2348 results about "Traffic sign" patented technology

A method in a computerized system including an image sensor mounted in a moving vehicle. The image sensor captures image frames consecutively in real time. In one of the image flames, a spot is detected of measurable brightness; the spot is matched in subsequent image frames. The image frames are available for sharing between the computerized system and another vehicle control system. The spot and the corresponding spot are images of the same object. The object is typically one or more of headlights from an oncoming vehicle, taillights of a leading vehicle, streetlights, street signs and / or traffic signs. Data is acquired from the spot and from the corresponding spot. By processing the data, the object (or spot) is classified. producing an object classification. The vehicle control system controls preferably headlights of the moving vehicle based on the object classification. The other vehicle control system using the image frames is one or more of: lane departure warning system, collision warning system and / or ego-motion estimation system.

A vehicle warning system for use in conjunction with road signs proximate a roadway and that are visible by passing motorists. The system has two assemblies, one on each side of a roadway and associated with a road sign. Each assembly has a power source, one or more lights that when lit project light that is visible to a passing motorist, a controller, a light activation device, and a wireless transceiver. Operation of the light activation device of a first of the assemblies causes the wireless transceiver of the first assembly to send a signal to the wireless transceiver of the second assembly, and both controllers to temporarily connect one or more lights of each assembly to the power source for the assembly, to light the one or more lights and thus project light that is visible to the motorist from both sides of the roadway.

A method for collecting data for a geographic database is disclosed. Speed and position data are collected using a plurality of mobile computing platforms moving in a geographic region. The speed and position data are analyzed to identify a location of a traffic sign corresponding to a change in the speed. The geographic database is updated to indicate the location of the traffic sign.

An area mixed traffic self-adapting signal coordinated control method relates to the technical field of the automatic control, wherein the vehicle information for entering the control junction is detected through a detector, and the vehicle information is transmitted to the traffic signal controller; the traffic signal controller performs the preheating on the traffic flow data, while the area coordinated control computer analyzes the traffic flow operation state of each inlet section of the junction, to perform the realtime analysis forecast, provides the optimized traffic signal project timing parameters to the traffic signal controller. The method of the invention divided the city road net into a plurality of subareas, adopts the layer net working to coordinated control the duration time of the traffic light at each junction, advances the traffic capacity, prevents the traffic congestion, reduces the off gas, ensures the traffic safety.

A method in a computerized system including an image sensor mounted in a moving vehicle. The image sensor captures image frames consecutively in real time. In one of the image flames, a spot is detected of measurable brightness; the spot is matched in subsequent image frames. The image frames are available for sharing between the computerized system and another vehicle control system. The spot and the corresponding spot are images of the same object. The object is typically one or more of headlights from an oncoming vehicle, taillights of a leading vehicle, streetlights, street signs and / or traffic signs. Data is acquired from the spot and from the corresponding spot. By processing the data, the object (or spot) is classified. producing an object classification. The vehicle control system controls preferably headlights of the moving vehicle based on the object classification. The other vehicle control system using the image frames is one or more of: lane departure warning system, collision warning system and / or ego-motion estimation system.

The invention discloses an automatic driving system based on enhanced learning and multi-sensor fusion. The system comprises a perception system, a control system and an execution system. The perception system high-efficiently processes a laser radar, a camera and a GPS navigator through a deep learning network so as to realize real time identification and understanding of vehicles, pedestrians, lane lines, traffic signs and signal lamps surrounding a running vehicle. Through an enhanced learning technology, the laser radar and a panorama image are matched and fused so as to form a real-time three-dimensional streetscape map and determination of a driving area. The GPS navigator is combined to realize real-time navigation. The control system adopts an enhanced learning network to process information collected by the perception system, and the people, vehicles and objects of the surrounding vehicles are predicted. According to vehicle body state data, the records of driver actions are paired, a current optimal action selection is made, and the execution system is used to complete execution motion. In the invention, laser radar data and a video are fused, and driving area identification and destination path optimal programming are performed.

The invention relates to the technical field of automatic driving, in particular to an automatic driving system based on a highway. The automatic driving system comprises a sensor, a positioning module, a man-machine interaction module, an automatic driving controller and a vehicle executing module. A traditional laser radar is replaced with a monocular camera, a stereo camera, a forward-direction long distance millimeter microwave radar and four-corner middle distance millimeter microwave radars which are arranged behind an inside-vehicle rearview mirror, at the center of a vehicle front bumper and on the two sides of the front bumper and a rear front bumper correspondingly. Multiple kinds of information in traffic sign road information and obstruction information are collected separately. The whole automatic driving system of perception fusion, path planning, decision planning, controlling and the like is integrated into an embedded type controller to achieve automatic driving. Compared with a traditional automatic driving system adopting the laser radar, the cost is low, and integration is easy. Perception precision is improved greatly, the system is high in integration level and small in size, the size of the automatic driving system is reduced greatly, the power consumption of the system is lowered, and mass production is easy.

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

The present invention relates to a pilotless automobile system and an automobile. The pilotless automobile system comprises an environmental sensing subsystem, a data fusion subsystem, a route planning and deciding subsystem and a travel control subsystem. Surrounding environment information including image information and three-dimensional coordinate information is fused through the data fusion subsystem, obstacle information, lane line information, traffic sign information and dynamic obstacle tracing information are extracted, and the recognition capability and recognition precision of the surrounding environment information are improved. The route planning and deciding subsystem is used for planning a travel route according to the information extracted by the data fusion subsystem and travel destination information, the travel control subsystem is used for generating a control instruction according to the travel route and controlling the pilotless automobile according to the control instruction, and a high-safety-performance pilotless function is fulfilled.

The invention discloses a method for recognizing a road traffic sign for an unmanned vehicle, comprising the following steps of: (1) changing the RGB (Red, Green and Blue) pixel value of an image to strengthen a traffic sign feature color region, and cutting the image by using a threshold; (2) carrying out edge detection and connection on a gray level image to reconstruct an interested region; (3) extracting a labeled graph of the interested region as a shape feature of the interested region, classifying the shape of the region by using a nearest neighbor classification method, and removing a non-traffic sign region; and (4) graying and normalizing the image of the interested region of the traffic sign, carrying out dual-tree complex wavelet transform on the image to form a feature vector of the image, reducing the dimension of the feature vector by using a two-dimension independent component analysis method, and sending the feature vector into a support vector machine of a radial basis function to judge the type of the traffic sign of the interested region. By using the method, various types of traffic signs in a running environment of the unmanned vehicle can be stably and efficiently detected and recognized.

This invention relates to one single cross mixture traffic signal control method by use of computer program, which comprises the following steps: summing up the automobile car number relative to standard car number by use of the computer program of the formula method and for the number of bicycle number; summing up each channel traffic flow standard car number per hour by use of data process program; signal machine judges and selects whether for single point time control type or signal sense control type or single optimization type for each type signal optimization scheme.

The invention relates to the technical field of traffic control and artificial intelligence and provides a traffic signal self-adaptive control method based on deep reinforcement learning. The method includes the following steps that 1, a traffic signal control agent, a state space S, a motion space A and a return function r are defined; 2, a deep neutral network is pre-trained; 3, the neutral network is trained through a deep reinforcement learning method; 4, traffic signal control is carried out according to the trained deep neutral network. By preprocessing traffic data acquired by magnetic induction, video, an RFID, vehicle internet and the like, low-layer expression of the traffic state containing vehicle position information is obtained; then the traffic state is perceived through a multilayer perceptron of deep learning, and high-layer abstract features of the current traffic state are obtained; on the basis, a proper timing plan is selected according to the high-layer abstract features of the current traffic state through the decision making capacity of reinforcement learning, self-adaptive control of traffic signals is achieved, the vehicle travel time is shortened accordingly, and safe, smooth, orderly and efficient operation of traffic is guaranteed.

There is provided a blue-green illumination system, including a semiconductor light emitter, and a luminescent material, wherein the system has an emission with CIE color coordinates located within an area of a of a pentagon on a CIE chromaticity diagram, whose corners have the following CIE color coordinates: i) x=0.0137 and y=0.4831; ii) x=0.2240 and y=0.3890; iii) x=0.2800 and y=0.4500; iv) x=0.2879 and y=0.5196; and v) x=0.0108 and y=0.7220. The luminescent material includes two or more phosphors. The illumination system may be used as the green light of a traffic light or an automotive display.

A traffic signal system for congested trafficways has a plurality of stationary alarm light / sensor-reader combinations and mobile alarm light / sensor-reader combinations monitoring each other and monitory tags placed on individuals, machines, and hazards to provide real time alarms to not only pedestrians but also machine operators, who are potentially approaching harm's way, or have the better ability to avert potential harm. Different forms of alarms are provided to indicate different kinds of alarm conditions and to reduce complacency to alarms, and thus improve effectiveness.

A driving assistance apparatus that assists driving of a vehicle, includes: a vehicle speed sensor; a communication unit that obtains traffic light information relating to a change in a display condition of a traffic light disposed in an advancement direction of the vehicle; a position calculation unit that calculates relative position information between the vehicle and a traffic light location where the traffic light is disposed; and a passage assistance control unit. The passage assistance control unit detects an operating condition of the vehicle at an intersection location before the traffic light, calculates a corrected vehicle speed on the basis of the operating condition and a current vehicle speed, and determines whether or not the vehicle is permitted to pass through the traffic light location on the basis of the corrected vehicle speed, the relative position information between the vehicle and the traffic light location, and the traffic light information.

The invention discloses a construction method and device applied to the test scene of a pilotless automobile. One specific implementation way of the method comprises the following steps: obtaining a road condition image which contains scene objects, wherein the scene objects comprise a road object, a traffic sign object, a vehicle object and a pedestrian object; on the basis of the road situation image, obtaining the attribute information of the scene object; and on the basis of the attribute information of the scene object, constructing the test scene of the pilotless automobile. The attributes of the real road object, traffic sign object, vehicle object and pedestrian object are used for constructing the test scene of the pilotless automobile so as to reduce the real road situation, and the real road situation is used as the test scene of the pilotless automobile so as to improve the test accuracy of the pilotless automobile.

A breakaway post base includes a pair of adjacent slip plates to allow separation of the upper portion of a traffic sign or the like from its permanently mounted base. The two plates are triangular with notches at their apices, with the plates and related structure secured together by bolts through the apex notches. An impact on the upper post dislodges the bolts, allowing the upper post to move freely and preventing significant damage to the sign structure. At least one of the slip base plates includes a sleeve extending therefrom, into which one end of the post is installed. The post is prevented from rotating relative to the slip base by a series of set screws installed through the slip base sleeve and locking the post immovably therein. Thus, a sign supported by the present assembly cannot rotate relative to the slip base plate.

The invention relates to the technical field of traffic control, in particular to a wireless traffic signal system and a method thereof cooperated with vehicle tracks at intersections. The invention adopts a special short-range communication mechanism. The system comprises intersection transmitting equipment, vehicle receiving equipment, a singlechip, voice output equipment, GPS (Global Position System) equipment and a vehicle display. The singlechip carries out data fusion processing on real-time traffic information and the longitude and the latitude of vehicles to obtain information of traffic signal lamps on the vehicle tracks and outputs the information to the vehicle display. The method comprises the step that the singlechip carries out data fusion on information of an electronic map, a real-time traffic lamp signal, vehicle track positioning and traveling direction and displays the traffic signal on the electronic map when the vehicles enter the communication range of a special short-range communication technology. The invention can ensure that the traffic signal is transmitted to the vehicles through the system under the condition that a driver cannot clearly see the front signal lamps and thereby the driver can clearly know about the current contents displayed by the traffic signal lamps by using a display or voice prompt system.

A traffic signal with integrated sensors. The present invention provides an apparatus for integrating sensors with a traffic signal. A signal case has a housing and a light source placed within the housing. A door attached to the housing is configured such that photons generated by the light may be sensed outside the housing. A tab is attached to the door. A sensor is attached to the tab. The housing or the door is adapted to allow the sensor to sense a parameter originating from outside the housing.

The invention discloses a vehicle-road collaborative vehicle-mounted terminal application system based on LTE-V. In the system, the vehicle maintains wireless short-wave communication with other vehicles and roadside equipment in real time by utilizing the characteristics of low delay and high coverage range of LTE-V communication, and interacts information with a vehicle-road collaborative background server through a 4G network. The method comprises the following steps: receiving real-time state information of other vehicles; The method comprises the following steps of: sensing surrounding traffic conditions by traffic participant real-time information sent by roadside equipment, and judging and analyzing a map road relationship, a road distance and collision time between a vehicle and other traffic participants, traffic signs or events according to the vehicle state information and local lane track point map information; According to different traffic scenes judged by the system, a driver is reminded of different traffic events and early warning information through visualization, so that the driving safety is enhanced, and meanwhile, the traffic efficiency is improved.

Vehicles, including autonomous vehicles, which receive external data from sources other than the sensors on the vehicles, analyze such external data and alter the driving behaviors of the vehicles based on the external data are disclosed. External data may be gathered from other vehicles, news feeds, social networking posts or may comprise data about previously observed behaviors of other vehicles or drivers. Such external data may include locations of and / or information regarding other vehicles, traffic signs and or signal lights, on or off ramps, road hazards, road conditions, traffic conditions, vehicular or pedestrian congestion, etc. In other aspects, systems for adjusting vehicle settings based on driver preferred settings are disclosed.

The invention provides a method for detecting and tracking vehicles through processing a video image of a traffic scene, comprising the following steps of: collecting images of the traffic scene; deblocking a traffic image according to 8 multiplied by 8 pixels; initiating and continuously updating a background image; setting a virtual detection line with a width of 8 pixels vertical to a direction of a traffic lane at the entrance of the traffic lane; detecting the vehicles through calculating the variation of a gray scale of blocks on the virtual detection line relative to the background image; labeling the blocks belonging to the regions of the vehicles by using a sequence that the vehicles reach the detection line; receiving initial positions of labels of the vehicles; calculating motion vectors of the vehicles by combining a three-step method and a full search method and constantly updating the positions of the labels of the vehicles by using the motion vectors so as to implement the tracking of vehicles. The method also performs detection and splitting against an occlusion occurrence between vehicles in a complicated traffic scene, thereby having the advantages of high accuracy of detection and tracking and good real-time performance.

The invention provides a positioning method and system based on a safe driving map and binocular recognition of traffic signs. Primary positioning of a running vehicle is carried out via the positioning system by means of a high-precision map. Meanwhile, images of the part in front of the vehicle are acquired, and traffic signs in the images are detected and identified. Coordinates of the traffic signs are recognized and obtained in the high-precision map, the distance between the vehicle and the signs are measured, and the position of the vehicle is calculated by comparing the coordinates of the traffic signs. In this way, the vehicle is positioned. By means of the invention, on the basis of traditional navigation data, acquisition of road traffic signs is added, roads signs are adopted to help positioning vehicles, the distance between vehicles and traffic signs is measured according to coordinates and sizes of signs which are recognized by left and right cameras, and vehicle positions are calculated according to spatial coordinates of traffic signs which are already stored in the high-precision map, so that submeter-level coordinate positioning is provided and a lane-based topology network is established.

The invention, which belongs to the technical field of intelligent traffic, discloses an intelligent vehicle control method and apparatus. The method comprises: after a terminal receives current driving road situation information sent by an intelligent vehicle, an obstacle is displayed on a first display interface; a lane line and a traffic sign on the current driving road are displayed on the first display interface according to lane line information and traffic sign information contained in the road situation information; a driving route of the intelligent vehicle is planned based on the lane line information and state description information contained in the road situation information; and the driving route is sent to the intelligent vehicle, so that the intelligent vehicle can be driven based on the driving route. According to the invention, the intelligent vehicle can be controlled by the terminal independent of the intelligent vehicle and the driving route is planned and displayed, so that the intelligent vehicle can be driven based on the driving route. The control range is large and the control way is intelligent.

An in-vehicle system for tracking events that occur at specific locations of a transportation route and alerting a driver of an impending significant event includes a location determination unit for determining an instantaneous location of the vehicle, and an event determination unit coupled to the location determination unit and responsive to the instantaneous location of the vehicle for communicating with an events database for obtaining an impending traffic sign that the vehicle is about to confront based on the vehicle's instantaneous location. A decision module coupled to the event determination unit is responsive to current parameters of the vehicle for determining whether the current parameters of the vehicle are conducive to safe driving based on the impending event, and a warning unit coupled to the decision module is responsive to at least one current parameter of the vehicle not being conducive to safe driving for alerting the driver of the impending event.

The invention provides a deep learning-based traffic sign automatic identifying and marking method, which is used in the technical field of environmental perception of intelligent vehicles. A semantic segmentation structure is adopted for locating and detecting traffic signs, and candidate regions with the traffic signs are obtained, wherein the semantic segmentation structure comprises two parts: an encoding network; and a decoding network and a pixel-based classification layer. Then, the traffic signs in the candidate regions are subjected to classified identification and locating through a convolutional neural network of a quick region. Based on the traffic sign automatic identifying and marking method, the invention furthermore correspondingly provides an effective map navigation information updating method. According to the method, the candidate regions with the traffic signs are located by using the semantic segmentation method, so that a new idea is provided, a training parameter quantity is reduced, the storage space is saved, and the computing time is shortened; and the method is high in identifying accuracy, and can perform relatively accurate traffic sign information updating on map navigation information, thereby better serving drivers conveniently.

The invention relates to a traffic signal light intelligent control system and a control method thereof, which belong to the technical field of intelligent traffic; the system comprises four CCD camera heads, a signal processor and a controller; and the method comprises the following steps: establishing a coordinate system and the transformation relation thereof; sequentially carrying out distortion correction, sharpening and perspective transformation on a traffic flow image; extracting edges of a vehicle image and filtering out lane lines and traffic sign arrows in the image; cutting the image; carrying out edge projection for obtaining pixel coordinates which correspond to the queue length of vehicles waiting to pass on each type of lane in each direction under the computer image coordinate system; calculating the actual queue length of the vehicles waiting to pass; obtaining time required for leading all the vehicles on each type of the lane in each direction to pass; and controlling the opening and the closing of a traffic signal light according to the time of leading all the vehicles to pass. The traffic signal light intelligent control system can control the opening time and the closing time of the traffic signal light in a high-efficient and energy-saving manner, thereby providing a scientific information base for realizing the urban intelligent traffic.

Systems and methods are disclosed for classifying traffic flows. A traffic agent operable to collect classification information for one or more traffic flows may be deployed at an end host communicatively coupled to a data-center network. The traffic agent, deployed in a user space independent of the operating system, may compare the classification information for a given traffic flow to a metric value. Where the classification information achieves a certain threshold indicated by the metric value, the traffic agent may classify the traffic flow as an elephant flow. In some examples, a library may be included with the traffic agent that may include a modified send function. The modified send function may provide classification information to the traffic agent indexed to the traffic flow for which it is called so that the traffic agent may analyze the classification information to potentially provide a classification for the traffic flow.