Abstract: Example embodiments are directed to systems and methods for generating and providing elevation-aware hotspots. In example embodiments, a network system detects an initiation of a request for a transportation service at a client device of a user and receives an indication of a location of the client device and corresponding signal strengths associated with the client device. The network system then determines a telematics vector based on the signal strengths associated with the client device. Based on the location of the client device and the telematics vector associated with the client device, the network system identifies one or more top ranked elevation-aware hotspots. A pickup point recommendation is then presented, by the network system on a user interface on the client device of the user, whereby the pickup point recommendation includes the one or more top ranked elevation-aware hotspots.

Abstract: Systems and methods for generating and presenting an optimized path using sequential location trace clustering is provided. The system receives a request for a transportation service from a client device of a user. The request indicates a destination point (i.e., a pickup location) and is associated with a start point (i.e., a location at a time the user requested the transportation service). Based on the start point and destination point, the system identifies one or more paths between the start point and the destination point, whereby the one or more paths are generated using sequential location trace clustering from previous transportation services involving the start point and the destination point. The system then causes presentation of a path of the one or more paths on a user interface on the client device of the user with which the user can use to navigate to the destination point.

Abstract: Example embodiments are directed to systems and methods for generating and providing elevation-aware hotspots. In example embodiments, a network system detects an initiation of a request for a transportation service at a client device of a user and receives an indication of a location of the client device and corresponding signal strengths associated with the client device. The network system then determines a telematics vector based on the signal strengths associated with the client device. Based on the location of the client device and the telematics vector associated with the client device, the network system identifies one or more top ranked elevation-aware hotspots. A pickup point recommendation is then presented, by the network system on a user interface on the client device of the user, whereby the pickup point recommendation includes the one or more top ranked elevation-aware hotspots.

Abstract: A network system receives, from each of a plurality of client devices, a transmission of a scan of signals from signal broadcasting devices. A vector is created from each scan, whereby the vector comprises a received signal strength indicator (RSSI) to each unique signal broadcasting device. Based on the vector created from each scan, the network system determines a probability that the client devices are co-present. The probability is determined based on applying the vectors to a copresence estimation function that uses an angular similarity, a magnitude similarity, and a number of signal broadcasting devices. Based on the probability, the network system triggers a component to perform a corresponding operation.

Abstract: Example embodiments are directed to systems and methods for providing high dimension copresence estimation. A network system receives, from each of a plurality of client devices, a transmission of a scan of signals from signal broadcasting devices. A vector is created from each scan, whereby the vector comprises a received signal strength indicator (RSSI) to each unique signal broadcasting device. Based on the vector created from each scan, the network system determines a probability that the client devices are co-present. The probability is determined based on applying the vectors to a copresence estimation function that uses an angular similarity, a magnitude similarity, and a number of signal broadcasting devices. Based on the probability, the network system triggers a component to perform a corresponding operation.

Abstract: Example embodiments are directed to systems and methods for generating and providing elevation-aware hotspots. In example embodiments, a network system detects an initiation of a request for a transportation service at a client device of a user and receives an indication of a location of the client device and corresponding signal strengths associated with the client device. The network system then determines a telematics vector based on the signal strengths associated with the client device. Based on the location of the client device and the telematics vector associated with the client device, the network system identifies one or more top ranked elevation-aware hotspots. A pickup point recommendation is then presented, by the network system on a user interface on the client device of the user, whereby the pickup point recommendation includes the one or more top ranked elevation-aware hotspots.

Abstract: Systems and methods for generating and presenting an optimized path using sequential location trace clustering is provided. The system receives a request for a transportation service from a client device of a user. The request indicates a destination point (i.e., a pickup location) and is associated with a start point (i.e., a location at a time the user requested the transportation service). Based on the start point and destination point, the system identifies one or more paths between the start point and the destination point, whereby the one or more paths are generated using sequential location trace clustering from previous transportation services involving the start point and the destination point. The system then causes presentation of a path of the one or more paths on a user interface on the client device of the user with which the user can use to navigate to the destination point.

Abstract: Systems and methods for dynamically re-ranking a pickup point are provided. The system receives a request for transportation service from a device of a rider that includes a selected pickup point. In response, the system establishes the transportation service including assigning a driver. Based on detecting that the transportation service is in a pre-pickup state, the system performs a re-rank analysis. The re-rank analysis determines whether an alternative pickup point exceeds the selected pickup point on an objective function by more than a predetermined threshold. The determining is based on a last known location of the rider, a last known location of the driver, and a predicted driver routeline. Responsive to the alternative pickup point exceeding the selected pickup point on the objective function by more than the predetermined threshold, the system causes presentation, on a device of the rider, of a suggestion to change to the alternative pickup point.

Abstract: Systems and methods for optimizing a pickup location are provided. A network system receives a request for transportation service from a device of a rider, whereby the request includes a requested pickup location. Based on the requested pickup location, the network system determines one or more candidate pickup locations that optimize for the pickup location. The determining the one or more candidate pickup locations includes determining an actual location of the rider, accessing index scores associated with the actual location, identifying dwell point and hotspot candidates based on corresponding index scores, and selecting one or more dwell point and hotspot candidates as the one or more candidate pickup locations. The network system then causes presentation of the one or more candidate pickup locations on a user interface on the device of the rider.