Abstract
Copenhagen is world-known for its large proportion of cyclists, forming a diverse group with a large variation of equipment and physical abilities. This leads to a considerable speed heterogeneity which needs to be taken into account when modelling the traffic on dedicated bicycle paths. Nevertheless, existing studies on bicycle traffic simulation have either neglected such speed heterogeneity altogether or modelled it by dividing cyclists into a few discrete classes ignoring the entirety of the speed distribution. This paper proposes an efficient bicycle traffic simulation model with continuously speed heterogeneous cyclists and corresponding congestion effects. Based on individual-specific desired speeds and headway distance preferences, the model shows realistic speed-flow relationships validated with on-site observations while being capable of delaying rapid cyclists more often than slower ones in moderate traffic flows. The scalability of the model allows it to be large-scale applicable for network loading purposes, and thus suitable for evaluating impacts of cycling related infrastructure investments.
| Original language | English |
|---|---|
| Journal | Transportation Research Part B: Methodological |
| Volume | 127 |
| Pages (from-to) | 72-98 |
| ISSN | 0191-2615 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- Bicycle congestion modeling
- Bicycle traffic
- Fundamental diagram
- Multi-lane traffic
- Simulation
- Speed heterogeneity
Cite this
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Fast or forced to follow: A speed heterogeneous approach to congested multi-lane bicycle traffic simulation. / Paulsen, Mads; Rasmussen, Thomas Kjær; Nielsen, Otto Anker.
In: Transportation Research Part B: Methodological, Vol. 127, 2019, p. 72-98.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - Fast or forced to follow: A speed heterogeneous approach to congested multi-lane bicycle traffic simulation
AU - Paulsen, Mads
AU - Rasmussen, Thomas Kjær
AU - Nielsen, Otto Anker
PY - 2019
Y1 - 2019
N2 - Copenhagen is world-known for its large proportion of cyclists, forming a diverse group with a large variation of equipment and physical abilities. This leads to a considerable speed heterogeneity which needs to be taken into account when modelling the traffic on dedicated bicycle paths. Nevertheless, existing studies on bicycle traffic simulation have either neglected such speed heterogeneity altogether or modelled it by dividing cyclists into a few discrete classes ignoring the entirety of the speed distribution. This paper proposes an efficient bicycle traffic simulation model with continuously speed heterogeneous cyclists and corresponding congestion effects. Based on individual-specific desired speeds and headway distance preferences, the model shows realistic speed-flow relationships validated with on-site observations while being capable of delaying rapid cyclists more often than slower ones in moderate traffic flows. The scalability of the model allows it to be large-scale applicable for network loading purposes, and thus suitable for evaluating impacts of cycling related infrastructure investments.
AB - Copenhagen is world-known for its large proportion of cyclists, forming a diverse group with a large variation of equipment and physical abilities. This leads to a considerable speed heterogeneity which needs to be taken into account when modelling the traffic on dedicated bicycle paths. Nevertheless, existing studies on bicycle traffic simulation have either neglected such speed heterogeneity altogether or modelled it by dividing cyclists into a few discrete classes ignoring the entirety of the speed distribution. This paper proposes an efficient bicycle traffic simulation model with continuously speed heterogeneous cyclists and corresponding congestion effects. Based on individual-specific desired speeds and headway distance preferences, the model shows realistic speed-flow relationships validated with on-site observations while being capable of delaying rapid cyclists more often than slower ones in moderate traffic flows. The scalability of the model allows it to be large-scale applicable for network loading purposes, and thus suitable for evaluating impacts of cycling related infrastructure investments.
KW - Bicycle congestion modeling
KW - Bicycle traffic
KW - Fundamental diagram
KW - Multi-lane traffic
KW - Simulation
KW - Speed heterogeneity
U2 - 10.1016/j.trb.2019.07.002
DO - 10.1016/j.trb.2019.07.002
M3 - Journal article
VL - 127
SP - 72
EP - 98
JO - Transportation Research. Part B: Methodological
JF - Transportation Research. Part B: Methodological
SN - 0191-2615
ER -