A mileage prediction and optimization system (FIG. 1) is disclosed for optimizing the mileage of a vehicle. The mileage prediction and optimization system comprises a prediction and optimization module (300) adapted to determine variation in mileage of the vehicle at least based on the current fuel volume, current speed, current fuel density, the current tire air pressure, the current tire air temperature, current fetched values from an ECU module (700) and the pre-defined mileage data of the vehicle. Further, the prediction and optimization module (300) is adapted to optimize the mileage of the vehicle by reducing variation of fuel density, reducing variation of tire air pressure and informing optimal gear-speed combinations to a user regardless of whether the vehicle is stationary or in motion.

The invention is notably directed to a method of steering an automated vehicle (2) in a designated area, thanks to a set (10) of offboard perception sensors (110-140). The method comprises repeatedly executing algorithmic iterations, where each iteration comprises the following steps. First, sensor data are dispatched to K processing systems (11, 12), whereby each processing system k of the K processing systems receives N.sub.k datasets of the sensor data as obtained from N.sub.k respective sensors of the set (10) of offboard perception sensors (110-140), where k=1 to K, K2, and N.sub.k2. The N.sub.k datasets are subsequently processed at each processing system k to obtain M.sub.k occupancy grids corresponding to perceptions from M.sub.k respective sensors of the offboard perception sensors, respectively, where N.sub.kM.sub.k1. The M.sub.k occupancy grids overlap at least partly. Data from the M.sub.k occupancy grids obtained are then fused, at each processing system k, to form a fused occupancy grid, whereby K fused occupancy grids are formed by the K processing systems (11, 12), respectively. The K fused occupancy grids are then forwarded to a further processing system (14), which merges the K fused occupancy grids to obtain a global occupancy grid for the designated area. Eventually, a trajectory is determined for the automated vehicle (2), based on the global occupancy grid. This trajectory is then forwarded to a drive-by-wire system (20) of the automated vehicle (2), to accordingly steer the latter. The invention is further directed to related systems and computer program products.

A traveling control apparatus is mounted on a vehicle that includes an electric motor and an internal combustion engine as power sources. The traveling control apparatus includes an electronic control unit configured to create a speed profile obtained by predicting speed of the vehicle at each time, derive, based on at least the speed profile, a coefficient profile that is a coefficient at each time used at the time of predicting an amount of regenerative energy recoverable by regenerative braking of the electric motor, approximate the speed profile with a predetermined approximation model and estimate a predicted amount of regenerative energy based on an approximation result and the coefficient profile, and determine the power source used for traveling based on the predicted amount of regenerative energy.

Exemplary implementations may: generate output signals conveying contextual information and vehicle information; determine, based on the output signals, the contextual information; determine, based on the output signals, the vehicle information, determine, in an ongoing manner, based on the contextual information and/or the vehicle information, values of a complexity metric, the complexity metric quantifying predicted complexity of a current contextual environment and/or predicted complexity of a likely needed response to a change in the contextual information; filter, based on the values of the complexity metric, the contextual information spatially; and control, based on the vehicle information and the spatially filtered contextual information, the vehicle such that the likely needed response is satisfied.

A method for operating a vehicle that includes an internal combustion engine that may be automatically stopped and started is described. In one example, selection of an engine starting device is based on a value of an engine starting torque reserve. The engine starting torque reserve may be dynamically adjusted so that life spans of engine starting devices may meet expectations.

An abnormality determination device is applied to a vehicle provided with a transmission configured to transmit power by rotation of a shaft. The abnormality determination device includes a processor and a memory. The memory configured to store mapping data that is data that defines mapping learned by machine learning. The processor is configured to execute an acquisition process and a determination process. The acquisition process is a process of acquiring a variable indicating a time-series data of a rotation speed of the shaft and using the variable as a value of an input variable of the mapping. The determination process is a process of determining whether an abnormality has occurred in the transmission based on a value of the output variable acquired using the value of the input variable and the mapping.

A system includes a computing device with memory configured to store instructions and a processor to execute the instructions for operations that include causing a request for mode 9 information to be transmitted from the computing device to a vehicle remote from the computing device. The request causes a controller of an auxiliary vehicle propulsion system to access a network bus of the vehicle within a pre-determined time period after the auxiliary vehicle propulsion system is installed and activated on the vehicle.

A non-transitory storage medium for use in an information processing device in a vehicle control system. The storage medium stores: pieces of positional information; pieces of cumulative relative frequency distribution information associated with individual vehicle traveling directions, the pieces of cumulative relative frequency distribution information being related to data on traveling loads associated with the individual vehicle traveling directions on a plurality of vehicles having traveled through points indicated by the pieces of positional information, or data on traveling load amounts depending on a traveling time or a traveling distance from the points; and instructions that are executable by processors to perform functions comprising calculating a predicted value of the traveling load amount depending on the traveling time or the traveling distance from an arbitrary point based on the cumulative relative frequency distribution information associated with individual vehicle traveling directions at the arbitrary point.

Methods and systems are provided for a hybrid electric vehicle. In one example, a method may include delaying an electric-only operation of the hybrid vehicle in response to a powertrain temperature being less than a threshold powertrain temperature and an electric-only range being less than a distance between a current location and a recharging location. The electric-only operation may be initiated in response to one or more of the powertrain temperature exceeding the threshold powertrain temperature and the electric-only range being equal to the distance.

To achieve saving of fuel consumption and noise reduction by adopting a hybrid type and miniaturizing an engine and to ensure safe and reliable battery charging in a case in which a charge amount of a battery is quite insufficient, a hydraulic work machine includes: a gate lock sensor (28); a forced charging switch (41); a work machine monitor (43) that notifies an operator that a charging rate of a battery (33) falls to be lower than a critical charging rate; and a machine controller (46). The machine controller (46) actuates a generator motor (31) as a generator to forcedly charge the battery (33) when a gate lock lever (26) is operated to a lock position (D), an engine control dial (12) designates a low idle engine speed, and the forced charging switch (41) is operated.