A plurality of items includes a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination. The value of a first vehicle parameter dependent on a mass of the first item and a mass of the second item is calculated for a first delivery route, the first delivery route being configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second. The value of a first vehicle parameter for a second delivery route is calculated, the second delivery route being configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first. A delivery route is determined that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter.

Systems and methods for determining and indicating an energy range of a host vehicle. A sensor can be positioned to acquire data corresponding to an amount of energy stored in an energy storage system of the host vehicle. An anticipated operating condition for a forthcoming location of the host vehicle can be determined based on at least one operating condition provided from at least one of a plurality of vehicles that 1) has a vehicle type that is the same as a vehicle type of the host vehicle and 2) is located at a respective location that is proximate to the forthcoming location of the host vehicle. The remaining energy range can be determined based on 1) the amount of energy stored in the energy storage system and 2) the anticipated operating condition, and an output system of the host vehicle can indicate the remaining energy range for the host vehicle.

An execution device executes an obtaining process that obtains a state of a vehicle, an operating process that operates an electronic device of the vehicle based on the state of the vehicle obtained by the obtaining process and operation data, a performance determining process that determines whether an environmental performance of the vehicle when the electronic device is operated is lower than a determination performance, and a data updating process that updates the operation data so as to increase the environmental performance of the vehicle when the performance determining process determines that the environmental performance of the vehicle is lower than the determination performance.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. A risk of malfunction and/or cyber-attack may be determined by collecting operating data from a plurality of autonomous vehicles and/or smart homes. The operating data may be analyzed to identify occurrences of a component malfunctioning. For each component, a risk associated with malfunctioning and/or cyber-attack may be determined based upon the identified occurrences. Based on the risks, at least one result associated with the malfunction and/or cyber-attack may be determined. A component profile may be generated based upon the determined risk and/or the impact of the determined results.

The present invention makes it possible to achieve both securing safety and energy saving at the time of following a preceding vehicle. In the present invention, the preceding vehicle feature amount extraction unit 101 extracts the feature amounts of the preceding vehicle based on the information transmitted from the outside world recognition unit 120, the own vehicle information recognition unit 130, the communication unit 140, and the information storage unit 150, the preceding vehicle classification unit 102 classifies the preceding vehicle based on the feature amount of the preceding vehicle obtained from the preceding vehicle feature amount extraction unit 101, and the travel planning unit 103 corrects the inter-vehicle distance or inter-vehicle time at the time of following the preceding vehicle, or proposes a lane change to an adjacent lane based on the classification result of the preceding vehicle classification unit 102.

A computer-implemented method of predicting and providing an efficient driving route for an electric vehicle (EV) based upon battery health impact includes (i) receiving geographical telematics data; (ii) generating one or more driving routes for the electric vehicle based upon at least the geographical telematics data; (iii) predicting a projected battery health impact on a battery of the electric vehicle for each driving route of the one or more driving routes, wherein the projected battery health impact for each driving route is based at least upon geographical characteristics of the driving route; (iv) determining one or more battery-efficient driving route recommendations based upon at least the projected battery health impact for each driving route; and/or (v) providing the one or more battery-efficient driving route recommendations to a user.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. An autonomous vehicle may determine an upcoming maneuver for the autonomous vehicle and identify a vehicle signal which is indicative of the upcoming maneuver. Then the autonomous vehicle may present the vehicle signal. After presenting the vehicle signal, the autonomous vehicle may perform the maneuver.

A method for the performance-enhancing driver assistance of a road vehicle driven on a track. The method comprises the steps of defining a dynamic model of the road vehicle, determining the actual position and orientation of the road vehicle, detecting a plurality of space data concerning the structure of the track, detecting a plurality of dynamic data of the vehicle, determining a passing through point of the road vehicle arranged in front of the road vehicle, solving an optimum control problem aimed at optimizing a cost function, taking into account, as boundary conditions, the plurality of environmental data, the actual position and the passing through point, so as to compute a mission optimizing the cost function, and driving the vehicle in an autonomous manner so as to show to the driver the mission optimizing the cost function.

A calibration table usable in operating an autonomous driving vehicle (ADV) is updated. The operations comprise: determining a first torque value at a first time instant prior to executing a control command; determining a control command based on a speed of the ADV, a desired acceleration, and an associated entry in the calibration table; executing the control command; determining a second torque value at a second time instant subsequent to executing the control command; determining a torque error value as a difference between the first and second torque values; updating the associated entry in the calibration table based at least in part on the torque error value; and generating driving signals based at least in part on the updated calibration table to control operations of the ADV.

A system and a method for controlling an operation of an autonomous vehicle are provided, in which information regarding front vehicles and surrounding traffic information is received in the autonomous vehicle. A traffic flow of the front vehicles and a time when a traffic light color is changed are estimated through the input information and a maximum vehicle velocity at which the autonomous vehicle is capable of crossing the traffic light is calculated while securing a safety distance from the front vehicle by regenerative braking force to generate an acceleration/deceleration control signal for adjusting a driving velocity. Braking is performed by distributing regenerative braking force and friction braking force of the driving vehicle according to the acceleration/deceleration control signal.