Reliability of Stockholm Subway - Index of

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$AI\TIEBOLAGET . STOCKHOLMS .SPÅRVÄGAR$

The dip in punctuality level in 2006 and 2007 for the three lines corresponds to the dip in level of satisfaction for the same time period. It supports the idea that punctuality is important for customers. One can notice the difference in punctuality of the lines and the level of satisfaction: the Blue line is the most punctual one nevertheless passengers of the line are the least satisfied with it. The difference can probably be explained with the different sensitivity of the passengers of the lines to punctuality. The Green line has more regular service than other lines; its headways are shorter therefore expected waiting time due to train delay will be on average shorter as well. Thus, the Green line commuters are supposed to be less sensitive to the train punctuality comparing to the Red and the Blue lines passengers. However, this is a suggestion which may more profoundly be studied in the future. The aim of SL for the whole transit network including subway, busses and commuter trains, during the spring 2010 to have minimum 75% of passengers that are satisfied with the service and maximum 10% that are unsatisfied with it. Concerning passengers of Stockholm subway the results of the survey (SL, 2009) show that 78% passengers are satisfied with the service while the share of unsatisfied commuters reaches 8%. See the figure 1.5. Figure 1.5 Level of passengers‟ satisfaction in subway (%), autumn 2009 14
The results of 2009 fit the SL aim of 2010. It means that passengers are satisfied enough according to the SL expectation. Nonetheless, it is necessary to wait for the results of the spring 2010 to define if it is a regular tendency or just a variability of the data. Besides, SL uses an independent contractor to operate and maintain the subway system. According to the agreement between SL and the actual subway operator there are stipulated bonuses for the operator in case of a punctual train service. That is why the operator is interested in a reliable transit too. In November 2009 the Hong Kong MTR Corporation became the operator of Stockholm subway. It is a new player in the Swedish transportation market. They have definitely introduced new solutions in the subway operations which will certainly influence overall reliability of the system and the customers‟ satisfaction which are of interest to study. SL has a source of data which can be widely used to examine the performance of the Stockholm subway. Data is electronically collected and stored in the database RUST. The database contains information on travel delays, travel and dwelling time. Applying computer analysis it is possible to investigate the changes of subway service performance on any date or during any time period. At the moment the company does not use the data widely and relies more on manually collected data of ÅF Group, AB. Next year there are plans in the company to begin more active RUST data using. To be confident in data reliability they carry out comparing it with manually collected data to reach as good concordance as possible. 15
Page 1: Reliability of Stockholm Subway A N
Page 5: Acknowledgments I am heartily thank
Page 8 and 9: 4.2.5 Rolling stock ...............
Page 10 and 11: Transit service reliability is a wi
Page 12 and 13: system operates 30 trains per hour
Page 16 and 17: 1.3 Research Objectives Concerning
Page 18 and 19: consuming and requires data that ma
Page 20 and 21: study case he also studies the impa
Page 22 and 23: scheduled one. The parameter can be
Page 24 and 25: 3.2 Measures of regularity 3.2.1 He
Page 26 and 27: 3.3 Analysis The analysis of Stockh
Page 29 and 30: Chapter 4: Description of the Stock
Page 31 and 32: Table 4.1 Lines of Stockholm subway
Page 33 and 34: there are two tracks for Nockebyban
Page 35 and 36: tramline of Tvärbana. Globen is th
Page 37 and 38: transfer between the platforms for
Page 39 and 40: Leaving passengers also some cases
Page 41 and 42: Figure 4.9 Maximum speed change alo
Page 43 and 44: The set of messages sending by inte
Page 45 and 46: distance, about 10 m. It fixed the
Page 47 and 48: the case when the information on fo
Page 49 and 50: Figure 4.14 Input table to select r
Page 51 and 52: Chapter 5: Study case: Green line 5
Page 53 and 54: 5.2 Timetable analysis Stockholm su
Page 55 and 56: One can notice that average headway
Page 57 and 58: HÄS HÄG JOL VBY RÅC BLB ILT ÄBP
Page 59 and 60: HÄS HÄG JOL VBY RÅC BLB ILT ÄBP
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6:30 7:00 7:30 8:00 8:30 9:00 9:30
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HÄS HÄG JOL VBY RÅC BLB ILT ÄBP
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Relative frequency Relative frequen
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For the platform of the northern di
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5.4 Detailed analysis at stations A
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6:30 7:00 7:30 8:00 8:30 9:00 9:30
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6:30 7:00 7:30 8:00 8:30 9:00 9:30
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6:30 7:00 7:30 8:00 8:30 9:00 9:30
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Chapter 6: Conclusions 6.1 Summary
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The other topic of data processing
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Litman Todd, Valuing Transit Servic
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Table A.1 On-time performance at st
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Sample mean, s st. deviation, s2 CV
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N mean, s st. deviation, s2 CV max,
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mean, s Standard deviation, s 2 CV
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Table A.6 Waiting time at stations
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Table A.7 Table of the stations wit
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