Prediction of driver-specific cruise speed using dynamic modeling
First Claim
1. A controller for predicting cruising speeds of a vehicle, the controller including a processor and comprising:
- a segmenting unit configured to segment trajectories of the vehicle including prior and current trajectories of the vehicle into segments including one or more cruising segments, deceleration segments, and acceleration segments;
an extracting unit configured to extract feature data from the segments of the trajectories, the feature data including cruising speeds of the vehicle during the one or more cruising segments and predictive feature data from one or more of the cruising segments, deceleration segments, and acceleration segments that are predictive of the cruising speeds of the vehicle;
a model generator configured to generate a probabilistic model based on the feature data from the segments of the trajectories by identifying ones of the feature data as the predictive feature data, wherein the probabilistic model associates the predictive feature data with the cruising speeds of the vehicle; and
a predicting unit configured to predict a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of a current or subsequent trajectory of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of the current trajectory,wherein the predicting unit is configured to predict the cruising speed of the vehicle for the target segment by conditioning the probabilistic model on a sequence number of a trajectory including the target segment relative to sequential trajectories forming a navigation path of the vehicle.
2 Assignments
0 Petitions
Accused Products
Abstract
A controller for predicting cruising speeds of a vehicle includes a processor and an extracting unit to extract feature data from segments of a prior trajectory of the vehicle, the feature data including cruising speeds of the vehicle and predictive feature data. The controller also includes a model generator to generate a probabilistic model associating the predictive feature data with the cruising speeds of the vehicle and a predicting unit to predict a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of a current trajectory.
28 Citations
28 Claims
-
1. A controller for predicting cruising speeds of a vehicle, the controller including a processor and comprising:
-
a segmenting unit configured to segment trajectories of the vehicle including prior and current trajectories of the vehicle into segments including one or more cruising segments, deceleration segments, and acceleration segments; an extracting unit configured to extract feature data from the segments of the trajectories, the feature data including cruising speeds of the vehicle during the one or more cruising segments and predictive feature data from one or more of the cruising segments, deceleration segments, and acceleration segments that are predictive of the cruising speeds of the vehicle; a model generator configured to generate a probabilistic model based on the feature data from the segments of the trajectories by identifying ones of the feature data as the predictive feature data, wherein the probabilistic model associates the predictive feature data with the cruising speeds of the vehicle; and a predicting unit configured to predict a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of a current or subsequent trajectory of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of the current trajectory, wherein the predicting unit is configured to predict the cruising speed of the vehicle for the target segment by conditioning the probabilistic model on a sequence number of a trajectory including the target segment relative to sequential trajectories forming a navigation path of the vehicle. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28)
-
-
25. A method of predicting cruising speeds of a vehicle, the method comprising:
-
segmenting trajectories of the vehicle including prior and current trajectories of the vehicle into segments including one or more cruising segments, deceleration segments, and acceleration segments; extracting feature data from the segments of the trajectories, the feature data including cruising speeds of the vehicle during the one or more cruising segments and predictive feature data from one or more of the cruising segments, deceleration segments, and acceleration segments that are predictive of the cruising speeds of the vehicle; generating a probabilistic model based on the feature data from the segments of the trajectories by identifying ones of the feature data as the predictive feature data, wherein the probabilistic model associates the predictive feature data with the cruising speeds of the vehicle; and predicting a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of a current or subsequent trajectory of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of the current trajectory, wherein the predicting includes predicting the cruising speed of the vehicle for the target segment by conditioning the probabilistic model on a sequence number of a trajectory including the target segment relative to sequential trajectories forming a navigation path of the vehicle.
-
-
26. A non-transitory computer readable storage medium storing computer readable instructions thereon which, when executed by a computer, cause the computer to perform a method of predicting cruising speeds of a vehicle, the method comprising:
-
segmenting trajectories of the vehicle including prior and current trajectories of the vehicle into segments including one or more cruising segments, deceleration segments, and acceleration segments; extracting feature data from the segments of the trajectories, the feature data including cruising speeds of the vehicle during the one or more cruising segments and predictive feature data from one or more of the cruising segments, deceleration segments, and acceleration segments that are predictive of the cruising speeds of the vehicle; generating a probabilistic model based on the feature data from the segments of the trajectories by identifying ones of the feature data as the predictive feature data, wherein the probabilistic model associates the predictive feature data with the cruising speeds of the vehicle; and predicting a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of a current or subsequent trajectory of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of the current trajectory, wherein the predicting includes predicting the cruising speed of the vehicle for the target segment by conditioning the probabilistic model on a sequence number of a trajectory including the target segment relative to sequential trajectories forming a navigation path of the vehicle.
-
-
27. A cruising speed prediction system comprising:
-
a controller aboard a vehicle, the controller being configured to collect trajectory data of the vehicle; and a remote processing server configured to predict cruising speeds of the vehicle based on the trajectory data of the vehicle, the remote processing server including; a segmenting unit configured to segment trajectories of the vehicle including prior and current trajectories of the vehicle into segments including one or more cruising segments, deceleration segments, and acceleration segments; an extracting unit configured to extract feature data from the segments of the trajectories, the feature data including cruising speeds of the vehicle during the one or more cruising segments and predictive feature data from one or more of the cruising segments, deceleration segments, and acceleration segments that are predictive of the cruising speeds of the vehicle; a model generator configured to generate a probabilistic model based on the feature data from the segments of the trajectories by identifying ones of the feature data as the predictive feature data, wherein the probabilistic model associates the predictive feature data with the cruising speeds of the vehicle; and a predicting unit configured to predict a cruising speed of the vehicle for a target segment, which is an upcoming cruising segment of a current or subsequent trajectory of the vehicle, by conditioning the probabilistic model on real-time predictive feature data of segments of the current trajectory, wherein the predicting unit is configured to predict the cruising speed of the vehicle for the target segment by conditioning the probabilistic model on a sequence number of a trajectory including the target segment relative to sequential trajectories forming a navigation path of the vehicle, and the controller transmits the collected trajectory data to the remote processing server and receives from the remote processing server the predicted cruising speed of the vehicle for the target segment.
-
Specification