Abstract: A method and system generates a collision warning to a driver of a host vehicle. The system includes an on-board sensor of the host vehicle to detect presence of a preceding vehicle, wireless communication circuitry to establish wireless communication with a remote vehicle, and processing circuitry to detect existence of a slow remote vehicle ahead of the host vehicle, track an immediately preceding vehicle ahead of the host vehicle, confirm that the slow remote vehicle is affecting the host vehicle's lane speed of traffic by detecting that the immediately preceding vehicle is decelerating. When it is determined that, that the remote vehicle is sow, display an information message indicating the existence of the slow remote vehicle, and output, when the remote vehicle is slow and the preceding vehicle is decelerating, the collision warning as an audio sound and a visual message.

Abstract: A method and system generates a collision warning to a driver of a host vehicle. The system includes an on-board sensor of the host vehicle to detect presence of a preceding vehicle, wireless communication circuitry to establish wireless communication with a remote vehicle, and processing circuitry to detect existence of a slow remote vehicle ahead of the host vehicle, track an immediately preceding vehicle ahead of the host vehicle, confirm that the slow remote vehicle is affecting the host vehicle's lane speed of traffic by detecting that the immediately preceding vehicle is decelerating. When it is determined that, that the remote vehicle is sow, display an information message indicating the existence of the slow remote vehicle, and output, when the remote vehicle is slow and the preceding vehicle is decelerating, the collision warning as an audio sound and a visual message.

Abstract: Distributed control of vehicles with coordinating cars that implement a cooperative control method, and non-coordinating cars that are presumed to follow predictable dynamics. A cooperative control method can combine distributed receding horizon control, for optimization-based path planning and feedback, with higher level logic, to ensure that implemented plans are collision free. The cooperative method can be completely distributed with partially synchronous execution, and can afford dedicated time for communication and computation, features that are prerequisites for implementation on real freeways. The method can test for conflicts and can calculate optimized trajectories by adjusting parameters in terminal state constraints of an optimal control problem.

Abstract: Distributed control of vehicles with coordinating cars that implement a cooperative control method, and non-coordinating cars that are presumed to follow predictable dynamics. A cooperative control method can combine distributed receding horizon control, for optimization-based path planning and feedback, with higher level logic, to ensure that implemented plans are collision free. The cooperative method can be completely distributed with partially synchronous execution, and can afford dedicated time for communication and computation, features that are prerequisites for implementation on real freeways. The method can test for conflicts and can calculate optimized trajectories by adjusting parameters in terminal state constraints of an optimal control problem.

Abstract: Distributed control of vehicles with coordinating cars that implement a cooperative control method, and non-coordinating cars that are presumed to follow predictable dynamics. A cooperative control method can combine distributed receding horizon control, for optimization-based path planning and feedback, with higher level logic, to ensure that implemented plans are collision free. The cooperative method can be completely distributed with partially synchronous execution, and can afford dedicated time for communication and computation, features that are prerequisites for implementation on real freeways. The method can test for conflicts and can calculate optimized trajectories by adjusting parameters in terminal state constraints of an optimal control problem.

Abstract: A platoon model allows improved prediction of preceding vehicle future state. In this context, the preceding vehicle is a vehicle immediately ahead of the host vehicle, and the dynamic state of the preceding vehicle was predicted based on data received from one or more vehicles in the platoon. The intelligent driver model (IDM) was extended to model car-following dynamics within a platoon. A parameter estimation approach may be used to estimate the model parameters, for example to adapt to different driver types. An integrated approach including both state prediction and parameter estimation was highly effective.

Abstract: Systems and methods for estimating local traffic flow are described. One embodiment of a method includes determining a driving habit of a user from historical data, determining a current location of a vehicle that the user is driving, and determining a current driving condition for the vehicle. Some embodiments include predicting a desired driving condition from the driving habit and the current location, comparing the desired driving condition with the current driving condition to determine a traffic congestion level, and sending a signal that indicates the traffic congestion level.

Abstract: A platoon model allows improved prediction of preceding vehicle future state. In this context, the preceding vehicle is a vehicle immediately ahead of the host vehicle, and the dynamic state of the preceding vehicle was predicted based on data received from one or more vehicles in the platoon. The intelligent driver model (IDM) was extended to model car-following dynamics within a platoon. A parameter estimation approach may be used to estimate the model parameters, for example to adapt to different driver types. An integrated approach including both state prediction and parameter estimation was highly effective.

Abstract: This disclosure relates to distributed control of a platoon of vehicles with nonlinear dynamics. Distributed receding horizon control algorithms are presented to derive sufficient conditions that guarantee asymptotic stability, leader-follower string stability, and predecessor-follower string stability, following a step speed change in the platoon. Vehicles compute their own control in parallel, and receive communicated position and velocity error trajectories from their immediate predecessor. Leader-follower string stability requires additional communication from the lead car at each update, in the form of a position error trajectory. Communication from the lead car is required only once at initialization. Provided an initially feasible solution can be found, subsequent feasibility of the algorithms are guaranteed at every update. The theory is generalized for nonlinear decoupled dynamics, and is thus applicable to fleets of planes, robots, or boats, in addition to cars.

Abstract: Distributed control of vehicles with coordinating cars that implement a cooperative control method, and non-coordinating cars that are presumed to follow predictable dynamics. A cooperative control method can combine distributed receding horizon control, for optimization-based path planning and feedback, with higher level logic, to ensure that implemented plans are collision free. The cooperative method can be completely distributed with partially synchronous execution, and can afford dedicated time for communication and computation, features that are prerequisites for implementation on real freeways. The method can test for conflicts and can calculate optimized trajectories by adjusting parameters in terminal state constraints of an optimal control problem.

Abstract: This disclosure relates to distributed control of a platoon of vehicles with nonlinear dynamics. Distributed receding horizon control algorithms are presented to derive sufficient conditions that guarantee asymptotic stability, leader-follower string stability, and predecessor-follower string stability, following a step speed change in the platoon. Vehicles compute their own control in parallel, and receive communicated position and velocity error trajectories from their immediate predecessor. Leader-follower string stability requires additional communication from the lead car at each update, in the form of a position error trajectory. Communication from the lead car is required only once at initialization. Provided an initially feasible solution can be found, subsequent feasibility of the algorithms are guaranteed at every update. The theory is generalized for nonlinear decoupled dynamics, and is thus applicable to fleets of planes, robots, or boats, in addition to cars.

Abstract: A method for predicting future states of a vehicle including the steps of selecting a model having n states reflecting dynamic features of the vehicle; inputting noisy sensor measurements representing a current state of the vehicle to generate (2n+1) sigma points Xi where i=0, . . . . 2n, each of the sigma points having n states; performing (2n+1) integrations, each integration includes propagating the n-states of the respective sigma points Xi through the non-linear function Yi=f(Xi); and combining the propagated sigma points to generate the predicted future states of the vehicle.

Abstract: Method and system of vehicular path prediction for a vehicle travelling on a road. A yaw rate of the vehicle is estimated over a prediction time period based on vehicle sensor information and map information for the road. Then, a further path of the vehicle on the road is predicted for the prediction time period based on a speed and a direction of the vehicle, and the estimated yaw rate. Map information includes a geometry for a portion of the road on which the vehicle is travelling, and the vehicle sensor information includes yaw rate information from a yaw rate sensor on the vehicle, and location information of the vehicle relative to the map information from a positioning device on the vehicle. A vehicle provided for path prediction includes a communication system for transmitting the predicted path to other vehicles for collision avoidance.

Abstract: Systems and methods for estimating local traffic flow are described. One embodiment of a method includes determining a driving habit of a user from historical data, determining a current location of a vehicle that the user is driving, and determining a current driving condition for the vehicle. Some embodiments include predicting a desired driving condition from the driving habit and the current location, comparing the desired driving condition with the current driving condition to determine a traffic congestion level, and sending a signal that indicates the traffic congestion level.

Abstract: Method and system of vehicular path prediction for a vehicle travelling on a road. A yaw rate of the vehicle is estimated over a prediction time period based on vehicle sensor information and map information for the road. Then, a further path of the vehicle on the road is predicted for the prediction time period based on a speed and a direction of the vehicle, and the estimated yaw rate. Map information includes a geometry for a portion of the road on which the vehicle is travelling, and the vehicle sensor information includes yaw rate information from a yaw rate sensor on the vehicle, and location information of the vehicle relative to the map information from a positioning device on the vehicle. A vehicle provided for path prediction includes a communication system for transmitting the predicted path to other vehicles for collision avoidance.

Abstract: A method for predicting future states of a vehicle including the steps of selecting a model having n states reflecting dynamic features of the vehicle; inputting noisy sensor measurements representing a current state of the vehicle to generate (2n+1) sigma points Xi where i=0, . . . . 2n, each of the sigma points having n states; performing (2n+1) integrations, each integration includes propagating the n-states of the respective sigma points Xi through the non-linear function Yi=f(Xi); and combining the propagated sigma points to generate the predicted future states of the vehicle.