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.

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 roadmanship system comprises a computational device and a vehicle comprising a plurality of sensors and a vehicle control system in communication with the computational device and the plurality of sensors. The computational device can be configured to: (i) receive driving data from a group of vehicles; (ii) calculate a regression curve based on the driving data; (iii) calculate a threshold value of an engineering parameter based on the regression curve and a predetermined roadmanship level; and (iv) output the threshold value to the vehicle control system. The vehicle control system can be configured to: (a) receive the threshold value from the computational device; (b) receive operational information associated with at least one of the vehicle and a driving environment surrounding the vehicle from the plurality of sensors; and (c) cause the vehicle to perform a vehicle maneuver based on the threshold value and the operational information.

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.

The present invention obtains a controller and a control method capable of appropriately assisting with driving by a rider.

In the controller and the control method according to the present invention, an acquisition section of a controller (60) acquires yaw rate information of a traveling straddle-type vehicle (100), and in a control mode in which behavior control operation to make the straddle-type vehicle (100) automatically decelerate or automatically accelerate is performed, an execution section of the controller (60) changes the behavior control operation according to the yaw rate information.

An automatic storage and retrieval system includes: a delivery vehicle; a storage container carried by the delivery vehicle; and an unloading station for unloading an item from the storage container while it is being carried by the delivery vehicle. The unloading station includes: an unloading device; and a destination conveyor configured to convey the item to a target destination, wherein the unloading device is configured to move the item through a side opening of the storage container to the destination conveyor.

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.

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.