Journal of Applied Science and Engineering

Published by Tamkang University Press


Impact Factor



Sheng Zhang1, Jun Liang1 and Zhengwu Wang This email address is being protected from spambots. You need JavaScript enabled to view it.1

1School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, P.R. China


Received: August 24, 2018
Accepted: May 7, 2019
Publication Date: September 1, 2019

Download Citation: ||  


In this paper, a method is proposed to evaluate the level of service (LOS) of bicycle lanes under a certain combination of road width, mixing ratio of vehicles, and cyclist characteristics based on user perception and capacity simulation. In this method, the concepts of bicycle lane capacity and the mental space of cyclists are highlighted; evaluation indicators are output through simulation under different traffic flow densities through construction of a space model for user perception and a multi-valued cellular automata model for hybrid bicycle flow, and the evaluation criteria of the level of service is determined through the clustering analysis method; thereafter, based on traffic density of the section under evaluation, the level of service of the lane can be determined. This method is adopted to evaluate the level of service of a bicycle lane in Hangzhou, China. The results show that this method can accurately describe the actual traffic flow state, user perception, and utilization of a road section.

Keywords: Traffic Engineering, Level of Service, Capacity Simulation of Bicycle Lane, Multi-valued Cellular Automata, User Perception


  1. [1] Shan, X. F., W. Wang, and H. Wang (2006) Properties of bicycle flow in non-congested road, Journal of Transport Information and Safety 24(6), 4143. doi: 10.3963/j.issn.1674-4861.2006.06.012
  2. [2] Zhang, J., H. Wang, and P. Li (2006) Bicycle flow modeling and simulation based on cellular automaton, Journal of Highway and Transportation Research and Development 23(1), 125129. doi: 10.3969/j.issn. 1002-0268.2006.01.031
  3. [3] Transportation Research Board (2010) Highway CapacityManual,WashingtonDC:NationalResearchCouncil.
  4. [4] Kang, K. W., and K. Lee (2012) Development of a bicycle level of service model from the user’s perspective, KSCE Journal of Civil Engineering 16(6), 1032– 1039. doi:10.1007/s12205-012-1146-z
  5. [5] Han, H. (2014) Studies about level of service of mixed non-motorized lane, Traffic & Transportation A02, 125129. doi: 10.3969/j.issn.1671-3400.2014.z2.033
  6. [6] Chen, X. H., L. S. S. Yue, and K. Yang (2017) Safety evaluation of overtaken bicycle on a shared bicycle path, Journal of Tongji University (Natural Science) 45(2), 215222. doi: 10.11908/j.issn.023-374x.2017.02.009
  7. [7] Xiao, L., M. Q. Xie, and X. D. Jia (2017) Use of entropy to analyze level of service of dedicated bike lanes in China, Advances in Mechanical Engineering 9(6), 112. doi: 10.1177/1687814017711857
  8. [8] Sambit, K. B., C. Haritha and K. B. Prasanta (2017) Urban road segment level of service based on bicycle users’perception under mixed traffic conditions, Journal of Modern Transportation 25(2), 116. doi: 10. 1007/s40534-017-0127-9
  9. [9] Liang, X. (2012) Dynamic Model to Simulate Bicycle MicroscopicBehavior,Ph.D.Desertation,BeijingJiaotong University, China.
  10. [10] Jin, S., X. B. Qu, and D. Zhou (2015) Estimating cycleway capacity and bicycle equivalent unit for electricbicycles,Transportation Research Part APolicy& Practice 77, 225248. doi: 10.1016/j.tra.2015.04.013
  11. [11] Xiao, L., M. Baohua, and X. Qi (2012) Perceptual process for bicyclist microcosmic behavior, International Conference on Traffic and Transportation Studies 43(4), 540549. doi: 10.1016/j.sbspro.2012.04.127
  12. [12] Xue,S.,B.Jia,andR.Jiang(2017)AnimprovedBurgers cellular automaton model for bicycle flow, Journal of Phys.A487,164177.doi:10.1016/j.physa.2017.05.036
  13. [13] Jia, B., X. J. Li, and R. Jiang (2007) Multi-value cellular automata model for mixed bicycle flow, European Physical Journal B 56(3), 247252. doi: 10.1140/epjb/ e2007-00116-5
  14. [14] Jin, S., X. B. Qu, and C. Xu (2015) An improved multi-value cellular automata model for heterogeneous bicycle traffic flow, Journal of Phys. A379(39), 2409 2416. doi: 10.1016/j.physleta.2015.07.031