Abstract: A method of determining a user-centric traffic estimation error parameter associated with an estimated road traffic condition that is electronically provided to a user of a device. the method comprises: at a first moment in time, acquiring an estimated travel time for a road segment, the estimated travel time having been computed for the first moment in time; responsive to the device approaching the road segment, displaying an application-generated estimated travel time for the road segment, the application-generated estimated travel time being based on a most recently acquired estimated travel time from the server; responsive to the device departing from the road segment, determining an actual travel time for the road segment; computing the user-centric traffic estimation error parameter based on the application-generated estimated travel time and the actual travel time; and transmitting the user-centric traffic estimation error parameter to the server for adjusting a traffic prediction algorithm.

Abstract: There is disclosed a computer-implemented method for evaluating traffic conditions, the method executable on a server. The method comprises receiving device movement data indicative of moving patterns of the at least some of the plurality of user devices. The method further comprises analyzing the device movement data by: selecting a specific road segment; retrieving at least a first movement pattern associated with a first user travelling the specific road segment and a second movement pattern associated with a second user travelling the specific road segment; and comparing the first movement pattern and the second movement pattern. Responsive to the first movement pattern and the second movement pattern being indicative of there being a disconnect between the first user and the second user entering and existing the specific road segment and proceeding to a same sequential road segment, the method comprises incrementing an overtaking score associated with the second user.

Abstract: There is disclosed a computer-implemented method for evaluating traffic conditions, the method executable on a server. The method comprises receiving device movement data indicative of moving patterns of the at least some of the plurality of user devices. The method further comprises analyzing the device movement data by: selecting a specific road segment; retrieving at least a first movement pattern associated with a first user travelling the specific road segment and a second movement pattern associated with a second user travelling the specific road segment; and comparing the first movement pattern and the second movement pattern. Responsive to the first movement pattern and the second movement pattern being indicative of there being a disconnect between the first user and the second user entering and existing the specific road segment and proceeding to a same sequential road segment, the method comprises incrementing an overtaking score associated with the second user.

Abstract: A method of determining a user-centric traffic estimation error parameter associated with an estimated road traffic condition that is electronically provided to a user of a device. the method comprises: at a first moment in time, acquiring an estimated travel time for a road segment, the estimated travel time having been computed for the first moment in time; responsive to the device approaching the road segment, displaying an application-generated estimated travel time for the road segment, the application-generated estimated travel time being based on a most recently acquired estimated travel time from the server; responsive to the device departing from the road segment, determining an actual travel time for the road segment; computing the user-centric traffic estimation error parameter based on the application-generated estimated travel time and the actual travel time; and transmitting the user-centric traffic estimation error parameter to the server for adjusting a traffic prediction algorithm.

Abstract: Disclosed are systems and methods for automatically moderating communications using hierarchical and nested whitelists. An example method comprises receiving a message including one or more words; determining whether the words of the message match any words in a first whitelist; determining whether the words of the message match any words in a second whitelist if it is determined that at least one of the words of the message does not match any of the words in the first whitelist; calculating an unacceptability value if it is determined that all of the words of the message match any of the words in the second whitelist; and publishing the message if the unacceptability value is below a predetermined threshold.