Macroscopic models are popularly used to describe and predict traffic conditions on roads. They provide an aggregate view of a stream or group of vehicles. Macroscopic models can be broadly divided into traffic relationships and traffic flow models. The former deals with the steady-state relationship between two of the three fundamental variables - flows, density, and speed. The latter deals with how the traffic states propagate in the time-space domain. Traditionally, macroscopic traffic flow models are developed for homogeneous and lane-based traffic conditions. In 1935, Greenshields proposed a fundamental relation that is linear in the speed-density plane. Since then, many other shapes (exponential, logarithmic, etc.) of fundamental relations have been proposed. The Daganzo (1994) fundamental relation is probably the most widespread and realistic for highways. Modeling non-lane-based heterogeneous traffic is challenging compared to lane-based homogeneous traffic. The stream has vehicle class heterogeneity, and the vehicles do not follow a lane-based movement. A systematic understanding of the fundamental relationships between traffic flow variables and traffic state propagation models for heterogeneous traffic is essential to manage these traffic systems effectively. Over the year, researchers have developed multi-class models that give steady-state relationships between states of varying vehicle classes to accommodate heterogeneous classes. Similarly, the traffic flow models can be classified as first-order (e.g., LWR) and higher-order models (e.g., Payne-type). A major limitation of the first-order model is that these are not able to capture hysteresis, two-capacity, phantom jam, and stop-and-go like traffic phenomena. Higher-order models incorporate relaxation and driver anticipation effects and address most of the limitations of first-order models (e.g., traffic hysteresis, negative wave speed, etc.). Thus, these models are different from the LWR model with an additional equation on vehicle speed. However, the major criticism of higher-order models is failed to produce anisotropy conditions and negative speed phenomena. This seminar emphasizes the mathematical formulations, assumptions, strengths, and limitations of these models.