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: A semiconductor package device is provided. The semiconductor package device includes a chip and a redistribution layer disposed on the chip and electrically connected to the chip. The redistribution layer includes a plurality of first metal lines and a plurality of second metal lines, wherein at least one of the second metal lines is disposed between two adjacent first metal lines. The included angle between the at least one of the second metal lines and the two adjacent first metal lines is greater than or equal to 0 degrees and less than or equal to 10 degrees. The first width of one of the two adjacent first metal lines is greater than the second width of the at least one of the second metal lines.

Abstract: A structure and a method of forming are provided. The structure includes a first dielectric layer overlying a first substrate. A first connection pad is disposed in a top surface of the first dielectric layer and contacts a first redistribution line. A first dummy pad is disposed in the top surface of the first dielectric layer, the first dummy pad contacting the first redistribution line. A second dielectric layer overlies a second substrate. A second connection pad and a second dummy pad are disposed in the top surface of the second dielectric layer, the second connection pad bonded to the first connection pad, and the first dummy pad positioned in a manner that is offset from the second dummy pad so that the first dummy pad and the second dummy pad do not contact each other.

Abstract: A semiconductor device includes a first region and a second region, and the second region surrounds the first region. The semiconductor device includes at least one electronic unit, a redistribution structure, a plurality of first pads, and a plurality of second pads. The redistribution structure may be electrically connected to at least one electronic unit. A plurality of first pads are arranged on the redistribution structure and correspondingly to the first region. There is a first pitch between two adjacent first pads. A plurality of second pads are arranged on the redistribution structure and correspondingly to the second region. There is a second pitch between two adjacent second pads, so that the first pitch is smaller than the second pitch.

Abstract: A semiconductor structure is provided. The semiconductor structure comprises a substrate, a via, a liner layer, a barrier layer, and a conductor. The via penetrates through the substrate. The liner layer is formed on a sidewall of the via. The barrier layer is formed on the liner layer. The barrier layer comprises a conductive 2D material. The conductor fills a remaining space of the via.

Abstract: A fabrication method is disclosed that includes: forming a first metal layer over first and second semiconductor structures; forming a first patterned photolithographic layer with an opening that exposes a portion of the first metal layer over the first semiconductor structure but not to a boundary between semiconductor structures; removing the exposed portion of the first metal layer; forming a second metal layer over the first and second semiconductor structures; forming a second patterned photolithographic layer with an opening that exposes a portion of the second metal layer over the second semiconductor structure but not to the boundary; removing the exposed portion of the first and second metal layers; wherein a barrier structure is generated between the first and second semiconductor structures that includes remaining portions of the first metal layer and a portion of the second metal layer overlying the remaining portions of the first metal layer.

Abstract: A mobile device includes a housing, a first radiation element, a second radiation element, a third radiation element, a first switch element, and a second switch element. The first radiation element has a first feeding point. The second radiation element has a second feeding point. The first radiation element, the second radiation element, and the third radiation element are distributed over the housing. The first switch element is closed or open, so as to selectively couple the first radiation element to the third radiation element. The second switch element is closed or open, so as to selectively couple the second radiation element to the third radiation element. An antenna structure is formed by the first radiation element, the second radiation element, and the third radiation element.

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.