Road construction detection systems and methods

1. A method of detecting road construction comprising:

receiving, from a sensor system, sensor data including optical sensor data, relating to an environment associated with a vehicle;

determining, with a processor, that construction-related objects are present within the environment based on the sensor data by applying the optical sensor data to a pre-trained machine-learning model stored within the vehicle;

determining, with a processor, whether a construction zone is present within the environment and whether the construction zone is a travel-impacting construction zone based on the presence of the construction-related objects in the environment and a number, a position, and a type of the construction-related objects;

determining, with a processor, an impact on a route from the construction zone;

classifying, with a processor, the impact on a route from the construction zone as:

a partial lane blockage when the construction zone causes a partial lane blockage, a lane blockage when the construction zone causes a lane closure, and a road blockage when the construction zone causes a blocked road; and

transmitting a geographical location of the construction zone and the classified impact from the construction zone over a network to an external server.

2. The method of claim 1 , further including receiving, at the vehicle, route information associated with a destination, the route information configured to avoid the travel-impacting construction zone.

3. The method of claim 1 , further including transmitting information related to the travel-impacting construction zone over a network to a server.

4. The method of claim 1 , wherein determining that the construction-related objects are present within the environment includes providing the sensor data to an artificial neural network model.

5. The method of claim 4 , wherein the sensor data is provided to a convolutional neural network model.

6. The method of claim 1 , wherein determining that construction-related objects are present within the environment includes determining the presence of at least one of: a traffic cone, a traffic barrier, a traffic barrel, a construction sign, a reflective vest, a construction helmet, an arrow-board trailer, and a piece of construction equipment.

7. The method of claim 1 , wherein the sensor data includes optical sensor data.

8. The method of claim 7 , wherein the sensor data includes lidar sensor data.

9. A system for controlling a vehicle, comprising:

a construction-related object module, including a processor and machine-readable software instructions stored on non-transitory media that, when executed by the processor, are configured to receive sensor data including optical sensor data relating to an environment associated with the vehicle and determine that construction-related objects are present within the environment based on the sensor data by applying the optical sensor data to a pre-trained machine-learning model stored within the vehicle; and

a construction zone determination module, including a processor and machine-readable software instructions stored on non-transitory media that, when executed by the processor, are configured to:

determine whether a construction zone is present within the environment and whether the construction zone is a travel-impacting construction zone based on the presence of the construction-related objects in the environment and a number, a position, and a type of the construction-related objects;

determine an impact on a route from the construction zone;

classify the impact on a route from the construction zone as: a partial lane blockage when the construction zone causes a partial lane blockage, a lane blockage when the construction zone causes a lane closure, and a road blockage when the construction zone causes a blocked road; and

transmit a geographical location of the construction zone and the classified impact from the construction zone over a network to an external server.

10. The system of claim 9 , further including a communication system configured to transmit information related to the travel-impacting construction zone over a network to a server.

11. The system of claim 10 , wherein the construction-related object module includes an artificial neural network model.

12. The system of claim 11 , wherein the artificial neural network model is a convolutional neural network.

13. The system of claim 9 , wherein the construction-related objects includes at least one of: a traffic cone, a traffic barrier, a traffic barrel, a construction sign, a reflective vest, a construction helmet, an arrow-board trailer, and a piece of construction equipment.

14. The system of claim 9 , wherein the sensor data comprises optical sensor data.

15. An autonomous vehicle, comprising:

at least one sensor that provides sensor data, including optical sensor data; and

a controller that, by a processor and based on the sensor data:

receives sensor data relating to an environment associated with a vehicle;

determines that construction-related objects are present within the environment based on the sensor data by applying the optical sensor data to a pre-trained machine-learning model stored within the vehicle;

determines whether a construction zone is present within the environment and whether the construction zone is a travel-impacting construction zone based on the presence of the construction-related objects in the environment and a number, a position, and a type of the construction-related objects;

determines an impact on a route from the construction zone;

classifies the impact on a route from the construction zone as: a partial lane blockage when the construction zone causes a partial lane blockage, a lane blockage when the construction zone causes a lane closure, and a road blockage when the construction zone causes a blocked road; and

transmits a geographical location of the construction zone and the classified impact from the construction zone over a network to an external server.

16. The autonomous vehicle of claim 15 , further including a communication system configured to transmit information related to the travel-impacting construction zone over a network to a server.

17. The autonomous vehicle of claim 16 , further including a navigation system configured to receive, from the server, route information associated with a destination, the route information configured to avoid the travel-impacting construction zone.

18. The autonomous vehicle of claim 15 , wherein the controller implements a convolutional neural network model.

19. The autonomous vehicle of claim 15 , wherein the at least one sensor includes at least one of an optical sensor and a lidar sensor.

20. The autonomous vehicle of claim 15 , wherein the construction-related objects includes at least one of: a traffic cone, a traffic barrier, a traffic barrel, a construction sign, a reflective vest, a construction helmet, an arrow-board trailer, and a piece of construction equipment.