Provided is a scooter radar detection system for a scooter, including: a control module for controlling operation of the scooter radar detection system; two detection radars flanking a license plate, facing the rear of the scooter, and being in signal connection with the control module; two flash alert units disposed at rear-view mirrors on two sides of the scooter, respectively, and being in signal connection with the control module; and a vibration alert module disposed below a seat and being in signal connection with the control module.

A method and an apparatus for controlling personal mobility device (PMD) depending on congestion includes identifying a target area according to an expected route of the PMD, acquiring a degree of congestion of the target area based on at least one of a type of objects, a movement of the objects, a distance between objects, the number of objects that is expected, and a speed limit of the target area, and controlling speed of the PMD according to the degree of congestion.

A system for controlling a smart mobility by risk level includes: an information collection unit to collect position and speed information of the smart mobility and camera sensing information including a front traffic sign or object; a front detection unit to detect a front obstacle or inclination using the camera sensing information and to output a detection result; a control unit to change a warning to a user and/or a method of controlling the smart mobility by risk level based on the information collected by the information collection unit and the detection result; and a warning unit to warn the user by changing a method by risk level under the control of the control unit.

In one embodiment, a computer-implemented method includes receiving a transportation request from a transportation requestor device to travel from a first location to a second location. The computer-implemented method also includes determining one or more routes from the first location to the second location and a characteristic associated with each route of the one or more routes. The computer-implemented method also includes selecting, based on the characteristic associated with each route of the one or more routes, a personal mobility vehicle from a fleet of personal mobility vehicles. The fleet of personal mobility vehicles includes different types of personal mobility vehicles. The computer-implemented method also includes providing instructions to a device associated with the personal mobility vehicle to direct the personal mobility vehicle to traverse a particular route of the one or more routes.

An electric power supply system configured to supply electric power to an electrical load device in accordance with a current requirement. The electric power supply system includes an engine configured to output rotational power, a generator configured to receive the rotational power and to supply a current to the electrical load device. The generator includes a rotor, and a stator including a winding and a stator core with the winding wound thereon, a magnetic circuit for the winding passing through the stator core, and a supply current adjustment device configured to adjust magnetic resistance of the magnetic circuit for the winding, to thereby change an inductance of the winding to adjust the supplied current. The electric power supply system further includes a control device configured to control the engine to adjust the output rotational power and to control the supply current adjustment device to adjust the inductance of the winding.

A device includes a battery case (42) that stores a battery (62A or 62B), a lock mechanism (133) that is capable of fixing and holding the stored battery (62A or 62B) in the battery case (42), and an operation member (44) that is capable of performing switching operation of the lock mechanism (133) between a battery-fixed state and a non-battery-fixed state. The lock mechanism (133) includes a movable block (160) which is supported by the battery case (42) in a displaceable manner. The movable block (160) has a battery restriction portion (160b or 160c) which restricts displacement of the battery (62A or 62B) in a separation direction in a state of being displaced to a battery fixing position, and a holding force receiving portion (160d) which receives a holding force for maintaining the movable block (160) at the battery fixing position from the operation member (44) in a state where the operation member (44) is operated within a predetermined positional range.

A bake-steering apparatus for controlling autonomous navigation of an electric scooter includes at least one electric motor coupled to at least one wheel of the scooter to provide driving power to enable forward momentum of the scooter, at least a pair of brake pads on the scooter such that each brake pad is adapted to make mechanical braking contact with respective ones of the wheels to provide navigational steering of the scooter, and a computational module on the scooter and electrically connected to each brake pad. The computational module is adapted to receive electrical signals and compute them into corresponding braking commands so as to determine the mechanical braking contact to generate corresponding slowing and turning of the forward momentum of the scooter so as to provide navigational steering of the scooter.

Presented are adaptive operator assistance systems for motor-assisted manually powered (MMP) vehicles, methods for making/using such systems, and electric scooters equipped with such systems. A method of operating an MMP vehicle using a handheld mobile computing device (MCD) includes the handheld MCD receiving path plan data for the MMP vehicle and then receiving, based on this path plan data, MMP-specific ambient data that is aligned with the vehicle's present location and contains surrounding environment data particular to the MMP vehicle. A wireless location device of the handheld MCD tracks the MMP vehicle's real-time location, and a sensing device of the handheld MCD detects MMP-specific threat data that is aligned with the vehicle's real-time location and contains user danger data particular to the MMP vehicle. The handheld MCD then commands a resident subsystem of the MMP vehicle to execute a control operation based on the MMP-specific ambient data and/or threat data.

The disclosed computer-implemented method may include tracking personal mobility vehicle batteries. In some embodiments, the method may track and maintain battery power for personal mobility vehicles to help to ensure that there are personal mobility vehicles with sufficient charge available to perform the needed transportation tasks within a dynamic transportation network. In some examples, a swappable battery for a personal mobility vehicle may communicate with a dynamic transportation management system and provide information about current and/or historical charge information. In some examples, the method may use the current state of charge and/or historical charge information to predict the performance of the battery. Based on the predicted performance, the method may predict the range of a personal mobility vehicles with the battery and/or a lifespan of the battery and make matching decisions accordingly. Various other methods, systems, and computer-readable media are also disclosed.

There may be provided a method for electrical scooter alert, the method may include sensing sensed information about an environment of a vehicle; detecting, based on the sensed information, a situation related to the environment; detecting, based on the sensed information, a electrical scooter within the environment; predicting, using a machine leaning process and based in the situation, a future behavior of the electrical scooter and an impact of the future behavior of the electrical scooter on a future progress of the vehicle; and responding to the predicting.