Traffic congestion
Traffic congestion is a condition in transport that is characterized by slower speeds, longer trip times, and increased vehicular queuing. Traffic congestion on urban road networks has increased substantially since the 1950s, resulting in many of the roads becoming obsolete. When traffic demand is great enough that the interaction between vehicles slows the traffic stream, this results in congestion. While congestion is a possibility for any mode of transportation, this article will focus on automobile congestion on public roads. Mathematically, traffic is modeled as a flow through a fixed point on the route, analogously to fluid dynamics.
As demand approaches the capacity of a road, extreme traffic congestion sets in. When vehicles are fully stopped for periods of time, this is known as a traffic jam, a traffic snarl-up or a tailback. Drivers can become frustrated and engage in road rage. Drivers and driver-focused road planning departments commonly propose to alleviate congestion by adding another lane to the road; however, this is ineffective as increasing road capacity induces more demand for driving.
Causes
Traffic congestion occurs when a volume of traffic generates demand for space greater than the available street capacity; this point is commonly termed saturation. Several specific circumstances can cause or aggravate congestion; most of them reduce the capacity of a road at a given point or over a certain length, or increase the number of vehicles required for a given volume of people or goods. About half of U.S. traffic congestion is recurring, and is attributed to sheer volume of traffic; most of the rest is attributed to traffic incidents, road work and weather events. In terms of traffic operation, rainfall reduces traffic capacity and operating speeds, thereby resulting in greater congestion and road network productivity loss.Individual incidents such as crashes or even a single car braking heavily in a previously smooth flow may cause ripple effects, a cascading failure also known as traffic waves, which then spread out and create a sustained traffic jam when, otherwise, the normal flow might have continued for some time longer.
Economic theories
Congested roads can be seen as an example of the tragedy of the commons. Because roads in most places are free at the point of usage, there is little financial incentive for drivers not to over-use them, up to the point where traffic collapses into a jam, when demand becomes limited by opportunity cost. Privatization of highways and road pricing have both been proposed as measures that may reduce congestion through economic incentives and disincentives. Congestion can also happen due to non-recurring highway incidents, such as a crash or roadworks, which may reduce the road's capacity below normal levels.File:Traffic jam in Haikou, Hainan, China 01.jpg|thumb|right|upright=0.9|Rapid economic growth in China has resulted in a massive increase in the number of private vehicles in its major cities. Shown here is a traffic jam in downtown Haikou, Hainan Province, China.
Economist Anthony Downs argues that rush hour traffic congestion is inevitable because of the benefits of having a relatively standard work day. In a capitalist economy, goods can be allocated either by pricing or by queueing ; congestion is an example of the latter. Instead of the traditional solution of making the "pipe" large enough to accommodate the total demand for peak-hour vehicle travel, either by widening roadways or increasing "flow pressure" via automated highway systems, Downs advocates greater use of road pricing to reduce congestion, in turn putting the revenues generated therefrom into public transportation projects.
A 2011 study in The American Economic Review indicates that there may be a "fundamental law of road congestion." The researchers, from the University of Toronto and the London School of Economics, analyzed data from the U.S. Highway Performance and Monitoring System for 1983, 1993 and 2003, as well as information on population, employment, geography, transit, and political factors. They determined that the number of vehicle-kilometers traveled increases in direct proportion to the available lane-kilometers of roadways. The implication is that building new roads and widening existing ones only results in additional traffic that continues to rise until peak congestion returns to the previous level.
Classification and modeling
Qualitative classification of traffic is often done in the form of a six-letter A–F level of service scale defined in the Highway Capacity Manual, a US document used worldwide. While this system generally uses delay as the basis for its measurements, the particular measurements and statistical methods vary depending on the facility being described. For instance, while the percent time spent following a slower-moving vehicle figures into the LOS for a rural two-lane road, the LOS at an urban intersection incorporates such measurements as the number of drivers forced to wait through more than one signal cycle.Another classification schema of traffic congestion is associated with some common spatiotemporal features of traffic congestion found in measured traffic data. Common spatiotemporal empirical features of traffic congestion are those features, which are qualitatively the same for different highways in different countries measured during years of traffic observations. Common features of traffic congestion are independent on weather, road conditions and road infrastructure, vehicular technology, driver characteristics, day time, etc. Examples of common features of traffic congestion are the features and for, respectively, the wide moving jam and synchronized flow traffic phases found in Boris Kerner's three-phase traffic theory. The common features of traffic congestion can be reconstructed in space and time with the use of the ASDA and FOTO models.
File:Motorcycles on Civic Boulevard 20080918.jpg|thumb|Congestion on a street in Taipei consisting primarily of motorcycles
Some traffic engineers have attempted to apply the rules of fluid dynamics to traffic flow, likening it to the flow of a fluid in a pipe. Congestion simulations and real-time observations have shown that in heavy but free flowing traffic, jams can arise spontaneously, triggered by minor events, such as an abrupt steering maneuver by a single motorist. Traffic scientists liken such a situation to the sudden freezing of supercooled fluid.
Because of the poor correlation of theoretical models to actual observed traffic flows, transportation planners and highway engineers attempt to forecast traffic flow using empirical models. Their working traffic models typically use a combination of macro-, micro- and mesoscopic features, and may add matrix entropy effects, by "platooning" groups of vehicles and by randomizing the flow patterns within individual segments of the network. These models are then typically calibrated by measuring actual traffic flows on the links in the network, and the baseline flows are adjusted accordingly.
A team of MIT mathematicians has developed a model that describes the formation of "phantom jams", in which small disturbances in heavy traffic can become amplified into a full-blown, self-sustaining traffic jam. Key to the study is the realization that the mathematics of such jams, which the researchers call "jamitons", are strikingly similar to the equations that describe detonation waves produced by explosions, says Aslan Kasimov, lecturer in MIT's Department of Mathematics. That discovery enabled the team to solve traffic-jam equations that were first theorized in the 1950s.
Negative impacts
Traffic congestion has a number of negative effects:- Wasting time of motorists and passengers. As a non-productive activity for most people, congestion reduces regional economic health.
- Delays, which may result in late arrival for employment, meetings, and education, resulting in lost business, disciplinary action or other personal losses.
- Inability to forecast travel time accurately, leading to drivers allocating more time to travel "just in case", and less time on productive activities.
- Wasted fuel increasing air pollution and carbon dioxide emissions owing to increased idling, acceleration and braking.
- Wear and tear on vehicles as a result of idling in traffic and frequent acceleration and braking, leading to more frequent repairs and replacements.
- Stressed and frustrated motorists, encouraging road rage and reduced health of motorists
- Emergencies: blocked traffic may interfere with the passage of emergency vehicles traveling to their destinations where they are urgently needed.
- Spillover effect from congested main arteries to secondary roads and side streets as alternative routes are attempted, which may affect neighborhood amenity and real estate prices.
- Higher chance of collisions due to tight spacing and constant stopping-and-going.
Road rage
Economic loss
| Area | Loss in billions | Note |
| US | $305 | |
| UK | $52.01 | |
| NYC | $33.7 | |
| LA | $19.2 | |
| Manila | $18.615 | |
| Bangladesh | $11.4 | |
| SF | $10.6 | |
| Atlanta | $7.1 | |
| Jakarta | $5 | |
| Dhaka | $4.463 | |
| GTHA | $3.3 |