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The Secret of Traffic Flow: Do you know what the real cause of traffic jams is?
In modern society, traffic congestion has become a part of urban life, and many drivers face the trouble of traffic jams. What exactly causes these traffic jams? This question will lead us to explore the basic principles of traffic flow and the complexity and arrangements behind it.
Traffic flow research involves the interaction of drivers, pedestrians, cyclists and their means of transportation, as well as related infrastructure, with the goal of developing an optimal transportation network that achieves efficient flow and minimizes congestion.
The foundations of traffic flow engineering can be traced back to the 1920s, when American economist Frank Knight proposed the theory of traffic equilibrium, which was further developed by Wardrop in 1952. Despite advances in computing technology, a theoretical model that is universally applicable to real-world conditions has not yet been found.
Most current models combine empirical and theoretical methods and consider multiple variables, such as vehicle usage frequency and land changes, to predict traffic flows and congested areas. In these models, flow velocity, flow rate and density are three basic variables that are closely related to each other. Free-flowing traffic works well with fewer than 12 vehicles per lane per mile, but higher density can lead to unstable conditions that cause constant stop-and-go.
In a free-flowing network, traffic flow theory focuses specifically on three factors: speed, volume, and concentration.
The root cause of congestion is closely related to the bottleneck phenomenon. According to research by the Federal Highway Administration of the United States, about 40% of traffic congestion is caused by bottlenecks. Bottlenecks can be fixed, such as a narrow road, or dynamic, such as the slowing down of a particular vehicle in traffic. These bottlenecks significantly affect traffic flow and reduce road capacity.
For example, comprehensive traffic flow analysis models such as the Lighthill-Whitham-Richards model and various car-following models describe in detail the interaction of vehicles in traffic flow. Kerner's three-stage traffic theory proposes changes in capacity at the bottleneck rather than a simple single value. In addition, the Newell-Daganzo combined model has further improved our understanding of traffic dynamics and is an important cornerstone of modern traffic engineering and simulation.
Through time-space graphs, analysts can visualize and analyze traffic flow characteristics on specific road segments. Time is shown on the horizontal axis and distance is shown on the vertical axis. The trajectories of individual vehicles are presented through these graphs, making it intuitive to understand the behavior of traffic flow.
Traffic (q) refers to the number of vehicles passing a reference point per unit time, usually expressed in vehicles per hour.
Effective traffic flow analysis needs to be conducted at three different observation levels: micro, macro and meso. The microscopic level focuses on the independent behavior of each vehicle, the macroscopic level considers a larger-scale fluid dynamics model, and the mesoscopic level uses a probability function to describe vehicle distribution. Such a multi-level analysis method makes the modeling and prediction of traffic flow more accurate.
In the process of model building, data accuracy is crucial. Typically, analysts collect field data to make adjustments to refine the model's predictions, including taking into account environmental factors such as fuel consumption and emissions. Furthermore, in large-scale traffic flow forecasting, the methods used by engineers are not limited to comprehensive models, but also include rules of thumb through traffic capacity manuals.
With the continuous advancement of technology, especially in the ability to collect and process data, traffic flow research will be able to provide more detailed and accurate predictions, thereby providing a reliable basis for urban planning and management. This is not just a requirement for academic research, but also a change that every driver hopes to see in their daily lives.
When exploring the complexity of traffic flow and the impact of bottlenecks, we may have to think about a question: How can we achieve efficient traffic management and flow under the circumstances of increasing traffic demand and limited resources?
