title: The kinematic features of motorcycles in congested urban networks.
abstract: The aim of this paper is to compare the kinematic features of motorcycles with those of passenger cars in urban traffic. The hypothesis that motorcycles' capability to swerve in urban traffic contributes to their seemingly assertive behaviour is examined. Data for this study were collected in afternoon peak hours at Central London using video recorders. Detailed information on the trajectories of 2109 vehicles (including 477 motorcycles and 1293 passenger cars) was extracted from the video images and the observable kinematic features were analysed. In addition, a model describing the longitudinal following behaviour of motorcycles was employed to analyse the impacts of motorcycles' swerving behaviour. The model was calibrated using Markov Chain Monte Carlo (MCMC) numerical methods. The observable kinematic features show that in comparison to passenger cars, motorcycles have shorter safety gaps, higher speeds and severer acceleration and deceleration rates reflecting their generally much higher power to weight ratios and usage of available braking power. However, the data also support the hypothesis that motorcyclists maintain a considerable safety margin as they have the ability to avoid a collision by swerving away.
authors.affiliation: Centre for Transport Studies, Department for Civil and Environmental Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK. jtclee@mail.ncku.edu.tw
authors.forename: Tzu-Chang
authors.initials: TC
authors.lastname: Lee
authors.forename: John W
authors.initials: JW
authors.lastname: Polak
authors.forename: Michael G H
authors.initials: MG
authors.lastname: Bell
authors.forename: Marcus R
authors.initials: MR
authors.lastname: Wigan
mesh_terms: D000054:Acceleration; D001334:Automobile Driving / Q000523:psychology / Q000706:statistics & numerical data; D001336:Automobiles; D001499:Bayes Theorem; D002947:Cities; D003654:Deceleration; D008131:London; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D009038:Motion; D009049:Motorcycles; D012449:Safety; D014741:Video Recording