Method for predicting channel load
A method of a first transportation vehicle for predicting channel load. The first transportation vehicle predicts a critical area with channel congestion of at least one communication channel, determines a propagation trajectory of at least one second transportation vehicle and compares the propagation trajectory of the at least one second transportation vehicle and the critical area. Based on the comparison, the first transportation vehicle then selectively transmits a message having information on the critical area to at least one second transportation vehicle. Also disclosed is a transportation vehicle for performing the method and a computer program having instructions for performing the method.
1. A method for a first transportation vehicle predicting communication channel load and for selectively sharing the predicted communication channel load with other transportation vehicles, the method comprising:
predicting a geographic area as a critical area having predicted channel congestion of at least one communication channel based on determining a number of transportation vehicles in the area during a certain time window;
determining propagation trajectory information of at least one second transportation vehicle;
comparing the propagation trajectory information of the at least one second transportation vehicle to the critical area to predict proximity of the at least one second transportation vehicle to the critical area within the time window; and
selectively transmitting a message comprising information about the critical area to the at least one second transportation vehicle based on the comparison so as to inform only transportation vehicles that drive approach the predicted critical area during the time window about the predicted channel congestion.
2. The method of claim 1 , wherein the predicted channel congestion of the at least one communication channel corresponds to channel quality information (CQI) below a predetermined first threshold and/or a channel load above a predetermined second threshold.
3. The method of claim 1 , wherein the predicting of the critical area comprises determining the geographic area as a high density area containing more than a predetermined number of transportation vehicles.
4. The method of claim 3 , wherein the predicting the high density area comprises predicting traffic flow data associated with a plurality of second transportation vehicles including the at least one second transportation vehicle.
5. The method of claim 4 , wherein the traffic flow data prediction is based on trajectory information of the plurality of second transportation vehicles obtained via sensor readings of the first transportation vehicle or based on at least one message transmitted by one of the plurality of second transportation vehicles received by the first transportation vehicle.
6. The method of claim 3 , wherein the high density area is determined based on road information and/or traffic information obtained by the first transportation vehicle.
7. The method of claim 6 , wherein the road information is obtained based on sensor readings of the first transportation vehicle and/or comprises static information related to the geographic area.
8. The method of claim 6 , wherein the traffic information is obtained based on sensor readings of the first transportation vehicle, and/or is obtained from at least one message received by the first transportation vehicle, and/or comprises dynamic information related to the geographic area.
9. The method of claim 3 , wherein the high density area is defined by a geographic coordinate and an area around the geographic coordinate, and/or by an identifier of at least one second transportation vehicle associated with the high density area.
10. The method of claim 1 , wherein the predicting the critical area comprises determining channel load in the area based on a predetermined channel load per transportation vehicle located in the geographic area.
11. The method of claim 10 , wherein the channel load per transportation vehicle is determined based on a vehicle class and/or on a channel usage history of the particular transportation vehicle.
12. The method of claim 1 , further comprising determining whether the propagation trajectory information of the at least one second transportation vehicle indicates a presence in the critical area at a time of criticality, wherein the selective transmission of the message comprising information about the critical area to the at least one second transportation vehicle only transmits the message to at least one second transportation vehicle present in the critical area at a time of criticality, thereby not transmitting the message to at least one second transportation vehicle not present in the critical area at a time of criticality.
13. The method of claim 1 , wherein the message is a shared channel quality (SCQ) message or a cooperative communication message (CCM).
14. The method of claim 1 , wherein the prediction of a geographic area as a critical area includes using a continuity equation to take into consideration a total number of transportation vehicles associated with the geographic area and time window based on an inflow and an outflow of transportation vehicles.
15. The method of claim 1 , wherein the propagation trajectory information is obtained via sensor readings of the first transportation vehicle.
16. The method of claim 15 , wherein the propagation trajectory information includes velocities and propagation directions of second transportation vehicles for use in determining traffic flow data associated with the second transportation vehicles.
17. A transportation vehicle comprising:
a communication module configured to communicate with another transportation vehicle and with a station of a communication network;
a plurality of first sensors configured to detect a propagation trajectory of another transportation vehicle; and
a control unit configured to control prediction of communication channel load and selective sharing of the predicted communication channel load with other transportation vehicles by:
prediction of a geographic area as a critical area having predicted channel congestion of at least one communication channel based on determination of a number of transportation vehicles in the area during a certain time window,
determination of propagation trajectory information of at least one second transportation vehicle,
comparison of the propagation trajectory information of the at least one second transportation vehicle to the critical area to predict proximity of the at least one second transportation vehicle to the critical area within the time window, and
selective transmission of a message comprising information about the critical area to the at least one second transportation vehicle based on the comparison so as to inform only transportation vehicles that drive approach the predicted critical area during the time window about the predicted channel congestion.
18. The transportation vehicle of claim 17 , wherein the prediction of a geographic area as a critical area includes using a continuity equation to take into consideration a total number of transportation vehicles associated with the geographic area and time window based on an inflow and an outflow of transportation vehicles.
19. The transportation vehicle of claim 17 , wherein the propagation trajectory information is obtained via sensor readings of the first transportation vehicle.
20. The transportation vehicle of claim 19 , wherein the propagation trajectory information includes velocities and propagation directions of second transportation vehicles for use in determining traffic flow data associated with the second transportation vehicles.
21. A non-transitory computer readable medium including a computer program comprising instructions which, when the program is executed by a control unit of a transportation vehicle, cause the control unit to predict channel load for a first transportation vehicle and selectively share the predicted communication channel load with other transportation vehicles by:
predicting a geographic area as a critical area having predicted channel congestion of at least one communication channel based on determining a number of transportation vehicles in the area during a certain time window;
determining propagation trajectory information of at least one second transportation vehicle;
comparing the propagation trajectory information of the at least one second transportation vehicle to the critical area to predict proximity of the at least one second transportation vehicle to the critical area within the time window; and
selectively transmitting a message comprising information about the critical area to the at least one second transportation vehicle based on the comparison so as to inform only transportation vehicles that drive approach the predicted critical area during the time window about the predicted channel congestion.
22. The transportation vehicle of claim 21 , wherein the predicted channel congestion of the at least one communication channel corresponds to channel quality information (CQI) below a predetermined first threshold and/or a channel load above a predetermined second threshold.
23. The non-transitory computer readable medium of claim 22 , wherein the predicted channel congestion of the at least one communication channel corresponds to channel quality information (CQI) below a predetermined first threshold and/or a channel load above a predetermined second threshold.
24. The non-transitory computer readable medium of claim 22 , wherein the predicting of the critical area comprises determining the geographic area as a high density area containing more than a predetermined number of transportation vehicles.
25. The non-transitory computer readable medium of claim 22 , wherein the prediction of a geographic area as a critical area includes using a continuity equation to take into consideration a total number of transportation vehicles associated with the geographic area and time window based on an inflow and an outflow of transportation vehicles.
26. The non-transitory computer readable medium of claim 22 , wherein the propagation trajectory information is obtained via sensor readings of the first transportation vehicle.
27. The non-transitory computer readable medium of claim 26 , wherein the propagation trajectory information includes velocities and propagation directions of second transportation vehicles for use in determining traffic flow data associated with the second transportation vehicles.
28. The transportation vehicle of claim 21 , wherein the predicting of the critical area comprises determining the geographic area as a high density area containing more than a predetermined number of transportation vehicles.