Systems and methods of visualizing predicted driving risk are provided herein. Vehicle sensor data associated with a vehicle operator may be analyzed. Based on the analysis of the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator may be predicted. Each vehicle operation risk may be associated with a portion of a vehicle associated with the vehicle operator. Additionally, each vehicle operation risk may be assigned a priority level, e.g., based on predicted likelihood of occurrence, predicted danger to the vehicle operator, predicted damage to the vehicle, etc. A display overview of the vehicle may be presented to the vehicle operator. In the display overview of the vehicle portions of the vehicle associated with each of the predicted vehicle operation risks may be highlighted. The portions may be highlighted differently (using different colors, heavier/lighter shading, etc.) based on the priority level of their associated risks.

The present invention achieves a technique that not only makes it possible to reduce sensor-related cost but also makes it possible to estimate a ground contact load of a vehicle with sufficiently high accuracy. A ground contact load estimation device (100) causes an acquisition section to acquire a physical quantity related to a vehicle, causes a reference inertia load calculation section (111) to calculate a reference inertia load with use of the physical quantity, uses the physical quantity to cause a correction value calculation section (112) to calculate an inertia load correction value, and causes an inertia load estimation section (110) to estimate an inertia load by adding the inertia load correction value to the reference inertia load.

A method of controlling driving force of a vehicle includes estimating a first maximum road surface frictional coefficient based on a driving stiffness defined by a micro slip ratio and driving force of drive wheels, in a first driving state where the vehicle travels straight at a constant acceleration, estimating a second maximum road surface frictional coefficient based on a steering reaction force detected by an electric power steering device, in a second driving state different from the first state and where the vehicle is steered, estimating a third maximum road surface frictional coefficient to be a given value in a third driving state different from the first and second states and where an outdoor air temperature is above a determination temperature, and controlling the driving force to settle within a friction circle defined by each of the highest frictional coefficients and a ground contact load of the drive wheels.

Systems and methods of visualizing predicted driving risk are provided herein. Vehicle sensor data associated with a vehicle operator may be analyzed. Based on the analysis of the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator may be predicted. Each vehicle operation risk may be associated with a portion of a vehicle associated with the vehicle operator. Additionally, each vehicle operation risk may be assigned a priority level, e.g., based on predicted likelihood of occurrence, predicted danger to the vehicle operator, predicted damage to the vehicle, etc. A display overview of the vehicle may be presented to the vehicle operator. In the display overview of the vehicle portions of the vehicle associated with each of the predicted vehicle operation risks may be highlighted. The portions may be highlighted differently (using different colors, heavier/lighter shading, etc.) based on the priority level of their associated risks.

A vehicle system comprises an engine driving a vehicle, a front wheel and a rear wheel, a suspension device with an attachment portion to a vehicle body which is located at a higher level than a center axis of the rear wheel, an electromagnetic coupling to distribute a torque of the engine to the front wheel and the rear wheel, a steering wheel to be operated by a driver, a steering angle sensor to detect a steering angle corresponding to operation of the steering wheel, and a controller to control the engine and the electromagnetic coupling. The controller is configured to control the electromagnetic coupling such that the torque distributed to the rear wheel is decreased in accordance with returning operation of the steering wheel which is detected by the steering angle sensor.

Various embodiments may include methods of limiting a steering command angle during operation of a vehicle. Various embodiments may include determining a speed of the vehicle, applying the determined speed to a dynamic model of the autonomous vehicle to determine a steering wheel command angle limit. Embodiments may further include determining whether a received or commanded steering command angle exceeds the steering wheel command angle limit and altering the steering command angle to an angle no greater than the maximum steering command angle if the received/commanded steering command angle exceeds the steering wheel command angle limit.

A vehicle control system may include a controller that obtains route information based on a driving route and a location of a vehicle, searches for an uneven road surface on the driving route based on the route information, calculates an impulse based on vehicle information and shape information about the found uneven road surface when the uneven road surface is found, and sets a target speed based on the calculated impulse and user data.

The present invention determines at least one dangerous driving indicator by use of a physical model based on the dynamics of a vehicle. According to the invention, a dynamic model of the vehicle determines a slip parameter of the vehicle, which deduces a representative dangerous driving indicator.

A vehicle can include throttle, braking, and steering systems. The vehicle can further include a computing system that obtains, from one or more sensors, data representing one or more of a velocity or an acceleration of the vehicle. The computing system can further determine an estimated weight of the vehicle based on the one or more of the velocity or the acceleration of the vehicle, and autonomously operate the throttle, braking, and steering systems of the vehicle based on the estimated weight of the vehicle.

A method of controlling driving force of a vehicle includes estimating a first maximum road surface frictional coefficient based on a driving stiffness defined by a micro slip ratio and driving force of drive wheels, in a first driving state where the vehicle travels straight at a constant acceleration, estimating a second maximum road surface frictional coefficient based on a steering reaction force detected by an electric power steering device, in a second driving state different from the first state and where the vehicle is steered, estimating a third maximum road surface frictional coefficient to be a given value in a third driving state different from the first and second states and where an outdoor air temperature is above a determination temperature, and controlling the driving force to settle within a friction circle defined by each of the highest frictional coefficients and a ground contact load of the drive wheels.