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1. 发明专利

JP2010280378A Road curvature estimation system and automotive target state estimation system 有权
标题翻译：道路曲线估计系统和汽车目标状态估计系统
公开(公告)号：JP2010280378A
公开(公告)日：2010-12-16
申请号：JP2010136483
申请日：2010-06-15
申请人： Automotive Systems Lab Inc , オートモーティブシステムズラボラトリーインコーポレーテッド
发明人： CONG SHAN , SHEN SHI , HONG LANG
IPC分类号： B60W40/02 , G08G1/16 , B60K31/00 , G01S13/58 , G01S13/72 , G01S13/93
CPC分类号： G01S13/931 , B60K31/0008 , B60K31/0083 , B60T2210/24 , B60T2260/08 , B60W2520/14 , B60W2550/143 , B60W2550/302 , B60W2550/304 , B60W2550/306 , G01S13/58 , G01S13/723 , G01S13/86 , G01S2013/9325 , G01S2013/9353 , G01S2013/9375
摘要： PROBLEM TO BE SOLVED: To estimate a curvature of a road by a Kalman filter. SOLUTION: In this estimation system, a first Kalman filter 52 estimates measured values of a yaw rate and speed from measured values generated by respective sensors 16, 18 in a host vehicle, and a second Kalman filter 54 estimates therefrom parameters of a clothoid model of road curvature. Measured values of a range, a range rate and an azimuth angle from a radar system 14, are processed by an extended Kalman filter 56 to provide an unconstrained estimate of the state of a target vehicle 36. Associated road constrained target state estimates are generated for one or more roadway lanes and are compared -either individually or in combination- with the unconstrained estimate. If a constrained target state estimate corresponds to the unconstrained estimate, then the state of the target vehicle is generated by fusing the unconstrained and constrained estimates; and otherwise is given by the unconstrained estimate alone. COPYRIGHT: (C)2011,JPO&INPIT
摘要翻译：要解决的问题：通过卡尔曼滤波器估计道路的曲率。解决方案：在该估计系统中，第一卡尔曼滤波器52根据由主车辆中的各个传感器16,18产生的测量值估计横摆率和速度的测量值，并且第二卡尔曼滤波器54从其估计道路曲率的回旋模型。来自雷达系统14的范围，范围速率和方位角的测量值由扩展卡尔曼滤波器56处理，以提供对目标车辆36的状态的无约束估计。产生相关的道路约束目标状态估计，用于一个或多个道路车道，并且单独地或组合地与无约束的估计进行比较。如果约束目标状态估计对应于无约束估计，则目标车辆的状态通过融合无约束和约束估计来产生; 否则由单独的无约束估计给出。版权所有（C）2011，JPO＆INPIT

2. 发明专利

JP2013209085A Road curvature estimation system and automotive target state estimation system 有权
标题翻译：道路曲线估计系统和汽车目标状态估计系统
公开(公告)号：JP2013209085A
公开(公告)日：2013-10-10
申请号：JP2013092625
申请日：2013-04-25
申请人： Automotive Systems Lab Inc , オートモーティブシステムズラボラトリーインコーポレーテッド
发明人： CONG SHAN , SHEN SHI , HONG LANG
IPC分类号： B60W40/072 , G08G1/16 , B60K31/00 , B60R21/00 , B60W30/095 , B62D6/00 , G01S13/58 , G01S13/72 , G01S13/93
CPC分类号： G01S13/931 , B60K31/0008 , B60K31/0083 , B60T2210/24 , B60T2260/08 , B60W2520/14 , B60W2550/143 , B60W2550/302 , B60W2550/304 , B60W2550/306 , G01S13/58 , G01S13/723 , G01S13/86 , G01S2013/9325 , G01S2013/9353 , G01S2013/9375
摘要： PROBLEM TO BE SOLVED: To provide a road curvature estimation system and an automotive target state estimation system for a predictive collision detection system.SOLUTION: A first Kalman filter 52 estimates true measures of yaw rate and vehicle speed from associated noisy measures thereof generated by respective sensors (16, 18) in a host vehicle, and a second Kalman filter 54 estimates therefrom parameters of a clothoid model of road curvature. Measures of range, range rate and azimuth angle from a target state estimation subsystem 44, e.g. a radar system 14, are processed by an extended Kalman filter 56 to provide an unconstrained estimate of the state of a target vehicle. Associated road constrained target state estimates are generated for one or more roadway lanes, and are compared either individually or in combination with the unconstrained estimate. Then the state of the target vehicle is generated by fusing the unconstrained and constrained estimates, and otherwise is given by the unconstrained estimate alone.
摘要翻译：要解决的问题：提供一种用于预测碰撞检测系统的道路曲率估计系统和汽车目标状态估计系统。解决方案：第一卡尔曼滤波器52通过相应的相关噪声度量估计偏航率和车辆速度的真实度量主车辆中的传感器（16,18）和第二卡尔曼滤波器54从其中估计道路曲率的回旋模型的参数。来自目标状态估计子系统44的范围，范围速率和方位角的测量，例如。雷达系统14由扩展卡尔曼滤波器56处理以提供目标车辆的状态的无约束估计。对于一个或多个道路车道生成相关道路约束目标状态估计，并且将其单独地或与无约束估计结合进行比较。然后通过融合无约束和约束估计来产生目标车辆的状态，否则由单独的无约束估计给出。

3. 发明专利

JP2012131496A Road curvature estimation system 有权
标题翻译：道路曲线估计系统
公开(公告)号：JP2012131496A
公开(公告)日：2012-07-12
申请号：JP2012004376
申请日：2012-01-12
申请人： Automotive Systems Lab Inc , オートモーティブシステムズラボラトリーインコーポレーテッド
发明人： CONG SHAN , SHEN SHI , HONG LANG
IPC分类号： B60W40/072 , B60W40/076 , G01S13/58 , G01S13/72 , G01S13/93 , G08G1/16
CPC分类号： G01S13/58 , G01S13/723 , G01S13/931 , G01S2013/9353
摘要： PROBLEM TO BE SOLVED: To estimate a curvature of a road in a predictive collision detection system.SOLUTION: Road curvature parameters are estimated from a curve fit of a host vehicle trajectory or from a second Kalman filter (54, 54.1) for which a state variable is responsive to a plurality of host state variables (72). Kalman filters (52, 52.1, 54, 54.1) can incorporate adaptive sliding windows. A curvature of a most likely road type is estimated with an interacting multiple model (IMM) algorithm using models of different road types. A road curvature fusion subsystem provides for fusing road curvature estimates from a plurality of road curvature estimators using either a host vehicle state, a map database responsive to a vehicle location, or measurements of a target vehicle with a radar system.
摘要翻译：要解决的问题：估计预测碰撞检测系统中的道路的曲率。解决方案：根据主车辆轨迹的曲线拟合或来自状态变量响应于多个主机状态变量（72）的第二卡尔曼滤波器（54,54.1）估计道路曲率参数。卡尔曼滤波器（52,52.1,54,54.1）可以包括自适应滑动窗口。通过使用不同道路类型的模型的交互式多模型（IMM）算法来估计最可能的道路类型的曲率。道路曲率融合子系统使用主车辆状态，响应于车辆位置的地图数据库或者具有雷达系统的目标车辆的测量来提供来自多个道路曲率估计器的道路曲率估计的融合。版权所有（C）2012，JPO＆INPIT

4. 发明专利

JP2012131495A Road curvature estimation system 有权
标题翻译：道路曲线估计系统
公开(公告)号：JP2012131495A
公开(公告)日：2012-07-12
申请号：JP2012004375
申请日：2012-01-12
申请人： Automotive Systems Lab Inc , オートモーティブシステムズラボラトリーインコーポレーテッド
发明人： CONG SHAN , SHEN SHI , HONG LANG
IPC分类号： B60W40/072 , B60W40/076 , G01S13/58 , G01S13/72 , G01S13/93 , G08G1/16
CPC分类号： G01S13/58 , G01S13/723 , G01S13/931 , G01S2013/9353
摘要： PROBLEM TO BE SOLVED: To estimate road curvature parameters.SOLUTION: A processor 26 using a first Kalman filter 52, 52.1 estimates a host vehicle state from speed U and a yaw rate ω, the yaw rate ω being obtained from a yaw rate sensor 16 if speed U is greater, and, if less, from a steer angle sensor and speed U. Road curvature parameters (C, C) are estimated from a curve fit of a host vehicle trajectory or from a second Kalman filter 54, 54.1 for which a state variable is responsive to a plurality of host state variables. Kalman filters 52, 52.1, 54, 54.1 incorporate adaptive sliding windows. Curvature of a road type is estimated with an interacting multiple model IMM algorithm using models of different road types. Road curvature estimates from a plurality of road curvature estimators using either a host vehicle state, a vehicle location map database, or measurements of a target vehicle with a radar system are fused.
摘要翻译：要解决的问题：估计道路曲率参数。解决方案：如果速度U较大，则使用第一卡尔曼滤波器52,52.1的处理器26从速度U和横摆率ω估计主车辆状态，从偏航率传感器16获得偏航率ω，（C 0 ，C 1 ）从a角度传感器和速度U 主车辆轨迹的曲线拟合或来自状态变量响应于多个主机状态变量的第二卡尔曼滤波器54,51.1的曲线拟合。卡尔曼滤波器52,52.1,54,54.1包括自适应滑动窗口。使用不同道路类型的模型，使用交互式多模型IMM算法估计道路类型的曲率。使用主车辆状态，车辆位置图数据库或具有雷达系统的目标车辆的测量的多个道路曲率估计器的道路曲率估计被融合。版权所有（C）2012，JPO＆INPIT

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