2297results about How to "Reduce traffic accidents" patented technology

A novel sleep regulating pharmaceutical formulation is introduced, typically implementing two principal drugs having actions which are reversive to one another, yet incorporated into a unitary solid dosage, and prepared for oral administration before bedtime. Usually, structure is configured to initially release a calmative or other sleep-compatible substance by prompt dissolution. The initial release is followed by a specific period of delay, which in basic formulations entails no release of any drug, and which allows a nominal interval of sleep. At the terminus of the delay, a final agent is released to induce wakeup. Incorporation of agents of opposite action within a unitary dosage form renders utility which is uniquely appropriate to the invention. In a preferred embodiment, delay of release and final delivery of wakeup agent are arranged by a dialysis membrane which eventually bursts as a result of osmotic pressure generated by a hydrophilic core.

The invention discloses intelligent traffic dispatching and commanding and information service method and system based on dynamic information. The method comprises the following steps of: collecting basic traffic data; normalizing the time, the space and the attributes of the basic traffic data; periodically evaluating and predicting the traffic state of the entire road network; periodically comparing the traffic state evaluation results and the historical data of the road network, and sending a warning prompt to a commander in case of exceeding a certain threshold; responding to a confirmed warning prompt, and creating a breakdown lorry dispatching scheme; and responding to the confirmed warning prompt and the evaluated and predicted road network traffic state, judging whether a serious traffic jam occurs, and creating and releasing abnormal traffic information or normal traffic information. The invention can increase the utilization ratio of the basic traffic data, can enhance the contact between the urban traffic command center and the 110 command center, and can improve the working efficiency of personnel in the command centers and the travelling efficiency of travelers.

The invention discloses a system for achieving fatigue driving judgment on the basis of image processing and fusion between the heart rate characteristic and the expression characteristic. The system comprises an information collection device, an information processing device and an early warning device. The system is characterized in that the information collection device is used for collecting a driver face image sequence, and providing the driver face image sequence for the information processing device; the information processing device is used for carrying out processing and analysis on the collected driver face image sequence to obtain expression characteristic information and heart rate characteristic information of a driver, and carrying out information fusion on the expression characteristic and the heart rate characteristic so that whether the driver is in the fatigue state or not can be judged; the early warning device is used for sending an instruction to an early warning prompting device according to the early warning strategy and the fatigue level when the driver is in fatigue driving, and carrying out prompting and early warning on the driver. According to the system for achieving fatigue driving judgment on the basis of image processing and fusion between the heart rate characteristic and the expression characteristic, the heart rate characteristic and the expression characteristic are combined through an image processing method, a fatigue driving judgment algorithm is achieved, a vehicle-mounted fatigue driving judgment device is obtained, and accuracy, robustness and reliability of the system for achieving fatigue driving judgment are improved.

The present invention discloses a driving behavior decision system of an automatic driving public traffic vehicle. The system comprises an external environment perception module, an information fusion processing module, a driving scene determination module and a driving behavior decision module. The external environment perception module comprises a vision sensor, a laser radar, a millimeter wave radar, a GPS location module and a high-precision map. The driving behavior decision module employs a limitation state machine model, and the driving behavior decision module employs a driving behavior determination decision model based on an ID3 decision tree; and the information fusion processing module performs fusion processing of the environment information sent by an external environment perception module and sends the information after fusion processing to the driving scene determination module and the driving behavior decision module. The driving behavior decision system of the automatic driving public traffic vehicle can improve the driving safety of the automatic driving public traffic vehicle and effectively reduce the probability of traffic accidents.

The invention provides a driving behavior safety evaluation method based on human-vehicle-environment multiple data sources and belongs to the field of automobile safety driving research in the aspectof road transportation application. The method comprises the steps that information data of a driver, driving data of a vehicle and environmental factor data are acquired as automobile driving sourcedata; according to the automobile driving source data, related factors which influence the driving safety are analyzed, and a driving risk evaluation index system is built; through statistical analysis, an evaluation value corresponding to an evaluation index is extracted in the source data, a driving risk score of a vehicle to be evaluated is calculated and obtained, and finally the driving behavior safety grade of the vehicle is determined. The driving behavior safety evaluation method has reliable evaluation results, can prevent dangerous driving behaviors, reduces traffic accidents and improves the traffic flow.

The invention is applicable to the technical field of communication, and provides a traffic safety prompting method, which comprises the steps as follows: when a mobile terminal is operated, the current position of the mobile terminal is detected, and a GPS unit is preferably started to detect the current position; a traffic dangerous area close to the current position is obtained; and if the distance between the current position of the mobile terminal and the traffic dangerous area reaches a preset distance threshold value, a traffic safety prompt is sent to a user. Accordingly, the invention further provides the mobile terminal. Therefore, the traffic safety prompting method can serve the function of traffic safety prompting during the operation of the mobile terminal, so as to ensure the user's safety.

The invention brings forward a traffic label identification method of vehicle-mounted laser scanning point cloud data. The method comprises the following steps: 1, point cloud real-time preprocessing; 2, point cloud structure feature obtaining; 3, multi-scale Markov random field point cloud clustering; and 4, traffic label identification. The method has the following advantages: "surface-shaped", "linear-shaped" and "scattered" features of point clouds are reinforced, differences between points are enhanced, and while under-segmentation is avoided, reasonable segmentation of the scale of a traffic label component can be rapidly realized; classification and identification of a traffic label can be conveniently realized from point cloud data of deficiency of a part of the traffic label, caused by ground object shielding or ground object self-occlusion; the method can effectively satisfy the requirements for rapid extracting, monitoring and identifying city components at present, can be conveniently promoted to the industry of manned or unmanned navigation and barrier avoiding based on computer vision, helps a driver to perform navigation and decision-making under complex road conditions, and effectively reduces the traffic accident probability.

The invention relates to an intelligent traffic system-based intelligent vehicle lane changing decision-making method. The method comprises the following steps of firstly, parsing the received broadcast data of an intelligent traffic system by an intelligent driving system, and extracting the event information; secondly, completing the coordinate conversion of a road event by the intelligent driving system, and obtaining an event influence factor according to the event information; finally, according to the event overall influence factor and the judgment result that the current road environment allows the lane changing decision of a vehicle, allowing the lane changing path re-planning, simultaneously calculating the desired behavior of the vehicle and changing the lane of the vehicle. According to the technical scheme of the invention, according to the attribute of a road event ahead of the vehicle and the environmental information around the vehicle, the influence factor of the current vehicle driving road is calculated. Therefore, the necessity, the security and the reliability of the lane changing decision of an automatic driving vehicle are evaluated. Meanwhile, preparations are made in advance before the lane changing of the vehicle.

The invention discloses a vehicle real scene navigation system and method. The system comprises a vehicle navigation terminal and a 'cloud' server, wherein the vehicle navigation terminal is used for acquiring the information of image/ position data; the vehicle navigation terminal also comprises a data acquisition module, a data fusion processing module connected with the data acquisition module, an augmented reality processing module connected with the data fusion processing module, and a real scene navigation module connected with the augmented reality processing module; the 'cloud' server is used for receiving the information of image and position data of the vehicle navigation terminal and returning the image information and the position information which are processed by a 'cloud' technology to the vehicle navigation terminal; the 'cloud' server is in two-way connection with a wireless communication module; the wireless communication module is respectively connected with the data acquisition module and the data fusion processing module.

The invention discloses a detecting system and a detecting method for fatigue driving of a driver, and belongs to the technical fields of image processing and pattern recognition. The system comprises a human face localization module, a human eye state judging module, a mouth state judging module and a fatigue determining module, wherein the human face localization module is connected with the human eye state judging module and the mouth state judging module for communication; the determining result is sent to the fatigue determining module. The detecting method comprises the following steps: 1, localizing and detecting the human face; 2, judging the human eye state; 3, judging the mouth state of the driver; 4, judging the mental state of the driver. The detecting system and the detecting method combine two obvious facial characteristics of the driver, namely the human eyes and the human mouth, for complex judging; compared with recognition detection using a single method, the method provided by the invention has a higher recognition accuracy; through determining the mental state of the driver, the driver under fatigue state is reminded to stop the vehicle for rest, so that traffic accidents are effectively reduced, and the safety of life and property is strongly guaranteed.

The invention discloses an unmanned pedestrian trajectory prediction method based on a convolutional neural network. The method comprises the steps of processing sample data, obtaining an input information sequence, constructing and optimizing the network, and testing and evaluating an optimal model. Real-time video collected by a visual sensor on an unmanned vehicle is segmented into images withframes as units to serve as sample data, target crowds about to pass through zebra stripes in the sample data are divided into three classes, and pedestrian position-proportion information sequence, the pedestrian skeleton information sequence and the motion sequence of the visual sensor,are obtained from samples;, ; the information sequence is input into a convolutional neural network for training to obtain a preliminary prediction model, and after testing and evaluation, finally a prediction track and an action category are output. According to the method, the convolutional neural network isadopted to predict the trajectory of the unmanned pedestrian, so that the probability of pedestrian collision in the road driving process of the unmanned vehicle can be effectively reduced.

The invention discloses an anti-collision method and system under different vehicle conditions, and belongs to the technical field of vehicle safety. The method includes the steps that the vehicle conditions are judged according to the vehicle speed and the corresponding safety distance, and the trajectory calculation quantity, the trajectory computing cycle, and the information sending cycle are determined according to the different vehicle conditions, vehicle trajectories are calculated according to the trajectory calculation quantity, the trajectory computing cycle and vehicle running states, the vehicle trajectories are periodically broadcast, anti-collision detection is conducted through the comparison between the vehicle trajectory of one vehicle and the vehicle trajectories of other vehicles, and if it is detected that a collision possible occurs, an early warning signal is output. The anti-collision method and system under the different vehicle conditions can achieve distinguishing of different risk levels of the vehicles through a vehicle condition determination strategy, targeted anti-collision warming for dangerous vehicles can be conducted, information transmission amount can be reduced through scattering the trajectory calculation to each vehicle, the decision making early warning speed test is improved, the occurrence of the vehicle collision is effectively prevented, and traffic accidents are reduced.

The present invention provides an intelligent full-automatic logistics conveying system and an application thereof. The system is applied to express and small piece logistics conveyance of each section between cities and within a city. The system is a sealed pipeline; a running track and an electricity transmission track are arranged in the pipeline; a trolley runs on the track; the pipeline consists of a main pipeline and branch pipelines; each branch pipeline is provided with a main freight station; a plurality of branch stations are arranged on the main pipeline; the main freight station and the branch stations are all connected to the main pipeline; and a station identification sensor and a vehicle intelligent identification system are arranged on the running track in the main pipeline and are used for identifying the position of the trolley and controlling the trolley to automatically drive into the main freight station on the branch pipelines or the branch stations on the main pipeline, corresponding to a trolley destination. The intelligent full-automatic logistics conveying system provided by the present invention has far lower cost than automotive transportation, so that the transportation cost is greatly reduced; and the system can run uninterruptedly in all weather for 24 hours securely and reliably to efficiently transport goods at a high speed.

The invention relates to a mountainous road traffic safety dynamic early-warning system which comprises a traffic accident analysis early-warning module, a traffic flow detection module, a road alignment module, a weather forecast module and a variable traffic sign LED display screen, wherein the traffic flow detection module, the road alignment module, the weather forecast module and the variable traffic sign LED display screen are connected with the traffic accident analysis early-warning module. The traffic flow detection module is used for dynamically collecting traffic flow data on the road, the weather forecast module is used for dynamically collecting weather conditions, the road alignment module conducts static collection and is used for collecting the geometrical features of the current road alignment, and the traffic accident analysis early-warning module conducts data real-time interaction with the traffic flow detection module, the weather module and the road alignment module. The mountainous road traffic safety dynamic early-warning system is mainly used for mountainous road traffic safety early-warning and is installed on a place where accidents frequently occur, and traffic accidents such as tailgating, handrail collision and the like when vehicles run on the mountainous road are avoided according to traffic controlling strategies of device output vehicle speed limit, traffic flow control and the like.