Research Rest-Stop — Understanding Congestion

Generally when we think of traffic congestion, we visualize intersections overflowing with gridlocked cars, stationary automobiles on the freeway, and frustrated drivers honking at each other.  However, traffic congestion can take multiple forms and can even benefit an area.

Automobile Congestion along 15th Street

Traditionally, traffic classification is done through a six-level (A-F) rating system.  A road with an ‘A’ Level-of-Service means that all automobiles are able to travel unimpeded, and an ‘F’ Level-of-Service means that there is very congested or even stopped traffic.  This classification is used by Transportation departments all over the country as well as the Texas Transportation Institute who argued that traffic congestion costs US drivers over $100 billion in time and fuel. Identifying economic failure as a negative externality of congestion overlooks a primary cause of congestion – high demand and economic success.  For instance, a restaurant that is in high demand will also be very congested, but that doesn’t mean that the patrons will be losing out. A recent article explores this relation between a metropolitan area’s traffic congestion and GDP.  It turns out that areas with higher congestion also have higher GDP.  This concept is illustrated well in CenterCity – many streets are very congested, yet the area has lots of activity and businesses do very well.

Pedestrian Congestion along Walnut Street

In short, high levels of congestion impair an area’s ability to act as a thoroughfare, but high levels of congestion benefit a location by promoting activity and economic growth.  The City of Philadelphia is working hard to find the right balance by advocating for corridor-wide congestion mitigation through traffic light synchronization and transit signal priority.  These measures will help bring people in to high activity areas and help cars drive through them.

Find out more:

Rethinking the Economics of Congestion

Learning to Love Congestion

Traditional Traffic Classification System


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