Abstract: A method for detecting an interior condition of a vehicle is provided to use a camera device and a radar device to acquire images and point cloud datasets with respect to an interior space of the vehicle. A computing device generates a synthesized image based on the images and the point cloud datasets, obtains a skeleton feature dataset and a facial feature dataset with respect to a living object in the synthesized image, and determines the interior condition of the vehicle based on the skeleton feature dataset and the facial feature dataset.

Abstract: A vehicle platoon following deciding system based on cloud computing is configured to decide a plurality of vehicle platoon accelerations of a leading vehicle and at least one following vehicle. A cloud processing unit receives a leading vehicle parameter group and at least one following vehicle parameter group. The cloud processing unit is configured to implement a cloud deciding step. The cloud deciding step includes judging whether the leading vehicle is manually driven according to the leading vehicle parameter group to generate a driving mode judging result, calculating a driving acceleration range according to a leading vehicle acceleration range and at least one following vehicle acceleration range, estimating a compensated acceleration according to the leading vehicle parameter group, and calculating the vehicle platoon accelerations according to the driving mode judging result and at least one of the driving acceleration range and the compensated acceleration.

Abstract: A vehicle positioning method via data fusion and a system using the same are disclosed. The method is performed in a processor electrically connected to a self-driving-vehicle controller and multiple electronic systems. The method is to perform a delay correction according to a first real-time coordinate, a second real-time coordinate, real-time lane recognition data, multiple vehicle dynamic parameters, and multiple vehicle information received from the multiple electronic systems with their weigh values, to generate a fusion positioning coordinate, and to determine confidence indexes. Then, the method is to output the first real-time coordinate, the second real-time coordinate, and the real-time lane recognition data that are processed by the delay correction, the fusion positioning coordinate, and the confidence indexes to the self-driving-vehicle controller for a self-driving operation.

Abstract: A stably braking system and a method using the same control wheels on a single axle of a ground vehicle. Firstly, at least one of a wheel deceleration and an actual slip of each of the wheels is calculated. Hydraulic control commands are generated when a braking operation is performed in response to a braking indication signal and it is detected that the wheel deceleration or the actual slip is higher. The hydraulic control commands are configured to control a hydraulic braking system to adjust the wheel speed. When the ground vehicle drives in a straight line or turns with a first pose physical quantity, the hydraulic control command with a low priority is replaced by the hydraulic control command with a high priority and the hydraulic braking system is controlled to adjust the wheel speeds based on the identical hydraulic control commands.

Abstract: An air brake electric control valve includes a valve body, a force balance unit including a guide member, and an electromagnetic urge unit including a movable column operable to move between an urging position and a retracted position. When the movable column is at the urging position, the movable column pushes the air guide member such that a through hole of the air guide member is blocked. When the movable column is at the retracted position, a gap is formed between the movable column and the air guide member such that an intermediate section and a second passage of the valve body are in fluid communication via the through hole of the air guide member and the gap.

Abstract: A method of simultaneous localization and mapping (SLAM) is provided to position a target object. Each of detected tracked objects in a surrounding environment of the target object is classified into a moving object or a static object based on data detected at different time points. The target object is then positioned without considering any of the tracked objects that are classified into a moving object.

Abstract: A vehicle hybrid communication system includes a vehicle communication device and a field communication device. The vehicle communication device includes a vehicle controller and multiple vehicle communication interfaces. The field communication device includes a field controller and multiple field communication interfaces. The vehicle communication device and the field communication device communicate via multiple communication channels established by the vehicle communication interfaces and the field communication interfaces. The vehicle controller respectively defines a bandwidth level and a speed level based on a real-time bandwidth and a real-time connection speed of each of the communication channels. The vehicle controller then creates a score based on the bandwidth level and the speed level of each of the communication channels. The vehicle controller then sets one of the communication channels with the best score as a main communication channel to transfer data to the field communication device.

Abstract: An intersection warning system based on information fusion and a method thereof, the system includes an intersection sensing device, an intersection computing device, a user device and a cloud server. The cloud server receives and stores on-site sensing information output from the intersection computing device and determines whether user positioning coordinates are received from the user device, if so, the cloud server reads the on-site sensing information and at least one background information, and calculates a fusion risk assessment value based on the on-site sensing information, the at least one background information, and multiple weightings; when the cloud server determines the fusion risk assessment value is greater than a threshold value, a warning command is output to the user device which sends out warning messages according to the warning command.

Abstract: A system and a method for updating and sharing crossroad dynamic map data are disclosed.

Abstract: An intersection warning system based on information fusion and a method thereof, the system includes an intersection sensing device, an intersection computing device, a user device and a cloud server. The cloud server receives and stores on-site sensing information output from the intersection computing device and determines whether user positioning coordinates are received from the user device, if so, the cloud server reads the on-site sensing information and at least one background information, and calculates a fusion risk assessment value based on the on-site sensing information, the at least one background information, and multiple weightings; when the cloud server determines the fusion risk assessment value is greater than a threshold value, a warning command is output to the user device which sends out warning messages according to the warning command.

Abstract: The invention provides a verification method of the dynamic virtual image display distance of a user interface, comprising the following steps: creating a tested image database; wherein the tested image database comprises a tested image displayed according to a standard virtual image display distance; displaying a first tested image; projecting a first image on a stacked image element; wherein the first image is displayed at a first virtual image display distance, which is the same with a first standard virtual image display distance of the first tested image; capturing the first tested image and the first image; performing a first reliability evaluation procedure for the first image and the first tested image; and calculating a first overlap ratio for the first image and the first tested image to verify accuracy of the user interface.

Abstract: A vehicle hybrid communication system includes a vehicle communication device and a field communication device. The vehicle communication device includes a vehicle controller and multiple vehicle communication interfaces. The field communication device includes a field controller and multiple field communication interfaces. The vehicle communication device and the field communication device communicate via multiple communication channels established by the vehicle communication interfaces and the field communication interfaces. The vehicle controller respectively defines a bandwidth level and a speed level based on a real-time bandwidth and a real-time connection speed of each of the communication channels. The vehicle controller then creates a score based on the bandwidth level and the speed level of each of the communication channels. The vehicle controller then sets one of the communication channels with the best score as a main communication channel to transfer data to the field communication device.

Abstract: A voice recognition device includes at least one position retrieving device, a directional voice receiving device, a noise suppressor, and a voice recognition processor. The position retrieving device is sequentially coupled to the directional voice receiving device, the noise suppressor, and the voice recognition processor. The position retrieving device retrieves the physical voice position of a voice source and outputs the voice position to the directional voice receiving device. The directional voice receiving device receives a voice signal generated by the voice source according to the voice position. The noise suppressor eliminates the noise of the voice signal to generate a voice recognition signal based on noise model corresponding to the voice position. The voice recognition processor receives the voice recognition signal and generates an operating signal based on the voice recognition signal.

Abstract: A system and a method for active steering control with automatic torque compensation are disclosed with a processor that generates a targeted torque signal after receiving a steering assistance signal generated by an active driver assistance device, overlays the targeted torque signal on a driver's torque signal after receiving the driver's torque signal sensed by a torque sensor to generate a steering torque signal, and performs an assistance logic algorithm according to the steering torque signal. As the assistance logic algorithm is performed based on both the steering assistance signal and the driver's torque signal, the steering assistance effect provided by the system and the method will not resist against the way of driver's steering, allowing the driver to easily and stably control the vehicle.

Abstract: An Anti-lock Braking System and control method are disclosed. The control method is performed after a control module intervenes a vehicle's braking system and comprises: receiving a wheel speed signal of a wheel and a vehicle acceleration signal; computing a tire-slip feedback value according to the wheel speed signal of the wheels and the vehicle acceleration signal; generating a feedback control voltage according to a tire-slip difference between a tire-slip target value and the tire-slip feedback value; generating a tire-slip compensation value by performing a differential compensation to the tire-slip feedback value; obtaining a feedforward voltage according to the tire-slip compensation value via a look-up table approach; generating a braking control voltage by adding the feedback control voltage to the feedforward voltage; and outputting the braking control voltage to a proportioning-valve brake, such that the proportioning-valve brake adjusts a braking pressure according to the braking control voltage.

Abstract: A dynamic velocity planning method for an autonomous vehicle is performed to plan a best velocity curve of the autonomous vehicle. An information storing step is performed to store an obstacle information, a road information and a vehicle information. An acceleration limit calculating step is performed to calculate the vehicle information according to a calculating procedure to generate an acceleration limit value range. An acceleration combination generating step is performed to generate a plurality of acceleration combinations according to the obstacle information, the road information, and the acceleration limit value range. An acceleration filtering step is performed to filter the acceleration combinations according to a jerk threshold and a jerk switching frequency threshold to obtain a selected acceleration combination. An acceleration smoothing step is performed to execute a driving behavior procedure to adjust the selected acceleration combination to generate the best velocity curve.

Abstract: A localization and mapping method is for localizing and mapping a moving apparatus in a moving process. The localization and mapping method includes an image capturing step, a feature point extracting step, a flag object identifying step, and a localizing and mapping step. The image capturing step includes capturing an image frame at a time point of a plurality of time points in the moving process by a camera unit. The flag object identifying step includes identifying whether the image frame includes a flag object among a plurality of the feature points in accordance with a flag database. The flag database includes a plurality of dynamic objects, and the flag object is corresponding to one of the dynamic objects. The localizing and mapping step includes performing localization and mapping in accordance with the image frames captured and the flag object thereof in the moving process.

Abstract: A driving risk assessment and control decision-making method for an autonomous vehicle includes: detecting the surrounding state of the vehicle multiple times to generate multiple sensing signals; quantifying the sensing signals to generate multiple sensing values and calculating a sensing average value of the sensing values; calculating a sensing error value between each sensing value and the sensing average value, a sensing error average value of sensing error values and a sensing error variation value; integrating the sensing error average value, the sensing error variation value and a sensor systematic error average value and a sensor systematic error variation value to generate a sensing signal correction value; combining the sensing values and the sensing signal correction value to generate multiple sensing signal reference values; judging whether a stability of the sensing signal reference values falls within a preset range; generating a control mechanism based on the judgement.

Abstract: A method for controlling movement of an autonomous vehicle includes: estimating a set of tire force margins with respect to each wheel of the vehicle and a set of dynamic chassis margins associated with a chassis module of the vehicle; based on the margins, determining whether the vehicle is capable of moving in accordance with a decision command; when the determination is negative, outputting a request for update of the decision command; and when an updated decision command has not been received, calculating a set of marginal actuating signals based on the decision command, the margins, required slip angles respectively for the wheels and a center of percussion of the vehicle so as to make the autonomous vehicle move accordingly.

Abstract: A map-information obstacle-tracking system and a method thereof are provided. The system is installed in a vehicle. The method includes: using a vehicular dynamic positioning module to acquire a position of a vehicle, and using a map-information module to acquire map-information routes of an area neighboring the position of the vehicle; comparing position of the vehicle with the map-information routes to find out candidate routes in the moving direction of the vehicle; determining one of the candidate routes where said obstacle appears, and predicting a moving trajectory of the obstacle; estimating and outputting a position of the obstacle. The present invention is characterized in using map-information and able to acquire the curvature and slope of the front curved lane. Therefore, the present invention can improve the precision of the obstacle position and stabilizes the accuracy of detecting an obstacle in a curved lane.