TL;DR: In this article, an ultrasonic sensor is used to measure the distance to a parked vehicle and a moving distance of the vehicle is calculated using a signal from a wheel speed sensor.
Abstract: When a vehicle advances in parallel with a parking frame to reach an initial stop position, measurement of a distance to a parked vehicle is continuously performed by means of an ultrasonic sensor and a moving distance of the vehicle is simultaneously calculated using a signal from a wheel speed sensor. When actuating an in-line mode switch under a state where the vehicle stops in the initial stop position, a turning angle is calculated so as to enable appropriate in-line parking to the parking frame from an actual initial stop position, based on a deviation of the vehicle from a reference position for the initial stop measured by the ultrasonic sensor. Information on a driving operation that is necessary for back parking is provided to a driver via a speaker based on this turning angle and output from a yaw rate sensor.
TL;DR: In this article, a parking assistance system is mounted in a vehicle, and has an image pick-up with a single camera, an image processing device, a display, a steering angle sensor, a wheel speed sensor, and a pulse counter.
Abstract: A parking assistance system is mounted in a vehicle, and has an image pick-up with a single camera, an image processing device, a display, a steering angle sensor, a wheel speed sensor, and a pulse counter. An A/D converter subjects two analog images picked up by the image pick-up at different locations to A/D conversion, and sends the results to frame memories. A CPU uses the digital image data and the transition data of the vehicle to calculate object data and a distance from the vehicle to the 3D object. An image thus obtained is then converted into a view from the above. The view from the above is stored in a frame memory, and outputted to the display under the control of a controller for display.
TL;DR: This paper proposes a sensor fusion-based low-cost vehicle localization system that fuses a global positioning system (GPS), an inertial measurement unit (IMU), a wheel speed sensor, a single front camera, and a digital map via the particle filter via the particles filter.
Abstract: This paper proposes a sensor fusion-based low-cost vehicle localization system. The proposed system fuses a global positioning system (GPS), an inertial measurement unit (IMU), a wheel speed sensor, a single front camera, and a digital map via the particle filter. This system is advantageous over previous methods from the perspective of mass production. First, it only utilizes low-cost sensors. Second, it requires a low-volume digital map where road markings are expressed by a minimum number of points. Third, it consumes a small computational cost and has been implemented in a low-cost real-time embedded system. Fourth, it requests the perception sensor module to transmit a small amount of information to the vehicle localization module. Last, it was quantitatively evaluated in a large-scale database.
TL;DR: In this paper, a system and method for maintaining a vehicle at a predetermined velocity on a graded surface is provided, which includes a propulsion system to supply motive torque to a vehicle wheel, a vehicle stability sensor, and a control system adapted to receive signal input from the vehicle stability sensors.
Abstract: A system and method for maintaining a vehicle at a predetermined velocity on a graded surface is provided, which includes a propulsion system to supply motive torque to a vehicle wheel, a vehicle stability sensor, and a control system adapted to receive signal input from the vehicle stability sensor. The control system controls magnitude of the motive torque supplied to the wheel. The propulsion system may include an electric wheel motor powered by an electrical energy storage system, a hybrid powertrain system, and an internal combustion engine and transmission. The vehicle stability sensor determines orientation of the vehicle relative to a horizontal plane, including a longitudinal acceleration sensor and a virtual longitudinal acceleration sensor. The control system receives inputs from a wheel speed sensor, an accelerator pedal sensor, and a brake pedal sensor to control motive torque. Motive torque is controlled to maintain wheel speed sensor at a null output.
TL;DR: In this article, a wheel deceleration computation unit is used to calculate the wheel speed and the wheel acceleration in order to set the target brake torque irrespective of any disturbance to a control system, any state change of the external side, and to prevent the braking force from being unnecessarily reduced.
Abstract: PROBLEM TO BE SOLVED: To adequately set the target brake torque irrespective of any disturbance to a control system, any state change of the external side, and to prevent the braking force from being unnecessarily reduced. SOLUTION: The brake control device 10 includes a wheel deceleration computation unit 53a for calculating the wheel deceleration GRe by the wheel speed detected by a wheel speed sensor 45 during the previous computation of the estimated deceleration GRDV of a vehicle body by a vehicle body deceleration computation unit 52, and the wheel speed detected by the wheel speed sensor 45 during the present computation, and an estimated vehicle body deceleration computation unit 53b for calculating the estimated vehicle body deceleration GRv. The vehicle body deceleration computation unit 52 computes the estimated deceleration GRDV of the vehicle body by executing the correction by the correction coefficient KD according to the ratio of the wheel deceleration GRe to the estimated vehicle body deceleration GRv. The correction coefficient KD is corrected so that the estimated deceleration GRDV is larger after the correction than before the correction when the wheel deceleration GRe is larger than the estimated vehicle body deceleration GRv. COPYRIGHT: (C)2010,JPO&INPIT