Abstract: A safe following distance estimation system and an estimation method thereof are provided. The safe following distance estimation system adapted for an autonomous vehicle includes a sensor and a processor. The sensor senses an adjacent vehicle to generate first sensing data, and senses the autonomous vehicle to generate second sensing data. The processor estimates a first friction parameter between wheels of the adjacent vehicle and a pavement according to pavement material data, and estimates a second friction parameter between wheels of the autonomous vehicle and the pavement according to the second sensing data. The processor calculates a safe following distance between the autonomous vehicle and the adjacent vehicle according to the first sensing data, the second sensing data, the first friction parameter, the second friction parameter.

Abstract: A vehicle driving control apparatus and a control method and a display method for the same are provided. The vehicle driving control apparatus includes a sensor and a processor. The sensor detects current relative position and current relative velocity of an object around a vehicle. The processor calculates a collision probability between the vehicle and the object based on the current relative position and current relative velocity of the object, and determines whether to adjust a driving dynamics of the vehicle based on the collision probability.

Abstract: A safe following distance estimation system and an estimation method thereof are provided. The safe following distance estimation system adapted for an autonomous vehicle includes a sensor and a processor. The sensor senses an adjacent vehicle to generate first sensing data, and senses the autonomous vehicle to generate second sensing data. The processor estimates a first friction parameter between wheels of the adjacent vehicle and a pavement according to pavement material data, and estimates a second friction parameter between wheels of the autonomous vehicle and the pavement according to the second sensing data. The processor calculates a safe following distance between the autonomous vehicle and the adjacent vehicle according to the first sensing data, the second sensing data, the first friction parameter, the second friction parameter.

Abstract: A trajectory planning method for lane changing of a vehicle includes steps of: calculating a current position of a reference point of the vehicle on a preliminary lane change trajectory that is received from an LCA system of the vehicle at a current time point; based on kinematics data received from an IMU of the vehicle, calculating longitudinal and lateral displacements of the reference point moving during a unit of time from the current time point to a next time point, and a yaw angle of the vehicle at the next time point; and obtaining a calibrated lane change trajectory based on the preliminary lane change trajectory, the current position, the longitudinal and lateral displacements, and the yaw angle.

Abstract: A trajectory planning method for lane changing of a vehicle includes steps of: calculating a current position of a reference point of the vehicle on a preliminary lane change trajectory that is received from an LCA system of the vehicle at a current time point; based on kinematics data received from an IMU of the vehicle, calculating longitudinal and lateral displacements of the reference point moving during a unit of time from the current time point to a next time point, and a yaw angle of the vehicle at the next time point; and obtaining a calibrated lane change trajectory based on the preliminary lane change trajectory, the current position, the longitudinal and lateral displacements, and the yaw angle.

Abstract: A lane tracking method is proposed for use by an autonomous vehicle running on a lane. A future location of the autonomous vehicle that corresponds to a future time point is estimated based on a current location and a measurement result of an inertial measurement unit of the autonomous vehicle. The future location of the autonomous vehicle, and a reference lane line data and a reference past location that correspond to a reference past time point are used to estimate a future lane line data that corresponds to the future time point.

Abstract: A lane tracking method is proposed for use by an autonomous vehicle running on a lane. A future location of the autonomous vehicle that corresponds to a future time point is estimated based on a current location and a measurement result of an inertial measurement unit of the autonomous vehicle. The future location of the autonomous vehicle, and a reference lane line data and a reference past location that correspond to a reference past time point are used to estimate a future lane line data that corresponds to the future time point.

Abstract: A vehicle lateral control system having a lane model with modulation weighting for controlling a vehicle includes a camera, an image processing device, a controller and a steering device. The camera is configured to capture a front image of the vehicle to generate a front image dataset. The front image dataset is analyzed by the image processing device to obtain a plurality of lane markers, and the image processing device establishes a lane fitting curve according to the lane markers and a target weighting. The controller has a plurality of vehicle dynamic parameters and a target distance. The target weighting is changeable according to the target distance. The controller generates a steering control weighting according to the lane fitting curve and the vehicle dynamic parameters. The steering device is configured to control a turning direction of the vehicle according to the steering control weighting.

Abstract: A vehicle lateral control system having a lane model with modulation weighting for controlling a vehicle includes a camera, an image processing device, a controller and a steering device. The camera is configured to capture a front image of the vehicle to generate a front image dataset. The front image dataset is analyzed by the image processing device to obtain a plurality of lane markers, and the image processing device establishes a lane fitting curve according to the lane markers and a target weighting. The controller has a plurality of vehicle dynamic parameters and a target distance. The target weighting is changeable according to the target distance. The controller generates a steering control weighting according to the lane fitting curve and the vehicle dynamic parameters. The steering device is configured to control a turning direction of the vehicle according to the steering control weighting.