Abstract: A method and a system for generating dynamic map information with environment information are provided, wherein the system includes a cloud server, multiple relay hosts distributed around the environment and multiple vehicle devices each installed respectively in different vehicles. Each vehicle device includes a LiDAR sensor and a camera for sensing the environment to respectively generate point cloud data and image data. When the point cloud data from different vehicles are transmitted to a neighboring relay host, the relay host performs a multi-vehicle data integration mode to merge the point cloud data and obtain 3D coordinates information of objects in the environment according to the merged data. Based on the 3D coordinates information of objects, the cloud server generates and transmits dynamic map information to the vehicles. By sharing sensing data of different vehicles, the sensing area of each vehicle is expanded to mitigate dark zones or blind zones.

Abstract: A method and a system for generating dynamic map information with environment information are provided, wherein the system includes a cloud server, multiple relay hosts distributed around the environment and multiple vehicle devices each installed respectively in different vehicles. Each vehicle device includes a LiDAR sensor and a camera for sensing the environment to respectively generate point cloud data and image data. When the point cloud data from different vehicles are transmitted to a neighboring relay host, the relay host performs a multi-vehicle data integration mode to merge the point cloud data and obtain 3D coordinates information of objects in the environment according to the merged data. Based on the 3D coordinates information of objects, the cloud server generates and transmits dynamic map information to the vehicles. By sharing sensing data of different vehicles, the sensing area of each vehicle is expanded to mitigate dark zones or blind zones.

Abstract: A multiple-positioning-system switching and fused calibration method and a device thereof are provided. A first sensing device generates first sensing information, and the central processor calculates the first positioning information of a current position according to the first sensing information and a starting position, and downloads map information from the cloud database. A second sensing device detects a feature object, and obtains the distance information of the feature object and the current position, to the central processor. The central processor calculates a current position in the map information, and generates second positioning information, and performs fused calculation on the first positioning information and the second positioning information according to the weight values of a weight distribution table, to generate new first positioning information to replace the first positioning information.

Abstract: A method for sampling and converting vehicular network data is executed by a vehicle host. The vehicle host selects one of multiple data signals from an original signal, and establishes a data table. The vehicle host further determines whether the original signal includes any data signal remaining unselected. When the original signal does not include any data signal remaining unselected, the vehicle host differentially samples data in the data table corresponding to other time sequences by using the data in the data table corresponding to a first time sequence as a reference to generate a differential data table, and compresses the differential data table. The method can reduce the amount of data by performing differential sampling, so that the compression ratio of the data can be effectively improved, and the delay of data transmission can be avoided.

Abstract: A foreign object detection device includes a processor, a detecting circuit assembly connected to the processor, a coil connected to the detecting circuit assembly, a signal generator connected to the processor and the detecting circuit assembly, and a coil configuring circuit connected to the processor and the coil. The processor outputs a control signal to the coil configuring circuit so as to control the coil configuring circuit to generate a switch signal for enabling the coil to switch to one of a closed mode and an open mode, and controls the signal generator to transmit a test signal to the coil via the detecting circuit assembly when the coil is in the open mode.

Abstract: A nighttime vehicle detecting method is for capturing an image by a camera and driving a computing unit to compute the image and then detect a highlight point of the image. The nighttime vehicle detecting method is for driving the computing unit to perform a communicating region labeling algorithm to label a plurality of highlight pixels connected to each other as a communicating region value, and then performing an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area. The nighttime vehicle detecting method is for driving the computing unit to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filtering the vehicle lamp moved at the speed smaller than a predetermined speed.

Abstract: The intelligent driving method applied to a vehicle includes a support vector machine providing step in which the support vector machine is provided. The support vector machine has been trained by a training process. In the training process, a training dataset is provided to the support vector machine. The training dataset is obtained after an original dataset processed by a dimensionality reducing module and a time scaling module. The intelligent driving method includes a dataset processing step in which p features from an environment sensing unit are processed by the dimensionality reducing module and the time scaling module, and the processed dataset will be provided to the support vector machine. The intelligent driving method further includes a deciding step for providing a driving decision for the vehicle according to a classed result of the support vector machine.

Abstract: The present disclosure provides a method for analyzing an error and an existence probability of a multi-sensor fusion. The method includes the ab obstacle sensing step, an obstacle predicting step, an error-model providing step, an existence-probability step, a tracking and fusing step and an error accumulating and correcting step. Therefore, by using the method, a plurality of fused obstacle datasets can be obtained, and an accumulation of error variations thereof can be corrected, which can improve the reliability for judging whether the obstacle exist or not.

Abstract: A dynamic graphic information classification device which is installed in a vehicle and comprises at least one automatic driving assistant system, a wireless communication interface, a storage device, a GPS module, and a processor. The wireless communication interface is connected with a cloud server where a high definition map and 3D point cloud map information are stored. The GPS module acquires position coordinates of the vehicle from an electronic map. The storage device stores at least one of at least one road curvature and at least one crossroads feature of a road environment of a predetermined driving path of the vehicle. The processor classifies the map information to be downloaded according to at least one of at least one road curvature and at least one crossroads feature and an automatic driving level of the automatic driving assistant system, whereby to reduce the time for download.

Abstract: A method of adaptive weighting adjustment positioning has the following steps: performing an initialization procedure, determining whether a first feature point is detected; when the first feature point is detected, based on multiple positioning methods, multiple positioning information will be generated, and multiple weightings will be set, and then based on the weightings and the positioning information, calculating the positioning information output; by way of adaptive weighting adjustment among the multiple positioning methods, the multiple positioning methods can be integrated. In this way, even if one of the positioning methods is temporarily unavailable, the positioning information can still be calculated by weighting adjustment between the positioning information of the remaining two available methods, and that allows users to continue to obtain accurate positioning information to confirm the current location.

Abstract: A hydrogen producing apparatus includes a reforming unit, a feed unit, and a heating unit. The reforming unit includes a casing defining a receiving space and having gas intake and outlet ports, a plurality of reformers disposed in the receiving space, at least one gas pipe winding around one of the reformers, and a connecting pipe in fluidic communication with the gas pipe. The feed unit is in fluidic communication with the reformers and the connecting pipe such that air delivered from the gas intake port through the gas pipe and the connecting pipe is mixed with a fuel in the feed unit to form a reactant mixture to be fed to the reformers for hydrogen production. The heating unit includes a heater connected to the casing.

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: An image positioning method and an image positioning device for using the same is disclosed. The method finds the position of a vehicle that is driving on a road, and a plurality of signs is arranged on the road. Firstly, an electronic map having a plurality of paths, a plurality reference images, and characteristic positions of the plurality of paths and the plurality reference images is provided. Next, at least two positioning images of the signs closest to the vehicle are sequentially retrieved. The reference image identical to the positioning images are searched on the electronic map and used as characteristic images. When the order of all the characteristic images corresponds to the order of all the positioning images, the position of the vehicle is estimated according to the path corresponding to all the characteristic images and the characteristic positions of all the characteristic images.

Abstract: A hydrogen producing apparatus includes a reforming unit, a feed unit, and a heating unit. The reforming unit includes a casing defining a receiving space and having gas intake and outlet ports, a plurality of reformers disposed in the receiving space, at least one gas pipe winding around one of the reformers, and a connecting pipe in fluidic communication with the gas pipe. The feed unit is in fluidic communication with the reformers and the connecting pipe such that air delivered from the gas intake port through the gas pipe and the connecting pipe is mixed with a fuel in the feed unit to form a reactant mixture to be fed to the reformers for hydrogen production. The heating unit includes a heater connected to the casing.

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 dynamic road surface detecting method based on a three-dimensional sensor is provided. The three-dimensional sensor receives a plurality of laser-emitting points reflected from a road surface to generate a plurality of three-dimensional sensor scan point coordinates which is transmitted to a point cloud processing module. The point cloud processing module transforms the three-dimensional sensor scan point coordinates to a plurality of vehicle scan point coordinates according to a coordinate translation equation, and then transforms a plurality of vehicle coordinate height values of the vehicle scan point coordinates to a road surface height reference line according to a folding line fitting algorithm. An absolute difference of two scan point height values of any two adjacent scan points on each of the scan lines is analyzed to generate a discontinuous point. The point cloud processing module links the discontinuous points to form a road boundary.

Abstract: A method for detecting an abnormality of a fluid filter includes: detecting a flow rate of a fluid in the fluid filter; detecting a pressure difference in the fluid filter; constructing an operating model of the fluid filter in accordance with a geometry of the fluid filter, a physical characteristic of the fluid, a porosity of the fluid filter, an impurity density, the flow rate and the pressure difference; obtaining an initial impurity accumulative quantity through the operating model; estimating a time dependent impurity accumulative status through a Kalman filter in accordance with the initial impurity accumulative quantity and the pressure difference; obtaining an impurity accumulative quantity in an estimated time in accordance with the time dependent impurity accumulative status, and then comparing the impurity accumulative quantity with a pre-determined value to determine if the fluid filter operates normally.

Abstract: A method for planning a trajectory for a self-driving vehicle on a road includes: generating multiple target planned trajectory sets based on information concerning the self-driving vehicle; calculating multiple projected moving ranges and multiple projected moving speeds of an obstacle based on information concerning the obstacle, the projected moving ranges corresponding respectively with multiple time points in a driving time period, the projected moving speeds corresponding respectively with the time points; and selecting one of the target planned trajectory sets as an optimal planned trajectory set based on the target planned trajectory sets, the projected moving ranges and the projected moving speeds for the obstacle.

Abstract: A safe warning system for automatic driving takeover includes a sensing unit, a wireless communicating unit, a driver detecting unit, a system self-testing unit, a human-machine interaction computing unit and an interface warning unit. The sensing unit senses an environmental condition to generate an environmental condition datum. The wireless communicating unit receives a cloud datum to generate a field status datum. The driver detecting unit detects the driver to generate a driver controlling datum. The system self-testing unit detects the sensing unit, the wireless communicating unit and the driver detecting unit to generate a system testing datum. The human-machine interaction computing unit receives and computes the environmental condition datum, the field status datum, the driver controlling datum and the system testing datum to generate an interface warning datum. The interface warning unit receives the interface warning datum and shows a warning signal to the driver.