Apparatus and methods determining a newly established vehicle-related rule within an area
An apparatus, method and computer program product are provided for determining a newly established vehicle-related rule within an area. In one example, the apparatus receives sensor data indicating attributes of an area for a first period. The attributes indicate a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof. The apparatus compares the sensor data to historical data associated with the area. The historical data indicate the attributes of the area for one or more second periods preceding the first period. Based on comparison of the sensor data and the historical data, the apparatus determines a likelihood of a vehicle-related rule established for the area, where the vehicle-related rule did not exist during the one or more second periods. The apparatus causes a notification indicating the likelihood at a user interface.
1 . An apparatus comprising at least one processor and at least one non-transitory memory including computer program code instructions, the computer program code instructions configured to, when executed, cause the apparatus to:
receive sensor data indicating attributes of an area for a first period, the attributes indicating a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof;
compare the sensor data to historical data associated with the area, the historical data indicating the attributes of the area for one or more second periods preceding the first period,
based on comparison of the sensor data and the historical data, determine a likelihood of a vehicle-related rule established for the area, wherein the vehicle-related rule did not exist during the one or more second periods;
responsive to the number of vehicle-related tickets issued within the area for the first period exceeding the number of vehicle-related tickets issued within the area for each of the one or more second periods, increase the likelihood; and
cause a notification indicating the likelihood at a user interface.
2 . The apparatus of claim 1 , wherein, to determine the likelihood, the computer program code instructions are further configured to, when executed, cause the apparatus to:
determine an average number of vehicle-related tickets issued within the area based on the historical data;
compare the average number of vehicle-related tickets to the number of vehicle-related tickets issued within the area for the first period;
responsive to the number of vehicle-related tickets issued within the area for the first period exceeding the average number of vehicle-related tickets, increase the likelihood.
3 . The apparatus of claim 1 , wherein the computer program code instructions are further configured to, when executed, cause the apparatus to:
based on the sensor data and the historical data, determine a type of vehicle-related rule established for the area; and
cause an additional notification indicating the type of vehicle-related rule at the user interface.
4 . The apparatus of claim 1 , wherein the computer program code instructions are further configured to, when executed, cause the apparatus to:
based on the sensor data, determine a spatial extent of which the vehicle-related rule is applied within the area; and
cause an additional notification indicating the spatial extent at the user interface.
5 . The apparatus of claim 1 , wherein the attributes further indicate, for each road portion within the area: (i) a road type; (ii) a functional class; (iii) a number of lanes; (iv) a presence of one or more bike lanes; (v) road dimensions; (vii) one or more points-of-interests (POIs) associated with said road portion; (viii) one or more road markings; (ix) one or more road signs associated with said road portion; or (x) a combination thereof.
6 . A non-transitory computer-readable storage medium having computer program code instructions stored therein, the computer program code instructions, when executed by at least one processor, cause the at least one processor to:
receive sensor data indicating attributes of an area for a first period, the attributes indicating a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof;
compare the sensor data to historical data associated with the area, the historical data indicating the attributes of the area for one or more second periods preceding the first period,
based on comparison of the sensor data and the historical data, determine a likelihood of a vehicle-related rule established for the area, wherein the vehicle-related rule did not exist during the one or more second periods;
responsive to the number of vehicle-related tickets issued within the area for the first period exceeding the number of vehicle-related tickets issued within the area for each of the one or more second periods, increase the likelihood; and
cause a notification indicating the likelihood at a user interface.
7 . The non-transitory computer-readable storage medium of claim 6 , to determine the likelihood, the computer program code instructions, when executed by the at least one processor, cause the at least one processor to:
determine an average number of vehicle-related tickets issued within the area based on the historical data;
compare the average number of vehicle-related tickets to the number of vehicle-related tickets issued within the area for the first period;
responsive to the number of vehicle-related tickets issued within the area for the first period exceeding the average number of vehicle-related tickets, increase the likelihood.
8 . The non-transitory computer-readable storage medium of claim 6 , to determine the likelihood, the computer program code instructions, when executed by the at least one processor, cause the at least one processor to:
determine one or more patterns of vehicle parking orientations within the area based on the historical data;
compare parking orientations of all vehicles within the area for the first period to the one or more patterns of vehicle parking orientations;
responsive to the parking orientations of all vehicles within the area for the first period deviating from the one or more patterns of vehicle parking orientations, increase the likelihood.
9 . The non-transitory computer-readable storage medium of claim 6 , the computer program code instructions, when executed by the at least one processor, cause the at least one processor to:
based on the sensor data and the historical data, determine a type of vehicle-related rule established for the area; and
cause an additional notification indicating the type of vehicle-related rule at the user interface.
10 . The non-transitory computer-readable storage medium of claim 6 , the computer program code instructions, when executed by the at least one processor, cause the at least one processor to:
based on the sensor data, determine a spatial extent of which the vehicle-related rule is applied within the area; and
cause an additional notification indicating the spatial extent at the user interface.
11 . The non-transitory computer-readable storage medium of claim 6 , wherein the attributes further indicate, for each road portion within the area: (i) a road type; (ii) a functional class; (iii) a number of lanes; (iv) a presence of one or more bike lanes; (v) road dimensions; (vii) one or more points-of-interests (POIs) associated with said road portion; (viii) one or more road markings; (ix) one or more road signs associated with said road portion; or (x) a combination thereof.
12 . An apparatus comprising at least one processor and at least one non-transitory memory including computer program code instructions, the computer program code instructions configured to, when executed, cause the apparatus to:
receive sensor data indicating attributes of an area for a first period, the attributes indicating a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof;
compare the sensor data to historical data associated with the area, the historical data indicating the attributes of the area for one or more second periods preceding the first period,
based on comparison of the sensor data and the historical data, determine a likelihood of a vehicle-related rule established for the area, wherein the vehicle-related rule did not exist during the one or more second periods;
determine one or more patterns of vehicle parking orientations within the area based on the historical data;
compare parking orientations of all vehicles within the area for the first period to the one or more patterns of vehicle parking orientations;
responsive to the parking orientations of all vehicles within the area for the first period deviating from the one or more patterns of vehicle parking orientations, increase the likelihood; and
cause a notification indicating the likelihood at a user interface.