Toyota Research Institute, Inc.

Toyota Jidosha Kabushiki Kaisha

Massachusetts Institute of Technology

Minoru Brandon Araki

Michael Thompson

Guy Rosman

Daniela Rus

Stephen G McGill

Avinash Balachandran

Luke S Fletcher

Yan Ming Jonathan Goh

John J Leonard

Sertac Karaman

Igor Gilitschenski

Alyssa Pierson

Moses Theodore Ort

Hanh Nguyen

James A Dallas

Yan Ming Goh

Izumi Karino

Phung Xuan Nguyen

Systems and methods provide for corrective assistance to maintain a stable controllable drift, while permitting a drift driving experience for the driver. Examples of the systems and methods disclosed herein include receiving first data corresponding to a current operational state of a vehicle while performing a controllable drift; receiving a request to operate the vehicle in a requested operational state; determining that the requested operational state exceeds a threshold operational state associated with an uncontrollable drift; and, in response to the determination, providing corrective assistance to operate the vehicle in a corrective operational state to prevent the vehicle from entering an uncontrollable drift.

Systems and methods for preventing uncontrollable vehicle drift

Systems and methods are provided for dynamic driver training, and may include: a communication interface to receive sensor data, the sensor data comprising driver biometric data and driver performance data for a driver operating a vehicle; a driver inference circuit to infer a skill level and emotional state of the driver operating the vehicle; and a driver training circuit to, based on the inferred skill level and emotional state of the driver operating the vehicle, dynamically adjust a driver training level for the driver while the driver is operating the vehicle.

Adaptive dynamic driver training systems and methods

Systems and methods described herein relate to estimating risk associated with a vehicular maneuver. One embodiment acquires a geometric representation of an intersection including a lane in which a vehicle is traveling and at least one other lane; discretizes the at least one other lane into a plurality of segments; determines a trajectory along which the vehicle will travel; estimates a probability density function for whether a road agent external to the vehicle is present in the respective segments; estimates a traffic-conflict probability of a traffic conflict in the respective segments conditioned on whether an external road agent is present; estimates a risk associated with the vehicle following the trajectory by integrating a product of the probability density function and the traffic-conflict probability over the at least one other lane and the plurality of segments; and controls operation of the vehicle based, at least in part, on the estimated risk.

Systems and methods for estimating the risk associated with a vehicular maneuver

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Saratoga, CA, United States of America

Minoru Brandon Araki