1时刻、t2时刻、t3时刻、t4时刻、t5时刻,通过IMU可以得到t1时刻、t2时刻、t3时刻、t4时刻、t5时刻的姿态角,对t1时刻、t2时刻、t3时刻、t4时刻、t5时刻的姿态角进行分析,确定相邻时刻的姿态角变化量是否为0,若相邻时刻的姿态角均为0或者大部分均为0,则表示车辆当前行驶路况为平稳路段,否则,表示车辆当前行驶路况为不平稳路段。Taking the preset change amount of 0 as an example, in the T time period, the T time period includes time t1, time t2, time t3, time t4, and time t5 in chronological order. The IMU can obtain time t1, time t2, The attitude angles at time t3, time t4, and time t5, analyze the attitude angles at time t1, time t2, time t3, time t4, and time t5, and determine whether the change amount of the attitude angle at the adjacent time is 0. If the attitude angle of the vehicle is 0 or most of them are 0, it means that the current road condition of the vehicle is a stable road section, otherwise, it means that the current road condition of the vehicle is an unstable road section.
上述t1时刻、t2时刻、t3时刻、t4时刻、t5时刻可以是在连续时间序列,也可以是离散时间序列,本实施例对此不做具体限定。另外,本实施方式中的当前行驶路况信息可以根据1个姿态角分析得到,也可以根据2个或3个姿态角分析得到。在根据2个或3个姿态角分析当前行驶路况信息的情况下,则其中一个姿态角的变化量大于预设变化量,就认为当前行驶路况为不平稳路段。The foregoing time t1, time t2, time t3, time t4, and time t5 may be in a continuous time series, or may be a discrete time series, which is not specifically limited in this embodiment. In addition, the current driving road condition information in this embodiment may be obtained by analyzing one attitude angle, or may be obtained by analyzing two or three attitude angles. In the case of analyzing the current driving road condition information according to two or three attitude angles, if the variation of one of the attitude angles is greater than the preset variation, it is considered that the current driving road condition is an unstable road section.
针对车辆在行驶过程中的当前路况信息,除了上述根据预设变化量的方式来确定之外,还可以通过中控系统之外的其他模块单元来从IMU获取姿态角,并根据姿态角确定车辆行驶过程中的当前路况信息。具体实施过程请参见如下内容的介绍:For the current road condition information during the driving process of the vehicle, in addition to the above-mentioned determination based on the preset change amount, other module units other than the central control system can also obtain the attitude angle from the IMU, and determine the vehicle according to the attitude angle. Information about current road conditions while driving. For the specific implementation process, please refer to the following introduction:
请继续参阅图4,可以将车辆的姿态信息输入预先训练得到的路况检测模型,得到车辆的当前行驶路况信息。其中,路况检测模型是采用获取车辆行驶过程中的姿态样本数据以及所述姿态样本数据对应的当前行驶路况标注信息;和将所述姿态样本数据作为神经网络的输入,将所述当前行驶路况标注信息作为所述神经网络的输出,所述神经网络进行迭代训练得到的。其中,对神经网络的迭代训练过程可以参见现有技术的介绍,此处不再赘述。Please continue to refer to FIG. 4 , the attitude information of the vehicle can be input into the road condition detection model obtained by pre-training, and the current road condition information of the vehicle can be obtained. Wherein, the road condition detection model adopts the attitude sample data obtained during the driving of the vehicle and the current driving road condition annotation information corresponding to the attitude sample data; and the attitude sample data is used as the input of the neural network, and the current driving road condition is marked The information is used as the output of the neural network, which is obtained by iterative training of the neural network. For the iterative training process of the neural network, reference may be made to the introduction of the prior art, which will not be repeated here.
惯性测量单元IMU不断采集车辆的姿态角,并输入路况检测模型,路况检测模型根据车辆在一段时间内的姿态角,输出车辆当前行驶路况预测信息至中控系统。在车辆行驶过程中,车辆的中控系统可以从路况预测模型不断地获取车辆的前方路况预测信息,以及根据IMU采集的车辆在一段时间内的姿态角确定的车辆当前所处路况,或者从路况检测模型不断地获取车辆的当前行驶路况信息。相较于直接使中控系统根据姿态角确定当前行驶路况信息的实施方式而言,采用路况检测模型的方式可以减少中控系统的计算压力,使得车辆调整更加及时。The inertial measurement unit IMU continuously collects the attitude angle of the vehicle and inputs the road condition detection model. The road condition detection model outputs the prediction information of the current driving road condition of the vehicle to the central control system according to the attitude angle of the vehicle within a period of time. During the driving process of the vehicle, the central control system of the vehicle can continuously obtain the prediction information of the road condition ahead of the vehicle from the road condition prediction model, as well as the current road condition of the vehicle determined according to the attitude angle of the vehicle collected by the IMU over a period of time, or from the road condition The detection model continuously obtains information about the current driving conditions of the vehicle. Compared with the implementation in which the central control system directly determines the current driving road condition information according to the attitude angle, the method of using the road condition detection model can reduce the calculation pressure of the central control system and make the vehicle adjustment more timely.
对于自动驾驶而言,在策略信息的确定过程中,策略的准确度至关重要,策略的准确度的高低决定了车辆行驶的安全性,因此,为了提高策略的准确度,还可以将车辆在行驶过程中的前方路况预测信息和当前行驶路况信息输入预先训练得到的策略确定模型,得到对车辆的悬挂系统进行调整的策略信息。其中,策略确定模型是采用获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据和当前行驶路况样本数据;以及将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练得到的。For automatic driving, in the process of determining policy information, the accuracy of the policy is very important, and the accuracy of the policy determines the safety of the vehicle. Therefore, in order to improve the accuracy of the policy, the vehicle can also be The forward road condition prediction information and the current driving road condition information during the driving process are input into the strategy determination model obtained by pre-training, and the strategy information for adjusting the suspension system of the vehicle is obtained. Wherein, the strategy determination model adopts the acquisition of training sample data and the adjustment strategy annotation information corresponding to the training sample data, the training sample data includes the sample data of the road conditions ahead and the sample data of the current driving road condition; and the training sample data is used as the neural network The input of the network is obtained by iteratively training the neural network by using the adjustment strategy annotation information as the output of the neural network.
示例性地,如图4所示,中控系统在获取到前方路况预测信息和当前行驶路况信息之后,将前方路况预测信息和当前行驶路况信息输入策略确定模型,策略确定模型就会输出相应的对车辆的悬挂系统进行调整的策略信息。当然,策略确定模型也可以是独立于中控系统之外,本领域技术人员可以根据实际情况进行相应设置,本实施例对此不作具体限定。Exemplarily, as shown in FIG. 4 , after obtaining the forecast information of the road conditions ahead and the information of the current driving road conditions, the central control system inputs the forecast information of the road conditions ahead and the information of the current road conditions into the strategy determination model, and the strategy determination model will output the corresponding information. Policy information for making adjustments to the vehicle's suspension system. Of course, the policy determination model may also be independent of the central control system, and those skilled in the art may perform corresponding settings according to the actual situation, which is not specifically limited in this embodiment.
示例性地,如图5所示,若路况预测模型根据车载相机采集的环境图像得到的预测结果指示路面湿滑,且路况检测模型根据IMU采集的姿态信息得到的检测结果指示当前路段为平稳路段,则中控系统就会确定调低车辆的悬挂系统的悬挂高度的策略信息,调整系统根据该策略信息调低车辆的悬挂系统的悬挂高度的策略信息。Exemplarily, as shown in FIG. 5 , if the prediction result obtained by the road condition prediction model according to the environmental image collected by the vehicle-mounted camera indicates that the road is slippery, and the detection result obtained by the road condition detection model according to the attitude information collected by the IMU indicates that the current road section is a stable road section , the central control system will determine the strategy information for lowering the suspension height of the vehicle's suspension system, and the adjustment system adjusts the strategy information for lowering the suspension height of the vehicle's suspension system according to the strategy information.
在上述实施例的基础上,还可以融合更多的传感器数据,例如车辆上的速度传感器采集的车辆速度数据,来确定对车辆的悬挂系统进行调整的策略信息。具体请参见如下实施例的介绍:On the basis of the above embodiment, more sensor data, such as vehicle speed data collected by a speed sensor on the vehicle, may also be fused to determine policy information for adjusting the suspension system of the vehicle. For details, please refer to the introduction of the following embodiments:
图6为本申请另一实施例提供的车辆行驶平稳性控制方法流程图。在上述实施例的基础上,本实施例提供的车辆行驶平稳性控制方法具体包括如下步骤:FIG. 6 is a flowchart of a vehicle driving stability control method provided by another embodiment of the present application. On the basis of the above embodiments, the vehicle driving stability control method provided in this embodiment specifically includes the following steps:
步骤601、获取车辆在行驶过程中的前方路况预测信息、当前行驶路况信息和风阻信息。Step 601: Acquire forward road condition prediction information, current driving road condition information and wind resistance information during the driving process of the vehicle.
其中,对于获取车辆在行驶过程中的前方路况预测信息、当前行驶路况信息,可以参考前述实施例的介绍,此处不再赘述。Wherein, for obtaining the predicted information of the road conditions ahead and the information of the current road conditions during the driving of the vehicle, reference may be made to the introduction of the foregoing embodiments, which will not be repeated here.
本实施例相较于前述实施例,增加了风阻信息,风阻信息是指车辆行驶过程中来自空气的阻力,风阻信息可以根据车辆的速度信息和形状结构信息确定。车辆的形状结构信息是指车辆的外形结构,例如车辆的尺寸(包括长度、宽度和高度)和流线结构。车辆的形状结构信息可以预先存储在车辆上,车辆的速度可以通过车辆上安装的速度传感器来采集得到。Compared with the previous embodiments, this embodiment adds wind resistance information. The wind resistance information refers to the resistance from the air during the running of the vehicle. The wind resistance information can be determined according to the speed information and shape structure information of the vehicle. The shape structure information of the vehicle refers to the shape structure of the vehicle, such as the size (including length, width and height) and streamline structure of the vehicle. The shape and structure information of the vehicle can be pre-stored on the vehicle, and the speed of the vehicle can be collected by a speed sensor installed on the vehicle.
通常来说,相同的车辆形状结构,车辆速度越大,风阻越大;而相同的车辆速度,车辆形状结构的尺寸越大,风阻越大。Generally speaking, for the same vehicle shape and structure, the greater the vehicle speed, the greater the wind resistance; and the same vehicle speed, the larger the size of the vehicle shape structure, the greater the wind resistance.
为了能够方便且快速地确定车辆当前的风阻信息,可以将车辆的速度信息和形状结构信息输入预设的风阻模型,得到车辆的风阻信息。其中,预设的风阻模型是根据车辆的速度信息和形状结构信息,以及对应的风阻信息建模得到。中控系统可以从风阻模型获取车辆当前的风阻信息。In order to conveniently and quickly determine the current wind resistance information of the vehicle, the speed information and shape structure information of the vehicle can be input into a preset wind resistance model to obtain the wind resistance information of the vehicle. The preset wind resistance model is obtained by modeling based on the speed information, shape and structure information of the vehicle, and corresponding wind resistance information. The central control system can obtain the current wind resistance information of the vehicle from the wind resistance model.
步骤602、根据前方路况预测信息、当前行驶路况信息和风阻信息,确定对车辆的悬挂系统进行调整的策略信息。Step 602: Determine strategy information for adjusting the suspension system of the vehicle according to the forecast information of the road conditions ahead, the current driving road condition information and the wind resistance information.
在一个可选的场景中,若前方路况预测信息指示路段平稳、当前行驶路况信息指示路段平稳并且风阻信息指示风阻持续增大,则确定调高车辆的悬挂系统的阻尼系数和悬挂高度。In an optional scenario, if the forward road condition prediction information indicates that the road section is stable, the current driving road condition information indicates that the road section is stable, and the wind resistance information indicates that the wind resistance continues to increase, it is determined to increase the damping coefficient and suspension height of the vehicle's suspension system.
在通过模型结合前方路况预测信息、当前行驶路况信息确定策略信息的方式的基础上,本实施例还可以将前方路况预测信息、当前行驶路况信息和风阻信息输入预先训练得到的策略确定模型,得到对所述车辆的悬挂系统进行调整的策略信息。相较于前述实施例的策略确定模型而言,本实施例中的策略确定模型是采用获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据、当前行驶路况样本数据、速度样本数据和车辆形状结构信息;以及将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练的方式得到的。其中,对于神经网络的具体训练过程可以参见现有技术的介绍,本实施例不再详细介绍。Based on the method of determining the strategy information by combining the forecast information of the forward road condition and the current driving road condition information through the model, this embodiment can also input the forecast information of the forward road condition, the current driving road condition information and the wind resistance information into the strategy determination model obtained by pre-training, and obtain Policy information for making adjustments to the vehicle's suspension system. Compared with the strategy determination model of the previous embodiment, the strategy determination model in this embodiment adopts the method of acquiring training sample data and adjustment strategy annotation information corresponding to the training sample data, and the training sample data includes the road condition sample data ahead. , current driving road condition sample data, speed sample data and vehicle shape and structure information; and using the training sample data as the input of the neural network, using the adjustment strategy labeling information as the output of the neural network, and performing the neural network obtained by iterative training. For the specific training process of the neural network, reference may be made to the introduction of the prior art, which is not described in detail in this embodiment.
其中,训练好的策略确定模型可以存储在中控系统中,当中控系统获取到前方路况预测信息、当前行驶路况信息和风阻信息之后,将前方路况预测信息、当前行驶路况信息和风阻信息输入训练好的策略确定模型,策略确定模型就会输出对车辆的悬挂系统进行调整的策略信息。该策略信息会发送至调整系统,例如悬挂系统的控制系统,以控制悬挂系统进行相应调整。Among them, the trained strategy determination model can be stored in the central control system. After the central control system obtains the forward road condition prediction information, the current driving road condition information and the wind resistance information, the forward road condition prediction information, the current driving road condition information and the wind resistance information are input into the training A good policy determination model will output policy information for adjusting the vehicle's suspension system. This strategy information is sent to a tuning system, such as the control system of the suspension system, to control the suspension system to adjust accordingly.
步骤603、根据策略信息,对车辆的悬挂系统进行调整。Step 603: Adjust the suspension system of the vehicle according to the policy information.
车辆的调整系统,例如悬挂系统的控制系统,在接收到对车辆的悬挂系统进行调整的策略信息之后,就会根据策略信息,对车辆的悬挂系统的阻尼系数和/或悬挂高度进行调整,以使悬挂系统的参数适应前方路况,使车辆平稳行驶,提高乘客乘坐舒适度。The adjustment system of the vehicle, such as the control system of the suspension system, after receiving the policy information for adjusting the suspension system of the vehicle, will adjust the damping coefficient and/or the suspension height of the suspension system of the vehicle according to the policy information, so as to The parameters of the suspension system are adapted to the road conditions ahead, so that the vehicle can run smoothly and improve the riding comfort of passengers.
示例性地,如图7所示,将图像采集设备获取的环境图像输入路况预测模型,将IMU采集的姿态信息输入路况检测模型,以及将车辆速度输入风阻模型,若路况预测模型预测的前方路况预测信息指示路段平稳、路况检测模型输出的当前行驶路况信息指示路段平稳,并且风阻模型输出的风阻信息指示风阻持续增大,则策略确定模型根据路况预测模型、路况检测模型和风阻模型的输出,确定调高车辆的悬挂系统的阻尼系数和调低悬挂高度的策略信息,并发送至调整系统,以使调整系统调高车辆的悬挂系统的阻尼系数和调低悬挂高度,则车辆的重心会降低,更加贴地,降低对车辆的风阻,使车辆更加平稳地行驶。Exemplarily, as shown in FIG. 7 , the environmental image acquired by the image acquisition device is input into the road condition prediction model, the attitude information collected by the IMU is input into the road condition detection model, and the vehicle speed is input into the wind resistance model. The prediction information indicates that the road section is stable, the current driving road condition information output by the road condition detection model indicates that the road section is stable, and the wind resistance information output by the wind resistance model indicates that the wind resistance continues to increase, then the strategy determination model is based on the output of the road condition prediction model, road condition detection model and wind resistance model, Determine the strategy information of raising the damping coefficient of the vehicle's suspension system and lowering the suspension height, and send it to the adjustment system, so that the adjustment system can increase the damping coefficient of the vehicle's suspension system and lower the suspension height, and the center of gravity of the vehicle will be lowered. , more close to the ground, reduce the wind resistance to the vehicle, and make the vehicle run more smoothly.
本申请实施例通过获取车辆在行驶过程中的前方路况预测信息、当前行驶路况信息和当前风阻信息,并根据前方路况预测信息、当前行驶路况信息和当前风阻信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。另外,根据姿态信息和风阻信息能够从不同角度确定车辆当前的状态,再结合前方路况预测信息,可以对车辆做出更加适合当前场景的调整策略信息,以对车辆进行调整,调整后的舒适度能够更好地满足乘客对于平稳性的要求。In the embodiment of the present application, the vehicle suspension system is determined to be adjusted according to the ahead road condition prediction information, the current driving road condition information and the current wind resistance information by acquiring the forward road condition prediction information, the current driving road condition information and the current wind resistance information during the driving process of the vehicle. According to the strategy information, the suspension system of the vehicle is adjusted to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort. In addition, according to the attitude information and wind resistance information, the current state of the vehicle can be determined from different angles, and combined with the forecast information of the road conditions ahead, the vehicle can make adjustment strategy information more suitable for the current scene, so as to adjust the vehicle and adjust the comfort level. It can better meet passengers' requirements for stability.
图8为本申请实施例提供的车辆行驶平稳性控制装置流程图。本实施例的车辆行驶平稳性控制装置,可以是上述实施例的中控系统中的模块,在上述实施例的基础上,本实施例提供的车辆行驶平稳性控制装置包括:获取模块81、策略确定模块82和调整模块83;其中,获取模块81,用于获取所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息;策略确定模块82,根据所述前方路况预测信息和当前行驶路况信息,确定所述车辆的悬挂系统进行调整的策略信息;调整模块83,用于根据所述策略信息,对所述车辆的悬挂系统进行调整。FIG. 8 is a flowchart of a vehicle driving stability control device provided by an embodiment of the present application. The vehicle driving stability control device of this embodiment may be a module in the central control system of the above-mentioned embodiment. On the basis of the above-mentioned embodiment, the vehicle driving stability control device provided by this embodiment includes: an
可选的,获取模块81获取所述车辆在行驶过程中的前方路况预测信息,包括:获取所述车辆上的图像采集设备采集的所述车辆周围环境的环境图像;将所述环境图像输入预先训练得到的路况预测模型,得到所述车辆在行驶过程中的前方路况预测信息。Optionally, the acquiring
可选的,该装置还包括第一训练模块84,所述第一训练模块84是采用如下过程对神经网络的训练得到路况预测模型的:获取车辆行驶过程中周围环境的环境样本图像以及所述环境样本图像对应的路况预测标注信息;将所述环境样本图像作为神经网络的输入,将所述路况预测标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述路况预测模型。Optionally, the device further includes a first training module 84, and the first training module 84 uses the following process to train the neural network to obtain the road condition prediction model: obtaining the environmental sample images of the surrounding environment during the driving of the vehicle and the Road condition prediction annotation information corresponding to the environmental sample image; the environmental sample image is used as the input of the neural network, the road condition prediction annotation information is used as the output of the neural network, and the neural network is iteratively trained to obtain the road condition prediction model.
可选的,所述获取模块81获取所述车辆的当前行驶路况信息,具体包括:获取所述车辆上的惯性测量单元采集的所述车辆的姿态信息;根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息。Optionally, the obtaining
可选的,所述获取模块81根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息,包括:根据预设时间段内所述车辆的姿态信息,确定所述姿态信息的变化量;在所述姿态信息的变化量大于预设变化量的情况下,确定当前行驶路况信息为不平稳路段;在所述姿态信息的变化量小于或等于预设变化量的情况下,确定当前行驶路况信息为平稳路段。Optionally, the obtaining
可选的,所述获取模块81根据所述车辆的姿态信息,确定所述车辆的当前行驶路况信息,包括:将所述车辆的姿态信息输入预先训练得到的路况检测模型,得到所述车辆的当前行驶路况信息。Optionally, the obtaining
可选的,该装置还包括第二训练模块85,所述第二训练模块85是采用如下过程对神经网络的训练得到路况检测模型的:获取所述车辆行驶过程中的姿态样本数据以及所述姿态样本数据对应的当前行驶路况标注信息;将所述姿态样本数据作为神经网络的输入,将所述当前行驶路况标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述路况检测模型。Optionally, the device further includes a
可选的,所述策略确定模块82根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,具体包括:将所述车辆在行驶过程中的前方路况预测信息和当前行驶路况信息输入预先训练得到的策略确定模型,得到对所述车辆的悬挂系统进行调整的策略信息。Optionally, the
可选的,该装置还包括:第三训练模块86,第三训练模块86是采用如下过程对神经网络的训练得到所述策略确定模型的:获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据和当前行驶路况样本数据;将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述策略确定模型。Optionally, the device further includes: a
可选的,所述策略确定模块82根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,具体包括:若所述前方路况预测信息指示路面湿滑且所述当前行驶路况信息指示为平稳路段,则确定调低所述车辆的悬挂系统的悬挂高度。Optionally, the
可选的,所述策略确定模块82根据所述前方路况预测信息和当前行驶路况信息,确定对所述车辆的悬挂系统进行调整的策略信息,具体包括:若所述前方路况预测信息指示路段颠簸且所述当前行驶路况信息指示当前路段的颠簸程度越来越大,则确定调低所述悬挂系统的阻尼系数并调高所述车辆的悬挂系统的悬挂高度。Optionally, the
可选的,所述获取模块81,还用于获取所述车辆的风阻信息;所述策略确定模块82,还用于根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息。Optionally, the obtaining
可选的,所述获取模块81获取所述车辆的风阻信息,具体包括:获取所述车辆的速度信息和形状结构信息;将所述车辆的速度信息和形状结构信息输入预设的风阻模型,得到所述车辆的风阻信息。Optionally, the obtaining
可选的,所述策略确定模块82根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息,具体包括:将所述前方路况预测信息、当前行驶路况信息和风阻信息输入预先训练得到的策略确定模型,得到对所述车辆的悬挂系统进行调整的策略信息。Optionally, the
可选的,第三训练模块86,还用于采用如下过程对神经网络的训练得到所述策略确定模型:获取训练样本数据以及所述训练样本数据对应的调整策略标注信息,所述训练样本数据包括前方路况样本数据、当前行驶路况样本数据、速度样本数据和车辆形状结构信息;将所述训练样本数据作为神经网络的输入,将所述调整策略标注信息作为所述神经网络的输出,对所述神经网络进行迭代训练,得到所述策略确定模型。Optionally, the
可选的,所述策略确定模块82根据所述前方路况预测信息、当前行驶路况信息和风阻信息,确定对所述车辆的悬挂系统进行调整的策略信息,具体包括:若所述前方路况预测信息指示路段平稳、当前行驶路况信息指示路段平稳并且风阻信息指示风阻持续增大,则确定调高所述车辆的悬挂系统的阻尼系数和调低悬挂高度。Optionally, the
图8所示实施例的车辆平稳行驶控制装置可用于执行上述方法实施例的技术方案,其实现原理和技术效果类似,此处不再赘述。The vehicle smooth running control device of the embodiment shown in FIG. 8 can be used to implement the technical solutions of the foregoing method embodiments, and the implementation principles and technical effects thereof are similar, and will not be repeated here.
本申请实施例通过获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息,并根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。In the embodiment of the present application, the vehicle's road condition prediction information and current driving road condition information are obtained during the driving process, and the strategy information for adjusting the suspension system of the vehicle is determined according to the forward road condition prediction information and the current driving road condition information, and according to the strategy information , Adjust the suspension system of the vehicle to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort.
根据本申请的实施例,本申请还提供了一种车辆行驶平稳性控制设备和一种可读存储介质。其中,该车辆行驶平稳性控制设备可以是上述实施例的中控系统,该中控系统包括可读存储介质。According to the embodiments of the present application, the present application further provides a vehicle driving stability control device and a readable storage medium. Wherein, the vehicle driving stability control device may be the central control system of the above embodiment, and the central control system includes a readable storage medium.
如图9所示,是根据本申请实施例的车辆行驶平稳性控制设备的框图。电子设备旨在表示各种形式的数字计算机,诸如,膝上型计算机、台式计算机、工作台、个人数字助理、服务器、刀片式服务器、大型计算机、和其它适合的计算机。电子设备还可以表示各种形式的移动装置,诸如,个人数字处理、蜂窝电话、智能电话、可穿戴设备和其它类似的计算装置。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例,并且不意在限制本文中描述的和/或者要求的本申请的实现。As shown in FIG. 9 , it is a block diagram of a vehicle driving stability control apparatus according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are by way of example only, and are not intended to limit implementations of the application described and/or claimed herein.
如图9所示,该车辆行驶平稳性控制设备包括:一个或多个处理器901、存储器902,以及用于连接各部件的接口,包括高速接口和低速接口。各个部件利用不同的总线互相连接,并且可以被安装在公共主板上或者根据需要以其它方式安装。处理器可以对在电子设备内执行的指令进行处理,包括存储在存储器中或者存储器上以在外部输入/输出装置(诸如,耦合至接口的显示设备)上显示GUI的图形信息的指令。在其它实施方式中,若需要,可以将多个处理器和/或多条总线与多个存储器和多个存储器一起使用。同样,可以连接多个电子设备,各个设备提供部分必要的操作(例如,作为服务器阵列、一组刀片式服务器、或者多处理器系统)。图9中以一个处理器901为例。As shown in FIG. 9 , the vehicle driving stability control device includes: one or
存储器902即为本申请所提供的非瞬时计算机可读存储介质。其中,所述存储器存储有可由至少一个处理器执行的指令,以使所述至少一个处理器执行本申请所提供的车辆平稳行驶控制方法。本申请的非瞬时计算机可读存储介质存储计算机指令,该计算机指令用于使计算机执行本申请所提供的车辆平稳行驶控制方法。The
存储器902作为一种非瞬时计算机可读存储介质,可用于存储非瞬时软件程序、非瞬时计算机可执行程序以及模块,如本申请实施例中的车辆平稳行驶控制的方法对应的程序指令/模块(例如,附图8所示的获取模块81、策略确定模块82和调整模块83)。处理器901通过运行存储在存储器902中的非瞬时软件程序、指令以及模块,从而执行服务器的各种功能应用以及数据处理,即实现上述方法实施例中的车辆平稳行驶控制方法。As a non-transitory computer-readable storage medium, the
存储器902可以包括存储程序区和存储数据区,其中,存储程序区可存储操作系统、至少一个功能所需要的应用程序;存储数据区可存储根据车辆平稳行驶控制的电子设备的使用所创建的数据等。此外,存储器902可以包括高速随机存取存储器,还可以包括非瞬时存储器,例如至少一个磁盘存储器件、闪存器件、或其他非瞬时固态存储器件。在一些实施例中,存储器902可选包括相对于处理器901远程设置的存储器,这些远程存储器可以通过网络连接至车辆行驶平稳性控制设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。The
车辆行驶平稳性控制设备还可以包括:输入装置903和输出装置904。处理器901、存储器902、输入装置903和输出装置904可以通过总线或者其他方式连接,图9中以通过总线连接为例。The vehicle driving stability control apparatus may further include: an
输入装置903可接收输入的数字或字符信息,以及产生与车辆平稳行驶控制的电子设备的用户设置以及功能控制有关的键信号输入,例如触摸屏、小键盘、鼠标、轨迹板、触摸板、指示杆、一个或者多个鼠标按钮、轨迹球、操纵杆等输入装置。输出装置904可以包括显示设备、辅助照明装置(例如,LED)和触觉反馈装置(例如,振动电机)等。该显示设备可以包括但不限于,液晶显示器(LCD)、发光二极管(LED)显示器和等离子体显示器。在一些实施方式中,显示设备可以是触摸屏。The
此处描述的系统和技术的各种实施方式可以在数字电子电路系统、集成电路系统、专用ASIC(专用集成电路)、计算机硬件、固件、软件、和/或它们的组合中实现。这些各种实施方式可以包括:实施在一个或者多个计算机程序中,该一个或者多个计算机程序可在包括至少一个可编程处理器的可编程系统上执行和/或解释,该可编程处理器可以是专用或者通用可编程处理器,可以从存储系统、至少一个输入装置、和至少一个输出装置接收数据和指令,并且将数据和指令传输至该存储系统、该至少一个输入装置、和该至少一个输出装置。Various implementations of the systems and techniques described herein can be implemented in digital electronic circuitry, integrated circuit systems, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpretable on a programmable system including at least one programmable processor that The processor, which may be a special purpose or general-purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device an output device.
这些计算程序(也称作程序、软件、软件应用、或者代码)包括可编程处理器的机器指令,并且可以利用高级过程和/或面向对象的编程语言、和/或汇编/机器语言来实施这些计算程序。如本文使用的,术语“机器可读介质”和“计算机可读介质”指的是用于将机器指令和/或数据提供给可编程处理器的任何计算机程序产品、设备、和/或装置(例如,磁盘、光盘、存储器、可编程逻辑装置(PLD)),包括,接收作为机器可读信号的机器指令的机器可读介质。术语“机器可读信号”指的是用于将机器指令和/或数据提供给可编程处理器的任何信号。These computational programs (also referred to as programs, software, software applications, or codes) include machine instructions for programmable processors, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages calculation program. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or apparatus for providing machine instructions and/or data to a programmable processor ( For example, magnetic disks, optical disks, memories, programmable logic devices (PLDs), including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
为了提供与用户的交互,可以在计算机上实施此处描述的系统和技术,该计算机具有:用于向用户显示信息的显示装置(例如,CRT(阴极射线管)或者LCD(液晶显示器)监视器);以及键盘和指向装置(例如,鼠标或者轨迹球),用户可以通过该键盘和该指向装置来将输入提供给计算机。其它种类的装置还可以用于提供与用户的交互;例如,提供给用户的反馈可以是任何形式的传感反馈(例如,视觉反馈、听觉反馈、或者触觉反馈);并且可以用任何形式(包括声输入、语音输入或者、触觉输入)来接收来自用户的输入。To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and can be in any form (including acoustic input, voice input, or tactile input) to receive input from the user.
可以将此处描述的系统和技术实施在包括后台部件的计算系统(例如,作为数据服务器)、或者包括中间件部件的计算系统(例如,应用服务器)、或者包括前端部件的计算系统(例如,具有图形用户界面或者网络浏览器的用户计算机,用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互)、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信(例如,通信网络)来将系统的部件相互连接。通信网络的示例包括:局域网(LAN)、广域网(WAN)和互联网。The systems and techniques described herein may be implemented on a computing system that includes back-end components (eg, as a data server), or a computing system that includes middleware components (eg, an application server), or a computing system that includes front-end components (eg, a user's computer having a graphical user interface or web browser through which a user may interact with implementations of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
计算机系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。A computer system can include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other.
根据本申请实施例的技术方案,通过获取车辆在行驶过程中的前方路况预测信息和当前行驶路况信息,并根据前方路况预测信息和当前行驶路况信息,确定对车辆的悬挂系统进行调整的策略信息,以及根据策略信息,对车辆的悬挂系统进行调整,以达到使车辆平稳行驶的目的。不仅获取了能够指示车辆在行驶过程中的当前行驶路况信息,还获取了对车辆行驶过程中前方路况的预测信息,根据前方路况预测信息能够提前感知前方路况,并结合当前行驶路况信息,及时做出对车辆的悬挂系统进行调整的策略信息,以使车辆的悬挂系统及时调整到适应前方路况的状态,使车辆平稳行驶,提高乘坐舒适度。According to the technical solutions of the embodiments of the present application, by acquiring the predicted information of the road conditions ahead and the information of the current road conditions during the driving process of the vehicle, and according to the predicted information of the road conditions ahead and the information of the current road conditions, the strategy information for adjusting the suspension system of the vehicle is determined. , and adjust the suspension system of the vehicle according to the strategy information to achieve the purpose of making the vehicle run smoothly. It not only obtains the current driving road condition information that can indicate the vehicle during driving, but also obtains the prediction information of the road conditions ahead during the driving process of the vehicle. The strategy information for adjusting the suspension system of the vehicle is generated, so that the suspension system of the vehicle can be adjusted in time to adapt to the state of the road ahead, so that the vehicle can run smoothly and improve the riding comfort.
应该理解,可以使用上面所示的各种形式的流程,重新排序、增加或删除步骤。例如,本发申请中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行,只要能够实现本申请公开的技术方案所期望的结果,本文在此不进行限制。It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present application can be performed in parallel, sequentially or in different orders, and as long as the desired results of the technical solutions disclosed in the present application can be achieved, no limitation is imposed herein.
上述具体实施方式,并不构成对本申请保护范围的限制。本领域技术人员应该明白的是,根据设计要求和其他因素,可以进行各种修改、组合、子组合和替代。任何在本申请的精神和原则之内所作的修改、等同替换和改进等,均应包含在本申请保护范围之内。The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application shall be included within the protection scope of this application.
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CN114148136B (en) | 2024-08-16 |
CN114148136A (en) | 2022-03-08 |
CN114148137B (en) | 2024-11-12 |
CN111347831B (en) | 2022-04-12 |
CN111347831A (en) | 2020-06-30 |
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