Xiang Liu

A method, system, and apparatus for estimation of a count of mobile devices include receiving one or more probe data points including a location and a session identifier, constructing a trajectory including the one or more probe data points having a same session identifier, constructing a trajectory including the one or more probe data points having a same session identifier and generated by one mobile device of the plurality of the mobile devices, dividing the trajectory area by an area of the… Show more

A method, system, and apparatus for estimation of a count of mobile devices include receiving one or more probe data points including a location and a session identifier, constructing a trajectory including the one or more probe data points having a same session identifier, constructing a trajectory including the one or more probe data points having a same session identifier and generated by one mobile device of the plurality of the mobile devices, dividing the trajectory area by an area of the observation area, and estimating the count of mobile devices in the observation area from at least the normalized trajectory area. A path of the trajectory is based on the location of the one or more probe data points expanding the path of the trajectory by a radius where a result of the expanding is a trajectory area. A result of the dividing is a first normalized trajectory area. Show less

A method, system, and apparatus for estimation of a number of mobile devices include receiving one or more probe data points including a location, a session identifier, and a timestamp, constructing a trajectory including the one or more probe data points having a same session identifier, calculating a trajectory duration for the trajectory based on the timestamps of the one or more probe data points, calculating a normalized trajectory from the trajectory duration and a predetermined… Show more

A method, system, and apparatus for estimation of a number of mobile devices include receiving one or more probe data points including a location, a session identifier, and a timestamp, constructing a trajectory including the one or more probe data points having a same session identifier, calculating a trajectory duration for the trajectory based on the timestamps of the one or more probe data points, calculating a normalized trajectory from the trajectory duration and a predetermined observation duration, and estimating the number of mobile devices from at least the normalized trajectory. A path of the trajectory is based on the location of the one or more probe data points. Show less

A method, system, and apparatus for estimation of a number of mobile devices include receiving one or more probe data points including a location, a session identifier, and a timestamp, constructing a trajectory including the one or more probe data points having a same session identifier, calculating a trajectory duration for the trajectory based on the timestamps of the one or more probe data points, calculating a normalized trajectory from the trajectory duration and a predetermined… Show more

A method, system, and apparatus for estimation of a number of mobile devices include receiving one or more probe data points including a location, a session identifier, and a timestamp, constructing a trajectory including the one or more probe data points having a same session identifier, calculating a trajectory duration for the trajectory based on the timestamps of the one or more probe data points, calculating a normalized trajectory from the trajectory duration and a predetermined observation duration, and estimating the number of mobile devices from at least the normalized trajectory. A path of the trajectory is based on the location of the one or more probe data points. Show less

An approach is provided for estimation of waiting time to park. The approach involves processing parking data from a parking area to determine a probability that all parking spots in the parking area are occupied. The parking data is collected from one or more parking sensors. The approach also involves building a remaining parking duration model for a plurality of cars parked in said all parking spots based on the parking data. The approach further involves calculating an estimated conditional… Show more

An approach is provided for estimation of waiting time to park. The approach involves processing parking data from a parking area to determine a probability that all parking spots in the parking area are occupied. The parking data is collected from one or more parking sensors. The approach also involves building a remaining parking duration model for a plurality of cars parked in said all parking spots based on the parking data. The approach further involves calculating an estimated conditional waiting time to park in the parking area based on the remaining parking duration model. The approach further involves calculating an estimated unconditional waiting time to park in the parking area based on the blocking probability and the conditional waiting time to park. Show less

An approach is provided for measuring parking duration from anonymized data. The approach involves receiving parking data indicating anonymized park in and park out events from connected vehicles. The approach also involves performing a first filtering of the parking data to remove the park out events that occur within a time interval and before a first park in event occurring within the time interval, and to remove the park in events that occur within the time interval and after a last park… Show more

An approach is provided for measuring parking duration from anonymized data. The approach involves receiving parking data indicating anonymized park in and park out events from connected vehicles. The approach also involves performing a first filtering of the parking data to remove the park out events that occur within a time interval and before a first park in event occurring within the time interval, and to remove the park in events that occur within the time interval and after a last park out event occurring within the time interval. The approach further involves performing a second filtering of the parking data remaining after the first filtering to remove park in events or park out events so that the numbers of park in and park out events are balanced. The approach then involves calculating parking duration data from the park in and park out events remaining after the second filtering. Show less

A method at a mobile device, the method comprising: receiving one or more data symbols; determining reduced symbols for each of the data symbols, the reduced symbols corresponding to each of at least two orthogonal components of the data symbols; and, storing the reduced symbols in a symbol buffer.

A method at a mobile device, the method comprising: receiving one or more data symbols; determining reduced symbols for each of the data symbols, the reduced symbols corresponding to each of at least two orthogonal components of the data symbols; and, storing the reduced symbols in a symbol buffer.

There are disclosed systems and methods for computing a reliability value for a bit of a received symbol value y associated with a constellation. In one embodiment, the method comprises computing the reliability value by obtaining a first minimum distance value, the first minimum distance value being a function of an absolute magnitude of an initial value associated with the bit, and combining the first minimum distance value with a second minimum distance value, the second minimum distance… Show more

There are disclosed systems and methods for computing a reliability value for a bit of a received symbol value y associated with a constellation. In one embodiment, the method comprises computing the reliability value by obtaining a first minimum distance value, the first minimum distance value being a function of an absolute magnitude of an initial value associated with the bit, and combining the first minimum distance value with a second minimum distance value, the second minimum distance value being a function of a distance between the received symbol value y and a symbol xb̂ in the constellation corresponding to a most likely pattern of bits transmitted given the received symbol value y. Show less

There are disclosed systems and methods for computing a reliability value for a bit of a received symbol value y associated with a constellation. In one embodiment, the method comprises computing the reliability value by obtaining a first minimum distance value, the first minimum distance value being a function of an absolute magnitude of an initial value associated with the bit, and combining the first minimum distance value with a second minimum distance value, the second minimum distance… Show more

There are disclosed systems and methods for computing a reliability value for a bit of a received symbol value y associated with a constellation. In one embodiment, the method comprises computing the reliability value by obtaining a first minimum distance value, the first minimum distance value being a function of an absolute magnitude of an initial value associated with the bit, and combining the first minimum distance value with a second minimum distance value, the second minimum distance value being a function of a distance between the received symbol value y and a symbol x_b in the constellation corresponding to a most likely pattern of bits transmitted given the received symbol value y. Show less