UIC comfort tests - VTI

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number of real votes3025201510500,250,50,7511,251,5Histogram of votesfor three estimated votes1,7522,252,52,75Real vote33,253,53,7544,254,5122,754,755Figure 11-12 Real votes for three zones of estimated votes. Here 1, 2 and 2.75are the abscisses of the vertical slices in the data figure.11.1.17 Study of the errors: Measured-EstimationA histogram of the distances between real and estimated votes gives followingresult.0,090,080,07referencedata0,060,050,040,030,020,010-2 -1 0 1 2Figure 11-13 Comparison between the experimental distributionand the normal distribution.The fuchsia curve is the normal distribution with an average of "0" and a standarddeviation of 0.65 comfort units.Taking into account that the estimation is done for a group of on average 5persons we need an average of 0.20 for a standard deviation equal to 0.1 comfortunit.The average of 35 persons gives a standard error of about 0.25 comfort units.VTI notat 56A-2003 87
11.1.18 Conclusions on comfort in curve transitionsThe best representation of the comfort in curve transitions is given by theexpressionComfort Note = 0.38* N’ VA + 0.64* & y& 0.1 max+ 0.15* & y& 0.1 max+ 0.032* & θ 0.1max[11.1]This uses parameters that are measured in the train, and with the relatively shortaveraging interval, are affected as much by the dynamic response of the train inthe transition, as they are by the track geometry.An alternative formulation is also proposed, which is considered to be moreuseful for track engineers when assessing the design geometry of a transitioncurve.Comfort Note = 0.79* & y& 1.0 max+ 0.24* & y&1.0 max+ 0.13* & θ1.0 max+ 0.48 [11.2]Although still using parameters measured in the vehicle, the use of a longer1.0-second averaging interval and elimination of the comfort parameter N’ VAmeans that the parameters in the equation can be more directly related to thedesign track geometry. However, there exits a high correlation between lateralacceleration and jerk when the averaging time is 1s.11.2 Analysis of Circular curves11.2.1 Test ConditionsTest results for all four tilt conditions (80%, 60%, 40% and 0%) were combinedinto a single dataset. Both directions of running were included, giving a total ofnine test runs after one of the 80% runs was repeated.Each test run included seven (Firenze to Arezzo) or eight (Arezzo to Firenze)curved track test sites, chosen to give differing levels of non-compensatedacceleration. In some runs not all sites were usable due to problems withinstrumentation or train speeds.Also included in the analysis dataset were the results from two straight tracktest sites on each test run. Straight track can be considered as a special case of acurve with zero lateral acceleration.At each test site, votes and acceleration measurements were available forpassengers at five different positions in the train. The votes for each group ofpassengers were averaged, and the average group vote used in regressions againstthe measured parameters for that group’s location.The groups at different positions in the train included four, six or eightpassengers. In the regression analysis, the average vote for the whole group wasused to help to improve the correlation of the results. However, to give the correctweight to each group according to its size, the results for groups of four wereincluded twice in the regression, results for groups of six were included threetimes and results for groups of eight were included four times.The combination of test runs, test sites and passenger locations gave a total ofexactly 400 separate observations. After weighting, 1281 observations were inputto the regressions.88 VTI notat 56A-2003
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VTI notat 56A • 2003VTI notat 56A
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ContentsPageAbbrivations and Notati
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10.5.1 Transitions 5311 Evaluation
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Abbrivations and NotationsAEAT AEA
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chosen test track with a minimum of
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1.8.2 ModelsThree different models
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3 What does comfort mean in the con
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Representation of passengers’ opi
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4 How comfort evolves with speed4.1
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Each element may provoke a potentia
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5.2.2 Theoretical behaviour of thos
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Nominal acceleration in the horizon
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6 Actual evaluation rulesAll the fo
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Important variancesS 0 = var(y)Sr =
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7 Choice of the test zone7.1 Choice
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9.008.007.006.00roll velocity5.004.
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8 Description of the test8.1 The tr
Page 35 and 36: 8.3.3 Synchronisation between votes
Page 37 and 38: 8.5 Registration of data, calculati
Page 39 and 40: DRIVER CAB8.6.2 Occupied places2224
Page 41 and 42: 9.3 Study of the car body angle9.3.
Page 43 and 44: 9.4.2 Influence of length of the co
Page 45 and 46: 9.4.4 Additional discomfort due to
Page 47 and 48: 10.1.1 ConclusionsThe actual distri
Page 49 and 50: 10.3 Seat positionThe influence of
Page 51 and 52: Average votes for the different tra
Page 53 and 54: Figures 10-5 to 10-10 show the infl
Page 55 and 56: Influence by roll velocity on voteA
Page 57 and 58: 5.0Influence by Pct on voteAll cate
Page 59 and 60: 11 Evaluation of local comfort11.1
Page 61 and 62: 11.1.4 Scaling of votesThe N’ VA
Page 63 and 64: Note that very high values of later
Page 65 and 66: 554433N'vaN'va221100 1 2 3 4Lateral
Page 68 and 69: Multiple regressions have therefore
Page 70 and 71: With the 1.0-second window, the jer
Page 72 and 73: The regression has been repeated wi
Page 74 and 75: (Table 11-12)Object: Simple and adj
Page 76 and 77: simple transitions, and with the re
Page 78 and 79: Table 11-18 Regression for track en
Page 80 and 81: Some characteristic data points of
Page 82 and 83: The probability that all coefficien
Page 84 and 85: Second conclusionThis also proves t
Page 88 and 89: 11.2.2 ParametersFour parameters we
Page 90 and 91: There are some observations from th
Page 92 and 93: Table 11-30 Two-parameter regressio
Page 94 and 95: Three-parameter regression - N'VA,
Page 96 and 97: The three-parameter regression was
Page 98 and 99: 12 Evaluation of average comfort12.
Page 100 and 101: Table 12-2 shows that the correlati
Page 102 and 103: 3.53.5332.52.5NVA21.5NVA21.5110.50.
Page 104 and 105: Table 12-5 Multiple regression for
Page 106 and 107: This is the preferred result to be
Page 108 and 109: 12.2.5 Density of importance of eac
Page 110 and 111: 13.3 Conclusions in relationship wi
Page 112 and 113: An identical observation can be mad
Page 114 and 115: 13.7.3 Evaluation of local comfort
Page 116 and 117: Appendix 1Page 1 (3)1 Preparing the
Page 118 and 119: Appendix 1Page 3 (3)2.5 Publish res
Page 120 and 121: Appendix 2Page 2 (10)For this progr
Page 122 and 123: Appendix 2Page 4 (10)Vertical accel
Page 124 and 125: Appendix 2Page 6 (10)Influence of l
Page 126 and 127: Appendix 2Page 8 (10)Red line : 0.1
Page 128 and 129: Appendix 2Page 10 (10)Study of aver
Page 130: Appendix 3Page 2 (2)Evaluation of h
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UIC comfort tests - VTI

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