9results about How to "Reduce driving risk" patented technology

The utility model belongs to the field of vehicle networking communication equipment especially a kind of vehicle-road cooperation communication terminal, it includes fixed link one and vehicle-road cooperation terminal machine;The one end of fixed link one is fixedly connected with multiple clamps, and multiple The abutment of clamp has same sphere, the upper fixed connection of sphere has fixed link two, the one end of fixed link two is installed with vehicle-road cooperation terminal machine, the same tightening sleeve is threadedly connected on the fixed link one and multiple The clamp of the upper of fixed link one is threadedly connected with screw rod one, arc plate one is welded on the fixed link one, the same sliding slot one is set in arc plate one and fixed link one, arc plate two is slidably connected in sliding slot, the utility model is adjusted the effect that the distance between vehicle-road cooperation terminal machine and user is adjusted by the cooperation of each component, and the effect that it is adjusted at multiple angles is also achieved.

The invention discloses an obstacle sensing method, a cleaning robot, a storage medium and a program product, and the obstacle sensing method comprises the steps: obtaining sensing data of a sensing sensor of the cleaning robot; in response to the situation that the cleaning robot is detected to be in a diving state according to the sensing data, a distance measuring sensor of the cleaning robot is controlled to emit first emitting light of a first wavelength, and the diving state is used for representing that the cleaning robot is immersed in water; the distance measuring sensor is controlled to receive first reflected light, the first reflected light is formed by reflecting the first emitted light through a first obstacle, and the first obstacle is immersed in water; and determining a first distance between the first obstacle and the cleaning robot according to the first emitted light and the first reflected light. According to the method, when it is detected that the cleaning robot dives into the water, the first distance of the underwater first obstacle is sensed based on the light of the first wavelength emitted by the distance measuring sensor, and the underwater driving risk of the cleaning robot can be reduced.

The application provides a secure encryption method, device, system, equipment and medium for vehicle information, comprising: obtaining first feature information of a smart terminal and second feature information of a vehicle terminal after establishing communication with the smart terminal; determining the communication state of the vehicle terminal and the smart terminal, and constructing an encryption key according to the communication state and the characters of the first feature information and the second feature information; calling the encryption key to encrypt the interactive vehicle information to obtain encrypted information. The application can construct a specific encryption key for each smart terminal based on the feature information of the vehicle terminal and the smart terminal, and can encrypt by using the specific encryption key, so as to reduce the risk of information cracking or leakage, improve the security and privacy of information, and ensure information security. Meanwhile, the control safety of the vehicle terminal can also be improved by interacting with the encrypted information, and the driving risk of the user is reduced.

The application discloses an intelligent traffic auxiliary correction method and system based on remote sensing monitoring, relates to the technical field of intelligent traffic assistance, and comprises effective point feedback and point driving correction. First, user historical eye movement and vehicle dynamic data are collected through the effective point feedback step, driving behavior concentration duration is calculated, behavior types are matched, and eye movement data occurrence rates are counted, current driving data and image recognition are combined, and the first preferred point of the user is determined; voice prompts are given and steering auxiliary force is adjusted. Secondly, historical remote sensing data are collected through the point driving correction step, invalid data are analyzed, and eye movement focus side view angle correction values are summarized; driving directions are prompted, and turning compensation force is applied. The application realizes precise driving assistance through multi-source data fusion, improves safety, adapts to different driving habits through the linkage of historical and real-time data, and improves the precision of the auxiliary system.

The application provides a cockpit implementation method and system based on emotion enhancement and scenario service flow intelligent agent, and belongs to the technical field of automobile intelligent cockpits. The method comprises the following steps: acquiring multi-modal data of a target user in real time, fusing the multi-modal data to generate comprehensive user states, planning a service flow based on scenario semantics and the user states, and generating and outputting action execution instructions of internal and external resources according to the service flow. Through multi-modal deep fusion and scenario semantic understanding, the application can accurately capture user states and demands, provide the most suitable service at the most appropriate time, and change passive response into active care. The application sets a user memory vector library to continuously learn and adapt to user preferences, provides a truly 'thousand faces for a thousand people' service, and as the use time increases, the service accuracy and user satisfaction present a continuously rising curve, thereby solving the problem of static experience of traditional systems.

This utility model discloses an emergency splicing device for signal cables, relating to the field of rail transit signaling technology. It includes two cable terminal boxes, a faulty cable, and two splicing cables. The faulty cable is cut into two ends, each connected to one of the two cable terminal boxes. The two cable boxes are connected by the two splicing cables. Each terminal box has multiple cable inlet holes of different diameters, through which the faulty cable end can pass. A gland lock is used to seal the inlet holes. This utility model, through the sealing of the terminal boxes and the design of prefabricated splicing cables, achieves the goals of quick connection, sealing, reliability, and versatility in emergency repairs. It meets the timeliness requirements of railway transportation repairs and reduces operational risks through structural optimization, representing a significant upgrade to traditional cable splicing technology.

This application provides a functional safety-based gear position monitoring method, device, and electronic device. When torque and speed information are available, ASILC-level torque and speed information is preferentially used as monitoring input information. This allows for direct calculation of the current gear at level C, improving the safety level of gear position monitoring and reducing driving risks caused by inaccurate gear position monitoring. When torque or speed information is unavailable, the current vehicle speed at level ASILB is used as input information to ensure uninterrupted monitoring of the current gear position. This strategy of using level C information as the primary source and level B information as a secondary source for monitoring the vehicle's functional safety gear positions enhances the safety level of gear position monitoring while ensuring that monitoring of the current gear position does not stop even if level C information monitoring malfunctions, thus improving the safety of the user while driving.

The application discloses a cockpit system time information processing method based on user state and related device, the method comprises: when the time when the vehicle travels is within a preset time period, the driving route where the vehicle is located is within a preset driving route, and the driving route where the vehicle is located is a congested route, the driver's gesture is collected through a camera, if the similarity of the collected driver's gesture and the pre-set gesture is greater than or equal to a first preset value, the driver's eye line focus area on the display screen is determined; the collected driver's eye line focus area is compared with the target time display area of the display screen, the target time display area is a preset display area that meets the driver's sitting posture under the current seat setting and has a display area greater than a preset area; if the matching degree of the collected driver's eye line focus area and the target time display area is greater than or equal to a second preset value, the display screen displays time-related information in the target time display area.

The application relates to a road section vehicle group dissolving method based on real-time vehicle speed regulation, which comprises the following steps: S1, acquiring real-time traffic information of a road section; S2, when the headway between a host vehicle and a front vehicle in the same lane is less than a safe following headway and the headways between the host vehicle and front vehicles in adjacent lanes are both less than a safe lane-changing headway, the front vehicle in the same lane and the front vehicles in the adjacent lanes form a vehicle group; S3, judging the risks of vehicles in the vehicle group, and the vehicle with the maximum risk value R being the risk source of the vehicle group; S4, regulating the vehicle speed of the risk source vehicle of the vehicle group; and S5, when the host vehicle satisfies the condition that the headway with the front vehicle in the same lane is greater than or the headway with the front vehicle in the adjacent lane is greater than, the original vehicle group is dissolved. The application dissolves the vehicle group and reduces the driving risk of the road section by regulating the real-time vehicle speed of the risk source vehicle.