Abstract: The disclosed method may include configuring one or more brakes based on a braking-related attribute expected at a geographic location being traversed by a personal mobility vehicle. By configuring the application of brakes of a personal mobility vehicle based on terrain, environmental conditions, and other geographic features, the system may reduce the risk of the vehicle skidding or tipping due to over-braking. In some embodiments, a rider may use a single brake lever to indicate a desire to brake and the system may make determinations about how to apply a combination of mechanical and electrical brakes to front and back wheels based at least in part on the location of the personal mobility vehicle. By configuring brake engagement based on a combination of controls and map data, the system may improve user experience and user safety, especially for inexperienced riders.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The disclosed computer-implemented method may include routing personal mobility vehicles based on road or path conditions. In some embodiments, trip routing for personal mobility vehicles participating in a dynamic transportation network may leverage road condition map data gathered from personal mobility vehicle sensors to evaluate potential routes for personal mobility vehicles. In some examples, the method may account for the type and/or characteristics of the personal mobility vehicle when evaluating a potential route. In some examples, the method may account for user preferences when evaluating a potential route. The method may also make matching decisions for a dynamic transportation matching system and/or personal mobility vehicle distribution decisions for the dynamic transportation network based on the conditions of prospective routes. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The disclosed computer-implemented method may include matching transportation requests to personal mobility vehicles. A dynamic transportation network may incorporate different types of vehicles, such as bicycles and/or scooters. Certain vehicles may have advantages over other vehicles in certain contexts but be disadvantageous in others. For example, a dynamic transportation matching system may match a user transporting a bulky package with a basket-equipped bike rather than a scooter without a basket. Moreover, the dynamic transportation matching system may account for a wide variety of other factors, including but not limited to route features, ambient conditions, and vehicle status when matching a transportation requestor to a specific vehicle. Moreover, some systems may account for vehicle wear-and-tear, battery power levels, operational status, etc. to avoid matching users vehicles that would be unable to fulfill a transportation request.

Abstract: A system for multiple brakes intelligently controlled by a single brake input on a personal mobility vehicle. By determining a front and rear brake differential based on the position and weight of the rider as well as the environmental and vehicle conditions, the system may reduce the risk of the vehicle skidding or tipping due to over-braking. In some embodiments, a rider may use a single brake lever to indicate a desire to brake and the system may make determinations about how to apply a combination of mechanical and electrical brakes to front and back wheels. By applying different braking systems based on a combination of controls and sensors, the system may improve user experience and user safety, especially for inexperienced riders.

Abstract: The disclosed method may include configuring one or more brakes based on a braking-related attribute expected at a geographic location being traversed by a personal mobility vehicle. By configuring the application of brakes of a personal mobility vehicle based on terrain, environmental conditions, and other geographic features, the system may reduce the risk of the vehicle skidding or tipping due to over-braking. In some embodiments, a rider may use a single brake lever to indicate a desire to brake and the system may make determinations about how to apply a combination of mechanical and electrical brakes to front and back wheels based at least in part on the location of the personal mobility vehicle. By configuring brake engagement based on a combination of controls and map data, the system may improve user experience and user safety, especially for inexperienced riders.

Abstract: The disclosed computer-implemented method may include routing personal mobility vehicles based on road or path conditions. In some embodiments, trip routing for personal mobility vehicles participating in a dynamic transportation network may leverage road condition map data gathered from personal mobility vehicle sensors to evaluate potential routes for personal mobility vehicles. In some examples, the method may account for the type and/or characteristics of the personal mobility vehicle when evaluating a potential route. In some examples, the method may account for user preferences when evaluating a potential route. The method may also make matching decisions for a dynamic transportation matching system and/or personal mobility vehicle distribution decisions for the dynamic transportation network based on the conditions of prospective routes. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: 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.

Abstract: 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.