A method for determining a speed profile to be followed by a vehicle, including acquiring event data including a distance from an event and a target speed at this event for the vehicle, and determining a speed profile to be followed as a function of time, between an initial speed and the target speed in three successive distinct phases, respectively a first phase in which the jerk is set constant at a predetermined maximum jerk value to reach an optimal target acceleration value, a second phase in which the optimal target acceleration value is kept constant, and a third phase in which the jerk is again set constant to reach a zero acceleration value at the end of the third phase. The optimal target acceleration value is such that the distance required to carry out the three phases of the profile is equal to the distance from the event.

A driving support apparatus includes a feedback control system. The feedback control system calculates each operation amount of a brake actuator and a drive actuator so as to match an actual value of a control amount indicating a motion state of the vehicle to a target value. The target value of the control amount is set so as to stop the vehicle to a target stop position. The driving support apparatus sets, when remaining distance from a current position of the vehicle to the target stop position is first distance, a feedback gain of the feedback control system to large value, as compared with the feedback gain set when the remaining distance is second distance which is greater than the first distance.

A computer implemented method for scenario generation for autonomous vehicle navigation that can include defining a cellular automaton layer that defines a road network level behavior with at least one rule directed to pathways by vehicles on a passageway for travel. The method may further include defining an active matter layer that defines a vehicle level behavior with at least one rule directed to movement of the vehicles on an ideal route for the pathways; and defining a driver agent layer that defines driving nature with at least one rule that impacts changes in the vehicle level behavior dependent upon a characterization of driver behavior. The method may further include combining outputs from the different layer to provide scenario generations for autonomous vehicle navigation. The combining of the outputs can utilize a pseudo random value to determine at an order in the execution and duration of execution for the layers.

A vehicle control device, a vehicle control method, and a vehicle control system according to the present invention obtain an inter-vehicle time based on a relative distance between a first vehicle traveling, in front of an own vehicle, in a second lane adjacent to a first lane in which the own vehicle travels and a second vehicle traveling in the second lane in front of the first vehicle and based on a relative velocity of the first vehicle relative to the second vehicle, obtain a relative acceleration of the first vehicle relative to the second vehicle, set the first vehicle as a high-stress vehicle based on a lane change space that is based on the inter-vehicle time, the relative acceleration, and a relative distance between the second vehicle and a third vehicle traveling in the first lane in front of the own vehicle, and output a control command for changing a driving state of the own vehicle based on a relative distance between the high-stress vehicle and the own vehicle. This makes it possible to improve the driving safety of a vehicle on a road with multiple lanes in each direction.

An autonomous driving system acquires information concerning a vehicle density in an adjacent lane that is adjacent to a lane on which an own vehicle is traveling, when the own vehicle travels on a road having a plurality of lanes. The autonomous driving system selects the adjacent lane as an own vehicle travel lane, when the vehicle density in the adjacent lane that is calculated from the acquired information is lower than a threshold density that is determined in accordance with relations between the own vehicle and surrounding vehicles. The autonomous driving system performs lane change to the adjacent lane autonomously, or propose lane change to the adjacent lane to a driver, when the adjacent lane is selected as the own vehicle travel lane.

An electro-mechanical actuation control system includes: a comparator configured to compare a desired vehicular component data to an actual vehicular component data; a controller that is configured to enable control of vehicular components and includes vehicle component controllers; a transmitter configured to remotely transmit input signals to the vehicle; a receiver configured to receive the transmitted input signals from the controller and mounted on the vehicle; an actuator driver configured to receive inputs from the receiver and mounted on the vehicle; an actuator coupled to the actuator driver and configured to be operable in any one of an enabled state and a disabled state caused by the actuator driver; and one or more vehicle components that comprise a drive unit including one of an engine assembly, an electric motor and a combination of the engine assembly and the electric motor.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. Example embodiments disclosed herein provide enhanced high-precision operation of an AV in low-speed environments, such as a toll booth facility or heavy traffic. One example method disclosed herein includes a control computer identifying a starting point of the toll booth facility on the roadway and a plurality of toll lanes associated with the toll booth facility; selecting a particular toll lane; determining a trajectory for the AV that extends through the particular toll lane; and in response to the autonomous vehicle arriving at the starting point for the toll booth facility, transmitting, over a subsystem interface to one or more drive subsystems of the AV, instructions configured to cause the drive subsystems to operate together to cause the AV to travel according to the trajectory.

A vehicle travel assistance system includes a travel assistance control unit, an operation unit, and a travel assistance setting unit. The travel assistance control unit is configured to perform travel assistance in a braking-and-driving-force distribution control mode and an automatic cruise control mode. The travel assistance setting unit supplies, to the travel assistance control unit, setting information of travel assistance in response to the received operation under a condition that the operation received by the operation unit is for selecting the braking-and-driving-force distribution control mode, the travel assistance setting unit automatically supplies setting information of the braking-and-driving-force distribution control mode to the travel assistance control unit regardless of the operation in a case where a speed of the vehicle becomes an automatic deactivation speed or higher and thereafter becomes an automatic reactivation speed or lower.

Provided are systems and methods for controlling a vehicle based on a map that designed using a factor graph. Because the map is designed using a factor graph, positions of the road can be modified in real-time while operating the vehicle. In one example, the method may include storing a map which is associated with a factor graph of variable nodes representing a plurality of constraints that define positions of lane lines in a road and factor nodes between the variable nodes on the factor graph which define positioning constraints amongst the variable nodes, receiving an indication from the road using a sensor of a vehicle, updating positions of the variable nodes based on the indication and an estimated location of the vehicle within the map, and issue commands capable of controlling a steering operation of the vehicle based on the updated positions of the factor nodes.

A device and a method for controlling autonomous driving control a speed of an autonomous vehicle before downhill travel. The device and method calculate a travel resistance of an autonomous vehicle on a travel-intended-route, including a downhill route, a main braking pressure required to travel at a constant speed, and a brake temperature based on braking. The device and method determine whether to reduce the main braking pressure based on the calculated brake temperature and calculates a decreased amount of the main braking pressure and an increased amount of a speed of the autonomous vehicle based on the decreased amount of the main braking pressure on the travel-intended-route when determining to reduce the main braking pressure. The device and method limit a maximum speed of the autonomous vehicle before entering the travel-intended-route based on the increased speed amount.