Experimental characterization of the probability density function of the operating loads supported by urban buses in Madrid, Spain
Description
In order to approach properly a wide variety of issues concerning urban large passenger transport vehicles, such as the
design of the bus structure, the comfort of passengers, the non-collision injury risk and the operating characteristics of
the bus, detailed knowledge of the loads that the buses support when operating is required. These loads depend on
numerous factors such as the geographic and urban features of the city where they operate, the type of route and the
driver. All these factors provide the nature of these loads with a wide variability, and so studies based on experimentally
obtained data during representative periods of operation must be developed. The main objective of the present paper is
to carry out a representative characterization of the operating loads supported by large passenger transport vehicles
during normal operation. It is with this aim that a study of the longitudinal accelerations and lateral accelerations to
which large passenger transport vehicles are subjected was conducted over urban routes by using the data collected by
the Global Positioning System. An extensive assessment of recorded data was carried out to evaluate whether the precision
and the sample rate of the Global Positioning System were sufficient to characterize these accelerations accurately.
To ensure that the sample was representative, data for an operation time of more than 600 h were recorded using 10
different models of large passenger transport vehicles operating over 13 different urban routes. From all the position
data recorded, the instant longitudinal accelerations were calculated using second-order central differentiation, and the
lateral accelerations were obtained using first-order central differentiation and the curvature radius. All the calculated
accelerations were then subjected to data processing developed on an ad-hoc basis to filter the information that did not
refer to accelerating manoeuvres. After this data-processing procedure, it was verified that both the lateral accelerations
and the longitudinal accelerations fit normal probability distributions with a minimum margin of error (maximum differences
of 0.165 m/s2 for lateral accelerations and 0.038 m/s2 for longitudinal accelerations).
Files
Restricted
The record is publicly accessible, but files are restricted to users with access.
Additional details
Identifiers
Funding
- Ministry of Education and Science
- OPTIVIRTEST TRA2009-14513-C02-01
Software
- Repository URL
- https://oa.upm.es/79515/
References
- Park SJ and Yoo WS. Rollover analysis for the body section structure of a large bus using beam and non-linear spring elements. Proc IMechE Part D: J Automobile Engineering 2006; 222(6): 955–962.
- Ruiz O, Ramı´rez EI, Jacobo VH, et al. Efficient optimization of the structure of a passenger bus by iterative finite element models with increasing degress of complexity. In: 3rd international conference on engineering optimization, Rio de Janeiro, Brazil, 1–5 July 2012, paper 475. Brazil: OptimizE – Engineering Optimization Lab, OPPE/Mechanical Engineering Program, Federal University of Rio de Janeiro
- Ning H, Pillay S and Vaidya UK. Design and development of thermoplastic composite roof door for mass transit bus. Mater Des 2009; 30: 983–991
- Lan F, Chen J and Lin J. Comparative analysis for bus side structures and lightweight optimization. Proc IMechE Part D: J Automobile Engineering 2004; 218(10): 1067–1075.
- Bala´ zs G. Dynamic analysis of a bus body frame: determination of the loads and stresses. Veh System Dynamics 2005; 43(11): 807–822
- Wideberg JP. Simplified method for evaluation of the lateral dynamic behaviour of a heavy vehicle. Int J Heavy Veh Systems 2004; 11(2): 195–207.
- Eriksson P. Optimisation of a bus body structure. Int J Heavy Veh Systems 2001; 8(1): 1–16.
- Palacio A, Tamburro G, O'Neill D and Simms CK. Non-collision injuries in urban buses –strategies for prevention. Accid Analysis Prevention 2009; 41: 1–9.
- Dols J, Pons V, Alcala´ E, et al. Analysis of dynamic behavior and safety of baby carriages in public transportation buses. Transpn Res Part A: Policy Practice 2013; 49: 1–9
- Robert T, Beillas P, Maupas A and Verriest J. Conditions of possible head impacts for standing passengers in public transportation: an experimental study. Int J Crashworthiness 2007; 12(3): 319–327.
- Asensio C, Lo´ pez JM, Paga´n R, et al. GPS-based velocity collection method for road traffic noise mapping. Transpn Res Part D: Transp Environ 2009; 14: 360–366.
- Preda I, Covaciu D and Ciolan G. Vehicle dinamics study based on GPS devices. DSpace at Transilvania University, ASPECKT, Automotive and Transport Engineering, Research Papers (Automotive & Transport Engineering), 2009.
- Sun Z and Ban X. Vehicle classification using GPS data. Transpn Res Part C 2013; 37: 102–117.
- Anderson R and Bevly D. Using GPS with a model-based estimator to estimate critical vehicle states. Veh System Dynamics 2010; 48: 1413–1438.
- Corte´s C, Gibson J, Gschwender A, et al. Commercial bus speed diagnosis based on GPS-monitored data. Transpn Res Part C 2013; 19: 695–707
- Bruton AM, Glennie CL and Schwarz KP. Differentiation of high-precision GPS velocity and acceleration determination. GPS Solutions 1999; 2(4): 7–21