A vehicle assistance system for a vehicle is provided. A corresponding computer implemented method and computer program product are also provided.

A vehicle assistance system for a vehicle is provided. A corresponding computer implemented method and computer program product are also provided.

[Problem] To provide a motion condition estimation device, a motion condition estimation method and a motion condition estimation program capable of accurately estimating the motion condition of monitored subjects even in a crowded environment. [Solution] A motion condition estimation device according to the present invention is provided with a quantity estimating means 81 and a motion condition estimating means 82. The quantity estimating means 81 uses a plurality of chronologically consecutive images to estimate a quantity of monitored subjects for each local region in each image. The motion condition estimating means 82 estimates the motion condition of the monitored subjects from chronological changes in the quantities estimated in each local region.

The present invention relates to a detection area setting method for detecting passing vehicles, and a traffic signal control method using the same and, more particularly, to a detection area setting method for detecting passing vehicles, and a traffic signal control method using the same, the detection area setting method being capable of enabling smooth traffic operation at a crossroad, for example preventing a spillback phenomenon, minimizing green time (green light display time) during which there are no passing vehicles, and extending the green time, if needed, by setting one or a plurality of detection areas at a crossroad so as to detect the traffic volume in respective moving directions of vehicles at a signalized intersection, determining the traffic state in the moving directions of the vehicles according to vehicle information in respective detection areas, and automatically controlling the crossroad signals accordingly.

In one embodiment, a cognitive load driving assistant increases driving safety based on cognitive loads. In operation, the cognitive load driving assistant computes a current cognitive load of a driver based on sensor data. If the current cognitive load exceeds a threshold cognitive load, then the cognitive load driving assistant modifies the driving environment to reduce the cognitive load required to perform the primary driving task and/secondary task(s), such as texting via a cellular phone. The cognitive load driving assistant may modify the driving environment indirectly via sensory feedback to the driver or directly through reducing the complexity of the primary driving task and/or secondary tasks. In particular, if the driver is exhibiting elevated cognitive loads typically associated with distracted driving, then the cognitive load driving assistant modifies the driving environment to allow the driver to devote appropriate mental resources to the primary driving task, thereby increasing driving safety.

A method performed by a database managing system for maintaining a database comprising reported traffic-affecting events is provided. The system derives a position of a first vehicle supporting detection of vehicle surroundings and determines by comparing the vehicle position to positions of reported traffic-affecting events comprised in the database, that the first vehicle is approaching at least a first traffic-affecting event. The system prompts the first vehicle to attempt to detect the first traffic-affecting event, which prompting comprises providing to the first vehicle an expected position of the first traffic-affecting event. The system receives a response from the first vehicle, which response indicates whether or not the expected position was at least partly unobstructedly observable by the first vehicle. The response further indicates—if the expected position was at least partly unobstructedly observable—whether or not the first traffic-affecting event was at least partly detected by the first vehicle.

A lighting device comprising a housing arranged with at least one first housing space and at least one second housing space; at least one first illumination module respectively arranged in the at least one or more first housing space and at least one first auxiliary functional module, respectively arranged in the at least one second housing spaces; wherein each of the first auxiliary functional modules includes at least one of a communication module, a sensor module or a camera module. The lighting device arranged according to an embodiment of the present invention not only satisfies the lighting demand of existing urban planning, but also facilitates the upgrading of intelligent lighting devices with such functions as temperature detection, traffic monitoring and alarm, at a low cost.

The present invention relates to a portable traffic management system comprising a portable traffic signal assembly; a portable signal assembly; and a control unit in wireless communication with the portable traffic signal assembly and the portable signal assembly. The present invention alleviates one or more of the problems associated with the presently available traffic management systems.

The present invention relates to a portable traffic management system comprising a portable traffic signal assembly; a portable signal assembly; and a control unit in wireless communication with the portable traffic signal assembly and the portable signal assembly. The present invention alleviates one or more of the problems associated with the presently available traffic management systems.

A system includes one or more video capture devices and a processor coupled to each video capture device. Each processor is operable to direct its respective video capture device to obtain an image of a monitored area and process the image to identify objects of interest represented in the image. The processor is also operable to generate bounding perimeter virtual objects for the identified objects of interest, each bounding perimeter virtual object surrounding at least part of its respective object of interest. The processor is further operable to determine danger zones for the identified objects of interest based on the bounding perimeter virtual objects. The processor is further operable to determine at least one near-miss condition based at least in part on an actual or predicted overlap of danger zones for multiple objects of interest, and may optionally generate an alert at least partially in response to the near-miss condition.