  Cycling is a green transportation mode, and is promoted by many governments
to mitigate traffic congestion. However, studies concerning the traffic
dynamics of bicycle flow are very limited. This study experimentally
investigated bicycle flow dynamics on a wide road, modeled using a 3-m-wide
track. The results showed that the bicycle flow rate remained nearly constant
across a wide range of densities, in marked contrast to single-file bicycle
flow, which exhibits a unimodal fundamental diagram. By studying the weight
density of the radial locations of cyclists, we argue that this behavior arises
from the formation of more lanes with the increase of global density. The extra
lanes prevent the longitudinal density from increasing as quickly as in
single-file bicycle flow. When the density is larger than 0.5 bicycles/m2, the
flow rate begins to decrease, and stop-and-go traffic emerges. A
cognitive-science-based model to reproduce bicycle dynamics is proposed, in
which cyclists apply simple cognitive procedures to adapt their target
directions and desired riding speeds. To incorporate differences in
acceleration, deceleration, and turning, different relaxation times are used.
The model can reproduce the experimental results acceptably well and may also
provide guidance on infrastructure design.
