US 12,230,128 B2
Dynamic arrangement of vehicles based on load capacity of smart crossing
Sudheesh S. Kairali, Kozhikode (IN); and Sarbajit K. Rakshit, Kolkata (IN)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Dec. 1, 2022, as Appl. No. 18/060,623.
Prior Publication US 2024/0185710 A1, Jun. 6, 2024
Int. Cl. G08G 1/01 (2006.01); G06F 30/20 (2020.01); G06F 113/00 (2020.01)
CPC G08G 1/0137 (2013.01) [G06F 30/20 (2020.01); G06F 2113/00 (2020.01)] 17 Claims
OG exemplary drawing
 
1. A computer-based method of dynamically arranging vehicles on a smart crossing, the method comprising:
receiving data relating to a maximum carrying capacity of a smart crossing having one or more sensors measuring one or more safety parameters of the smart crossing;
predicting a current load carrying capacity of the smart crossing based on the maximum carrying capacity and the one or more safety parameters;
identifying a number of vehicles on a roadway traveling towards the smart crossing within a pre-defined distance of the smart crossing, wherein the pre-defined distance is a maximum distance away from the smart crossing on a roadway for which the number of vehicles is identified;
identifying one or more specifications and a current arrangement of each vehicle within the pre-defined distance of the smart crossing;
executing a digital twin simulation of a digital twin model of each vehicle within the pre-defined distance driving across the smart crossing in accordance with the one or more specifications and the current arrangement, wherein the digital twin model of each vehicle within the pre-defined distance has identical specifications and an identical current arrangement to that of a corresponding vehicle traveling on the roadway;
determining whether the current load carrying capacity of the smart crossing is exceeded based on the executed digital twin simulation;
in response to determining the current load carrying capacity is exceeded, assigning a priority level to each vehicle within the pre-defined distance based on a classification of each vehicle;
predicting a modification of the current arrangement of each vehicle based on the priority level of each vehicle and the one or more specifications; and
automatically deploying each vehicle to the smart crossing consistent with the modification of the current arrangement of each vehicle.