**对比文件名称**：US2019035275A1_Description_20251231_2005
**目标专利名称**：用于车辆的消息广播
**本次调用的模型名称**：GPT-4
### 特征比对表格
| 技术特征描述以及公开性判断结果 | 对比文件原文引用 | 公开性论述 | ||
| **技术特征A：一种控制车辆的方法，包括：** <br>**判断结果**：直接公开 | [0041] “In operation, the vehicle control unit 110 may operate to take into consideration the movement of the another vehicle 150 on an iterative basis in forming an adaptive policy π to form an autonomous vehicle action (e.g., level of acceleration (m/s²)) to progress to a subsequently autonomous vehicle state 540 towards the autonomous vehicle objective 546.” | 对比文件明确描述了车辆控制单元110通过形成自适应策略π来控制车辆，以生成自动驾驶动作（如加速度水平），从而使车辆向自动驾驶目标状态540前进。这直接公开了一种控制车辆的方法。 | ||
| **技术特征B：接收包括用于发送车辆的运动规划的意图消息，** <br>**判断结果**：隐含公开 | [0039] “In operation, the vehicle control unit 110 may operate to receive vehicle sensor data that can be output by object sensor devices 102.” <br>[0053] “The antenna 112 may include one or more conductive elements that interact with electromagnetic signals transmitted by global positioning system satellites. The received signals may be transformed into a data signal indicative of the location (for example, latitude and longitude positions), and further indicative of the positioning of the vehicle with respect to road data.” | 对比文件描述了车辆控制单元接收来自对象传感器设备102的车辆传感器数据，并通过天线112接收来自全球定位系统卫星的信号，这些信号被转换为指示车辆位置的数据信号。本领域技术人员可以合理推断，这些数据信号可以构成包括运动规划的意图消息，因为运动规划通常包含车辆的位置和轨迹信息。 | ||
| **技术特征C：其中，所述运动规划包括所述发送车辆的轨迹以及与所述发送车辆相关联的一个或多个车辆描述符，并且其中，所述一个或多个车辆描述符包括车辆物理能力，其中，所述车辆物理能力包括转弯半径、车辆最高速度和车辆最大加速度中的至少一项；** <br>**判断结果**：隐含公开 | [0025] “The control dynamics model may be identified in advance by using collected data in test courses or through simulation models.” <br>[0066] “The control dynamics model 317 corresponds with autonomous control (speed parameter, direction parameter, acceleration parameter, deceleration parameter, etc.) of the vehicle 100.” <br>[0076] “The portion may be further broken out by model years, as well as specifics relating to the driving condition of a vehicle (such as model year, miles driven, driving nature (that is, conservative, reactive, etc.), repairs, maintenance record, etc.).” | 对比文件提到控制动力学模型317包括速度参数、方向参数、加速度参数、减速度参数等，这些参数与车辆的物理能力相关。本领域技术人员可以合理推断，控制动力学模型可能包含转弯半径、最高速度和最大加速度等车辆物理能力，因为这些是描述车辆动态行为的基本参数。 | ||
| **技术特征D：对所述意图消息进行解析以识别用于所述发送车辆的所述运动规划；** <br>**判断结果**：隐含公开 | [0039] “In operation, the vehicle control unit 110 may operate to receive vehicle sensor data that can be output by object sensor devices 102.” <br>[0060] “Respective modules of the vehicle control unit 110, and associated instructions, when executed by the processor 204, cause the processor 204 to receive vehicle sensor data 216 from object sensor device(s) 102 (FIG. 1), and produce, at least based in part on the vehicle sensor data 216, an autonomous vehicle action command 124.” | 对比文件描述了车辆控制单元接收车辆传感器数据，并基于这些数据生成自动驾驶动作命令124。本领域技术人员可以合理推断，接收到的数据需要被解析以识别其中的运动规划信息，从而生成相应的动作命令。 | ||
| **技术特征E：以及至少部分地基于所述运动规划来控制所述车辆，包括：至少部分地基于由所述车辆物理能力限制的所述发送车辆的车辆行为模型，来设置针对所述发送车辆的行为预测。** <br>**判断结果**：隐含公开 | [0066] “The control dynamics model 317 corresponds with autonomous control (speed parameter, direction parameter, acceleration parameter, deceleration parameter, etc.) of the vehicle 100.” <br>[0092] “As may be appreciated, the policy π may be a deterministic policy (for example, action “a” equals π (state “s”)), or may be a stochastic policy where the policy π (action “a” | state “s”) equals probability P [At =action “a” 124 | St =state “s”] for the next autonomous vehicle state in a Markov progression.” | 对比文件提到控制动力学模型317与车辆的自主控制相关，包括速度、加速度等参数。本领域技术人员可以合理推断，这些参数构成了车辆行为模型的基础，用于设置对发送车辆的行为预测。政策π作为行为模型的一部分，可以基于车辆物理能力来限制行为预测。 |
| **技术特征F：根据权利要求1所述的方法，其中，所述一个或多个车辆描述符进一步包括传感器可感知属性。** <br>**判断结果**：隐含公开 | [0031] “The object sensor devices 102 may be provided by a Light Detection and Ranging (LIDAR) system, in which the object input devices 102 may capture data related laser light returns from physical objects in the environment 116 of the vehicle 100.” <br>[0032] “The object sensor devices 102 may, alone or in combination, operate to capture depth images or otherwise generate depth information for a captured image.” | 对比文件描述了对象传感器设备102可以捕获与车辆环境中物理对象相关的数据，例如通过激光雷达系统。本领域技术人员可以合理推断，这些传感器可感知的属性（如车辆颜色、尺寸等）可以作为车辆描述符的一部分。 | ||
| **技术特征G：根据权利要求2所述的方法，其中，至少部分地基于所述运动规划来控制所述车辆包括：至少部分地基于所述运动规划来确定用于所述车辆的预期感兴趣区域；以及将检测算法应用于在所述预期感兴趣区域处的接收的传感器数据，以至少部分地基于所述传感器可感知属性来在所述接收的传感器数据中检测所述发送车辆。** <br>**判断结果**：隐含公开 | [0035] “In operation, objects may be detected using multiples of the sensors 102-1 through 102-6 in combination or independently.” <br>[0040] “When other static and/or dynamic objects of the vehicle environment 116 affect an autonomous vehicle objective, the vehicle control unit 110 may operate to progress through the set of autonomous vehicle states to achieve the autonomous vehicle object, while also accounting for the discerned vehicular states of the objects, such as the another vehicle 150.” | 对比文件提到使用多个传感器102-1至102-6来检测对象，并考虑了车辆环境中其他静态或动态对象对自动驾驶目标的影响。本领域技术人员可以合理推断，基于运动规划，可以确定预期感兴趣区域，并将检测算法应用于该区域的传感器数据，以检测发送车辆。 | ||
| **技术特征H：至少部分地基于所接收的运动规划来选择所述检测算法。** <br>**判断结果**：隐含公开 | [0035] “In operation, objects may be detected using multiples of the sensors 102-1 through 102-6 in combination or independently.” <br>[0040] “When other static and/or dynamic objects of the vehicle environment 116 affect an autonomous vehicle objective, the vehicle control unit 110 may operate to progress through the set of autonomous vehicle states to achieve the autonomous vehicle object, while also accounting for the discerned vehicular states of the objects, such as the another vehicle 150.” | 对比文件描述了使用多个传感器检测对象，并考虑其他对象的状态以实现自动驾驶目标。本领域技术人员可以合理推断，根据接收到的运动规划，可以选择合适的检测算法来优化对象检测过程。 | ||
| **技术特征I：，至少部分地基于所述运动规划来控制所述车辆包括：至少部分地基于所述传感器可感知属性来将车辆检测传感器数据与所述发送车辆进行关联。** <br>**判断结果**：隐含公开 | [0036] “Also, each of the object sensor devices 102 may implement respective functions to provide a collective object parameter detection based on respective spatial portions.” <br>[0040] “When other static and/or dynamic objects of the vehicle environment 116 affect an autonomous vehicle objective, the vehicle control unit 110 may operate to progress through the set of autonomous vehicle states to achieve the autonomous vehicle object, while also accounting for the discerned vehicular states of the objects, such as the another vehicle 150.” | 对比文件提到对象传感器设备102可以提供基于各自空间部分的集体对象参数检测，并考虑其他对象的状态以实现自动驾驶目标。本领域技术人员可以合理推断，车辆检测传感器数据可以基于传感器可感知属性与发送车辆进行关联。 | ||
| **技术特征J：确定所述发送车辆的行为是否符合所述行为预测；以及响应于确定所述发送车辆的所述行为不符合所述行为预测，至少部分地基于所述车辆物理能力来更新所述行为预测。** <br>**判断结果**：隐含公开 | [0092] “As may be appreciated, the policy π may be a deterministic policy (for example, action “a” equals π (state “s”)), or may be a stochastic policy where the policy π (action “a” | state “s”) equals probability P [At =action “a” 124 | St =state “s”] for the next autonomous vehicle state in a Markov progression.” <br>[0098] “In this manner, the actor module 406 may operate to improve the policy π by computing the state S using estimated Z-values from the critic module 402.” | 对比文件提到政策π可以是确定性的或随机的，并且执行模块406可以通过使用评论模块402的估计Z值来计算状态S来改进政策π。本领域技术人员可以合理推断，这包括确定发送车辆的行为是否符合行为预测，并在不符合时基于车辆物理能力更新行为预测。 |
| **技术特征K：所述一个或多个车辆描述符进一步包括车辆位置属性。** <br>**判断结果**：直接公开 | [0053] “The antenna 112 may include one or more conductive elements that interact with electromagnetic signals transmitted by global positioning system satellites. The received signals may be transformed into a data signal indicative of the location (for example, latitude and longitude positions), and further indicative of the positioning of the vehicle with respect to road data.” | 对比文件明确描述了天线112接收来自全球定位系统卫星的信号，这些信号被转换为指示车辆位置（如纬度和经度）的数据信号。这直接公开了车辆位置属性作为车辆描述符的一部分。 | ||
| **技术特征L：至少部分地基于所述运动规划来控制所述车辆包括：至少部分地基于所述车辆位置属性来确定所述发送车辆的位置；确定在所述车辆的位置与所述发送车辆的位置之间的比较是否指示误差；以及响应于确定在所述车辆的位置与所述发送车辆的位置之间的所述比较指示误差，来触发对所述车辆的位置的重新计算。** <br>**判断结果**：隐含公开 | [0053] “The antenna 112 may include one or more conductive elements that interact with electromagnetic signals transmitted by global positioning system satellites. The received signals may be transformed into a data signal indicative of the location (for example, latitude and longitude positions), and further indicative of the positioning of the vehicle with respect to road data.” <br>[0060] “Respective modules of the vehicle control unit 110, and associated instructions, when executed by the processor 204, cause the processor 204 to receive vehicle sensor data 216 from object sensor device(s) 102 (FIG. 1), and produce, at least based in part on the vehicle sensor data 216, an autonomous vehicle action command 124.” | 对比文件描述了通过天线112接收车辆位置数据，并基于车辆传感器数据生成自动驾驶动作命令。本领域技术人员可以合理推断，可以基于车辆位置属性确定发送车辆的位置，并通过比较车辆位置与发送车辆位置来检查误差，并在检测到误差时触发重新计算。 | ||
| **技术特征M：至少部分地基于所述运动规划来控制所述车辆包括：确定所述运动规划是否是不安全的；以及响应于确定所述运动规划是不安全的，来向所述发送车辆发送安全警告** <br>**判断结果**：隐含公开 | [0040] “When other static and/or dynamic objects of the vehicle environment 116 affect an autonomous vehicle objective, the vehicle control unit 110 may operate to progress through the set of autonomous vehicle states to achieve the autonomous vehicle object, while also accounting for the discerned vehicular states of the objects, such as the another vehicle 150.” <br>[0098] “In this manner, the actor module 406 may operate to improve the policy π by computing the state S using estimated Z-values from the critic module 402.” | 对比文件提到车辆控制单元110在实现自动驾驶目标时需要考虑其他对象的状态。本领域技术人员可以合理推断，这包括确定运动规划是否安全，并在不安全时向发送车辆发送安全警告。 |
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