Reconsidering the Safety in Numbers Effect for Vulnerable Road Users: An Application of Agent-Based Modeling

References

• Adams JGU. Smeed's law: some further thoughts. Traffic Engineering and Control. 1987;10(7):70–73.
   Google Scholar
• Aldred R. “On the outside”: constructing cycling citizenship. Soc Cult Geogr. 2010;11:35–52.
   Web of Science ®Google Scholar
• Barceló J, Casas J. Dynamic network simulation with AIMSUN. In: Simulation Approaches in Transportation Analysis. Springer; 2005:57–98.
   Google Scholar
• Bauman A, Rissel C, Garrard J, et al. Cycling—Getting Australia Moving: Barriers, Facilitators and Interventions to Get More Australians Physically Active Through Cycling. Melbourne, Australia: Department of Health and Ageing; 2008.
   Google Scholar
• Bhalla K, Ezzati M, Mahal A, Salomon J, Reich M. A risk-based method for modeling traffic fatalities. Risk Anal. 2007;27:125–136.
   PubMed Web of Science ®Google Scholar
• Bhatia R, Wier M. “Safety in numbers” re-examined: can we make valid or practical inferences from available evidence? Accid Anal Prev. 2011;43:235–240.
   PubMed Web of Science ®Google Scholar
• Bo C, Cheng HH. A review of the applications of agent technology in traffic and transportation systems. IEEE Trans Intell Transp Syst. 2010;11:485–497.
   Web of Science ®Google Scholar
• Bonomi A, Manzoni S, Pisano A, Vizzari G. Experimenting situated cellular agents in indoor scenario: pedestrian dynamics during lecture hall evacuation. In: Proceedings of the Web Intelligence and Intelligent Agent Technologies, 2009.
   Google Scholar
• Bumann D, Krause J, Rubenstein D. Mortality risk of spatial positions in animal groups: the danger of being in the front. Behaviour. 1997;134:1063–1076.
   Web of Science ®Google Scholar
• City of Yarra. City of Yarra Bicycle Strategy. Melbourne, Australia: Author; 2010.
   Google Scholar
• Department for Transport Energy and Infrastructure. Safety in Numbers. A Cycling Strategy for South Australia 2006–2010. Adelaide, Australia: Author; 2006.
   Google Scholar
• Department of Transport. Bike Ahead. Perth, Australia: Author; 1997.
   Google Scholar
• De Vos A, O’Riain MJ. Movement in a selfish seal herd: do seals follow simple or complex movement rules? Behav Ecol. 2012;24:190–197.
   Web of Science ®Google Scholar
• Ehlert PAM, Rothkrantz LJM. Microscopic traffic simulation with reactive driving agents. In: Proceedings of the Intelligent Transportation Systems, 2001.
   Google Scholar
• Elvik R. The Handbook of Road Safety Measures. 2nd ed. Bingley, UK: Emerald; 2009a.
   Google Scholar
• Elvik R. The non-linearity of risk and the promotion of environmentally sustainable transport. Accid Anal Prev. 2009b;41:849–855.
   PubMed Web of Science ®Google Scholar
• European Environmental Agency. Climate for a Transport Change. Term 2007: Indicators Tracking Transport and Environment in the European Union. Luxembourg: Author; 2008.
   Google Scholar
• Furness Z. Critical mass, urban space and vélomobility. Mobilities. 2007;2:299–319.
   Google Scholar
• Gilbert N. Agent-Based Models. London, UK: Sage; 2008.
   Google Scholar
• Gomes G, May A, Horowitz R. Congested freeway microsimulation model using VISSIM. Calibration and Validation of Simulation Models. 2004;1876:71–81.
   Google Scholar
• Hamilton WD. Geometry for the selfish herd. J Theor Biol. 1971;31:295–311.
   PubMed Web of Science ®Google Scholar
• Hickman R, Fremer P, Breithaupt M, Saxena S. Changing Course in Urban Transport. An Illustrated Guide. Asian Development Bank; 2011.
   Google Scholar
• Hirsch BT, Morrell LJ. Measuring marginal predation in animal groups. Behav Ecol. 2011;22:648–656.
   Web of Science ®Google Scholar
• Hood J, Sall E, Charlton B. A GPS-based bicycle route choice model for San Francisco, California. Transp Lett. 2011;3:63–75.
   Web of Science ®Google Scholar
• Hoogendoorn SP, Bovy PHL. Continuum modeling of multiclass traffic flow. Transp Res Part B. 2000;34(2):123–146.
   Web of Science ®Google Scholar
• Howard C, Burns EK. Cycling to work in Phoenix—route choice, travel behavior, and commuter characteristics. Transp Res Rec.. 2001;1773:39–46.
   Web of Science ®Google Scholar
• Jacobsen PL. Safety in numbers: more walkers and bicyclists, safer walking and bicycling. Inj Prev. 2003;9:205–209.
   PubMed Web of Science ®Google Scholar
• Khalesian M, Delavar M. A multi-agent based traffic network micro-simulation using spatio-temporal GIS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2008;12(7):31–35.
   Google Scholar
• Kopits E, Cropper M. Traffic fatalities and economic growth. Accid Anal Prev. 2005;37:169–178.
   PubMed Web of Science ®Google Scholar
• Laskowski M, Demianyk BC, Witt J, Mukhi SN, Friesen MR, Mcleod RD. Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study. IEEE Trans Inf Technol Biomed. 2011;15:877–889.
   PubMed Web of Science ®Google Scholar
• Lawson AR, Pakrashi V, Ghosh B, Szeto WV. Perception of safety of cyclists in Dublin City. Accid Anal Prev. 2013;50:499–511.
   PubMed Web of Science ®Google Scholar
• Li Y. Agent-based modeling: a case study in urban traffic simulation system. In: Proceedings of the Management Science and Engineering, 2006.
   Google Scholar
• Luo LB, Zhou SP, Cai WT, et al. Agent-based human behavior modeling for crowd simulation. Comput Animat Virtual Worlds. 2008;19(3–4):271–281.
   Web of Science ®Google Scholar
• Marin M, Yanshen Z, Meade PT, Sargent M, Warren J. System dynamics and agent-based simulations for workforce climate. In: Proceedings of the Simulation Conference, 2006.
   Google Scholar
• Minikel E. Cyclist safety on bicycle boulevards and parallel arterial routes in Berkeley, California. Accid Anal Prev. 2012;45:241–247.
   PubMed Web of Science ®Google Scholar
• Morrell LJ, Ruxton GD, James R. Spatial positioning in the selfish herd. Behav Ecol. 2010;22:16–22.
   Web of Science ®Google Scholar
• Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic. J Phys I. 1992;2:2221–2229.
   Google Scholar
• The National Cycling Charity. Safety in Numbers . Guildford, UK: CTC Charitable Trust;2009.
   Google Scholar
• Owen N, De De Bourdeaudhuij I, Sugiyama T, et al. Bicycle use for transport in an Australian and a Belgian city: associations with built-environment attributes. J Urban Health. 2010;87(2):189–198.
   PubMed Web of Science ®Google Scholar
• Phillips RO, Bjørnskau T, Hagman R, Sagberg F. Reduction in car–bicycle conflict at a road–cycle path intersection: evidence of road user adaptation? Transp Res Part F Traffic Psychol Behav. 2011;14(2):87–95.
   Web of Science ®Google Scholar
• Pucher J, Buehler R, Seinen M. Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transp Res Part A Policy Pract. 2011;45:451–475.
   Web of Science ®Google Scholar
• Pucher J, Dill J, Handy S. Infrastructure, programs, and policies to increase bicycling: an international review. Prev Med. 2010;50(Suppl 1):S106–S125.
   PubMed Web of Science ®Google Scholar
• Pucher J, Garrard J, Greaves S. Cycling down under: a comparative analysis of bicycling trends and policies in Sydney and Melbourne. J Transp Geogr. 2011;19:332–345.
   Web of Science ®Google Scholar
• Reynolds C, Harris M, Teschke K, Cripton P, Winters M. The impact of transportation infrastructure on bicycling injuries and crashes: a review of the literature. Environ Health. 2009;8.
   PubMed Web of Science ®Google Scholar
• Reynolds C, Winters M, Ries F, Gouge B. Active Transportation in Urban Areas: Exploring Health Benefits and Risks. National Collaborating Centre for Environmental Health; 2010.
   Google Scholar
• Robinson DL. Safety in numbers in Australia: more walkers and bicyclists, safer walking and bicycling. Health Promot J Austr. 2005;16:47–51.
   PubMedGoogle Scholar
• Safe Cycling Australia. Safe Cycling Australia. 2013.
   Google Scholar
• San Francisco Municipal Transportation Agency. 2011 Bicycle Count Report. San Francisco, CA: Author; 2011.
   Google Scholar
• San Francisco Municipal Transportation Agency. 2010–2011 San Francisco Collisions Report. Sustainable Streets Division. San Francisco, CA: City of San Francisco; 2012.
   Google Scholar
• Sarvi M, Kuwahara M. Microsimulation of freeway ramp merging processes under congested traffic conditions. IEEE Trans Intell Transp Syst. 2007;8:470–479.
   Web of Science ®Google Scholar
• Savino G, Giovannini F, Baldanzini N, Pierini M, Rizzi M. Assessing the potential benefits of the motorcycle autonomous emergency braking using detailed crash reconstructions. Traffic Inj Prev. 2013;14(Suppl):S40–S49.
   PubMed Web of Science ®Google Scholar
• Sener IN, Eluru N, Bhat CR. An analysis of bicycle route choice preferences in Texas, US. Transportation. 2009;36:511–539.
   Web of Science ®Google Scholar
• Shiwakoti N, Sarvi M, Rose G, Burd M. Biologically inspired modeling approach for collective pedestrian dynamics under emergency conditions. Transp Res Rec. 2010;2196:176–184.
   Web of Science ®Google Scholar
• Smeed RJ. Some statistical aspects of road safety research. J R Stat Soc Ser A Stat Soc. 1949;112:1–34.
   Web of Science ®Google Scholar
• Stinson MA, Bhat CR. Commuter bicyclist route choice: analysis using a stated preference survey. Transp Res Rec. 2003;1828:107–115.
   Google Scholar
• Stordy J. Casualties in Greater London During 2012. London, UK: Transport for London; 2013.
   Google Scholar
• Teschke K, Harris MA, Reynolds CC, et al. Route infrastructure and the risk of injuries to bicyclists: a case-crossover study. Am J Public Health. 2012;102:2336–2343.
   PubMed Web of Science ®Google Scholar
• Teschke K, Reynolds CC, Ries FJ, Gouge B, Winters M. Bicycling: health risk or benefit? UBC Med J. 2012;3(2):6–10.
   Google Scholar
• Tin ST, Woodward A, Thornley S, Ameratunga S. Regional variations in pedal cyclist injuries in New Zealand: safety in numbers or risk in scarcity? Aust N Z J Public Health. 2011;35:357–363.
   PubMed Web of Science ®Google Scholar
• Transport for London. Travel in London Supplementary Report: London Travel Demand Survey (LTDS). London, UK: Author; 2011.
   Google Scholar
• Turner A, Penn A. Encoding natural movement as an agent-based system: an investigation into human pedestrian behaviour in the built environment. Environ Plann B. 2002;29:473–490.
   Web of Science ®Google Scholar
• University of New South Wales. A virtuous cycle: safety in numbers for bicycle riders. Science Daily. 2008 . September 7th, 2008 http://www.sciencedaily.com/releases/2008/09/080903112034.htm
   Google Scholar
• Wegman F, Zhang F, Dijkstra A. How to make more cycling good for road safety? Accid Analy Prev. 2012;44:19–29.
   PubMed Web of Science ®Google Scholar
• Wilensky U. Netlogo. IL: Centre for Connected Learning and Computer-Based Modeling, Northwestern University; 2013.
   Google Scholar
• Winters M, Teschke K. Route preferences among adults in the near market for bicycling: findings of the cycling in cities study. Am J Health Promot. 2010;25:40–47.
   PubMed Web of Science ®Google Scholar
• World Health Organization. Global Status Report on Road Safety. Luxembourg: World Health Organization Press; 2013.
   Google Scholar
• Zhang K, Qin R-B, Zheng H-R, Niu J-Q. An agent-based modeling approach for stochastic molecular events of biochemical networks. In: Proceedings of the Intelligent Computation Technology and Automation (ICICTA), 2011.
   Google Scholar