question: How does traffic happen on highways?
comment: A single car changing lanes at the wrong time or breaking too hard could cause a traffic jam as the cars behind also need to brake and it causes a chain reaction. [Here's a great GIF]( URL_0 ) explaining how it happens. If you want to learn more about it, take a look at [this video]( URL_1 ) by CGP Grey on Youtube.
passages: Section::::Enterprises.
   Section::::Basic statements.:Speed-flow.
   Section::::History.
   This process is best explained by an example. Let's say that someone in Wisconsin wants to send a birthday greeting to Aunt Mary in California. They telephone their local ham friend and give him the message.
  
  BULLET::::- At 6:30 local time, the Wisconsin ham attends ("checks into") the Wisconsin "Section" net. One station there has been designated to accept all outgoing messages, and Aunt Mary's message is sent to that station.
   Section::::History.
   Traffic is formally organized in many jurisdictions, with marked lanes, junctions, intersections, interchanges, traffic signals, or signs. Traffic is often classified by type: heavy motor vehicle (e.g., car, truck), other vehicle (e.g., moped, bicycle), and pedestrian. Different classes may share speed limits and easement, or may be segregated. Some jurisdictions may have very detailed and complex rules of the road while others rely more on drivers' common sense and willingness to cooperate.
   Section::::Plot.
   Section::::In the United States.:In Washington State.:Hard shoulder running and junction control.
   Section::::Traffic assignment.:Time delay.:Reactive Time Delay.
   Section::::Traffic stream properties.:Stationary traffic.
   Section::::Traffic systems.
   BULLET::::- Case II:
   The method of modeling traffic flow at macroscopic level originated under an assumption that traffic streams as a whole are comparable to fluid streams. The first major step in macroscopic modeling of traffic was taken by Lighthill and Whitham in 1955, when they indexed the comparability of ‘traffic flow on long crowded roads’ with ‘flood movements in long rivers’. A year later, Richards (1956) complemented the idea with the introduction of ‘shock-waves on the highway’, completing the so-called LWR model. 
   Section::::Randomization.
   However, calculations about congested networks are more complex and rely more on empirical studies and extrapolations from actual road counts. Because these are often urban or suburban in nature, other factors (such as road-user safety and environmental considerations) also influence the optimum conditions.
  
  There are that are qualitatively the same for different highways in different countries, measured during years of traffic observations. Some of these common features of traffic congestion define synchronized flow and wide moving jam traffic phases of congested traffic in Kerner’s three-phase traffic theory of traffic flow.
  
  Section::::Single vehicle dynamics.
   Section::::Methods of analysis.
  
  Analysts approach the problem in three main ways, corresponding to the three main scales of observation in physics:
  
  BULLET::::- Microscopic scale: At the most basic level, every vehicle is considered as an individual. An equation can be written for each, usually an ordinary differential equation (ODE). Cellular automation models can also be used, where the road is divided into cells, each of which contains a moving car, or is empty. The Nagel–Schreckenberg model is a simple example of such a model. As the cars interact it can model collective phenomena such as traffic jams.
   Traffic mix
  
  Traffic mix is a traffic model in telecommunication engineering and teletraffic theory.
  
  Section::::Definitions.
   In measured traffic data, have been found that are qualitatively the same for different highways in different countries. Some of these common features distinguish the wide moving jam and synchronized flow phases of congested traffic in Kerner's three-phase traffic theory.
  
  Section::::Congested traffic.:Rush hour.
  
  During business days in most major cities, traffic congestion reaches great intensity at predictable times of the day due to the large number of vehicles using the road at the same time. This phenomenon is called "rush hour" or "peak hour", although the period of high traffic intensity often exceeds one hour.
  
  Section::::Congestion mitigation.
   Traffic behaves in a complex and nonlinear way, depending on the interactions of a large number of vehicles. Due to the individual reactions of human drivers, vehicles do not interact simply following the laws of mechanics, but rather display cluster formation and shock wave propagation, both forward and backward, depending on vehicle density. Some mathematical models of traffic flow use a vertical queue assumption, in which the vehicles along a congested link do not spill back along the length of the link.
   Traffic flow
  
  In mathematics and transportation engineering, traffic flow is the study of interactions between travellers (including pedestrians, cyclists, drivers, and their vehicles) and infrastructure (including highways, signage, and traffic control devices), with the aim of understanding and developing an optimal transport network with efficient movement of traffic and minimal traffic congestion problems.
  
  Section::::History.
  
  Attempts to produce a mathematical theory of traffic flow date back to the 1920s, when Frank Knight first produced an analysis of traffic equilibrium, which was refined into Wardrop's first and second principles of equilibrium in 1952.
   State A represents normal approaching traffic flow, again at speed v. State U, with flowrate q, corresponds to the queuing upstream of the truck. On the fundamental diagram, vehicle speed v is slower than v. But once drivers have navigated around the truck, they can again speed up and transition to downstream state D. While this state travels at free flow, the vehicle density is less because fewer vehicles get around the bottleneck.
   There are three main variables to visualize a traffic stream: speed (v), density (indicated k; the number of vehicles per unit of space), and flow (indicated q; the number of vehicles per unit of time).
  
  Section::::Traffic stream properties.:Speed.
  
  Speed is the distance covered per unit time. One cannot track the speed of every vehicle; so, in practice, average speed is measured by sampling vehicles in a given area over a period of time. Two definitions of average speed are identified: "time mean speed" and "space mean speed".
   Section::::Microsimulation.:Comparison with HCM Queues.
   Using a time-space diagram, we may model the bottleneck event. Suppose that at time 0, traffic begins to flow at rate B and speed v. After time t1, vehicles arrive at the lower flowrate A.
   Section::::Congestion mitigation.:Intelligent transportation systems.
  