Today we linked up with doctoral students working at TU Delft under a grant called Allegro. The purpose of the Allegro grant is to study bicyclist and pedestrian behavior. Surprisingly, this subject is terribly understudied. The purpose of the grant is to collect data and test theories on how bicyclists and pedestrians behave under different conditions for micro (individual behavior) and macro (group behavior) applications.
In the Netherlands, all doctoral students are guaranteed full funding for the entire three years of their doctoral work, which is very different than in the U.S. where students generally must earn their own funding year after year and it's rarely guaranteed. The doctoral students we worked with were super energetic and enthusiastic about their work. They stayed with us all day, from about 9am to 5pm.
Together, we designed, performed, and analyzed an experiment on traffic flow. The experiment was fun and intensive. I’m honestly very impressed with how quickly we pulled together such a productive test.
The purpose of the experiment was to test how different factors of bunching behavior, particularly density, affects the flow of bicycle traffic through a green traffic light. Bunching behavior is when bicyclists bunch together when stopping for a red light, and flow is the number of bicycles that can make it through a light before it turns red again.
The 20 of us from the U.S. – 18 students and 2 professors – rode our bicycles in random order up to a mock red traffic light. We were instructed to bunch in different formations. Some of these formations were high density, three or four bicycles across, while others were low density, with only two bicyclists side-by-side. Other factors were included in different iterations of the experiment, such as the positioning of our pedals, and whether or not we had a footstool like a cinder block to push off of when the light turned green.
A small camera recorded each iteration of the test from above. After we completed 23 iterations of the experiment, we divided up the video between five groups so that we could more easily record the data. Each group watched videos of 4 or so tests and counted how long it took each person to pass through the mock intersection for each iteration. We had to find a video player that displayed playback time up to the millisecond because most bikes passed through the intersection only milliseconds apart. For future reference, Windows Media Player Classic has this function. Finally, we calculated how long it took each person to pass through the intersection.
The results of the experiment found that indeed, when bikes are bunched up in a higher density, they flow through an intersection faster.
This information can be useful for bicycle intersection design in several ways. For example, bike boxes allow a higher density of people to pull up to an intersection side-by-side. This data can also be used to inform signal timing, turn/merge lane design, and street width. Other factors like curbs that bicyclists can push off of can help more bicycles get through an intersection each time the light turns green. Because apparently, in places like the Netherlands, there are often so many bicycles on the road that they experience traffic congestion, same as cars do! If only we could achieve this type of non-polluting congestion in the United States someday!
In the Netherlands, all doctoral students are guaranteed full funding for the entire three years of their doctoral work, which is very different than in the U.S. where students generally must earn their own funding year after year and it's rarely guaranteed. The doctoral students we worked with were super energetic and enthusiastic about their work. They stayed with us all day, from about 9am to 5pm.
Together, we designed, performed, and analyzed an experiment on traffic flow. The experiment was fun and intensive. I’m honestly very impressed with how quickly we pulled together such a productive test.
The purpose of the experiment was to test how different factors of bunching behavior, particularly density, affects the flow of bicycle traffic through a green traffic light. Bunching behavior is when bicyclists bunch together when stopping for a red light, and flow is the number of bicycles that can make it through a light before it turns red again.
The 20 of us from the U.S. – 18 students and 2 professors – rode our bicycles in random order up to a mock red traffic light. We were instructed to bunch in different formations. Some of these formations were high density, three or four bicycles across, while others were low density, with only two bicyclists side-by-side. Other factors were included in different iterations of the experiment, such as the positioning of our pedals, and whether or not we had a footstool like a cinder block to push off of when the light turned green.
Seen here, TU Delft students fastening a camera to the top of a building.
The results of the experiment found that indeed, when bikes are bunched up in a higher density, they flow through an intersection faster.
This information can be useful for bicycle intersection design in several ways. For example, bike boxes allow a higher density of people to pull up to an intersection side-by-side. This data can also be used to inform signal timing, turn/merge lane design, and street width. Other factors like curbs that bicyclists can push off of can help more bicycles get through an intersection each time the light turns green. Because apparently, in places like the Netherlands, there are often so many bicycles on the road that they experience traffic congestion, same as cars do! If only we could achieve this type of non-polluting congestion in the United States someday!
The TU Delft Bike Lab where we performed the experiment was really beautiful and had plenty of space for us to ride our bikes around and get into our formations. |