Mobility Data | Real-time transit information (RTI)

Rider Benefits

Decrease Wait Times

Riders perceive time spent waiting at stops to be much longer than it actually is. Real-time information decreases perceived wait time, and also reduces actual wait time by allowing riders to time their arrival at stops in order to minimize waiting.

A study in Seattle found that RTI decreases perceived wait times by approximately 45 seconds and actual wait time by 2 minutes.

Brakewood, Candace, Sean Barbeau, and Kari Watkins. “An Experiment Evaluating the Impacts of Real-Time Transit Information on Bus Riders in Tampa, Florida.” Transportation Research Part A: Policy and Practice 69 (November 2014): 409–22. https://doi.org/10.1016/j.tra.2014.09.003.

Brakewood, Candace, Francisca Rojas, Christopher Zegras, Kari Watkins, and Joshua Robin. “An Analysis of Commuter Rail Real-Time Information in Boston.” Journal of Public Transportation 18, no. 1 (March 2015): 1–20. https://doi.org/10.5038/2375-0901.18.1.1.

Chow, William, David Block-Schachter, and Samuel Hickey. “Impacts of Real-Time Passenger Information Signs in Rail Stations at the Massachusetts Bay Transportation Authority.” Transportation Research Record: Journal of the Transportation Research Board 2419, no. 1 (January 2014): 1–10. https://doi.org/10.3141/2419-01.

Dziekan, Katrin, and Karl Kottenhoff. “Dynamic At-Stop Real-Time Information Displays for Public Transport: Effects on Customers.” Transportation Research Part A: Policy and Practice 41, no. 6 (July 2007): 489–501. https://doi.org/10.1016/j.tra.2006.11.006.

Dziekan, Katrin, and Arjan Vermeulen. “Psychological Effects of and Design Preferences for Real-Time Information Displays.” Journal of Public Transportation 9, no. 1 (February 2006): 1–19. https://doi.org/10.5038/2375-0901.9.1.1.

Ferris, Brian, Kari Watkins, and Alan Borning. “OneBusAway: Results from Providing Real-Time Arrival Information for Public Transit.” In Proceedings of the 28th International Conference on Human Factors in Computing Systems - CHI ’10, 1807. Atlanta, Georgia, USA: ACM Press, 2010. https://doi.org/10.1145/1753326.1753597.

Ji, Yanjie, Liangpeng Gao, Yingling Fan, Chu Zhang, and Ruochen Zhang. “Waiting Time Perceptions at Bus and Metro Stations in Nanjing, China: The Importance of Station Amenities, Trip Contexts, and Passenger Characteristics.” Transportation Letters, November 2, 2017, 1–7. https://doi.org/10.1080/19427867.2017.1398854.

Liu, Yang, Jing Shi, and Meiying Jian. “Understanding Visitors’ Responses to Intelligent Transportation System in a Tourist City with a Mixed Ranked Logit Model.” Journal of Advanced Transportation 2017 (2017): 1–13. https://doi.org/10.1155/2017/8652053.

Papangelis, Konstantinos, John D. Nelson, Somayajulu Sripada, and Mark Beecroft. “The Effects of Mobile Real-Time Information on Rural Passengers.” Transportation Planning and Technology 39, no. 1 (January 2, 2016): 97–114. https://doi.org/10.1080/03081060.2015.1108085.

Reed, T.B. “Reduction in the Burden of Waiting for Public Transit Due to Real-Time Schedule Information: A Conjoint Analysis Study.” In Pacific Rim TransTech Conference. 1995 Vehicle Navigation and Information Systems Conference Proceedings. 6th International VNIS. A Ride into the Future, 83–89. Seattle, WA, USA: IEEE, 1995. https://doi.org/10.1109/VNIS.1995.518822.

Watkins, Kari Edison, Brian Ferris, Alan Borning, G. Scott Rutherford, and David Layton. “Where Is My Bus? Impact of Mobile Real-Time Information on the Perceived and Actual Wait Time of Transit Riders.” Transportation Research Part A: Policy and Practice 45, no. 8 (October 2011): 839–48. https://doi.org/10.1016/j.tra.2011.06.010.

Reduce Travel Times

Transit service can be very dynamic due to unplanned service changes RTI allows riders to choose the path that minimizes their travel time, and, especially for frequency-based service, gives riders an exact expected arrival time. Simulations show that the ability to select the fastest itenerary can significatnly reduce the average travel times for a transit system.

A number of simulated models indicate that widespread use of RTI can significantly reduce travel times.

Cats, Oded, Haris N. Koutsopoulos, Wilco Burghout, and Tomer Toledo. “Effect of Real-Time Transit Information on Dynamic Path Choice of Passengers.” Transportation Research Record: Journal of the Transportation Research Board 2217, no. 1 (January 2011): 46–54. https://doi.org/10.3141/2217-06.

Fonzone, Achille, and Jan-Dirk Schmöcker. “Effects of Transit Real-Time Information Usage Strategies.” Transportation Research Record: Journal of the Transportation Research Board 2417, no. 1 (January 2014): 121–29. https://doi.org/10.3141/2417-13.

Hickman, Mark D., and Nigel H.M. Wilson. “Passenger Travel Time and Path Choice Implications of Real-Time Transit Information.” Transportation Research Part C: Emerging Technologies 3, no. 4 (August 1995): 211–26. https://doi.org/10.1016/0968-090X(95)00007-6.

Stone, Merlin, and Eleni Aravopoulou. “Improving Journeys by Opening Data: The Case of Transport for London (TfL).” The Bottom Line 31, no. 1 (March 12, 2018): 2–15. https://doi.org/10.1108/BL-12-2017-0035.

Zargayouna, Mahdi, Amine Othman, Gerard Scemama, and Besma Zeddini. “Impact of Travelers Information Level on Disturbed Transit Networks: A Multiagent Simulation.” In 2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2889–94. Gran Canaria, Spain: IEEE, 2015. https://doi.org/10.1109/ITSC.2015.464.

Increase Peace of Mind

Riders using RTI spend less time waiting at stops and know when a vehicle will arrive. This leads to increased feelings of safety and peace of mind, particularly if riders are waiting at night.

In Seattle, 32% of survey respondents reported increased feelings of safety as a result of RTI.

McCord, Mark R., Rabi G. Mishalani, and Mahsa Ettefagh. “Effect of Real-Time Passenger Information Systems on Perceptions of Transit’s Favorable Environmental and Traffic Reduction Roles.” Transportation Research Record: Journal of the Transportation Research Board 2538, no. 1 (January 2015): 102–9. https://doi.org/10.3141/2538-12.

Agency Benefits

Gather Valuable Data

Realtime information isn’t just useful to riders. Transit agencies can use data from RTI sensors for a wide variety of planning and decision making purposes. Without RTI, collecting this sort of data is often expensive and time consuming.

AVL data from Utrecht, Netherlands was used to identify bottlenecks in the transit system and provided insight into actual performance.

G. Strathman, James, Thomas J. Kimpel, Kenneth Dueker, Richard L. Gerhart, and Steve Callas. Evaluation of Transit Operations: Data Applications of Tri-Met’s Automated Bus Dispatching System. Vol. 29, 2002. https://doi.org/10.1023/A:1015633408953.

Mesbah, Mahmoud, Graham Currie, Claudia Lennon, and Trevor Northcott. “Spatial and Temporal Visualization of Transit Operations Performance Data at a Network Level.” Journal of Transport Geography 25 (November 2012): 15–26. https://doi.org/10.1016/j.jtrangeo.2012.07.005.

Oort, Niels van, Daniel Sparing, Ties Brands, and Rob M. P. Goverde. “Data Driven Improvements in Public Transport: The Dutch Example.” Public Transport 7, no. 3 (December 1, 2015): 369–89. https://doi.org/10.1007/s12469-015-0114-7.

Stewart, Colin, Ehab Diab, Robert Bertini, and Ahmed El-Geneidy. “Perspectives on Transit: Potential Benefits of Visualizing Transit Data.” Transportation Research Record: Journal of the Transportation Research Board 2544, no. 1 (January 2016): 90–101. https://doi.org/10.3141/2544-11.

Tribone, Dominick, Laura Riegel, Ritesh Warade, and David Barker. “Measuring Transit Agency Performance Using Open Realtime Data.” Transportation Research Board, 2016. https://trid.trb.org/view/1393881.

Increased Ridership & Satisfaction

Increased ridership and customer satisfaction are good for any transit agencies. Many studies show that RTI leads to small gains in ridership and significant gains in ridership satisfaction.

Chicago and New York both found a 2% improvement in ridership direction attributable to real-time information on bus lines. In Seattle, 92% of riders using RTI reported being more satisfied with overall transit servce.

Carlin, Kelly, and Greg Rucks. “Interoperable Transit Data: Enabling a Shift to Mobility as a Service.” Rocky Mountain Institute, n.d. https://www.rmi.org/insight/interoperable-transit-data/.

Gooze, Aaron, Kari Edison Watkins, and Alan Borning. “Benefits of Real-Time Transit Information and Impacts of Data Accuracy on Rider Experience.” Transportation Research Record: Journal of the Transportation Research Board 2351, no. 1 (January 2013): 95–103. https://doi.org/10.3141/2351-11.

“Measuring Transit Agency Performance Using Open Realtime Data,” n.d. https://rmi.org/wp-content/uploads/2017/03/consortium_approach_to_ITD_report2016.pdf.

Monzon, Andres, Sara Hernandez, and Rocio Cascajo. “Quality of Bus Services Performance: Benefits of Real Time Passenger Information Systems.” Transport and Telecommunication 14, no. 2 (January 1, 2013). https://doi.org/10.2478/ttj-2013-0013.

Tang, Lei, and Piyushimita (Vonu) Thakuriah. “Ridership Effects of Real-Time Bus Information System: A Case Study in the City of Chicago.” Transportation Research Part C: Emerging Technologies 22 (June 2012): 146–61. https://doi.org/10.1016/j.trc.2012.01.001.

Return on Investment

RTI systems pose a significant initial cost to transit agencies; however, studies have shown that RTI boosts ridership and quickly pays back this investment. Additionally, RTI provides many other benefits to riders, transit agencies and society at large making it an excellent investment.

Transit agencies in Chicago and New York City found that real-time information paid for itself in three months by increasing ridership.