A traveling control apparatus performs a target-following control process on a target to be followed detected by a target detecting unit. Further, the traveling control apparatus calculates a probability that the target to be followed is within an own lane, and determines whether a degree of recognition by the target detecting unit of the target to be followed is in a weakly recognized state where the degree of recognition is weaker than a predetermined degree. The apparatus sets a reliability of the target to be followed on the basis of the probability calculated by a probability calculating process and a determination result by a determining process, and controls acceleration of an own vehicle so that a jerk which is a differential value of the acceleration becomes smaller as the reliability of the target to be followed is lower while the target-following control process is performed.

Technologies and techniques for the lateral control of a vehicle. Environment data of a vehicle is detected when travelling a route, and stored environment data, detected when travelling the route by a plurality of other vehicles not currently travelling the route, is received. The plausibility of the stored environment data is checked on the basis of the environment data detected. Lateral control of the vehicle is executed on the basis of the environment data checked for plausibility. The present disclosure also relates to an arrangement for the lateral control of a vehicle.

In order to generate an improved travel path with sufficient accuracy, a vehicle travel path generation device includes a first travel path generation part (60) which approximates a lane on which a host vehicle (1) travels to output first travel path information, a second travel path generation part (70) which approximates a road division line ahead of the host vehicle (1) to output second travel path information, a travel path weight setting part (90) which sets a weight between the first travel path information and the second travel path information, and an integrated path generation part (100) which generates an integrated path information using the first travel path information, the second travel path information, and the weight by the travel path weight setting part (90), wherein the travel path weight setting part (90) sets the weight, on the basis of at least one of outputs from a bird's-eye view detection travel path weight setting part (91), a vehicle state weight setting part (92), a path distance weight setting part (93) and a peripheral environment weight setting part (94).

In an overhead-structure recognition device to be mounted to a vehicle, a determination unit is configured to, in response to there being, among specific pieces of range point data each having a direction variable indicating a predefined direction, a predefined number or more of pieces of range point data each having a distance variable taking a plurality of values, determine that an object of interest corresponding to a subset of interest of pieces of range point data is an overhead structure. The predefined direction is a direction such that a horizontal angle difference from a direction indicated by the direction variable of the piece of range point data corresponding to the object of interest is within a predefined angle range and an angle with respect to a vertical direction is greater than an angle between the vertical direction and a direction of travel of the vehicle.

An embodiment sensor information fusion method includes estimating, by a host vehicle, reliability of shared sensor fusion information received from a neighboring vehicle, the shared sensor fusion information being generated by the neighboring vehicle, and generating, based on the estimated reliability, fusion track information of an object located near the host vehicle or the neighboring vehicle using host vehicle sensor fusion information generated by the host vehicle and the shared sensor fusion information.

A method for ascertaining which one of at least two traffic light systems located in the area in front of a motor vehicle is to be observed by this motor vehicle. The ascertainment is performed by evaluating the driving behavior of a vehicle traveling in front as a function of the current light status of the traffic light systems.

Disclosed is an apparatus and method for estimating a road profile for a vehicle. The apparatus includes a camera, processors, and a controller. The processors are configured to obtain a state of the vehicle including a behavior of the vehicle, and obtain a road height from information provided by the camera. The controller is configured to estimate the road profile by changing coordinates of the camera according to the behavior of the vehicle based on a vehicle height, compensating for the road height and a recognition road distance, and matching and filtering multiple road heights.

An apparatus for a motor vehicle driver assistance system is provided. The apparatus is configured to optimise object clusters, where each object cluster includes a sequence of position measurements for at least one object in the vicinity of the vehicle. Initially, in a pre-clustering phase, the assignment of the measured object positions to the object clusters may be based on the relative proximity of the measured object positions. The apparatus identifies a rogue object cluster on the basis of a first diagnostic, and a rogue object track from the measurements within the rogue object cluster. The position measurements from the rogue object track are removed from the clusters, and remaining position measurements in the rogue object cluster are reassigned to the other object clusters. The rogue object cluster is removed. Thus the object clusters are optimised.

Techniques relating to monitoring map consistency are described. In an example, a monitoring component associated with a vehicle can receive sensor data associated with an environment in which the vehicle is positioned. The monitoring component can generate, based at least in part on the sensor data, an estimated map of the environment, wherein the estimated map is encoded with policy information for driving within the environment. The monitoring component can then compare first information associated with a stored map of the environment with second information associated with the estimated map to determine whether the estimated map and the stored map are consistent. Component(s) associated with the vehicle can then control the object based at least in part on results of the comparing.

Another computer implemented method for estimating lanes for a vehicle may include the following steps carried out by computer hardware components: determining measurement data at a location of the vehicle using a sensor mounted at the vehicle; transforming the measurement data of the sensor into a global coordinate system to obtain transformed measurement data; and estimating lanes at the location for the vehicle based on the transformed measurement data.