930 results about "Vehicle behavior" patented technology

A method is provided for vehicle to vehicle communication among vehicles having wireless communication links. Upon receiving notification of a sudden change in vehicle behavior, a vehicle broadcasts a priority message to surrounding vehicles within a transmission range. If an emergency event has occurred, a repeat cycle is defined for re-broadcasting the message, and a maximum number of initial repetitions for the message is specified. The message is transmitted repeatedly by a leader vehicle, with a pause between each transmission, until the maximum number of repetitions has been reached.

A method for facilitating cooperation between humans and remote vehicles comprises creating image data, detecting humans within the image data, extracting gesture information from the image data, mapping the gesture information to a remote vehicle behavior, and activating the remote vehicle behavior. Alternatively, voice commands can by used to activate the remote vehicle behavior.

Device, system and method, in a vehicle communication system, of transmitting a risk value in a message, wherein the risk value identifies quantitatively a risk of vehicle collision. Embodiments determine risk value by combining sub-risk values wherein sub-risks comprise: (i) vehicle behavior; (ii) weather and road conditions; (iii) current traffic; and (iv) location history. Embodiments include driver warnings responsive to the risk value in a received message. Embodiments include a collision type in a message. Embodiments include unique features of: risk is applicable to receiving vehicles; risk is applicable to a geographical region; computation and storage of location histories; messages free of IP and MAC addresses; haptic devices used for driver warning.

An autonomous driving merge management system includes an autonomous driving control device and an intention decision management system. The management system includes a candidate strategy subsystem generating a plurality of candidate driving strategies, a merging vehicle behavior recognition subsystem predicting a merging intention of a merging vehicle; an intention-based interactive prediction subsystem predicting future merging scenarios between the host vehicle and merging vehicle as a function of inputs by the merging vehicle behavior recognition subsystem and inputs by the candidate strategy subsystem, and a cost function-based evaluation subsystem determining a cost for each future merging scenario generated by the intention-based interactive prediction subsystem. A processor selects a merge strategy of the host vehicle based on intention-based prediction results and cost function-based evaluation results. The autonomous driving control device applies the merge strategy to the host vehicle for allowing the merging vehicle to cooperatively merge with the host vehicle.

A method and apparatus are provided for determining whether a driving environment has changed relative to previously stored information about the driving environment. The apparatus may include an autonomous driving computer system configured to detect one or more vehicles in the driving environment, and determine corresponding trajectories for those detected vehicles. The autonomous driving computer system may then compare the determined trajectories to an expected trajectory of a hypothetical vehicle in the driving environment. Based on the comparison, the autonomous driving computer system may determine whether the driving environment has changed and / or a probability that the driving environment has changed, relative to the previously stored information about the driving environment.

Systems and methods for obtaining data about road conditions as they pertain to an individual vehicle, using this information to build a model of vehicle behavior as a function of its environment, and aggregating information concerning multiple vehicles along with data from other sources in order to predict vehicle behavior in future environments.

A system for monitoring operator and motor vehicle behavior, including at least one mobile device; application software resident on the mobile device, wherein the application software is operative to gather and record information relevant to both the behavior of a motor vehicle and the behavior of an operator of the motor vehicle, and wherein the application software is activated or deactivated based on certain predetermined trigger events; and at least one information processor in communication with and / or resident on the mobile device, wherein the information processor is operative to process and characterize the information gathered by the application software and communicate the processed and characterized information to a user of the system.

A method for facilitating cooperation between humans and remote vehicles comprises creating image data, detecting humans within the image data, extracting gesture information from the image data, mapping the gesture information to a remote vehicle behavior, and activating the remote vehicle behavior. Alternatively, voice commands can by used to activate the remote vehicle behavior.

In a data collection apparatus mounted on a vehicle, an electric control unit sets an abnormality detection condition to detect abnormality of the vehicle based on a condition signal received from an external apparatus located outside the vehicle. The electric control unit determines whether the detection condition is satisfied and stores vehicle control data or vehicle behavior data upon satisfaction of the detection condition as freeze data. The abnormality of the vehicle is analyzed using the freeze data.

A system and method for providing vehicle collision avoidance at an intersection include receiving vehicle parameters from a reference vehicle and environmental parameters from roadside equipment. The system and method also include processing a vehicle behavioral map based on the vehicle parameters and the environmental parameters and transmitting the vehicle behavioral map to a target vehicle. The system and method additionally include processing a confidence table based on the vehicle behavioral map and vehicle parameters provided by the target vehicle. The system and method further include providing a collision avoidance response based on the confidence table, wherein the collision avoidance response is provided to the target vehicle to avoid a possible collision with the reference vehicle at the intersection.

Disclosed is a driver-assistance vehicle including one or more lighting members which are placed within peripheral vision of a driver and which are arranged on respective sides of the vehicle. Furthermore, the driver-assistance vehicle includes a vehicle behavior sensing unit for predicting or sensing a state of the vehicle, and a light controller for controlling the lighting members, based on the sensed state. With this driver-assistance vehicle, the driver can be assisted in distributing his attention.

An autonomous driving merge management system includes an autonomous driving control device and an intention decision management system. The management system includes a candidate strategy subsystem generating a plurality of candidate driving strategies, a merging vehicle behavior recognition subsystem predicting a merging intention of a merging vehicle; an intention-based interactive prediction subsystem predicting future merging scenarios between the host vehicle and merging vehicle as a function of inputs by the merging vehicle behavior recognition subsystem and inputs by the candidate strategy subsystem, and a cost function-based evaluation subsystem determining a cost for each future merging scenario generated by the intention-based interactive prediction subsystem. A processor selects a merge strategy of the host vehicle based on intention-based prediction results and cost function-based evaluation results. The autonomous driving control device applies the merge strategy to the host vehicle for allowing the merging vehicle to cooperatively merge with the host vehicle.

A vehicle behavior analysis system performs an analysis of vehicle operation by displaying behavior data in an organized and analyzed form. A vehicle behavior data collecting unit records information on the vehicle's driving as behavior data and an analysis unit analyzes a recorded content of the vehicle behavior data collecting unit. A recorded data unit obtaining part obtains the recorded data units recorded in a memory of the vehicle behavior data collecting unit and a displaying part displays the content concerning at least a predetermined item among the contents shown by obtained each recorded data unit in a form of a table sectioned for each recorded data units and arranged at a side of the analysis unit, and a risk degree calculated based on the content shown by each recorded data units is contained in the predetermined item displayed by the displaying part.

Vehicle motion control devices and methods systematically treat a conditions of each wheel to acquire and maintain the vehicle behavior stability together with anti wheel lock and wheel spin processing, braking forces distribution. Device for controlling a running behavior of a vehicle estimates a road reaction force on each wheel, calculates a yaw moment around a centroid of the vehicle body generated by the road reaction force on each wheel, and controls driving and braking forces on each wheel based upon the yaw moments so as to stabilize a running of the vehicle. Spin and Drift conditions are detected through presently generated yaw moments and critical yaw moments which can be generated by a road reaction force assumed to be maximized. Physical parameters of each wheels, required for detecting and controlling the behavior of the vehicle are estimated with a theoretical tire model.

The invention discloses a fatigue driving fusion detection method based on soft computing, which can detect the fatigue driving of the driver and is characterized in that: the fatigue driving is detected in fusion mode through two aspects which include two facial characteristics for directly indicating the fatigue state of the driver and two vehicle behavior characteristics for indirectly indicating the fatigue state of the driver, wherein the two facial characteristics respectively are frequent blinking and yawning, and the two vehicle behavior characteristics respectively are abnormal vehicle lane deviation and abnormal steering wheel rotation; the invention utilizes the TS fuzzy neural network to recognize fatigue driving, adopts abstraction clustering for the optimized recognition of the network structure, and determines the number of fuzzy rules of the fuzzy neural network and the initial values of the relevant network parameters; genetic algorithm is utilized to train and optimize the network parameters, and determine the optimum network parameters; the TS fuzzy neural network is utilized to detect the fatigue driving of the driver in real-time according to the optimum network parameters and the four fatigue characteristic parameters.

A system for monitoring operator and motor vehicle behavior, including at least one mobile device; application software resident on the mobile device, wherein the application software is operative to gather and record information relevant to both the behavior of a motor vehicle and the behavior of an operator of the motor vehicle, and wherein the application software is activated or deactivated based on certain predetermined trigger events; and at least one information processor in communication with and / or resident on the mobile device, wherein the information processor is operative to process and characterize the information gathered by the application software and communicate the processed and characterized information to a user of the system.

Vehicle behavior learning apparatuses, methods, and programs acquire image information of an area around a vehicle and perform image recognition of a particular feature included in the image information. The apparatuses, methods, and programs detect a behavior of the vehicle and acquire relation information indicating the relationship between the detected behavior of the and the recognized particular feature before the recognition of the behavior. The apparatuses, methods, and programs store detected behavior information including behavior property information indicating a property of the detected behavior of the vehicle and the acquired relation information associated with the behavior in a memory and produce learned behavior information indicating a result of learning of the behavior related to the particular feature on the basis of the stored detected behavior information.

Vehicle motion control devices and methods systematically treat a conditions of each wheel to acquire and maintain the vehicle behavior stability together with anti wheel lock and wheel spin processing, braking forces distribution. Device for controlling a running behavior of a vehicle comprises means for estimating a road reaction force on each wheel, means for calculating a yaw moment around a centroid of the vehicle body generated by the road reaction force on each wheel, and means for controlling driving and braking forces on each wheel based upon the yaw moments so as to stabilize a running of the vehicle. Spin and Drift conditions are detected through presently generated yaw moments and critical yaw moments which can be generated by a road reaction force assumed to be maximized. Physical parameters of each wheels, required for detecting and controlling the behavior of the vehicle are estimated with a theoretical tire model.

A vehicle driving operation support apparatus for a vehicle, includes a sensing section to sense a traveling condition of the vehicle including a surrounding condition inclusive of an obstacle around the vehicle; and a control section to calculate a risk potential for the vehicle in accordance with the traveling condition. The control section performs a support control to support the driver in accordance with the risk potential, performs a first assist control to restrain disturbance (such as vibration from a road) transmitted to the driver in accordance with the risk potential, and performs a second assist control to produce inducement simulating a condition change (such as a vehicle behavior) attributable to an increase of the risk potential, in accordance with the risk potential. The control section further performs a cooperation control to coordinate the first assist control and the second assist control.

A driving assistance system has a driving information acquisition unit that acquires any of an amount of operations by a driver, a vehicle behavior, a state of the driver, and information regarding the environment surrounding a vehicle as driving information, a vehicle location information acquisition unit that acquires vehicle location information, a statistical information generation unit that generates statistical information by statistically processing the driving information as a time-series pattern, an information associating unit that associates the statistical information with the vehicle location information at the time of the acquisition of the driving information, an information reference unit that references and reads the statistical information based on the location information acquired by the vehicle location information acquisition unit, a driving assistance unit that performs driving assistance based on the statistical information read by the information reference unit, and a communication unit.

A vehicle driving assist system has a controller configured to urge a driver to slow down (decelerate) in locations where visibility is poor. The controller detects a traveling condition of a host vehicle, e.g., when the host vehicle is approaching a designated area, such as a school zone, and then selectively executes an imaginary speed limiting road protrusion control that generates an imaginary speed limiting road protrusion by artificially reproducing a vehicle behavior that simulates the host vehicle crosses an actual speed limiting road protrusion arranged on a road surface, based on the traveling condition of the host vehicle.

A technique for simulating natural behaviors of moving objects is provided. A road traffic simulation apparatus includes a simulation unit for performing a traffic simulation, a display unit for displaying a progress status of the traffic simulation and a control unit for controlling the simulation unit. The simulation unit has a traffic environment database and a moving object model. The moving object model has a driver model in which a driving operation of a driver is modeled and a vehicle dynamics model in which a vehicle behavior is modeled. The driver model performs different processes in parallel in respective different cycles. The results of each cycle process are integrated and output to the vehicle dynamics model.

The present invention is for a modular, extensible software system for use with multi-modal, autonomous, or semi-autonomous vehicles. The design of the present invention involves the coherent integration of modules with responsibilities for human-interaction, training, path planning, mission execution, navigation, and safety to develop and complete missions. The present invention provides a modular software system that expresses vehicle behaviors through numerous small-grain elements to complete a mission. The system can be easily adapted or modified by adding new software modules or modifying existing modules as missions change or expand, with the smaller-grain modules being easier to adapt and reuse.

The present invention provides a mode change control method of a hybrid vehicle, which can improve driving performance and power performance and provide a more stable vehicle behavior control during a mode change from an EV mode to a HEV mode. For this purpose, a transmission input speed is compared with an engine idle speed. If the transmission input speed is lower than the engine idle speed, the pressure of a clutch is open-loop controlled so that an optimal engine torque of operation point determination circuit can be transferred to the clutch. On the other hand, if the transmission input speed is equal to or higher than the engine idle speed, the clutch pressure is feedback-controlled so that a delta RPM follows a target delta RPM profile.

A vehicle surroundings monitoring apparatus, a vehicle surroundings monitoring method, and a vehicle surroundings monitoring program which can rapidly determine an object such as a pedestrian to be avoided which must be avoided from coming into contact with the vehicle from an image of the surroundings of the vehicle and can provide information to a driver or control the vehicle behaviors. The vehicle surroundings monitoring apparatus includes an object extraction process unit (11) which extracts objects existing around a vehicle (10) from images taken by infrared cameras (2R, 2L), a pedestrian extraction process unit (12) which extracts a pedestrian from the extracted objects, a posture determination process unit (13) which determines the posture of the extracted pedestrian, an object-to-be-avoided determination process unit (14) which determines whether the extracted object is an object to be avoided which must be avoided from coming into contact with the vehicle (10) by executing a determination algorithm including at least a first determination process on the posture of the pedestrian determined by the posture determination process unit (13), and a vehicle equipment control process unit (15) which controls equipment of the vehicle (10) at least according to the determination result of the object-to-be-avoided determination process unit (14).

The invention discloses a vehicle multiparameter identification method based on a multitask convolution nerve network. The method comprises the following steps of designing and training of a convolution nerve network structure; and vehicle parameter identification based on the convolution nerve network. In the invention, through the convolution nerve network, original data is converted into an abstract high-level expression through a simple and nonlinear model. Therefore, in the convolution nerve network, a recessive character reflecting an essence of an object to be identified can be learned from a lot of training samples. Compared to a shallow learning classifier, by using the method, high expandability is possessed, identification of various kinds of objects in a traffic environment is satisfied and identification precision is high. When being applied to the complex traffic environment, the method has a high anti-environment interference capability. In the invention, the convolution nerve network is applied to multiparameter identification of a vehicle; the trained convolution nerve network is used to identify a type characteristic, pose information and a vehicle light state of the vehicle in an image so that predictable performance of a potential vehicle behavior is enhanced.

A vehicle behavior analysis system performs an analysis of vehicle operation by displaying behavior data in an organized and analyzed form. A vehicle behavior data collecting unit records information on the vehicle's driving as behavior data and an analysis unit analyzes a recorded content of the vehicle behavior data collecting unit. A recorded data unit obtaining part obtains the recorded data units recorded in a memory of the vehicle behavior data collecting unit and a displaying part displays the content concerning at least a predetermined item among the contents shown by obtained each recorded data unit in a form of a table sectioned for each recorded data units and arranged at a side of the analysis unit, and a risk degree calculated based on the content shown by each recorded data units is contained in the predetermined item displayed by the displaying part.