Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data
Tài liệu tham khảo
Australian Bureau of Statistics (ABS) [WWW Document], 2016. Reg. Popul. Growth August 2014–15. URL <http://www.abs.gov.au/ausstats/[email protected]/mf/3218.0> (accessed 5.2.16).
Australian Bureau of Statistics (ABS) [WWW Document], 2013. 2011 Census QuickStats. URL <http://www.censusdata.abs.gov.au/census_services/getproduct/census/2011/quickstat/0?opendocumen&navpos%C2%BC220> (accessed 5.2.16).
Bagchi, 2005, The potential of public transport smart card data, Transp. Policy Road User Charging: Theory Pract. W. Saleh, 12, 464, 10.1016/j.tranpol.2005.06.008
Chu, 2016, Reproducing longitudinal in-vehicle traveler experience and the impact of a service reduction with public transit smart card data, Transp. Res. Rec. J. Transp. Res. Board, 2541, 81, 10.3141/2541-10
Chudyk, 2015, Destinations matter: the association between where older adults live and their travel behavior, J. Transp. Health Transp. Travel Mobility Later Life, 2, 50
Dieleman, 2002, Urban form and travel behaviour: micro-level household attributes and residential context, Urban Stud., 39, 507, 10.1080/00420980220112801
Douglas, 1973, Algorithms for the reduction of the number of points required to represent a digitized line or its caricature, Cartogr. Int. J. Geogr. Inform. Geovisual., 10, 112
Gärling, 2003, Introduction: habitual travel choice, Transportation, 30, 1, 10.1023/A:1021230223001
Google Developers [WWW Document], 2015. Gen. Transit Feed Specif. GTFS. URL <https://developers.google.com/transit/gtfs/> (accessed 3.19.16).
Gordon, 1989, Gender differences in metropolitan travel behaviour, Reg. Stud., 23, 499, 10.1080/00343408912331345672
Goulet-Langlois, 2016, Inferring patterns in the multi-week activity sequences of public transport users, Transp. Res. Part C Emerg. Technol., 64, 1, 10.1016/j.trc.2015.12.012
Handy, 1996, Methodologies for exploring the link between urban form and travel behavior, Transp. Res. Part Transp. Environ., 1, 151, 10.1016/S1361-9209(96)00010-7
Herfindahl, 1950
Hirschman, 1945
Hong, 2014, How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales, Transportation, 41, 419, 10.1007/s11116-013-9462-9
Innocenti, 2013, Car stickiness: heuristics and biases in travel choice, Transp. Policy, 25, 158, 10.1016/j.tranpol.2012.11.004
Jánošíková, 2014, Estimation of a route choice model for urban public transport using smart card data, Transp. Plan. Technol., 37, 638, 10.1080/03081060.2014.935570
Kieu, 2015, Passenger segmentation using smart card data, IEEE Trans. Intell. Transp. Syst., 16, 1537, 10.1109/TITS.2014.2368998
Kotval-K, 2015, The socio-economics of travel behavior and environmental burdens: a Detroit, Michigan regional context, Transp. Res. Part Transp. Environ., 41, 477, 10.1016/j.trd.2015.10.017
Kurauchi, 2014, Variability of commuters’ bus line choice: an analysis of oyster card data, Public Transp., 6, 21, 10.1007/s12469-013-0080-x
Kwan, 2016, Algorithmic geographies: big data, algorithmic uncertainty, and the production of geographic knowledge, Ann. Am. Assoc. Geogr., 106, 274
Lee, 2013, Trip purpose inference using automated fare collection data, Public Transp., 6, 1, 10.1007/s12469-013-0077-5
Liu, 2010, Transit users’ route-choice modelling in transit assignment: a review, Transp. Rev., 30, 753, 10.1080/01441641003744261
Ma, 2013, Mining smart card data for transit riders’ travel patterns, Transp. Res. Part C Emerg. Technol., 36, 1, 10.1016/j.trc.2013.07.010
Ma, 2015, Modeling bus travel time reliability with supply and demand data from automatic vehicle location and smart card systems, Transp. Res. Rec. J. Transp. Res. Board, 2533, 17, 10.3141/2533-03
Moran, 1950, Notes on continuous stochastic phenomena, Biometrika, 37, 17, 10.1093/biomet/37.1-2.17
Morency, 2007, Measuring transit use variability with smart-card data, Transp. Policy, 14, 193, 10.1016/j.tranpol.2007.01.001
Munizaga, 2012, Estimation of a disaggregate multimodal public transport origin-destination matrix from passive smartcard data from Santiago, Chile, Transp. Res. Part C Emerg. Technol., 24, 9, 10.1016/j.trc.2012.01.007
Nassir, 2015, Behavioural findings from observed transit route choice strategies in the farecard data of Brisbane, Presented at the Australasian Transport Research Forum, Department of Infrastructure and Regional Development
Nishiuchi, 2012, Spatial-temporal daily frequent trip pattern of public transport passengers using smart card data, Int. J. Intell. Transp. Syst. Res., 11, 1
Pelletier, 2011, Smart card data use in public transit: a literature review, Transp. Res. Part C Emerg. Technol., 19, 557, 10.1016/j.trc.2010.12.003
Prato, 2011, Latent variables and route choice behavior, Transportation, 39, 299, 10.1007/s11116-011-9344-y
Queensland Government [WWW Document], 2016. Gen. Transit Feed Specif. GTFS—South East Qld. URL <https://data.qld.gov.au/dataset/general-transit-feed-specification-gtfs-seq> (accessed 3.19.16).
Rasouli, 2015, Employment status transitions and shifts in daily activity-travel behavior with special focus on shopping duration, Transportation, 42, 919, 10.1007/s11116-015-9655-5
Schlich, 2003, Habitual travel behaviour: evidence from a six-week travel diary, Transportation, 30, 13, 10.1023/A:1021230507071
Schmöcker, 2013, Generation and calibration of transit hyperpaths, Transp. Res. Part C Emerg. Technol., 36, 406, 10.1016/j.trc.2013.06.014
Simpson, 1949, Measurement of diversity, Nature, 163, 688, 10.1038/163688a0
Sun, 2015, Characterizing multimodal transfer time using smart card data: the effect of time, passenger age, crowdedness, and collective pressure, Presented at the Transportation Research Board 94th Annual Meeting
Tao, 2014, Exploring bus rapid transit passenger travel behaviour using big data, Appl. Geogr., 53, 90, 10.1016/j.apgeog.2014.06.008
Tao, 2014, Examining the spatial–temporal dynamics of bus passenger travel behaviour using smart card data and the flow-comap, J. Transp. Geogr., 41, 21, 10.1016/j.jtrangeo.2014.08.006
Thøgersen, 2006, Understanding repetitive travel mode choices in a stable context: a panel study approach, Transp. Res. Part Policy Pract., 40, 621, 10.1016/j.tra.2005.11.004
TransLink [WWW Document], 2016. Go Card Journey Trip. URL <http://translink.com.au/tickets-and-fares/fares/go-card-journey-and-trip> (accessed 5.1.16).
Vacca, 2015, Understanding route switch behavior: an analysis using GPS based data, Transp. Res. Proc. SIDT Sci. Semin., 2013, 56
Viggiano, 2014, User behavior in multiroute bus corridors, Transp. Res. Rec. J. Transp. Res. Board, 2418, 92, 10.3141/2418-11
Yue, 2014, Zooming into individuals to understand the collective: a review of trajectory-based travel behaviour studies, Travel Behav. Soc., 1, 69, 10.1016/j.tbs.2013.12.002
Zhong, 2016, Variability in regularity: mining temporal mobility patterns in London, Singapore and Beijing using smart-card data, PLoS ONE, 11, e0149222, 10.1371/journal.pone.0149222