Opportunities & Challenges Using Passively Collected Data In Travel Demand Modeling 15 th TRB Transportation Planning Applications Conference Atlantic.

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Presentation transcript:

Opportunities & Challenges Using Passively Collected Data In Travel Demand Modeling 15 th TRB Transportation Planning Applications Conference Atlantic City, NJ May 19, 2015 Andy Mullins Ipek Sener, PhD Rich Lee Texas A&M Transportation Institute

Overview Project background Data Types & Use Review Web survey results Applications to Advance Use of Data Conclusions 2

Project Background Passive data used roadway operations monitoring Stand-alone GPS units used for supplements to personal travel surveys. Mobile phones and particularly smart phones have enhanced supplemental use. Instances of replacement of some forms of travel surveying – like external or corridor. 3

Project Background Barriers to wider use of data in model development? Replacement for traditional data in model development? 4

Data Types & Uses Cell Data Identified efforts directed toward applications in: – Model calibration – Route choice modeling – Trip distribution modeling – Activity-based modeling Numerous sub-regional/corridor applications 5

Data Types & Uses Cell Data Sub-regional/corridor applications examples – Trip length – District-to-district flows – Highway traffic volume Generally comparable 6

Data Types & Uses GPS Supplement to traditional travel survey – Improve accuracy of diaries External data sets – Transit & truck event-driven data GPS-only surveys 7

Data Types & Uses GPS - Smartphones Research in use of other on-board technology with GPS – Mode detection – Purpose imputation App-based data collection – Specific use apps – Passive? 8

Data Types & Uses Bluetooth Initially small geographies & single corridors – Travel times Expanded use – Travel times – O/D matrix estimation – Route choice – Mode detection 9

Data Types & Uses Bluetooth Considerations – Scale – Infrastructure dependent Other Technologies Social Networking Data Smart Card Data 10

Data Uses - Summary Integration of with traditionally collected data Hybrid approaches attractive Key challenges to wider use – Data fusion – Margins of error/sample bias – Data processing standardization 11

Survey of Use of Passively Collected Data MPOs and Model Practitioners Region Characteristics Use of survey data Why/how used passive data used Type of passive data used Concerns about passive data Data merging/imputation 12

Survey of Use of Passively Collected Data Follow-up for details on Use of passively-collected data Model accommodation of passive data Comparisons to other data sources 13

Use of Travel Survey Data 14

Passively Collected Travel Survey Data – Type 15

Passively Collected Travel Survey Data – Use in Travel Modeling 16

Passively Collected Travel Survey Data – Reasons/concerns for not to use 17

Passively Collected Travel Survey Data – Should provide the same info? 18

Passively Collected Travel Survey Data – Should provide the same info? 19 Bias Content Clear accuracy information Need secondary data

Passively Collected Travel Survey Data – Should provide the same info? 20 Additional data worth data loss Supplemental use Change to model development process

Future Efforts Evaluate data content – Full or partial trips – Trip Chaining – Origin, Destination, Route, Mode Precision Data Characteristics – Evaluation of sampling bias – Data expansion 21

Future Efforts Demonstrated use – Case studies – Proofs-of-concept – Small implementations Atypical demand Supplemental vs. exclusive use Continuous data collection 22

Conclusions Passive data collection methods – Technology influences uses – Limitations of use Uses in modeling – Modeling of trip patterns, lengths, times – Mostly supplement traditional surveys – Hybrid uses – Some exclusive use as source for model development 23

Conclusions Increased Use through applications that – Evaluate data Traditional data substitute Data linkage and fusion Establish traditional survey data statistics Potential enhancements by data collectors Potential direct access to data 24

Conclusions Increased Use through applications that – Capitalize on inherent advantages Amount and variety Elements of a continuous source – Non-traditional demand modeling – Evaluate use in forecasting contexts – Alternative model development methods 25

Thank You