A driving assistance apparatus includes an outside recognition device, a locator unit, and a driving control unit. The outside recognition device is configured to acquire traffic environment information around the vehicle. The locator unit is configured to store road map information and detect a position of the vehicle based on a positioning signal. The driving control unit is configured to control the vehicle based on forward traffic environment information acquired by the outside recognition device. The driving control unit is configured to execute a wrong-way driving detection process and a restricted traffic zone determination process to determine whether the vehicle is performing wrong-way driving in an oncoming lane. The wrong-way driving detection process involves detecting wrong-way driving of the vehicle from the traffic environment information, and the restricted traffic zone determination process involves detecting a restricted traffic zone in a driving lane of the vehicle from the traffic environment information.

The present disclosure includes systems and methods for controlling the lane positions of a plurality of vehicles to reduce roadway wear. At least one controller is configured to receive information regarding a reference that may indicate a lane boundary. The controller determines a lane position offset from the reference, where the offset may be randomly selected or deterministically determined with an algorithm. The at least one controller is further configured to assign the lane position offset to one vehicle of a group of vehicles so that the assigned offset is different from the lane position offsets of the other vehicles. The assignment of different lane position offsets distributes wear across the lane of the roadway.

A method and system are provided in which maintenance vehicles collect information from sensors and operators, forward the collected information to a server, and, in response, receive maps and operator instructions.

The invention relates to a device for determining the driving behavior of a driver, the device comprising at least means for receiving data from two or more data sources, of which at least one produces data relating to changes in the state of motion of a vehicle and at least one other produces measured data on the well-being of the driver; means for scoring the received data by comparing it with data-specific reference values; means for forming a respective sub-index from each scored item of data; means for determining a driving behavior index on the basis of the formed sub-indices; and means for controlling control equipment of the vehicle on the basis of the driving behavior index and/or for storing the driving behavior index in a database.

A system and method for managing driving maneuvers including: providing a requesting driving maneuver management system (DMMS) module in a requesting vehicle, and a responding DMMS module associated with a responding road user; by the requesting DMMS module, sending a request indicating an intended driving maneuver using vehicle-to-everything (V2X) communications; and by the responding DMMS module, receiving the request and providing a request notification to the associated responding road user of the request.

An approach is provided for automatic road closure detection. The approach, for example, involves designating a dynamic time window comprising one or more time epochs ending before a current time epoch. The approach also involves retrieving a first set of probe data collected from a road link during the dynamic time window. The approach further involves adjusting a size of the dynamic time window by adding or removing another time epoch ending before the current time epoch until at least one criterion related to the probe data, the dynamic time window, or a combination thereof is met. The approach further involves extracting a plurality of features from the first set of probe data, from a second set of probe data collected from the road link during the current time epoch, or a combination thereof. The approach then involves detecting a closure status of the road link based on the plurality of features.

Systems, methods, and computer-readable media are described for performing real-time vehicular incident risk prediction using real-time vehicle-to-everything (V2X) data. A vehicular incident risk prediction machine learning model is trained using historical V2X data such as historical incident data and historical vehicle operator driving pattern behavior data as well as third-party data such as environmental condition data and infrastructure condition data. The trained machine learning model is then used to predict the risk of an incident for a vehicle on a roadway segment based on real-time V2X data relating to the roadway segment and/or vehicle operators on the roadway segment. A notification of a high risk of incident can then be sent to a V2X communication device of the vehicle to inform an operator of the vehicle.

A system, program product, and method for automatic collection, generation, and presentation of real time information to vehicular occupants are presented. The method includes determining a first driver profile for a first driver of a first vehicle. The method also includes determining, subject to the first driver profile determination, a color assignment for the first driver. The color assignment is at least partially indicative of the driver profile and the color assignment is at least a portion of a representation of the first driver. The method further includes communicating the color assignment to one or more of one or more potential occupants of the first vehicle and one or more occupants of the first vehicle.

An apparatus for indicating an expected speed of a vehicle includes an information provider configured to provide vehicle driving information and deceleration event information required to determine the expected speed of the vehicle at a deceleration event point while the vehicle travels, a controller configured to detect a deceleration event on a travel path based on the vehicle driving information and the deceleration event information provided by the information provider and to determine the expected speed of the vehicle at the detected deceleration event point, and a display unit configured to receive a signal indicating the expected speed of the vehicle at the deceleration event point and the deceleration event information from the controller and to display the received expected speed of the vehicle in a predetermined form of an augmented reality (AR) image and a position of the deceleration event on an information display screen.

A speedometer system is disclosed that replaces reliance on the feedback from a vehicle transmission and instead tracks the vehicle speed from an external source. In some embodiments, a global positioning unit (GPS) is connected to a microcontroller that drives an electric motor to turn and display a speed for an improved speedometer reading. The speedometer system further including a calibration unit that allows for the manipulation of the electric motor to display a predetermined calibration speed on the speedometer.