55 results about "Car following" patented technology

The invention discloses a car following control method and a related product. According to the scheme, multi-source data are acquired, and the multi-source data are fused to obtain a fusion result; based on the fusion result, performing multi-modal trajectory prediction on the driving behavior of the preceding vehicle to obtain a prediction result of the driving behavior of the preceding vehicle; the multi-modal trajectory prediction comprises longitudinal motion prediction and transverse motion prediction; quantifying a car following risk by using a multi-dimensional risk index to obtain a risk level; constructing a multi-target cost function based on the fusion result, the front vehicle driving behavior prediction result and a control vector, and solving the multi-target cost function by using a preset constraint condition to obtain an initial control parameter of the vehicle; and on the basis of the risk level, initial control parameters of the vehicle are adjusted, and target control parameters of the vehicle are obtained. Compared with the problem of response lag in adaptive cruise control in the prior art, the adaptive cruise control method has obvious advantages.

The invention relates to the technical field of automobile control, in particular to a car following control method and system and a medium, and the car following control method comprises the steps that a target car which can be followed by a current car is recognized according to the real-time car state, the surrounding environment state and the traffic participant state; presenting the following state of each target vehicle based on the information of the target vehicle which can be followed by the current vehicle; configuring a following mode responding to the user instruction; and when the following mode of the user instruction is responded, the vehicle is planned and controlled to follow the target vehicle to realize the driving behavior, and the driving behavior at least comprises the following target trajectory tracking and the vehicle trajectory planning. The user can be assisted in controlling the vehicle to follow the dynamic target vehicle designated by the user to dynamically drive, and the experience of the user in the using process of the intelligent driving assistance function is improved.

The invention provides a vehicle sliding energy recovery method and device, equipment and a storage medium, and the method comprises the steps: obtaining vehicle following parameters of a target vehicle when it is detected that the target vehicle enters a sliding state; the car following parameters are input into a strategy network model used for determining the target regenerative braking torque of a target vehicle motor, so that the target regenerative braking torque output by the strategy network model is obtained; and controlling the target vehicle motor to output the target regenerative braking torque so as to recover the vehicle sliding energy. By adopting the technical scheme provided by the invention, collaborative optimization of the sliding energy recovery efficiency and the driving smoothness is realized.

The invention discloses an automatic driving vehicle path planning method based on a remote sensing image, and relates to the technical field of image recognition. The method comprises the following steps: an edge server pre-processes an original remote sensing image collected by an unmanned aerial vehicle and received in real time; analyzing the preprocessed remote sensing image, identifying roads and vehicles in the remote sensing image, and marking the vehicles as CAV vehicles and HDV vehicles; constructing a vehicle kinetic equation, analyzing the traffic flow, and selecting a car-following model or a lane changing model; after the lane changing model is selected, the automatic driving vehicle carries out rasterizing processing on the road ahead, and the optimal path of migration to a target grid is calculated. According to the method, through cooperative processing of the unmanned aerial vehicle remote sensing image and edge calculation, the global view of the autonomous vehicle is improved, the unmanned aerial vehicle can accurately obtain a long-distance road topological structure and dynamic obstacle distribution, and planning lag or decision errors caused by a local view blind area are avoided.

The invention provides a following driving method, system and equipment for a heavy commercial child-mother vehicle based on inter-vehicle communication, and belongs to the technical field of commercial child-mother vehicles, the mother vehicle starts a predictive self-adaptive cruise function, and the child vehicle starts a following mode. The mother vehicle obtains speed limit and curvature information through a map and carries out dynamic planning in combination with the state of the mother vehicle. The child car receives the operation information of the mother car in real time through the DSRC technology and corrects the air resistance coefficient of the child car according to the distance between the cars. The child car determines a safe car-following distance according to the car speed, the load difference and the ramp, and the torque demand of the child car is calculated through an inverse dynamics model based on the mother car state. The sensor is kept coincident with the longitudinal center line of the mother vehicle, and the steering angle is calculated when transverse deviation occurs. And the child vehicle also performs smooth processing on the deceleration of the mother vehicle, and sends torque, steering and deceleration requests to the execution unit. According to the invention, the driving safety is improved, the fatigue strength of a driver is reduced, and safe exit during communication interruption is ensured.

The invention discloses suspension bridge steel box girder bridge floor dismantling equipment and method based on fine planing and milling, the equipment comprises a vehicle body, the bottom of the vehicle body is connected with a crawler belt through a hydraulic cylinder, a hydraulic rod is arranged at the bottom of the vehicle body, and a slag conveying device is arranged on the advancing side of the vehicle body; the milling mechanism comprises a fixed frame, a lifting plate and a milling device; the monitoring mechanism comprises a sliding frame, a protection frame, a hardened steel wheel, a first rack and a second gear; the marking mechanism comprises a sliding sleeve, a fixed block, a second rack and a sixth gear; and the lifting motion of the sliding sleeve is controlled by the lifting of the hardened steel wheel through the meshing of the second rack and the sixth gear. The conical head is used for knocking the ground to form a hole, marking liquid flows into the hole, a car following person can conveniently find and stop milling operation in time, the damage condition of the tool bit is found in time, the situation that the damaged tool bit is continuously used for milling is avoided, the milling quality is greatly improved, and the service life of equipment is greatly prolonged.

The application discloses a kind of driver real-time state perception's car-following behavior intelligent modeling method and system, specifically including the following steps: (1) data acquisition, the driving data of vehicle in actual road is collected, the data needed to be acquired include the speed of current vehicle and front vehicle, position change information and the change information of relative distance;(2) data screening and processing, the data obtained in step (1) are screened, and the vehicle historical data with following characteristics on a road are selected;(3) the corresponding simulation environment is constructed in Matlab by method;(4) by the following state transformation method, the real driving situation of driver is simulated by constantly changing state in Matlab simulation environment.The method considers human factors in car-following model, so as to ensure the accuracy of car-following.

The invention provides a car following control method, a computer program product and electronic equipment, according to the car following control method provided by the invention, target related information of a current car following target of a car can be acquired; if the current car-following target of the car and the historical car-following target of the car belong to the same object and the preset comfortable braking condition of the car is met, smoothing processing can be carried out on the original longitudinal distance between the current car-following target and the car in the target related information; the target longitudinal distance between the current car following target and the car is obtained.

The invention discloses an automatic driving test method and system. Belongs to the technical field of automatic driving testing. According to the method, a high-fidelity virtual environment is constructed by collecting real scene data, and a virtual sensor is configured; mapping the real track to a virtual space, and generating a dynamic traffic flow in combination with a car following and lane changing model; after the real vehicle and the virtual intelligent agent are synchronously initialized, the real vehicle runs in the physical field and periodically updates the state; the virtual traffic flow is dynamically evolved according to the state of the main vehicle, and the virtual sensor senses the target in the field of view and generates a virtual sensing result; real sensor data is used as a reference, and virtual and real perception information is fused to form unified input; and circularly executing until the task is completed, wherein each virtual agent only participates in one test. According to the scheme, high-reality and high-efficiency closed-loop testing is achieved, the defects of a traditional method in the aspects of scene richness and testing safety are overcome, and the reliability and repeatability of verification of the automatic driving system are improved.

The invention provides a vehicle-following target determination method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining a lane changing behavior of a first vehicle under the condition that the first vehicle has a lane changing direction, determining a lane changing state of the first vehicle and a target lane into which the first vehicle needs to be driven, determining a position relation of a second vehicle in front of the first vehicle relative to the target lane; and determining a target tracking vehicle of the first vehicle from the second vehicles according to the lane changing behavior, the lane changing state and the position relationship. According to the invention, the accuracy and smoothness of vehicle following target switching can be improved during automatic driving of the vehicle.

The invention discloses a car following track generation method and device, and the method comprises the steps: obtaining a first predicted driving track of a current car and a second predicted driving track of a target front car in an automatic driving mode; performing near-end point taking processing on the first predicted driving track to obtain position information of a plurality of near-end control points; performing far-end point taking processing on the second predicted driving track to obtain position information of a plurality of far-end control points; and according to the position information of each near-end control point and the position information of each far-end control point, determining a Bezier curve equation for predicting the following track of the vehicle in the future target duration. Therefore, the high-order Bezier curve is combined with a control point dynamic adjustment mechanism, and the vehicle following robustness can be improved. Meanwhile, part of control points are generated through the high-order Bezier curve and the predicted driving track of the vehicle, the smoothness of the vehicle following track under the complex road condition is improved, and the carsickness of passengers is reduced.

The invention belongs to the technical field of heterogeneous traffic flow modeling and intelligent traffic management, and relates to a heterogeneous traffic flow macroscopic fundamental diagram experimental modeling method considering takeover behaviors, which comprises the following steps of: firstly, performing stage division on driving behaviors of L3-level man-machine co-driving vehicles, and selecting a car-following model; integrating TOV permeability and takeover rate, four typical car-following modes in heterogeneous traffic flow and a function degradation mechanism of cooperative adaptive cruise control to deduce theoretical scale models of vehicles of various models in the traffic flow. A joint simulation platform is built to restore a heterogeneous traffic flow scene, and a two-stage multi-cycle experiment process is designed to collect comprehensive traffic flow data under different density levels. Whether the experimental vehicle model proportion is matched with the theoretical vehicle model proportion or not is checked, and if yes, the improved Underwood model is used for fitting experimental data to obtain an experimental model of the macroscopic fundamental diagram. The method has the advantage that an accurate model basis is provided for heterogeneous traffic flow characteristic analysis and CAV cooperative control strategy formulation.

The application discloses a kind of net link environment under the bend traffic safety discrimination and regulation method, comprising:1, calculate the following car follow path;2, calculate the collision time of two cars;3, calculate the collision time change rate;4, traffic safety discrimination is carried out in combination with collision time and collision time change rate;5, consider front and rear car safety risk and regulate;6, the above steps are recycled until the control duration ends.The application can accurately carry out traffic safety discrimination when vehicle runs on curved road section, real-time explore potential traffic accident, so as to reduce the driving risk of vehicle when driving on curve, and can improve the operation efficiency and safety of vehicle on curve.

The invention provides a vehicle following control method, a computer program product and electronic equipment, according to the vehicle following control method provided by the invention, a target overlapping rate between a target object existing in front of a vehicle and a lane where the vehicle is located can be determined in combination with a vehicle surrounding environment image of the vehicle; and according to the bending degree of the road in front of the vehicle, a preset threshold positively correlated with the bending degree is determined, so that the vehicle following target of the vehicle is determined from the target objects with the target overlapping rate reaching the preset threshold.

The invention discloses a predictive self-adaptive cruise control method for a vehicle. The method comprises the following steps of: 1, positioning the position of the vehicle through a GPS (Global Positioning System) or positioning equipment assembled on the vehicle; 2, solving an economic optimal driving speed; step 3, entering a predictive self-adaptive cruise car following mode; fourthly, P-THW is calculated according to the predicted vehicle speeds vp1, vp2... vpn of the vehicle; fifthly, the vehicle is controlled to run with vp1 as the slope entering speed; if vp1lt; vtv, and v1gt; when vtv, enabling v1 to be equal to vtv, and re-planning vp1; 6, driving according to the planned vehicle speed; when vp1lt; vtv, and v1gt; when vtv, taking vtv as a new v1 for re-planning; and 7, calculating the safe turning speed vsafety of the vehicle, wherein the vsafety is the rollover prevention speed. The method has the advantages that vehicle speed is reduced, vehicle safety is guaranteed, and fuel economy is improved; the situation that the vehicle speed is too high in the downhill process after follow-up acceleration is avoided, and fuel consumption is reduced. Unnecessary acceleration behaviors are avoided, the situation that speed reduction is still needed during turning after acceleration is prevented, and energy waste is avoided.

The invention relates to the technical field of video monitoring processing, and particularly discloses a video monitoring method and system for barrier gate car following prevention, and the method comprises the following steps: extracting a foreground target in a video frame; extracting a target residual area based on the mirror surface highlight area of the foreground target; generating a complete contour model of the foreground target based on the target residual region; determining a position point of the complete contour model in each video frame, and connecting the position points to form a motion track of the foreground target; and sorting the foreground targets according to the sequence of the foreground targets appearing in the monitoring area, obtaining motion tracks A1 and A2 of two adjacent foreground targets in the sorting, and judging whether a car following behavior exists or not based on the motion tracks A1 and A2. According to the invention, the accuracy of car following judgment is improved.

The invention provides a vehicle, a vehicle following control method thereof and a storage medium in the field of vehicles. The vehicle following control method comprises the steps that the current cruise type and the current slip rate of the vehicle and the current rainfall level state of the position where the vehicle is located are determined; determining a target car following control strategy according to the current cruise type; determining a target expected acceleration according to the current slip rate and the current rainfall level state based on the target vehicle following control strategy; and performing vehicle following control on the vehicle according to the target expected acceleration. Therefore, the problems that the vehicle following distance control is inaccurate, the vehicle following distance is insufficient when the rainfall is large and the like due to the fact that the road condition cannot be accurately reflected in rainy days and the influence of different rainfall on driving cannot be distinguished in rainy days can be effectively solved, and the driving safety in rainy days is remarkably improved; therefore, the car following safety, the driving stability and the driving adaptability are synchronously improved under the complex weather condition.

The utility model relates to the technical field of vehicle brake devices, in particular to a safety linkage device for an auxiliary brake air brake signal switch of a learner-driven vehicle, which comprises a fixed base, a fulcrum rotating shaft, a transmission lever and a reset spring. The fulcrum rotating shaft is rotatably clamped in one set of adjusting clamping grooves, the rear portion of the transmission lever penetrates through the middle of the fulcrum rotating shaft in a swinging mode and is inserted into the fixed base, the front portion of the transmission lever is warped upwards and abuts against the lower surface of the auxiliary brake pedal in a sliding mode, and the electrical signal switch is installed in the fixed base. The rear end of the transmission lever is provided with a touch piece used for touching the electrical signal switch, and the reset spring is connected between the rear portion of the transmission lever and the front side wall of the box body of the fixed base. According to the device, through linkage arrangement, the brake lamp of the vehicle can be triggered to be lightened no matter the main brake or the auxiliary brake is stepped down, a brake prompt is sent to a following vehicle behind, and rear-end collision accidents of the vehicle are reduced.

A system for identifying autonomous vehicles includes at least one sensor that may be configured to provide sensor data associated with at least two vehicles. A pre-processing module may be coupled to the at least one sensor and may be configured to determine a set of data including at least car following data based on the sensor data. An autonomous vehicle (AV) / human-driven vehicle (HV) identification neural network may be coupled to the pre-processing module and configured to generate an AV / HV identifier for at least one of the at least two vehicles based on at least the car following data during a predetermined time period.

The invention provides a heterogeneous driving behavior feature extraction and online identification method in a man-machine cooperation scene, and the method comprises the steps: obtaining traffic data in multiple man-machine cooperation driving scenes, and carrying out the research based on a data set; carrying out preprocessing methods such as target detection, multi-target tracking and acceleration smoothing on the data set, and extracting characteristic parameters in a car following process; a clustering index is calculated from the characteristic parameters, clustering analysis is carried out on the car following behaviors based on a K-Means clustering algorithm, and the car following behaviors are divided into three types according to driving behavior differences; on the basis of a factor analysis method, common factors are extracted from the characteristic parameters, and heterogeneous driving behavior car-following characteristic parameter extraction is achieved; according to the extracted common factors, an online identification model is constructed through an artificial neural network (ANN), three types of heterogeneous driving behaviors are classified in real time, and the problem that ACC cannot accurately identify the car following characteristics of the heterogeneous driving behaviors under man-machine cooperative driving can be solved.

The application relates to a ship traffic flow basic map drawing method based on a microscopic car following theory, which comprises the following steps: S1, acquiring AIS data in a selected area, carrying out AIS data pretreatment, and establishing a rectangular coordinate system on the area; S2, segmenting a single channel according to a division standard, and preliminarily screening the pretreated AIS data; S3, drawing a ship trajectory map according to conversion information, and screening effective ship car following data pairs from the preliminarily screened AIS data; S4, drawing a speed-car following distance basic map; S5, drawing a speed-density basic map; S6, drawing a speed-traffic volume basic map; and S7, drawing a traffic volume-density basic map. The application screens effective ship car following data by processing AIS data in a selected area, draws a complete maritime traffic flow basic map according to the relationship among traffic flow characteristic parameters, and provides a reference basis for traffic characteristics and traffic conditions of the water area.

The utility model discloses a coaxial double-focal-plane HUD optical system. The coaxial double-focal-plane HUD optical system comprises an image source, an eye box, a prism, a first reflecting mirror, a second reflecting mirror and an automobile windshield, the prism, the first reflecting mirror and the second reflecting mirror are all arranged on a light path of the image source, the first reflecting mirror is used for carrying out first reflection on light rays emitted by the prism, and the second reflecting mirror is used for carrying out second reflection on the light rays reflected by the first reflecting mirror; the automobile windshield is used for reflecting the light reflected by the second reflector to the eye box. The image source is divided into two parts, the prism, the first reflecting mirror and the second reflecting mirror are arranged on the light path of the image source, a near-focus virtual image and a far-focus virtual image are formed at the position in front of the windshield, and a driver can be ensured to have a good visual effect under the condition that the visual field of the driver is poor such as car following or traffic jam through switching of the far-focus face and the near-focus face. And the virtual image surface can be seen, and the driving information of the vehicle can be obtained in time.

A method for planning lane-change actions considering string stability in a target lane is provided. The method includes learning a car following model based on training data related to a region, obtaining information about vehicles in a target lane in the region, simulating movements of the vehicles in the target lane responsive to an ego vehicle moving into the target lane based on the learned car following model and the information about the vehicles, determining whether the vehicles in the target lane will be string stable responsive to the ego vehicle moving into the target lane based on the simulated movements of the vehicles in the target lane, and instructing the ego vehicle to change lanes from a current lane to the target lane in response to determining that the vehicles in the target lane will be string stable responsive to the ego vehicle moving into the target lane.

The invention provides a mixed traffic flow vehicle following control method for a tunnel environment. The method comprises the following steps: acquiring environmental parameters in a tunnel, traffic flow state data and vehicle type information; generating environmental factors based on the environmental parameters; a three-layer coupling car-following model is constructed and comprises a basic physical layer, an intelligent driver model is adopted as a dynamic core, and car-following key parameters of the basic physical layer are dynamically adjusted through an environment adaptation layer; the environment adaptation layer is used for dynamically adjusting car-following key parameters according to the environment factors, and the car-following key parameters comprise the response time and comfortable deceleration of a human driving vehicle and the minimum safety distance and maximum acceleration of an automatic driving vehicle; the behavior decision-making layer is used for executing a differential interaction strategy according to the vehicle type of the preceding vehicle; based on the three-layer coupling car-following model, a reinforcement learning algorithm is adopted to generate a longitudinal acceleration control instruction of the automatic driving vehicle, and mixed traffic flow collaborative car-following is achieved.

The invention discloses a car following track optimization control method and system considering energy saving. The method comprises the following steps: determining a historical track and a future track of a front car according to a future state calculation strategy; taking a combined track of the historical track and the future track as a preliminary reference track of the vehicle; determining a state variable based on the preliminary reference trajectory, and constructing a trajectory prediction model of the vehicle according to the state variable; based on a trajectory deviation factor, a following stability factor, an energy loss factor and an obstacle collision factor, determining an optimization objective function of the vehicle; according to the optimized target function and the trajectory prediction model, controlling the self-vehicle to complete the vehicle following action of the front vehicle; the method can achieve the dynamic response of the future state of the front vehicle and the expected vehicle following distance through prediction control, achieves the balance among accurate and stable following, safe obstacle avoidance and energy saving, synchronously considers the vehicle rotation energy consumption and braking energy recovery, effectively reduces the energy consumption, and improves the tracking efficiency.

To provide systems and methods for an intelligent road infrastructure system (IRIS), which facilitate vehicle operations and control for connected automated vehicle highway (CAVH) systems.SOLUTION: IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for the vehicles to fulfill driving tasks such as car following, lane changing, and route guidance. The IRIS systems and methods also manage transportation operations and management services for both freeways and urban trunk lines. The IRIS includes one or more of physical subsystems: (1) a roadside unit (RSU) network; (2) a traffic control unit (TCU) and a traffic control center (TCC) network; (3) a vehicle onboard unit (OBU); (4) traffic operations centers (TOCs); and (5) cloud information and computing services.SELECTED DRAWING: Figure 2

The invention discloses an intelligent driving control method, device and equipment based on a nonlinear vehicle following model and a storage medium, and relates to the technical field of intelligent driving, and the method comprises the steps: predicting the speed probability distribution of a front vehicle in a future preset time period according to a historical speed sequence and a current acceleration of the front vehicle in speed information; inputting the own vehicle state, the front vehicle state, the road information, the traffic flow information and the speed probability distribution into an improved intelligent driving model to obtain a basic acceleration request; according to the method, the basic acceleration request is optimized, and vehicle control is realized based on the optimized basic acceleration request, so that the problems of lagging vehicle-following control and frequent acceleration and deceleration caused by the fact that an existing intelligent driving system only depends on current moment information are solved, and advanced planning of vehicle-following behaviors and smooth transition of control instructions are realized; the working conditions of sudden acceleration and sudden brake are effectively reduced, and the fuel economy is remarkably improved while the vehicle following safety is guaranteed.

The invention provides a lane changing-car following model construction method and system based on a risk field, and the method comprises the steps: constructing a risk field model for surrounding vehicles through employing an asymmetric dynamic risk attenuation factor based on the motion state information of the surrounding vehicles, and constructing a risk situation map according to a risk maximum value judgment method. Determining a lane changing end point interval of the vehicle according to the maximum acceleration information of the vehicle and the limit acceleration information of turning and rollover, then generating a lane changing track of the vehicle by adopting a quintic polynomial method, finding the lane changing track which is smaller than a risk threshold value and has the shortest distance as a final lane changing track based on the risk situation map, and if the lane changing track is not found, determining that the lane changing end point interval of the vehicle is not found. If so, the own vehicle and the front vehicle are driven to delay lane changing. And after the lane change of the vehicle succeeds, the motion of the vehicle degenerates into a car-following model according to the risk information, the risk faced by the vehicle during car-following is reflected by adopting a scalar and vector superposition mode, and the car-following model considering the risk information is constructed to control the vehicle to run.

The invention discloses a target screening method and device in a curve scene, electronic equipment and a storage medium, and relates to the field of automatic driving, and the method comprises the steps: obtaining the detection information of a left lane line and a right lane line of a lane where a vehicle is located, and generating a vehicle center trajectory; obtaining target visual detection position information and visual detection corner point information of a vehicle in front of the vehicle; according to the target visual detection position information of the vehicle in front of the vehicle and the central trajectory of the vehicle, calculating the nearest distance between the target visual position of the vehicle and the central trajectory of the vehicle, and judging whether the nearest distance is smaller than a dangerous collision distance threshold; according to the visual detection angular point information and the central trajectory of the vehicle, calculating the nearest distance between the target visual detection angular point of the vehicle and the central trajectory of the vehicle, and judging whether the nearest distance is smaller than a dangerous collision distance threshold value or not; setting a car following target; the step of setting the vehicle following target comprises setting the vehicle in front of the vehicle determined as the dangerous target as the vehicle following target and outputting the vehicle following target to vehicle control execution.