Simulation technology is increasingly being used within the automotive space, saving time, money and allowing for simulated repeats of real-world scenarios.

New York City’s mass transit system is central to the region’s economic vitality; congestion pricing can help revitalize it.

We design a cost function and then use Hamilton-Jacobi-Bellman equation to derive an optimal control law that uses real-time information to determine an optimal tolling price. Simulations are ...

To alleviates these problems, we introduce DCQCN, an end-to-end congestion control scheme for RoCEv2. To optimize DCQCN performance, we build a fluid model, and provide guidelines for tuning switch ...

Deep reinforcement learning (DRL) has been used in congestion control algorithms (CCAs) for its ability to adapt to different network environments. However, its effectiveness is often hindered by the ...