Road element sensors and identifiers
Systems and techniques are described for identifying, monitoring, and sharing vehicle information amongst sensors. In some implementations, a system includes a central server and a plurality of sensors. The plurality of sensors are positioned in a fixed location relative to a roadway. Each sensor in the plurality of sensors is configured to: detect vehicles in a first field of view on the roadway. For each detected vehicle, each sensor is configured to identify features of the detected vehicle and perform operations for each feature. The operations include generating feature data representing the feature, generating a unique identification of the detected vehicle from the detected vehicles by concatenating the feature data representing the identified features of the detected vehicle, and adding the unique identification to a list.
1. A system comprising:
a plurality of sensors configured to monitor a roadway of traversing vehicles, the plurality of sensors comprising a first sensor and a second sensor, wherein
the first sensor is configured to:
detect a first vehicle traveling along the roadway;
assign an identifier for the first vehicle;
add the identifier to a list;
transmit the list to the second sensor;
the second sensor is configured to:
receive the list from the first sensor;
detect a second vehicle traveling along the roadway;
generate data of the detected second vehicle;
compare the generated data of the second vehicle to one or more portions of the identifier in the list;
based on the comparison, determine whether the first vehicle matches to the second vehicle;
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the identifier in the list, determine that the first vehicle is the second vehicle.
2. The system of claim 1 , wherein the generated data corresponds to generated features of the detected second vehicle, and the features comprises one or more of: a color of the detected second vehicle, a class of the detected second vehicle, and a volume of the detected second vehicle.
3. The system of claim 1 , wherein the list comprises one or more unique identifiers of detected vehicles in an order as seen by the plurality of sensors, and each of the one or more unique identifiers comprises a hexadecimal value, or a string representation.
4. The system of claim 1 , wherein the second sensor:
based on the comparison, determine whether the first vehicle matches to the second vehicle; and
in response to determining that the generated data of the detected second vehicle does not match to the one or more portions of the identifier in the list, determine that the first vehicle is not the second vehicle.
5. The system of claim 1 , wherein the second sensor:
in response to determining that the first vehicle is not the second vehicle, identify a second identifier in the list;
compare the generated data to one or more portions of the second identifier in the list, wherein the second identifier is ranked below the identifier in the list, and the first sensor is configured to rank the identifiers in the list; and
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the second identifier, determine that the second vehicle has switched positions with the first vehicle while traversing the roadway.
6. The system of claim 1 , wherein the first sensor is configured to detect one or more vehicles in a first field of view and the second sensor is configured to detect the one or more vehicles in a second field of view, and the first field of view and the second field of view (i) juxtapose one another or (ii) overlap one another.
7. The system of claim 6 , wherein the first sensor transmits the list to the second sensor at a rate proportional to the overlapping field of view between the first field of view and the second field of view, wherein the first sensor is configured to determine the rate proportional to the overlapping field of view by:
determining the rate that a detected vehicle moves through the first field of view;
determining a vector of the detected vehicle in the first field of view from the determined rate;
projecting the determined vector to the second field of view of the second sensor; and
determining the rate proportional to the overlapping field of view based on the vector projected to the second field of view.
8. A computer-implemented method comprising:
monitoring, by a plurality of sensors, a roadway of traversing vehicles, wherein the plurality of sensors comprises a first sensor and a second sensor,
detecting, by the first sensor, a first vehicle traveling along the roadway;
assigning, by the first sensor, an identifier for the first vehicle;
adding, by the first sensor, the identifier to a list;
transmitting, by the first sensor, the list to the second sensor;
receiving, by the second sensor, the list from the first sensor;
detecting, by the second sensor, a second vehicle traveling along the roadway;
generating, by the second sensor, data of the detected second vehicle;
comparing, by the second sensor, the generated data of the second vehicle to one or more portions of the identifier in the list;
based on the comparison, determining, by the second sensor, whether the first vehicle matches to the second vehicle; and
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the identifier in the list, determining, by the second sensor, that the first vehicle is the second vehicle.
9. The computer-implemented method of claim 8 , wherein the generated data corresponds to generated features of the detected second vehicle, and the features comprises one or more of: a color of the detected second vehicle, a class of the detected second vehicle, and a volume of the detected second vehicle.
10. The computer-implemented method of claim 8 , wherein the list comprises one or more unique identifiers of detected vehicles in an order as seen by the plurality of sensors, and each of the one or more unique identifiers comprises a hexadecimal value, or a string representation.
11. The computer-implemented method of claim 8 , further comprising:
based on the comparison, determining, by the second sensor, whether the first vehicle matches to the second vehicle; and
in response to determining that the generated data of the detected second vehicle does not match to the one or more portions of the identifier in the list, determining, by the second sensor, that the first vehicle is not the second vehicle.
12. The computer-implemented method of claim 8 , further comprising:
in response to determining that the first vehicle is not the second vehicle, identifying, by the second sensor, a second identifier in the list;
comparing, by the second sensor, the generated data to one or more portions of the second identifier in the list, wherein the second identifier is ranked below the identifier in the list, and the first sensor is configured to rank the identifiers in the list; and
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the second identifier, determining, by the second sensor, that the second vehicle has switched positions with the first vehicle while traversing the roadway.
13. The computer-implemented method of claim 8 , further comprising detecting, by the first sensor, or more vehicles in a first field of view and the second sensor is configured to detect the one or more vehicles in a second field of view, and the first field of view and the second field of view (i) juxtapose one another or (ii) overlap one another.
14. The computer-implemented method of claim 13 , further comprising:
determining, by the first sensor, a rate proportional to the overlapping field of view, wherein the rate is determined by:
determining, by the first sensor, the rate that a detected vehicle moves through the first field of view;
determining, by the first sensor, a vector of the detected vehicle in the first field of view from the determined rate;
projecting, by the first sensor, the determined vector to the second field of view of the second sensor; and
determining, by the first sensor, the rate proportional to the overlapping field of view based on the vector projected to the second field of view; and
transmitting, by the first sensor, the list to the second sensor at the rate proportional to the overlapping field of view between the first field of view and the second field of view.
15. One or more non-transitory machine-readable media storing instructions that, when executed by one or more processing devices, cause the one or more processing devices to perform operations comprising:
monitoring, by a plurality of sensors, a roadway of traversing vehicles, wherein the plurality of sensors comprises a first sensor and a second sensor,
detecting, by the first sensor, a first vehicle traveling along the roadway;
assigning, by the first sensor, an identifier for the first vehicle;
adding, by the first sensor, the identifier to a list;
transmitting, by the first sensor, the list to the second sensor;
receiving, by the second sensor, the list from the first sensor;
detecting, by the second sensor, a second vehicle traveling along the roadway;
generating, by the second sensor, data of the detected second vehicle;
comparing, by the second sensor, the generated data of the second vehicle to one or more portions of the identifier in the list;
based on the comparison, determining, by the second sensor, whether the first vehicle matches to the second vehicle; and
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the identifier in the list, determining, by the second sensor, that the first vehicle is the second vehicle.
16. The non-transitory machine-readable media of claim 15 , wherein the generated data corresponds to generated features of the detected second vehicle, and the features comprises one or more of: a color of the detected second vehicle, a class of the detected second vehicle, and a volume of the detected second vehicle.
17. The non-transitory machine-readable media of claim 15 , wherein the list comprises one or more unique identifiers of detected vehicles in an order as seen by the plurality of sensors, and each of the one or more unique identifiers comprises a hexadecimal value, or a string representation.
18. The non-transitory machine-readable media of claim 15 , further comprising:
based on the comparison, determining, by the second sensor, whether the first vehicle matches to the second vehicle; and
in response to determining that the generated data of the detected second vehicle does not match to the one or more portions of the identifier in the list, determining, by the second sensor, that the first vehicle is not the second vehicle.
19. The non-transitory machine-readable media of claim 15 , further comprising:
in response to determining that the first vehicle is not the second vehicle, identifying, by the second sensor, a second identifier in the list;
comparing, by the second sensor, the generated data to one or more portions of the second identifier in the list, wherein the second identifier is ranked below the identifier in the list, and the first sensor is configured to rank the identifiers in the list; and
in response to determining that the generated data of the detected second vehicle matches to the one or more portions of the second identifier, determining, by the second sensor, that the second vehicle has switched positions with the first vehicle while traversing the roadway.
20. The non-transitory machine-readable media of claim 15 , further comprising detecting, by the first sensor, or more vehicles in a first field of view and the second sensor is configured to detect the one or more vehicles in a second field of view, and the first field of view and the second field of view (i) juxtapose one another or (ii) overlap one another.