The control of signalized intersections using decentralized techniques has received increased attention in recent years. Backpressure (a.k.a. max weight) control, introduced independently by Varaiya (2013) and Wongpironmsarn et al. (2012), sparked this trend, and more recently, Mercader et al. (2020) demonstrated its viability in the real world. Backpressure techniques were originally developed for packet routing in communications networks, and inherit two notable advantages in the context or urban traffic control: (1) They do not require knowledge of traffic demands (exogenous arrival rates). (2) They come with network-wide theoretical guarantees of performance (namely, stability). However, they do come with some limitations from a traffic operations perspective, namely, the necessity of infinite queue sizes and their failure to capture the queues' spatial distribution. An important consequence is that standard backpressure techniques fail to account for spillback dynamics. The talk will discuss the advantage of developing backpressure control using continuum traffic modeling. The method is called Position Weighted Backpressure (PWBP). I will first present the traditional Lyapunov stability framework and show the limitations that PWBP overcomes. I will then present a Lyapunov stability framework based on continuum traffic modeling. The infinite capacities limitation is overcome with a simple modeling trick that I will present. This modeling trick is independent of the dynamics.