Adaptative Optimal Control of Nonlinear Systems Simulation to Support Hazardous Materials Traffic Management

Deep learning and mobile control system for hazardous materials transportation

“…The simulations have used the same configuration over two scenarios, considering The first set of simulations considers a small difference between drivers' behavior, 15 so there are few shockwaves and, even though the 150-min obstruction has a big queue formation there was time to recover it, as presented in Figure 15. The impact caused by vehicle congestion is calculated according to half of the product between the queue time and the maximum number of vehicles in a queue.…”

“…Otherwise, a relation lower than one means stability in the system and recovery time. The impact caused by vehicle congestion is calculated according to the area of the queue function, called total delay, [14][15][16][17] presented in Figure 1. The total delay is half of the product of the maximum number of vehicles in a queue, and the total queuing time.…”

“…The first set of simulations considers a small difference between drivers' behavior, 15 so there are few shockwaves and, even though the 150‐min obstruction has a big queue formation there was time to recover it, as presented in Figure 15.…”

“…The second set of simulations considers a high difference in drivers' behavior, 15 so it is possible to conclude that the system is unstable in 150‐min obstruction and recovers in the optimized scenario with 93‐min obstruction, so the system is shown to be stronger, as presented in Figure 17.…”