Bicycling and Walking to Work in the United States

Pavel Prikhodko, Ph.D. Machine Learning

According to the United States Census Bureau data for 2008-2012, more than half of all Americans commute to work every working day. Personal cars and public transportation are not the only modes of commuting, but they are the most popular. Year by year, walking and riding a bicycle are becoming more and more popular, and the corresponding infrastructure is developing rapidly. One can agree that walking and bicycling have a few advantages over motorized travel. They are healthier, ecologically pure and require less expensive infrastructure than other commuting modes. Of course, the distribution of the number of pedestrians and bicyclists in the states is not uniform. The city with the highest percentage of walkers is Ithaca, NY. Portland, OR has the highest percentage of bicyclists.

These maps show the percentage of workers who commute to work on foot or by bike. The size of the marker shows the total number of workers in the current city, and the color becomes redder as the percentage rises. As you can see, the percentages are not static in time. Generally, the number of bicyclists goes up but the percentage of walkers stays relatively stable.

Percentages are different for different social groups. According to ACS data, only 7.8 percent of American workers from age 16 to 24 use non-motorized travel, but this percentage is less than 3.9 percent in any other age group. Household income also affects the preferences of commuters. In fact, the poorest class who cannot afford cars are forced to commute to work by foot, public transportation or bicycles.

One more interesting (and expected) fact is that the percentage of non-motorized commuters depends on the travel time to work. It also explains why walking and bicycling is more popular in small cities than in larger ones: it is not needed to use vehicles or public transportation to commute to work.

Considering all this, non-motorized commuting is becoming more popular in the U.S. The increase is different for different social groups, climates, infrastructure and the size of cities.

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About Pavel Prikhodko

Pavel Prikhodko, Ph.D. Machine Learning

Pavel has worked for many years as a researcher and developer on a wide range of applications (varying from mechanics and manufacturing to social data, finance and advertising), building predictive systems and trying to find stories that data can tell.

In his free time, he enjoys being with his family.

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