Abstract: A magnet-guiding switching system includes a lane magnetic field device, a switching controlling module and a route controlling center. As the switching controlling unit informs the magnetic field switching unit to turn on the first switching electromagnets and to turn off the second switching electromagnets according to the driving signal, the vehicle is guided by magnetic fields of the first switching electromagnets to drive from the first section of the first route to the second section along the guiding section; as the switching controlling unit informs the magnetic field switching unit to turn on the second switching electromagnets and to turn off the first switching electromagnets according to the driving signal, the vehicle is guided by magnetic fields of the second switching electromagnets to drive from the first section of the first route to the continuous section of the second route along the switching section.

Abstract: A magnet-guiding switching system includes a lane magnetic field device, a switching controlling module and a route controlling center. As the switching controlling unit informs the magnetic field switching unit to turn on the first switching electromagnets and to turn off the second switching electromagnets according to the driving signal, the vehicle is guided by magnetic fields of the first switching electromagnets to drive from the first section of the first route to the second section along the guiding section; as the switching controlling unit informs the magnetic field switching unit to turn on the second switching electromagnets and to turn off the first switching electromagnets according to the driving signal, the vehicle is guided by magnetic fields of the second switching electromagnets to drive from the first section of the first route to the continuous section of the second route along the switching section.

Abstract: A deciding system for stopping and dispatching vehicles includes a memory and a cloud processing unit. The cloud processing unit is configured to determine one of a fixed vehicle dispatching algorithm and a non-fixed vehicle dispatching algorithm to be executed by the cloud processing unit according to a temporary car-hailing order message; execute the one of the fixed vehicle dispatching algorithm and the non-fixed vehicle dispatching algorithm to generate a stop message corresponding to a stop station according to a dispatch parameter set from the memory, and generate a stop number set corresponding to the first vehicle according to the stop message; and execute the one of the fixed vehicle dispatching algorithm and the non-fixed vehicle dispatching algorithm to generate a dispatch message according to the dispatch parameter set, and generate a dispatch vehicle number set corresponding to the second vehicle according to the dispatch message.

Abstract: An allochronic obstacle avoidance system for platooning is configured to decide an obstacle avoidance of a leading vehicle and at least one following vehicle. A sensing device is configured to generate an obstacle position and an obstacle speed. A leading vehicle processing unit is configured to transmit a leading vehicle parameter group. At least one following vehicle processing unit is configured to transmit at least one following vehicle parameter group. A cloud processing unit is configured to implement a cloud deciding step including predicting a leading vehicle free space and at least one following vehicle free space according to the leading vehicle parameter group and the at least one following vehicle parameter group, and deciding the obstacle avoidance of the leading vehicle and the at least one following vehicle according to the leading vehicle free space and the at least one following vehicle free space.

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 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 hybrid planning method in an autonomous vehicle is performed to plan a best trajectory function of a host vehicle. A parameter obtaining step is performed to sense a surrounding scenario of the host vehicle to obtain a parameter group to be learned. A learning-based scenario deciding step is performed to receive the parameter group to be learned and decide one of a plurality of scenario categories that matches the surrounding scenario of the host vehicle according to the parameter group to be learned and a learning-based model. A learning-based parameter optimizing step is performed to execute the learning-based model with the parameter group to be learned to generate a key parameter group. A rule-based trajectory planning step is performed to execute a rule-based model with the one of the scenario categories and the key parameter group to plan the best trajectory function.

Abstract: An automatic driving method and device able to diagnose decisions is disclosed herein, wherein a vehicle body signal sensor detects vehicle body information, and an environment sensor detects traffic environment information. The information is transmitted to a central processor to generate a future driving track. The central processor examines whether the differences between the future driving track and the traffic environment information and the indexes of the future driving track meet tolerances. If no, the central processor transmits notification information to an automatic driving controller. If yes, the central processor transmits the future driving track to the automatic driving controller to make the automatic driving controller undertake automatic driving according to the future driving track. The present invention can automatically judge whether the future driving track generated by the central processor is within tolerances and determine whether the automatic driving track is safe.

Abstract: An intersection speed deciding method includes a dataset obtaining and calculating step and a speed adjusting step. At least one of the vehicles expected to pass through one of the points is defined as the approaching vehicle, and a first arrival time of the approaching vehicle is obtained. Whether a preceding vehicle is on the host route is judged. If yes, a second arrival time of the preceding vehicle is obtained. Whether the host vehicle is expected to wait for a red light is judged. If yes, a red light duration is obtained. A time difference exists between a best arrival time and a corresponding expected arrival time, and each time difference is minimized based on the first arrival time, the second arrival time and the red time duration. A speed of the host vehicle is adjusted or remained based on the expected arrival times.

Abstract: An intersection speed deciding method includes a dataset obtaining and calculating step and a speed adjusting step. At least one of the vehicles expected to pass through one of the points is defined as the approaching vehicle, and a first arrival time of the approaching vehicle is obtained. Whether a preceding vehicle is on the host route is judged. If yes, a second arrival time of the preceding vehicle is obtained. Whether the host vehicle is expected to wait for a red light is judged. If yes, a red light duration is obtained. A time difference exists between a best arrival time and a corresponding expected arrival time, and each time difference is minimized based on the first arrival time, the second arrival time and the red time duration. A speed of the host vehicle is adjusted or remained based on the expected arrival times.

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 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: An automatic driving method and device able to diagnose decisions is disclosed herein, wherein a vehicle body signal sensor detects vehicle body information, and an environment sensor detects traffic environment information. The information is transmitted to a central processor to generate a future driving track. The central processor examines whether the differences between the future driving track and the traffic environment information and the indexes of the future driving track meet tolerances. If no, the central processor transmits notification information to an automatic driving controller. If yes, the central processor transmits the future driving track to the automatic driving controller to make the automatic driving controller undertake automatic driving according to the future driving track. The present invention can automatically judge whether the future driving track generated by the central processor is within tolerances and determine whether the automatic driving track is safe.

Abstract: A superimposition device of virtual guiding indication and reality image includes at least an image capturing device, a processor, a graphic processing unit (GPU), and a display device. The image capturing device captures reality image including instant scene. The processor receives the reality image and obtains height variation information. The GPU performs image correction processing on the reality image to obtain corrected image, generates updated transformation matrix according to the height variation information, and performs inverse perspective projection transformation by using the updated transformation matrix to generate bird's-eye view image of the corrected image and superimposes virtual guiding indication on the bird's-eye view image and performs perspective projection transformation on the bird's-eye view image to transform the bird's-eye view image into three-dimensional (3D) navigation image which includes the guiding indication.

Abstract: The present disclosure provides an OLED structure. The OLED structure includes a cathode layer, an organic light emitting layer, and an anode layer. The organic light emitting layer is located between the cathode layer and the anode layer. A reflective layer is formed under the cathode layer and the anode layer, an insulation isolation layer is formed on the reflective layer. In the present disclosure, structural modification is performed on the anode of the OLED structure to directly avoid possibility of hill lock in the anode. Thus, improvement in the reliability, productivity and yield of the OLED is ensured.

Abstract: A self-locking and positioning device for a dental brace, comprising: a brace main body, an elastic piece, and an upper cover. Wherein, on the brace main body is provided with a track and a fixing slot, while on the elastic piece is provided with a positioning piece and a slot. The positioning piece is provided with a barb, while the upper cover slides and fixes into the brace main body through the track. Then, the barb of the positioning piece on the elastic piece will act against a block portion on bottom of said upper cover, to restrict movement of the upper cover, to lock automatically the upper cover into position. The dental brace is simple in construction and easy to assemble, hereby raising production efficiency and yield.

Abstract: A self-locking and positioning device for a dental brace, comprising: a brace main body, an elastic piece, and an upper cover. Wherein, on the brace main body is provided with a track and a fixing slot, while on the elastic piece is provided with a positioning piece and a slot. The positioning piece is provided with a barb, while the upper cover slides and fixes into the brace main body through the track. Then, the barb of the positioning piece on the elastic piece will act against a block portion on bottom of said upper cover, to restrict movement of the upper cover, to lock automatically the upper cover into position. The dental brace is simple in construction and easy to assemble, hereby raising production efficiency and yield.

Abstract: The present invention discloses a manufacturing method of a test strip, which comprises making a first semi-finished product and a second semi-finished product. The manufacturing process of the first semi-finished product comprises: providing a substrate, forming a plurality of electrodes on the substrate, forming a supporting layer with a plurality of channels on the substrate, and providing a reaction material to fill in the channels. The manufacturing process of the second semi-finished product comprises: providing a lid, forming a hydrophilic layer on a first surface of the lid, forming an adhesive layer on the first surface without the hydrophilic layer. Thereafter, a test strip assembly is formed by adhering the channels of the first semi-finished product to the hydrophilic layer of the second semi-finished product. Finally, a plurality of test strips are produced by cutting the test strip assembly along a first axis of the substrate.

Abstract: Sideways-extending speaker apparatus and methods that include a speaker box that is adjustable to fit within given information handling system or electronic device chassis form factor constraints, while also being selectably extendable and expandable to provide increased speaker box volume to achieve improved sound quality performance both in terms of increased speaker spatial separation and wider dynamic range.

Abstract: The present invention provides a testing strip for detecting a fluidic sample for testing a fluidic sample. The testing strip for detecting a fluidic sample comprises a substrate, a plurality of electrodes, a supporting layer and a cover that are serially stacked. The testing strip for detecting a fluidic sample includes a longitudinal long axis and a transverse short axis. The testing strip for detecting a fluidic sample includes a first end and a second end opposing to the first end along the longitudinal long axis. The testing strip for detecting a fluidic sample includes a reacting region located at the terminal of the first end, and the reacting region is defined and enclosed by the cover, the supporting layer and the substrate. The reacting region has a C-liked structure from a cross-sectional view taken along a direction perpendicular to the longest flowing path of the fluidic sample.