A Development of Crowdsourcing Smartphones in Measuring Train Ride Quality Azzoug, Adam; Kaewunruen, Sakdirat
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RideComfort: a development of crowdsourcing smartphones in measuring train ride quality Azzoug, Adam; Kaewunruen, Sakdirat DOI: 10.3389/fbuil.2017.00003 License: Creative Commons: Attribution (CC BY) Document Version Publisher's PDF, also known as Version of record Citation for published version (Harvard): Azzoug, A & Kaewunruen, S 2017, 'RideComfort: a development of crowdsourcing smartphones in measuring train ride quality: crowdsourcing smartphones in measuring train ride quality', Frontiers in Built Environment, vol. 3, 3. https://doi.org/10.3389/fbuil.2017.00003 Link to publication on Research at Birmingham portal General rights Unless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. 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Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive. If you believe that this is the case for this document, please contact [email protected] providing details and we will remove access to the work immediately and investigate. Download date: 01. Feb. 2019 ORIGINAL RESEARCH published: 03 February 2017 doi: 10.3389/fbuil.2017.00003 RideComfort: A Development of Crowdsourcing Smartphones in Measuring Train Ride Quality Adam Azzoug1 and Sakdirat Kaewunruen2* 1 Department of Civil Engineering, School of Engineering, The University of Birmingham, Birmingham, UK, 2 Birmingham Centre for Railway Research and Education, The University of Birmingham, Birmingham, UK Among the many million train journeys taking place every day, not all of them are being measured or monitored for ride comfort. Improving ride comfort is important for rail- way companies to attract more passengers to their train services. Giving passengers the ability to measure ride comfort themselves using their smartphones allows railway companies to receive instant feedback from passengers regarding the ride quality on their trains. The purpose of this development is to investigate the feasibility of using smartphones to measure vibration-based ride comfort on trains. This can be accom- plished by developing a smartphone application, analyzing the data recorded by the Edited by: application, and verifying the data by comparing it to data from a track inspection vehicle Chris Hendrickson, or an accelerometer. A literature review was undertaken to examine the commonly used Carnegie Mellon University, USA standards to evaluate ride comfort, such as the BS ISO 2631-1:1997 standard and Reviewed by: Sperling’s ride index as proposed by Sperling and Betzhold (1956). The literature review Rasa Ušpalyte˙-Vitku¯niene˙, Vilnius Gediminas Technical has also revealed some physical causes of ride discomfort such as vibrations induced University, Lithuania by roughness and irregularities present at the wheel/rail interface. We are the first to use Cheul Kyu Lee, Korea Railroad Research Institute, artificial neural networks to map data derived from smartphones in order to evaluate ride South Korea quality. Our work demonstrates the merits of using smartphones to measure ride com- *Correspondence: fort aboard trains and suggests recommendations for future technological improvement. Sakdirat Kaewunruen Our data argue that the accelerometers found in modern smartphones are of sufficient [email protected], [email protected] quality to be used in evaluating ride comfort. The ride comfort levels predicted both by BS ISO 2631-1 and Sperling’s index exhibit excellent agreement. Specialty section: This article was submitted to Keywords: railway infrastructure, ride quality, operations monitoring, artificial neural networks, mobile application Transportation and Transit Systems, a section of the journal Frontiers in Built Environment INTRODUCTION Received: 18 October 2016 Every day, many million train journeys take place and passengers traveling on these trains are Accepted: 11 January 2017 exposed to the vibrations, noises, temperatures, etc. present in the train for the duration of their Published: 03 February 2017 trips. Passengers will experience the train environment differently based on their individual prefer- Citation: ences and expectations. Making passengers feel comfortable aboard their trains is something many Azzoug A and Kaewunruen S (2017) railway companies strive to do (Suzuki, 1998; Förstberg, 2000; Karakasis et al., 2005). With the RideComfort: A Development of Crowdsourcing Smartphones in advent of smartphones, passengers can potentially measure the ride comfort themselves. This opens Measuring Train Ride Quality. the door for many commercial opportunities, allowing passengers to provide on the fly feedback Front. Built Environ. 3:3. on the comfort of their journey and equipping railway companies with information they can use doi: 10.3389/fbuil.2017.00003 to further improve ride comfort for passengers. There is potential for this technology to be used Frontiers in Built Environment | www.frontiersin.org 1 February 2017 | Volume 3 | Article 3 Azzoug and Kaewunruen Crowdsourcing Smartphones for Train-Ride Quality to detect track faults and indicate which sections of track are in where aw(t) is the instantaneous frequency-weighted accelera- need of maintenance, possibly saving on maintenance costs and tion (meters per square second), t is the time (seconds), t0 is the improving the safety of the railway. time of observation (seconds), and τ is the integration time for Railway passengers expect a certain level of comfort dur- running averaging (seconds). The value gained from Eq. 1 is ing their journeys. In general, the comfort of passengers can meant to be compared to the values presented in Table 1, which be affected by a range of different factors such as temperature, underlines the relationship between the rms acceleration and humidity, odors, noise, accelerations, and vibrations. The expected passenger reaction. standard BS ISO 2631-1:1997 gives an approximate indication Another widely used method to measure ride comfort is of possible reactions to varying magnitudes of vibration found Sperling’s ride index from Sperling and Betzhold (1956) (cited in public transport, shown in Table 1. It is important to note in Förstberg, 2000, p. 54), which is also called the Werzungzahl that passenger reaction to motion is also influenced not only (Wz) method (Karakasis et al., 2005; Narayanamoorthy et al., by other factors in their environment such as temperature and 2008; Darlton and Marinov, 2015). The original mathematical noise but also of their expectations, i.e., certain vibrations that are form given by Sperling is defined by considered comfortable and expected in train journeys might be = 03. considered uncomfortable in a car (British Standards Institution, Wazw 44. 2 ,rms (2) 1997a, BS ISO 2631-1:1997; British Standards Institution, 2001, where aw,rms is the rms value of the measured frequency-weighted BS ISO 2631-4:2001; British Standards Institution, 2009, BS ISO acceleration in meters per square second. The Wz values are 2041:2009). intended to be compared to the values in Table 2. A Wz value of In this research and development project, we aim to produce a 2.5 is comparable to a BS ISO 2631-1:1997 rms value of 0.25 m/s2 smartphone application that can record the vibrations measured according to Narayanamoorthy et al. (2008). by a smartphone and to investigate how well the smartphone can Other standards for evaluating ride comfort do exist such as measure ride comfort aboard trains compared to a more sophis- UIC513, BS 6841, and ENV-12999 (Dumitriu, 2013); however, ticated accelerometer. they do not seem to be employed in any of the papers that have Prior to the development, a critical literature and technology been reviewed and appear to have been made obsolete by BS review have been carried out in order to investigate different ISO2631-1:1997. Karakasis et al. (2005) state that the BS ISO ways in which ride comfort is measured and evaluated. The 2631-1:1997 is the most precise method but also argue that in review also examines previous products and investigates certain circumstances where two or more situations need to be potential causes of vibrations in trains and also reviews other compared, the Sperling’s ride index can be more convenient and developments concerning the use of smartphones in measuring appropriate. Darlton and Marinov (2015) agree with this and ride comfort. In this paper, we will demonstrate the development state that due to the Sperling’s ride index need for each direc- of smartphone application that can capture internal data and tion to be determined separately, it is less accurate compared correlate the data with actual onboard sensors using artificial to BS ISO 2631-1:1997. Darlton and Marinov (2015) also argue neural networks. that the Sperling’s ride index is easier to read and understand. All of the authors seem to agree that BS ISO 2631-1:1997 is RIDE COMFORT far superior to the Sperling’s ride index in the accuracy and quality of results it produces. However, Sperling’s ride index Different methods of assessing and quantifying ride comfort have method still sees use since the results are easier to read and been developed to make it possible to evaluate and predict the understand.