A method, system and medium for assisted driving of a vehicle are disclosed. The method comprises predicting a target intersection based on map information, a positioning location of the vehicle, and a motion status of the vehicle, where the target intersection is an intersection that the vehicle is to first pass in the future; determining a distance between the vehicle and the target intersection based on the map information and the positioning location of the vehicle; collect a turn light status of the vehicle; and when the distance between the vehicle and the target intersection is less than a first threshold, generating prompt information based on the turn light status of the vehicle and a first turning rule of a first lane in which the vehicle is located at the target intersection, where the prompt information prompts that the turn light status does not conform to the first turning rule.

Systems and methods are provided for intelligent driving monitoring systems, advanced driver assistance systems and autonomous driving systems, and providing alerts to the driver of a vehicle, based on anomalies detected between driver behavior and environment captured by the outward facing camera. Various aspects of the driver, which may include his direction of sight, point of focus, posture, gaze, is determined by image processing of the upper visible body of the driver, by a driver facing camera in the vehicle. Other aspects of environment around the vehicle captured by the multitude of cameras in the vehicle are used to correlate driver behavior and actions with what is happening outside to detect and warn on anomalies, prevent accidents, provide feedback to the driver, and in general provide a safer driver experience.

A driver assistance device acquires information about vehicle-driving environment ahead of the vehicle to detect an intersection. Upon determining that the vehicle makes a right- or left-hand turn at the intersection, the driver assistance device sets a projected course of the vehicle and recognizes a moving object ahead in a direction in which the vehicle making a right- or left-hand turn is headed. The driver assistance device calculates a movement vector from positional changes of the moving object to calculate a meeting point of a path of the object and the projected course. When an interval between times at which the vehicle and the moving object reach the meeting point is found to fall within a predetermined range, the driver assistance device determines that there is a possibility of interference between the vehicle and the moving object and then causes the vehicle to halt short of the meeting point.

When a marker on a road is detected, an automated driving apparatus mounted on a vehicle determines whether to perform automated driving based on comparison between a relative movement log from the marker as a start point according to autonomous navigation and shape point data concerning a lane acquired from the most recent map data.

An information providing device includes an external environment recognition unit that recognizes an external environmental situation of a movable body, an information providing control unit that provides a notification of recommended stopping information based on a current indication of traffic signals recognized by the external environment recognition unit, and a determination unit which determines, in the case that a first intersection and a second intersection are positioned in a travel direction of the movable body, whether or not a degree of proximity of the first intersection and the second intersection satisfies a predetermined condition. In the case it is determined by the determination unit that the predetermined condition is satisfied, the information providing control unit prevents the recommended stopping information based on a current indication of the traffic signal belonging to the second intersection from being provided.

A system for regulating the speed of a vehicle includes defining a first border for a first geographic region. The border has a first speed within the border and a second speed outside of the border. The system includes determining a first velocity of the vehicle including a vehicle speed and direction of the vehicle approaching the border. The difference between the vehicle speed and the second speed is the calculated, as is a distance between the vehicle and the border. If the difference between the vehicle speed and the second speed divided by the distance is greater than a predetermined value, the vehicle is decelerated at a rate so that the vehicle will have a second speed when the vehicle reaches the border.

Location polygons are defined along traffic lanes and parking spaces to facilitate determination of the location of a vehicle relative to features associated with the location polygons. The location polygons are used, in one application, to identity entrance and exit of a special toll lane along a roadway, and to ensure that the vehicle properly enters and exits the tolling lane.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.

Determination of a trajectory for a first vehicle (1) by model predictive control (MPC) is provided. Trajectory information about a second vehicle (18) traveling in the area ahead of the first vehicle (1) is utilized. In particular, discretization points (P.sub.1, P.sub.2, P.sub.3) and arrival times of the vehicles (1, 18) at the discretization points (P.sub.1, P.sub.2, P.sub.3) are utilized to generate constraints for the model predictive control of the first vehicle (1).

An automated method of controlling a speed of a vehicle includes identifying parameters of a driving instance of the vehicle; identifying a predetermined profile that is applicable to the driving instance based on the identified parameters; identifying a predetermined speed policy applicable to the driving instance based on the identified profile; and implementing the identified speed policy during the driving instance. The method may be repeated during the driving instance, whereby the speed policy that is implemented is automatically updated when one or more changes in the identified parameters cause a different predetermined speed policy to be identified. Parameter may include driver parameters (e.g., driver age and driver experience); vehicle parameters (e.g., vehicle age, mileage, and tire wear) tire maintenance information); behavior parameters (e.g., speed, acceleration, hard braking of the vehicle, following distance, swerving, and cornering); and circumstance parameters (e.g., time of day, road information, inclement weather, and traffic congestion).