top-and-go traffic is a frequently observed phenomenon in congested highway traffic, but it has not been accurately modeled in existing traffic models. Car-following models based on kinematic flow theory cannot model stop-and-go traffic. Other approach assumed traffic states deviating from the equilibrium curve in the fundamental diagram, and the transitions between them, but no explanation was provided on the reason for the existence of different states. There is a need to understand the mechanism of stop-and-go traffic in terms of generation, propaga-tion and dissipation in order to accurately model traffic dynamics. We propose an asymmetric traffic theory and explain the stop-and-go traffic phenomenon in light of the developed theory. The proposed theory is verified using individual vehicle trajectories from two freeway sites in California, US, collected as part of the Next Generation Simulation (NGSIM) project.1. Introduction Stop-and-go traffic is a frequently observed phenomenon in congested traffic and its understanding and modeling is important for modeling the formation and propagation of traffic jams and estimating congestion impacts. However, the mechanism of the generation and evolution of the stop-and-go traffic in time-space have not been well understood yet. This lack of understanding on traffic phenomenon is due to data limitations and theory deficiency. In order to reveal the detail mechanism of stop-and-go traffic, large quantities of microscopic data on individual vehicle trajectories on congested freeways are required. But, acquisition and analyses of sufficient amount of trajectory data is very expensive and time consuming. Recently, the NGSIM (Next Generation SIMulation, 2006) database became available which provides a unique opportunity to study microscopic driver behavior and develop improved traffic flow models grounded on experimental ob-servations. The traditional macroscopic traffic flow theory of LWR (Lighthill and Whitham 1955; Richards 1956) has shown good agreement with experimental ob-servations in congested traffic at a macroscopic level, but it cannot satisfactorily explain the mechanism of stop-and-go traffic. Recently, Nagel and Nelson (2005)