Systems and methods are provided herein for managing scooter fleets based on geolocation boundaries. In certain embodiments, individual scooters of the scooter fleet may be associated with geographical areas in which they are allowed to operate, and such areas may be defined by a geolocation boundary. The geographical areas may be provided to prevent scooters from being used and subsequently left in an undesirable location (for example, at an airport terminal or an area where crime is commonplace).

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.

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.

There is provided a control device configured to perform a collision preventing control based on an output of an obstacle detection unit. A risk level determination unit determines a collision risk level based on a distance between the obstacle and the electric vehicle. A control level adjustment unit adjusts a control level of the collision preventing control based on the collision risk level. The control level adjustment unit lowers the control level when a releasing unit configured to temporarily release the collision preventing control is operated by a driver during the collision preventing control and causes the electric vehicle to display presence of the obstacle.

A torque-speed curve or data of load that is used as a standard to determine an external condition in which an electric vehicle is operating such as incline or no incline, head wind or no headwind, high temperature or low temperature. The system compares samples of actual torque-speed of load data to the standard. Based on the comparison, the system determines the external condition (going up a hill, traveling into a headwind, operating at high temperature) or an abnormal operation of the vehicle powertrain, for example, low tire pressure, elevated friction, wheels out of alignment. Based on the determination, the system takes an action to govern a maximum torque output of the motor to control temperature of the vehicle battery; to raise a wind deflector; to govern maximum speed of the vehicle to reduce danger resulting from low tire pressure, elevated powertrain friction or out of alignment wheels; or to initiate an indication of abnormal conditions.

Electric motor scooters are disclosed. In one embodiment, an electric motor scooter includes an electric drive, an electric battery, an actuation unit, and a control unit. The actuation unit may be brought in to one of a plurality of positions along an actuation distance, and the control unit is configured to selective a drive mode depending on the position of the actuation unit along the actuation distance. The drive modes include a recuperation mode, a coasting mode, an acceleration mode, and a boost mode. When in the recuperation mode, at least a portion of the energy generated in the electric drive may be delivered to the battery.

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.

The disclosed computer-implemented method may include automated signaling for networked personal mobility vehicles (PMVs). In some embodiments, a system may identify a PMV in use by a transportation requestor taking a trip. The system may also predict one or more actions of the PMV based on navigational data for the trip. Additionally, the system may select one or more signals corresponding to a predicted action of the PMV. In some embodiments, the system may determine, based on a current state of the PMV, that the predicted action of the PMV will be initiated within a time frame. Furthermore, the system may send a start command to the PMV to initiate a signal in response to determining the predicted action will be initiated. Various other methods, systems, and computer-readable media are also disclosed.

The disclosed computer-implemented method may include improving safety in operating personal mobility vehicles. The method may track and/or control personal mobility vehicles associated with dynamic transportation networks. The method may improve safety related to PMV operation by taking advantage of the various sources and types of information related to PMV operation that are available in the dynamic transportation network. Other methods, systems, and computer-readable media are disclosed.

Personal mobility vehicles, their various components, methods and systems for controlling, using, tracking, and/or interacting with personal mobility vehicles, and methods and systems for integrating personal mobility vehicles within dynamic transportation networks so that a personal mobility vehicle (PMV) can be used in combination with a vehicle of a transportation provider to efficiently complete a transportation request are discussed. For example, a PMV may be used in combination with a lane-constrained vehicle to improve travel time between two locations in situations where the time it may take for a lane-constrained vehicle to reach the starting location may be affected by traffic congestion at the starting location. The PMV may transport a transportation requestor from a starting location to an intermediate location away from the traffic congestion to then transfer to a lane-constrained vehicle for the remainder of the trip.