A vehicle includes: camera monitoring apparatus including a side-view camera having a field of view facing a rear lateral side of the vehicle and a side-view display configured to display a side-view image captured by the side-view camera; and a driver assistance system including a corner radar having a field of view facing a side of the vehicle, and configured to process radar data of the corner radar. The driver assistance system is configured to provide the camera monitoring apparatus with a virtual side-view image based on processing of the radar data of the corner radar when a failure of the side-view camera is detected. The camera monitoring apparatus is configured to display the virtual side-view image of the driver assistance system on the side-view display based on the failure of the side-view camera.

The present disclosure is directed to improving safety of drivers that drive vehicles that belong to a fleet of vehicles. This may include identifying individual drivers that should receive a training or coaching session. Scores that associated vehicle type, vehicle weight class, time of day, number of stops/starts, and other factors could be evaluated to identify drivers that may have been assigned a highest risk factor. Company telematic data as well as public data that identify types of roadways, roadway conditions, experience levels, and other factors may be combined with numbers of accidents or speeding tickets when an analysis is performed. Methods described herein may be implemented according to a machine learning model based on a processor executing instructions out of a memory. This may include deep learning or the neural network technology.

The present disclosure is directed to improving safety of drivers that drive vehicles that belong to a fleet of vehicles. This may include identifying individual drivers that should receive a training or coaching session. Scores that associated vehicle type, vehicle weight class, time of day, number of stops/starts, and other factors could be evaluated to identify drivers that may have been assigned a highest risk factor. Company telematic data as well as public data that identify types of roadways, roadway conditions, experience levels, and other factors may be combined with numbers of accidents or speeding tickets when an analysis is performed. Methods described herein may be implemented according to a machine learning model based on a processor executing instructions out of a memory. This may include deep learning or the neural network technology.

Methods and apparatus for adjusting a suspension of a vehicle are described herein. An example apparatus includes a memory storing a plurality of suspension profiles. Each of the suspension profiles includes a stored performance parameter of a vehicle and a suspension setting. The apparatus includes a sensor to detect a driver performance parameter of a driver driving the vehicle. The driver performance parameter represents a behaviour of the driver of the vehicle. The apparatus further includes a processor to compare the driver performance parameter to at least one of the plurality of suspension profiles stored in the memory, and a controller to adjust a suspension of the vehicle according to a first suspension setting of a first suspension profile of the plurality of suspension profiles if the driver performance parameter corresponds to a first stored performance parameter of the first suspension profile.

Methods and apparatus for adjusting a suspension of a vehicle are described herein. An example apparatus includes a memory storing a plurality of suspension profiles. Each of the suspension profiles includes a stored performance parameter of a vehicle and a suspension setting. The apparatus includes a sensor to detect a driver performance parameter of a driver driving the vehicle. The driver performance parameter represents a behaviour of the driver of the vehicle. The apparatus further includes a processor to compare the driver performance parameter to at least one of the plurality of suspension profiles stored in the memory, and a controller to adjust a suspension of the vehicle according to a first suspension setting of a first suspension profile of the plurality of suspension profiles if the driver performance parameter corresponds to a first stored performance parameter of the first suspension profile.

Systems and methods are disclosed for determining, and displaying, the regulatory compliance status of a motorized vehicle, a driver of a motorized vehicle, or a non-vehicle machine. An authorized agent, such as a law enforcement officer, can perform a remotely-initiated safe stop of a motorized vehicle to prevent a high-speed chase. A system management center can receive, store, and transmit regulatory compliance records indicating the regulatory compliance status of drivers, motorized vehicles, and non-vehicle machines. A motorized vehicle can detect, and report, a driver “tail-gating” the motorized vehicle. The regulatory compliance history of drivers, motorized vehicles, and non-vehicle machines can be queried by authorized users.

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).

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).

A vehicle and control method thereof are intended to promote safe driving of a driver by securing a map of surroundings around the vehicle and displaying a guide line for safe driving when the driver needs to display a guide line for safe driving while the vehicle is driving. The control method of the vehicle includes: checking whether a preset condition for generating a map and displaying a guide line is satisfied while the vehicle is driving; and generating a new map of the surroundings around a place where the vehicle is located and displaying the guide line for safe driving on the map when the preset condition for generating the map and displaying the guide line is satisfied.

A vehicle and control method thereof are intended to promote safe driving of a driver by securing a map of surroundings around the vehicle and displaying a guide line for safe driving when the driver needs to display a guide line for safe driving while the vehicle is driving. The control method of the vehicle includes: checking whether a preset condition for generating a map and displaying a guide line is satisfied while the vehicle is driving; and generating a new map of the surroundings around a place where the vehicle is located and displaying the guide line for safe driving on the map when the preset condition for generating the map and displaying the guide line is satisfied.