An approach is provided for providing mobility insight data related to shared vehicles for a point of interest (POI). The approach involves retrieving shared vehicle data for the POI. The shared vehicle data indicates one or more shared vehicle events that have occurred, that are occurring at a given time, or a combination thereof within a threshold proximity of the POI. The approach also involves processing the shared vehicle data to determine mobility insight data. The mobility insight data includes a shared vehicle usage pattern, a shared vehicle availability pattern, or a combination thereof under one or more contexts for travel to or from the POI. The approach further involves presenting the mobility insight data in a location-based user interface.

A power generation system for wheeled objects comprises a generator mechanically coupled to one or more of the object's wheels to convert wheel rotational energy into electrical energy. The power generation system may comprise an electrical storage device configured to store the electrical power produced by the generator. Power from the generator and/or the electrical storage device can be used to provide power to other electrical systems in or on the object. In certain embodiments, the electrical storage device comprises a bank of high-capacity capacitors connected in series. Some embodiments use a control circuit, for example, to regulate the charging and discharging of the capacitor bank and to provide suitable voltages for other systems. The power generation system may be disposed within an object's wheel, such as a wheel of a shopping cart.

A method and a gateway system of a mobile asset are described. A voltage produced by a power system of the mobile asset is monitored by a gateway system. In response to determining that a first fluctuation occurs in the voltage produced by the power system of the mobile asset over a first interval of time, the gateway system operates in a first mode. In response to determining that a value of the voltage produced by the power system of the mobile asset is less than a voltage threshold, the gateway system automatically transitions to operating in a second mode, which is different from the first mode and causes the gateway system to consume less power than when it is operating in the first mode.

Disclosed are systems and methods relating to providing corridor metrics based on road network data and telematic data.

Disclosed are systems and methods relating to providing corridor metrics based on road network data and telematic data.

Disclosed are systems, methods, and non-transitory computer-readable media for automated fleet tracking. A route management system enables fleet managers to define and assign routes for vehicles in a fleet, as well as set route tracking configurations for customized tracking of the vehicles. For example, the route tracking configuration may include customizations to the scheduled start and/or end time of a route, a threshold for determining that a vehicle has arrived and/or departed from a scheduled stop, and the like.

A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include determining a trajectory of the object, determining an intent of the trajectory, and sending the trajectory and the intent to a vehicle computing system to control an autonomous vehicle. The vehicle computing system may implement a machine learned model to process data such as sensor data and map data. The machine learned model can associate different intentions of an object in an environment with different trajectories. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on object's intentions and trajectories.

At least a method for determining risk behavior of a driver is described. While a vehicle is being driven, data is obtained related to the position and movement of a wireless communications device. The data may indicate the type of behavior exhibited by the driver while the vehicle is being driven.

A method includes receiving vehicle data indicative of a least one operating characteristic of one or more vehicles and one or more fault codes from the one or more vehicles, each of the one or more fault codes having a corresponding component; aggregating the one or more fault codes based on the corresponding components of the one or more fault codes; interpreting the vehicle data and the one or more fault codes to determine a potential root cause for the one or more fault codes by comparing vehicle data of a first vehicle of the one or more vehicles to the vehicle data of the one or more vehicles; and providing a graphical user interface to a display device for depicting the one or more fault codes based on the potential root cause.