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B.1 Data for public transit planning, marketing and model development. 17 participants 10 countries Australia Austria Brazil Canada Chile France Germany Israel Nigeria USA. Chair: Orlando Strambi Resource paper: Gerd Sammer 2 contributed papers: Chapleau, Trépanier and Chu
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B.1 Data for public transit planning, marketing and model development 17 participants 10 countries Australia Austria Brazil Canada Chile France Germany Israel Nigeria USA • Chair: Orlando Strambi • Resource paper: Gerd Sammer • 2 contributed papers: • Chapleau, Trépanier and Chu • van der Waerden, Timmermans and Bérénos • Discussant: Linda Cherrington • Rapporteur: Martin Trépanier
What is changing in the public transport scene (1)? • Transit agencies/operators have increasing focus on business practices (in some cases, a market-like situation) • Performance, benchmarking, customer satisfaction • Multi-modal, multi-agency, multi operator • Public policy to increase use of public transport as beneficial to sustainability • Increased concern about personal security
What is changing in the public transport scene (2)? • Transit rider response to surveys are increasingly more difficult • New technology tools for data collection– and data analysis • AVL, AFC, APC, cameras... • Increasing modeling capabilities and processing power • Data analysis requirements and choice of technology must be integrated • But, do they provide a complete picture?
Are these our data needs? • Data Needs • Ridership (and revenue) • Detailed info about trip stages and intermodality • Needs of specific groups of the population • Performance/Service quality (objective/subjective) • Customer satisfaction (subjective) • Benchmarking (requires comparable data) • Allocation of passenger miles (and revenue) • Market potential (new users, lost users) • Attitudes of the general public towards public transport
Are these our data sources? • Data sources • Administrative (network/operational) • Routes, schedules • Inter-modal terminals, stations, stops • Vehicles • Operators • Costs/Revenues • ITS (passive) • AVL (automatic vehicle location) • AFC (automatic fare collection) • APC (automatic passenger counting) • Surveys (active) – remember! this is a survey methods conference • Others • Spatial data (GIS) – census, land use
What type of surveys do we need? • If passive data is available, surveys can be more focused • HH surveys focused on PT info at higher level of spatial resolution) • OBAD on-board surveys • Customer satisfaction, preferences, attitudes • Special needs / Mobility impaired • Other markets? • What type of analyses will we do with this (and other) data? • Model user behavior • Identify market segments • Identify relevant service improvements • To retain current users • To attract new users • To improve Revenue/Cost
Research needs • Ways to cope with decreasing response rates • Integrated use of additional sources of data • Automated data • PT system data • Land use/Census data • Methodological developments • Data fusion for PT information • Analysis of variability in multiday data • Data on potential markets • Survey improvements • Adapt HH surveys to PT data needs • Accommodate improved level of spatial resolution
Data harmonization • Not much discussion on the workshop • But, some good examples identified • On board surveys • Common practice, similar approaches • Automated data collection provides similar data • Important • Harmonization of attitudes towards public transportation
Attitudinal Surveys for P.T. “In the event of conflict P.T. has priority over car traffic”