A method for moving a vehicle to a component of an object at a distance therefrom, the vehicle having a navigation module which has a camera and an evaluation electronics, and an identification element is attached to the object in a predetermined position in such a way that it is recognized by the camera in a far range (D.sub.max) of the vehicle from the object, and a reverse driving line of the vehicle is calculated by the evaluation electronics from the perspective position of the camera in relation to the identification element. The method improves the approach of a vehicle to a stationary object. A close-range (D.sub.min) is defined in the direction of the object by a close-range radius (R.sub.min) and the reverse driving line is calculated up to a virtual pre-positioning point (S.sub.Vi, S.sub.Vii, S.sub.Viii) lying on the close-range radius (R.sub.min).

A method for moving a vehicle to a component of an object at a distance therefrom, the vehicle having a navigation module which has a camera and an evaluation electronics, and an identification element is attached to the object in a predetermined position in such a way that it is recognized by the camera in a far range (D.sub.max) of the vehicle from the object, and a reverse driving line of the vehicle is calculated by the evaluation electronics from the perspective position of the camera in relation to the identification element. The method improves the approach of a vehicle to a stationary object. In a start position (S) of the vehicle, the navigation module generates a static object coordinate system (K.sub.O) and a reverse driving line is calculated from the start position (S) to a pre-positioning point (S.sub.Vi, S.sub.Vii, S.sub.Viii).

A mobile robot includes a position distance calculation command transmission unit 1, a position distance calculation command transfer unit 2, a reply position distance calculation command transmission unit 3, a direction storage unit 4, a reply position distance calculation command transfer unit 5, a first head robot unit determination command transmission unit 6, a robot unit determination unit 7, a first movement unit 8, a second movement unit 9, a next head robot unit selection command transmission unit 10 and a second head robot unit determination command transmission unit 11, for example.

The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.

A method for a follower vehicle following a lead vehicle, comprising establishing, in a first control mode of the follower vehicle, a path for the follower vehicle to follow the lead vehicle, characterized by generating environmental data which is related to the environment of the lead vehicle, determining, based on the generated environmental data, an expected behaviour of an operational parameter of the lead vehicle, determining an actual behaviour of the lead vehicle operational parameter, comparing the determined expected behaviour of the lead vehicle operational parameter and the determined actual behaviour of the lead vehicle operational parameter, determining based on said comparison whether to continue in first control mode of the follower vehicle, or in a second control mode of the follower vehicle, differing from the first control mode.

A control system for a transportation vehicle comprises a sensor vehicle that has at least one sensor for scanning an environment, wherein the sensor vehicle is configured to move autonomously to the detected transportation vehicle, and a control unit for controlling the transportation vehicle on the basis of sensor data from the at least one sensor.

A system and method for mitigating or avoiding risks due to hazards encountered by platooning vehicles. The system and method involve interrogating, with one or more sensors, a space radially extending from a lead vehicle as the lead vehicle travels over the road surface, perceiving the environment within the space, ascertaining a hazard caused by an object in the space, and causing a following vehicle, operating in a platoon with the lead vehicle, to take a preemptive braking action to avoid or mitigate risks resulting from the hazard caused by the object in the space.

A transport robot may include a wheel driver, a power supply, and a processor. The transport robot may execute artificial intelligence (AI) algorithms and/or machine learning algorithms, and may communicate with other electronic devices in a 5G communication environment. Thus, user convenience can be improved.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous vehicles may be automatically refueled by routing the vehicles to available fueling stations when not in operation, according to methods described herein. A fuel level within a tank of an autonomous vehicle may be monitored until it reaches a refueling threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to refuel the vehicle may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a fueling station, refill a fuel tank, and return to its starting location in order to refuel when not in use.

A platooning management device, a vehicle system including the same, and a method thereof are provided. The platooning management device includes a processor that calculates driving costs of vehicles in a platooning line, and compares the driving costs of the vehicles to determine whether it is necessary to change a location of a leading vehicle in the platooning line. When it is necessary to change the location, the processor performs location change control. A storage stores driving costs obtained by the processor and information received from the vehicles in the platooning line.