Provided is a vehicle braking support device. The braking support device includes: detection units for detecting a state around a host vehicle; a braking support control unit for executing braking support by a braking device according to the detected state; and a vehicle stop control unit for maintaining a stopped state of a host vehicle after the host vehicle is stopped by the braking support control unit, and for releasing the stopped state of the host vehicle after a predetermined period has elapsed. The vehicle stop control unit, in a case where by using the detected state it is determined that it is desirable to maintain the stopped state of the host vehicle beyond the predetermined period, the vehicle stop control unit does not release the stopped state of the host vehicle until an operation by a driver is detected.

A device for virtualizing a driving environment surrounding a first node, which includes: a data acquisition device, configured to acquire position data of the first node, position data and sensing data of at least one second node, where the at least one second node and the first node are in a first communication network; and a scene construction device, configured to construct a scene virtualizing the driving environment surrounding the first node based on the position data of the fist node and the at least one second node, and on the sensing data of the at least one second node. Accordingly, by utilizing position data and sensor data of a node, a scene for virtualizing a driving environment can be constructed in real time for a driver, which improves driving safety.

The systems and methods described herein disclose detecting obstacles in a vehicular environment using host vehicle input and associated trust levels. As described here, measured vehicles, either manual or autonomous, that detect an obstacle in the environment will operate to respond to the obstacle. As such, those movements can be used to determine if an obstacle exists in the environment, even if the obstacle cannot be detected directly. The systems and methods can include a host vehicle receiving prediction data about an evasive behavior from one or more measured vehicles in a vehicular environment. A trust level can then be established for the measured vehicles. An obscured obstacle can be determined using the evasive behavior and the trust level which can then be mapped in the vehicular environment. A guidance input can then be created for the host vehicle using the obscured obstacle and the trust level.

A non-transitory computer readable storage medium has instructions executed by a processor to obtain the relative speed between a first traffic object and a second traffic object. The separation distance between the first traffic object and the second traffic object is received. The relative speed and the separation distance are combined to form a quantitative measure of hazard encountered by the first traffic object. The obtain, receive and combine operations are repeated to form cumulative measures of hazard associated with the first traffic object. The cumulative measures of hazard are analyzed to derive a first traffic object safety score for the first traffic object.

The present disclosure relates to vehicle positioning methods, apparatus, controllers, intelligent vehicles, and systems. One example vehicle positioning method includes obtaining a first relative pose between a first vehicle and a help providing object, obtaining a global pose of the help providing object, and calculating a global pose of the first vehicle based on the first relative pose and the global pose.

An assessment system for performance evaluation and updating of a PMUD of an ego-vehicle. The assessment system obtains world view data from a perception module configured to generate the world view data based on sensor data obtained from vehicle-mounted sensors; obtains other world view data generated by another perception module; forms a joint world view by matching the world view data the other world view data; and obtains perception data based on a perception model and sensor data obtained from one or more vehicle-mounted sensors. The assessment system further matches the perception data to the formed joint world view; evaluates the obtained perception data in reference to the joint world view to determine an estimation deviation in an identified match between the perceptive parameter of the perception data and a corresponding perceptive parameter in the joint world view; and updates parameters of the perception model based on the estimation deviation.

The proposed invention relates to methods for controlling energy consumption by a motor vehicle, and can be used in transportation industry. The technical problem to be solved by the claimed invention is to provide a method and a non-transitory computer-readable medium that do not possess the drawbacks of the prior art and thus make it possible to generate an accurate energy-efficient track for a motor vehicle that allows to reduce energy consumption by the motor vehicle moving along a highway, including as part of a convoy.

A system for controlling a smart mobility by risk level includes: an information collection unit to collect position and speed information of the smart mobility and camera sensing information including a front traffic sign or object; a front detection unit to detect a front obstacle or inclination using the camera sensing information and to output a detection result; a control unit to change a warning to a user and/or a method of controlling the smart mobility by risk level based on the information collected by the information collection unit and the detection result; and a warning unit to warn the user by changing a method by risk level under the control of the control unit.

A method for eliminating sensor errors, in particular ambiguities when detecting dynamic objects, by a control device, is provide. Measurement data are received from at least one first sensor and object hypotheses are formed from the received measurement data. Data of at least one reference object, which is detected based on measurement data from at least one second sensor, are received. The formed object hypotheses are compared with the at least one detected reference object. Object hypotheses that do not match the detected reference object are rejected. A method for eliminating sensor errors, in particular ambiguities when detecting static objects is also provided.

A method for operating a motor vehicle in the event of an unavoidable collision with a collision object, in particular another vehicle. Environment data relating to the collision object are determined by an environment sensor device including at least one environment sensor and are evaluated to determine at least one driving intervention information for reducing the consequences of a collision. The motor vehicle is automatically guided in accordance with the driving intervention information, and the evaluation of the environment data is carried out together with structural information of the own motor vehicle describing the vehicle structure, in particular including elements absorbing collision energy of the motor vehicle, in such a way that a changed collision point maximizing the deformation energy absorbed by the vehicle structure and to be produced by the driving intervention information is determined when the driving intervention information is determined.