An advice target location at which a user had a predetermined emotion, for example, is determined based on location information, user biological information, and user transportation means information, which have been acquired by a terminal device (20) being used by the user. Advice information containing information indicating an advice presentation region set by a server device (50) is generated based on the advice target location. This advice information is supplied from the server device (50) to the terminal device (20), so that the terminal device (20) presents advice. With this, advice as to locations pedestrians find dangerous can be presented to drivers, and advice as to locations drivers find dangerous can be presented to pedestrians. Accordingly, accidents and the like can be prevented.

A method for acquiring the surrounding environment of a motor vehicle. The motor vehicle has at least one ultrasound sensor. The ultrasound sensor includes an ultrasound transducer for sending, the ultrasound sensor receiving acoustic environmental signals, in particular audible environmental signals, in that the ultrasound sensor is controlled in its evaluation in such a way that sound waves having frequencies below a resonant frequency of the ultrasound transducer, in particular audible sound waves, of an environmental signal are acquired and evaluated. Environmental signals are understood as acoustic signals that are not produced by the ultrasound transducer itself, but rather by an external sound source that in particular differs from the motor vehicle. This can be for example the siren of a rescue vehicle or emergency vehicle, or the horn of some other motor vehicle.

A method, apparatus and computer program product are provided to determine lane status confidence indicators of lane status predictions such as closures and/or shifting. Lane statuses and corresponding confidence indicators are determined based on probe data, such as probe data collected from vehicle and/or mobile devices traveling along a road segment. Probe data may be partitioned into clusters and compared to partitioned subsets of the probe data. Cluster stability for the segment and corresponding lane status confidence indicators can be determined based on the comparison. Accordingly, determinations of whether to transmit predicted lane statuses to another system, service, and/or user device may be made.

Mobile wireless terminals, such as vehicles in traffic, can determine the relative positions of other vehicles with improved precision by arranging to acquire GNSS (global navigational satellite system) signals simultaneously, and then analyzing the various data sets differentially. Simultaneous acquisition can cancel many important errors such as motional errors of the vehicles, atmospheric distortions, and satellite timebase errors. Differential analysis to determine the relative positions of vehicles (as opposed to their overall geographical coordinates) can reduce errors related to satellite ephemeris and velocity, as well as roundoff errors. Localization with a precision of less than 1 meter can greatly improve collision avoidance while discriminating near-miss scenarios from imminent collisions, according to some embodiments. Messaging examples, in 5G and 6G, to manage the simultaneous acquisition and differential analysis, are provided in examples. Many other aspects are disclosed.

The driving assistance system includes an imaging device capable of capturing a first monochrome image in a vehicle traveling direction, a first neural network for segmentation processing, a second neural network for depth estimation processing, a determination portion determining a center of a portion cut off from the first monochrome image on the basis of the segmentation processing and the depth estimation processing, a third neural network for colorization processing of only a second cut-off monochrome image, and a display device for enlargement of the second monochrome image subjected to the colorization processing.

Systems, methods, and devices are disclosed for improving traffic safety and efficiency. The system includes various signal transmitters and receivers positioned throughout roadways, within automobiles, in smartphones, or supported by a cellular network backbone, for distributing traffic related information to users and traffic controller equipment. Embodiments of the present disclosure allow for vehicles and/or pedestrians to initiate a dual-transmission of cellular and RF signals for changing a traffic light state, where the first signal received at a traffic intersection controller unit is processed for changing the traffic light state (e.g., changing a light from red to green on-demand). Other embodiments of the present disclosure allow for users to receive visible and/or audible traffic related alerts on mobile devices, where the alerts are based on data shared between nearby drivers, pedestrians, and the traffic controlling equipment.

In an apparatus for determining a traveling position of an own vehicle that is an autonomous driving vehicle equipped with the apparatus, a judgment section is configured to judge presence or absence of at least one of a travel history of other vehicles regarding the lane in which the own vehicle is traveling and an object that is located in the vicinity of the own vehicle within the lane in which the own vehicle is traveling and should be avoided coming into contact with. The traveling position is a widthwise position of the own vehicle within a lane in which the own vehicle is traveling. A determination section is configured to determine the traveling position using the travel history in response to the judgment section judging that the travel history exists and using position information of the object in response to the judgment section judging that the object exists.

A vehicular display control apparatus includes: a condition determination portion that determines whether a deviation prediction condition has been established, the deviation prediction condition being a condition based on which a deviation between a sensible speed for a driver and an actual traveling speed is predicted; a speed difference determination portion that determines whether a speed difference between the actual traveling speed and a speed limit is a switching determination value or larger, and whether a shortage of the traveling speed from the speed limit is the switching determination value or larger; and a switching control portion that switches a speed display indicating the traveling speed to an emphasized display in a case when the condition determination portion determines that the deviation prediction condition has been established, and also when the speed difference determination portion determines that the speed difference is the switching determination value or larger.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

An information processing device (20) includes a route acquisition unit (202) and an automatic driving section determination unit (204). The route acquisition unit (202) acquires route information indicating a moving route of a mobile body. The automatic driving section determination unit (204) acquires adaptation coefficients for a plurality of sections included in the moving route indicated by the route information, with reference to an adaptation coefficient storage unit (206) that stores automatic driving adaptation coefficients set for the respective sections. Further, the automatic driving section determination unit (204) determines the automatic driving sections of the mobile body in the moving route, based on the acquired adaptation coefficients.