Automotive Research & Testing Center

Automotive Research & Test Center

Po-Kai Tseng

Shun-Hung Chen

Jin-Yan Hsu

Chih-Neng Liang

Shih-Chieh Huang

Chao-Yang Lee

Tong-Wen Wang

Wei-Feng Hsu

An automatic land following control system is provided and includes an image sensor, a steering angle sensor, an inertial measurement unit, a vehicle speed sensor and a controller. The image sensor senses a vehicle lane to generate a land data. The steering angle sensor senses a steering angle to generate a steering angle data. The IMU senses an acceleration, a yaw rate and a roll angle of the vehicle to generate an acceleration data, a yaw rate data and a roll angle data. The vehicle speed sensor senses a speed of the vehicle to generate a vehicle speed data. The controller receives a digital map data, the lane data, the steering angle data, the acceleration data, the yaw rate data, the roll angle data and the vehicle speed data to calculate a compensation angle data of the wheel.

Automatic lane following control system and method for vehicles

A composite autonomous driving assistant system for making decision and a method of using the same is provided. A longitudinal-controlling autonomous driving assistant device and a lateral-controlling autonomous driving assistant device start to automatically assist in driving a vehicle. Then, a sensing device senses states of the vehicle and an environment and generates one sensing signal. When a controller determines that the collision period is less than a preset collision period and that a deceleration signal of the sensing signal is larger than a preset deceleration, the controller generates a turn-stopping signal. When the controller determines that a turn angle signal of the sensing signal is larger than a preset angle, the controller generates a speed-stopping signal. The system establishes a switching threshold condition when the plurality autonomous driving assistant devices coexist.

Composite autonomous driving assistant system for making decision and method of using the same

A driving control system mounted in a vehicle receives multiple pieces of information through a status detection module and a vehicle safety determination module thereof, performs a safety and collision analysis to predict whether a driving danger exists, when a driving danger exists, instructs an emergency control module to calculate an optimal barrier-avoiding path and send a corresponding control signal to a vehicle control module, and when no driving danger exists, instructs a normal control module to perform an adaptive algorithm according to different road conditions and driver's behavior information and send a control signal to the vehicle control module. Accordingly, the driving control system can instantly plan a barrier-avoiding path according the degree of emergency and collision danger to achieve the goal of enhancing safety and stability of the vehicle and driver in driving.

Driving control system and dynamic decision control method thereof

The present invention discloses an autonomous driving system able to make driving decisions and a method thereof, which decide a safer vehicle movement, wherein a processor generates a left-turn signal, a forward signal and a right-turn signal, receives and vectorizes a vehicle movement signal and object movement signals to determine whether one object is a dangerous or non-dangerous object, inputs the results into a corresponding equation to generate dangerous and non-dangerous object weights, substitutes the dangerous and non-dangerous object weights into a space weight equation to calculate left-turn, forward and right-turn lane section weights, uses the lane section weights to generate left-turn, forward and right-turn signal weights, generates a movement signal or a braking signal according to whether a highest one of the signal weights is over or below preset weight.

Automatic driving system able to make driving decisions and method thereof

The present invention provided a sliding mode trajectory voting strategy module. The sliding mode trajectory voting strategy module integrates a reaction time and a relative distance into an obstacle feature sliding surface by utilize sliding mode control theory, and calculates the obstacle feature sliding surface and a road curvature value in combination with fuzzy theory to obtain an orientation angle of a safety path.

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Changhua County, Taiwan

Po-Kai Tseng