A method for detecting an infringement by vehicle operator is described. The method comprises detecting a vehicle; receiving one or more image of at least a part of the vehicle operator; automatically analysing with a neural network the one or more captured received image to detect an infringing act; and providing the one or more captured received images comprising the detected infringing act to thereby detect the infringement. Also described are a system, a device, a computer system and a computer program product all for detecting an infringement by a vehicle operator. The device may comprise one or more flash for illuminating the vehicle or a part thereof with light at a narrow band and one or more camera comprising a narrow band filter that lets through only the wavelengths of light produced by the one or more flash.

The disclosure is generally directed to systems and methods for receiving from a mobile device that is optically tethered to a vehicle for remote driver assistance, an estimate of a speed of the vehicle, an orientation of the vehicle and a trajectory of the vehicle, comparing the estimate of the speed, orientation and trajectory received from the vehicle with a measured speed determined by one or more vehicle sensors, and preventing vehicle motion if a threshold difference from the comparison is exceeded. Another method is directed to determining at a mobile device an estimate of a speed of a vehicle, an orientation of the vehicle, a trajectory of the vehicle and a time stamp, transmitting the data to the vehicle, and untethering from optical tethering if the data are outside of a threshold or if the data indicate that the mobile device is tethered to an unintended vehicle.

The disclosure is generally directed to systems and methods for receiving from a mobile device that is optically tethered to a vehicle for remote driver assistance, an estimate of a speed of the vehicle, an orientation of the vehicle and a trajectory of the vehicle, comparing the estimate of the speed, orientation and trajectory received from the vehicle with a measured speed determined by one or more vehicle sensors, and preventing vehicle motion if a threshold difference from the comparison is exceeded. Another method is directed to determining at a mobile device an estimate of a speed of a vehicle, an orientation of the vehicle, a trajectory of the vehicle and a time stamp, transmitting the data to the vehicle, and untethering from optical tethering if the data are outside of a threshold or if the data indicate that the mobile device is tethered to an unintended vehicle.

A computer-implemented method for generating a speeding ticket. The method includes generating a first image of at least a part of a vehicle by a first camera, detecting a first set of the characters of the number plate of the vehicle dependent on the first image, and generating a secured file by a first camera using the first set of the characters and a first character code. The method further includes generating a second image of the part of the vehicle by a second camera and detecting a second set of the characters of the number plate dependent on the second image. The method further includes generating the speeding ticket, in response to determining that the vehicle violates a speed limit and in response to verifying that the first set of the characters is equal to the second set of the characters.

A computer-implemented method for generating a speeding ticket. The method includes generating a first image of at least a part of a vehicle by a first camera, detecting a first set of the characters of the number plate of the vehicle dependent on the first image, and generating a secured file by a first camera using the first set of the characters and a first character code. The method further includes generating a second image of the part of the vehicle by a second camera and detecting a second set of the characters of the number plate dependent on the second image. The method further includes generating the speeding ticket, in response to determining that the vehicle violates a speed limit and in response to verifying that the first set of the characters is equal to the second set of the characters.

A retrofittable modular school bus safety apparatus comprising a CPU, a plurality of sensors and scanners, an electrical plug device, and an output device. The electrical plug device is preferably adapted to plug into an auxiliary power port, a USB port or an OBD port to provide electrical power to the apparatus and to provide actuatable communication to school bus devices such as lights, horns, crossing arm, etc. The sensors include machine vision sensors, proximity detection sensors, and speed detection sensors. The apparatus is adapted to “read” a vehicle's license plate via ALPR, perform facial recognition, automatically monitor and warn/alert traffic proximate the school bus, to automatically respond with an appropriate level of response depending on an observed level of a moving violation, and to automatically wirelessly obtain the traffic laws/regulations applicable to location of the school bus and to operate accordingly.

A retrofittable modular school bus safety apparatus comprising a CPU, a plurality of sensors and scanners, an electrical plug device, and an output device. The electrical plug device is preferably adapted to plug into an auxiliary power port, a USB port or an OBD port to provide electrical power to the apparatus and to provide actuatable communication to school bus devices such as lights, horns, crossing arm, etc. The sensors include machine vision sensors, proximity detection sensors, and speed detection sensors. The apparatus is adapted to “read” a vehicle's license plate via ALPR, perform facial recognition, automatically monitor and warn/alert traffic proximate the school bus, to automatically respond with an appropriate level of response depending on an observed level of a moving violation, and to automatically wirelessly obtain the traffic laws/regulations applicable to location of the school bus and to operate accordingly.

Embodiments described herein may provide a method for using vehicle probe data to identify speed funnels that are related to road construction. Methods may include: receiving probe data including sensor data from a probe apparatus collected along a sequence of road segments; determining, from the sensor data, if an indication of a start of road work has been detected; constructing a Finite State Automata (FSA) for the probe data collected along the sequence of road segments; determining, in the probe data, sensor data indicative of a sequence of speed limit value observations; identifying, using the FSA, a speed funnel based on a pattern of speed limit values within the sequence of speed limit value observations; and providing an indication of the speed funnel occurring within the sequence of road segments for at least one of navigational assistance or at least semi-autonomous vehicle control.

A priority request handler may receive a priority request to associate a priority label with a sensed data file, the sensed data file being included within a time series of sensed data files received from a plurality of sensors. A queue manager may then store the sensed data file within a priority queue in association with the priority label, and independently of a temporal order of a time series of sensed data files. The queue manager may thus retrieve the sensed data file from the priority queue, based on the priority label, for processing thereof to obtain a sensed data record.

A priority request handler may receive a priority request to associate a priority label with a sensed data file, the sensed data file being included within a time series of sensed data files received from a plurality of sensors. A queue manager may then store the sensed data file within a priority queue in association with the priority label, and independently of a temporal order of a time series of sensed data files. The queue manager may thus retrieve the sensed data file from the priority queue, based on the priority label, for processing thereof to obtain a sensed data record.