The traveler costs of unplanned transport network disruptions an activity based approach
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The traveler costs of unplanned transport network disruptions: An activity-based approach. Erik Jenelius Royal Institute of Technology, Sweden Lars-Göran Mattsson Royal Institute of Technology, Sweden David Levinson University of Minnesota. Background.

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The traveler costs of unplanned transport network disruptions: An activity-based approach

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The traveler costs of unplanned transport network disruptions an activity based approach

The traveler costs of unplanned transport network disruptions: An activity-based approach

Erik Jenelius Royal Institute of Technology, SwedenLars-Göran Mattsson Royal Institute of Technology, SwedenDavid Levinson University of Minnesota


Background

Background

  • How to value increases in travel time due to unplanned transport network disruptions (floods, snowfall, severe car crashes etc.)?

  • In cost-benefit analysis

  • For bonus provision for restoration work

  • State of practice: Standard value of time

  • Related but different: Value of reliability/variability

variability

extreme events

travel time

average travel time


The traveler costs of unplanned transport network disruptions an activity based approach

Aim

  • Build theoretical foundation for the traveller delay costs of unplanned transport network disruptions

  • Capture the following aspects:

    • Large delays – marginal values may be misleading

    • Long disruptions – more than one trip may be affected

    • Unexpected events, imperfect information – less ability to adjust travel and daily schedule optimally

    • Flexibility – smaller intrusion of delay

    • Time of day – less room for schedule adjustments later


Framework

Framework

  • Trips are made between two activities, e.g., home and work

  • Costs arise as we rather spend time at home or at work than in car

  • Schedule preferences expressed as utility maximization

  • We consider three activities (”morning”, ”work”, ”evening”), two trips (”morning commute”, ”evening commute”)

  • Calibration against empirical results from Tseng & Verhoef (2008)


Variables

Variables

  • Marginal activity and travel utilities:u1(t), u2(t–ξts2), u3(t), ν

  • Marginal utility of activity 2 (work) may depend on arrival time:Parameter ξ controls schedule flexibility:ξ = 0clock-time only ξ = 1duration only

  • Travel times T1, T2 (assumed exogenous here, departure time dependent in paper)

  • Departure times td1, td2, arrival times ts2 = td1 + T1, ts3 = td2 + T2


The model

The model

  • Daily utility U determined by departure times


Travel costs

Travel costs

  • To avoid new notation, assume utility is money metric. Marginal WTP functions for activity/travel transitions:

  • Assume optimally timed trips normally

  • FOC and marginal VOT can be found

  • Travel cost


Delay costs

Delay costs

  • Journey delays T1, T2

  • Delay costs

  • Depend on:

    • journey delays (magnitude and distribution)

    • schedule adjustments (information)

    • work schedule flexibility


Adjustments

Adjustments

  • Evidence from I-35W bridge collapse

  • We consider:

    • no adjustment

    • no + optimal

    • over-adjustment

    • over + optimal

    • optimal adjustment


Calibration

Calibration

  • Calibrated against time-varying WTP for home/work from Tseng & Verhoef (2008) and some findings from Hess et al. (2007)

  • Parameterized logistic functions for marginal WTP functionsa1(t), a2(t – xts2), a3(t): min, max, steepness, location


Numerical results

Numerical results

  • Delay on both morning and evening trip (baseline tr. time 240 min)

  • Fixed (left) vs. flexible (right) work hours


Numerical results1

Numerical results

  • Delay on morning trip only or evening trip only

  • Fixed (left) vs. flexible (right) work hours


Some conclusions

Some conclusions

  • Delay costs increase rapidly with length of delay

  • Better adjustments (information) can reduce costs significantly

  • Flexible work hours great if journey delay occurs early

  • Previous model-based valuations of disruption impacts (I-35W bridge collapse etc.) have probably underestimated delay costs

  • We here only considered work trips and individuals’ own stated costs


Thank you

Thank you!


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