A vehicle control device comprising: a balance gradient calculation unit configured to calculate a balance gradient that is a gradient at which a propulsive force of the vehicle and a resistance force applied to the vehicle are balanced when the vehicle travels in a gear-in coasting state in which an engine is connected to a gear and the vehicle travels without supplying fuel to the engine, in a case where a traveling state of the vehicle is a neutral coasting state; and a traveling control unit configured to: switch, based on the calculated balance gradient and a specified road gradient, the traveling state of the vehicle from the neutral coasting state to the gear-in coasting state in a case where the traveling state of the vehicle is the neutral coasting state; and end, the gear-in coasting state when determining that an end condition is satisfied.

Methods, systems, and non-transitory computer readable media configured to perform operations comprise determining, by a computing system, speeds and stations of a plurality of leading vehicles traveling ahead of an ego vehicle; calculating, by the computing system, a coasting viability factor based on the speeds and stations of the plurality of leading vehicles and a speed and station of the ego vehicle; comparing, by the computing system, the coasting viability factor to a coasting viability threshold; and determining, by the computing system, whether the ego vehicle should coast based on the comparing.

Various embodiments include methods for operating a motor vehicle during a journey along a route comprising: determining an upcoming potential stopping point along the route; upon approach to the potential stopping point, calculating a value for a probability of a stopping procedure of the motor vehicle at the stopping point at least in part on a stopping model; and, if the probability value is in a predetermined range of values defining a likely occurrence of the stopping procedure, triggering a predetermined operating measure to adapt operation of the motor vehicle to the stopping procedure. The stopping model includes a statistical model providing intermediate values between 0% and 100% for the probability value.

A method includes detecting, via a processor of an autonomous vehicle, an upcoming downhill road segment of a route on which the autonomous vehicle is currently travelling. The detection is based on map data, camera data, and/or inertial measurement unit (IMU) data. In response to detecting the upcoming downhill road segment, a descent plan is generated for the autonomous vehicle. The descent plan includes a speed profile and a brake usage plan. The brake usage plan specifies a non-zero amount of retarder usage and an amount of foundation brake usage for a predefined time period. The method also includes autonomously controlling the autonomous vehicle, based on the descent plan, while the autonomous vehicle descends the downhill road segment.

A motor vehicle having a combustion engine for vehicle propulsion can be automatically stopped when engine propulsion is not needed, such as during a gliding condition when the vehicle is coasting down to a slower speed (e.g., stopping) or down an incline. The engine is automatically restarted as needed. To ensure a capacity of a battery or other electrical storage device to support nominal operation of electrical loads (including a starter motor for restarting the engine) during an Auto Stop event, predicted future states of a vehicle battery are determined using a battery state of function (SOF) in response to load transients that may need to be supported.

A method of controlling an engine and a transmission of a vehicle includes: determining, by a controller, whether the engine is restarted after releasing the vehicle's SSC (Start & Stop coasting) or whether the vehicle is accelerating during NCC (Neutral Coasting control), determining an RPM and gear stage of the transmission if it is determined that the engine is restarted after releasing the vehicle's SSC or the vehicle is accelerating during NCC, determining a mild hybrid starter and generator (MHSG) target RPM and an MHSG target RPM gradient of the vehicle, performing, by the controller, MHSG RPM control of the vehicle to follow the MHSG target RPM and the MHSG target RPM gradient, determining whether the MHSG RPM slips compared to the MHSG target RPM, and performing proportional-integral-derivative (PID) control to follow the MHSG target RPM if the MHSG RPM slips compared to the MHSG target RPM.

A method for controlling a coasting guide function is provided. The method may include: detecting a speed limit and an average speed of a peripheral vehicle; detecting a valid speed limit when a coasting event occurs; and calculating a target speed by using a speed factor computed by using at least one of the valid speed limit, the average speed of the peripheral vehicle, or a current speed.

An anti-jerk control method for an electric vehicle incorporates an anti-jerk function that can be performed more accurately and effectively by utilizing a real-time weight change of an electric vehicle. The anti-jerk control method includes: estimating vehicle weight by a controller based on vehicle driving information collected from a vehicle; determining a required torque command of a driver by the controller based on the vehicle driving information collected from the vehicle; determining anti-jerk torque according to the vehicle weight based on calculated speed deviation and the estimated vehicle weight information; and controlling a drive motor according to a compensated motor torque command by compensating the required torque command with the anti-jerk torque in the controller.

A method includes detecting, via a processor of an autonomous vehicle, an upcoming downhill road segment of a route on which the autonomous vehicle is currently travelling. The detection is based on map data, camera data, and/or inertial measurement unit (IMU) data. In response to detecting the upcoming downhill road segment, a descent plan is generated for the autonomous vehicle. The descent plan includes a speed profile and a brake usage plan. The brake usage plan specifies a non-zero amount of retarder usage and an amount of foundation brake usage for a predefined time period. The method also includes autonomously controlling the autonomous vehicle, based on the descent plan, while the autonomous vehicle descends the downhill road segment.

A computing device configured to: obtain images representative of an environment of a host vehicle, the host vehicle traveling on a roadway; detect, from the images, a mark located on the roadway; identify, from the images, points corresponding to the mark on the roadway; identify the mark as a type of roadway marking, corresponding to the identified points, the type of roadway marking selected from multiple types of roadway markings; determine a position of the mark on the roadway relative to the host vehicle, using the identified points corresponding to the mark; and determine a trajectory to navigate the host vehicle on the roadway, based on the position of the mark within the roadway and the type of roadway marking.