1. Valuation of Travel Time Uncertainty & Delays Joel P. Franklin Assistant Professor, KTH – Transport and Location Analysis

2. Topics Concepts of Travel Time Delay and Variability Brief State-of-the-Art in Research and Practice Selected Research Results: 1.Modeling Variability 2.Value of Variability 3.Measuring Vulnerability

3. Stockholm Congestion Charges: Effects of the Stockholm congestion charges: 30-50% less time in queues & less variability Inner main roads, inbound Inner main roads, outbound Inner streets Inner main roads, northbound Inner main roads, southbound Delay time, PM peak

4. Results from the ongoing National Transport Investment Plan National Transport Investment Plan 2010-2021 Reliability included in CBA for the first time Road: Travel time reliability benefits around 10% of time benefits Rail: 20% of time benefits

5. Some Concepts Start with Delays: Travel times longer than a reference ”ideal” travel time Something can be done to reduce these travel times

6. Some Concepts Travel Time: Freeflow Travel Time

7. Some Concepts Travel Time: Freeflow Travel Time Delay: Recurring Delay

8. Some Concepts Travel Time: Freeflow Travel Time Delay: Recurring Delay Non-Recurring Delay: ”Normal” Delay

9. Some Concepts Travel Time: Freeflow Travel Time Delay: Recurring Delay Non-Recurring Delay: ”Normal” Delay ”Abnormal” Delay

10. Travel Time Implications for Travelers ComponentTraveler Implications Freeflow Travel TimeBest-Case Scenario Recurring Delay Normal Non- Recurring Delay Abnormal Non- Recurring Delay

11. Travel Time Implications for Travelers ComponentTraveler Implications Freeflow Travel TimeBest-Case Scenario Recurring DelayEasily to Plan For Normal Non- Recurring Delay Abnormal Non- Recurring Delay

12. Travel Time Implications for Travelers ComponentTraveler Implications Freeflow Travel TimeBest-Case Scenario Recurring DelayEasily to Plan For Normal Non- Recurring Delay Can be Planned For, With SomeUncertainty:  Buffer Times, Sometimes Early Arrivals Abnormal Non- Recurring Delay

13. Travel Time Implications for Travelers ComponentTraveler Implications Freeflow Travel TimeBest-Case Scenario Recurring DelayEasily to Plan For Normal Non- Recurring Delay Can be Planned For, With SomeUncertainty:  Buffer Times, Sometimes Early Arrivals Abnormal Non- Recurring Delay Beyond What is Planned For; Travelers ”Cope” While En-Route

14. Incorporating into BCA Need Forecasts Not just mean travel time Variability measures: standard deviation? ”Full-distribution” forecasts? Need Valuations How much is standard deviation worth? Or, how much is arriving one minute late worth, relative to departing one minute early?

15. State-of-the-Art ComponentPredictionValuation Freeflow Travel Time Established Engineering Practice Established Value-of-Time Studies Recurring Delay Normal Non- Recurring Delay Abnormal Non- Recurring Delay

16. State-of-the-Art ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Abnormal Non- Recurring Delay

17. State-of-the-Art ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Difficult, but Some Simple Models Available (e.g. Eliasson; Franklin) Developing Theory (e.g. Fosgerau & Karlström); Growing Body of Studies on Value of Delays (e.g. Börjesson et al) Abnormal Non- Recurring Delay 1 2

18. State-of-the-Art ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Difficult, but Some Simple Models Available (e.g. Eliasson; Franklin) Developing Theory (e.g. Fosgerau & Karlström); Growing Body of Studies on Value of Delays (e.g. Börjesson et al) Abnormal Non- Recurring Delay Nearly impossible to predict Network vulnerability studies, e.g. Jenelius 3 1 2

19. Modeling Variability ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Difficult, but Some Simple Models Available (e.g. Eliasson; Franklin) Developing Theory (e.g. Fosgerau & Karlström); Growing Body of Studies on Value of Delays (e.g. Börjesson et al) Abnormal Non- Recurring Delay Nearly impossible to predict Network vulnerability studies, e.g. Jenelius 1

20. Modeling Variability (Eliasson, 2006) How variable will travel times be in future scenarios? Std.Dev. = f( Mean Time; Time of Day; Phase of Queue) Used data from automatic travel time measurements for 41 urban links

21. Some Theory (Fosgerau & Karlström) What’s important to travelers isn’t ”standard deviation”… …but rather, ”lateness” Yet, these can be related to one another, given a scheduling model, e.g.  Marginal utility Time Buffer Time Actual Travel Time Marginal Value at Home Marginal Value at Work

22. Modeling Variability (Franklin, 2009) How variable will travel times be in future scenarios? Mean Lateness = f( Mean Time; Rate of Queue Buildup Freeflow Speed Length of Segment Geographic Area) (same dataset as Eliasson) Not much improvement over Standard Deviation

23. Valuation of Variability ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Difficult, but Some Simple Models Available (e.g. Eliasson; Franklin) Developing Theory (e.g. Fosgerau & Karlström); Growing Body of Studies on Value of Delays (e.g. Börjesson et al) Abnormal Non- Recurring Delay Nearly impossible to predict Network vulnerability studies, e.g. Jenelius 2

24. Valuation of Variability (Börjesson, Eliasson & Franklin) In theory, it’s lateness that should be important Depends on that scheduling model  But is this the correct model? Marginal utility Time Buffer Time Actual Travel Time Marginal Value at Home Marginal Value at Work

25. Valuation of Variability SP Survey: The Direct Approach Departure 1Departure 2 Delay (if you made this trip every day): Once every other month, the train is 45 min delayed. All other trips are on-time. Once every other week, the train is 10 min delayed. All other trips are on-time. Travel time according to the timetable: 3 min shorter than today10 min shorter than today Ticket price 2 kr higher than today10 kr higher than today I choose:  1 1  2 2 Cancel the trip  3

26. Valuation of Variability SP Survey: The Scheduling Approach Departure 1Departure 2 Start Time 25 min later than today5 min later than today Travel Time 15 min longer than today45 min longer than today Ticket Price 7 kr higher than today4 kr lower than today Arrival Time 40 min later than today50 min later than today I choose:  1 1  2 2 Cancel the trip  3

27. Valuation of Variability Findings Estimated values of validity were not the same So, the Direct Approach and the Schedling Approach do not seem equivalent Raises questions about the scheduling model: Is there a such thing as ”fixed” constraint? Is uncertainty per se a cost to be counted? Marginal utility Time

28. Valuation of Variability ComponentPredictionValuation Freeflow Travel Time Established Roadway Engineering Practice Established Value-of-Time Studies Recurring DelayStandard Travel Demand Models Same, or…Vary Value-of- Time by Time-of-Day Normal Non- Recurring Delay Difficult, but Some Simple Models Available (e.g. Eliasson; Franklin) Developing Theory (e.g. Fosgerau & Karlström); Growing Body of Studies on Value of Delays (e.g. Börjesson et al) Abnormal Non- Recurring Delay Nearly impossible to predict Network vulnerability studies, e.g. Jenelius 3

29. A complement: The vulnerability approach ”Vulnerability” approach: Identify critical links (through e.g. vulnerability maps) Analyse how the consequences of a breakdown of given critical links are affected by e.g. an added link

30. Conclusions Travel time reliability important factor in CBA 10-20% extra benefits on average; higher for some projects … even more so when regulations (pricing etc.) and information infrastructure become more important tools than physical investments Predicting Variability: Some simple models for roadway variability; very little for rail, other fixed- schedule services Valuation of Reliability Several estimates of the value of delays But, some problems with the model these are based on (scheduling model) In some contexts, other approaches such as ”vulnerability studies” can help out, such as for rare, unplanned delays