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Dynamic Pricing Leveraging Technology to Manage Pricing During Changing Conditions Kapsch TrafficCom

Kapsch TrafficCom Dynamic Pricing - IBTTA · 2017. 7. 18. · | Get It Right, Out of the Gate Elasticity of price demand: quick primer How consumer behavior responds to changes in

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  • Dynamic PricingLeveraging Technology to Manage Pricing During Changing Conditions

    Kapsch TrafficCom

  • Dynamically Priced Managed Lanes

    Shaping traffic through the value of timeStraightforward modeling and system acceptanceBehavior changes: Short-term – incidents Long-term – behavior

    Leverage technology for predictable flexibility and consistencyFuture work

  • www.kapsch.net |

    Get It Right, Out of the Gate

    Elasticity of price demand: quick primer How consumer behavior responds to

    changes in price

    May appear positive, especially at outset, but demand is elastic over time1

    Establish value of time2

    Surveys

    Traffic studies

    Demographic data Consultants

    Political climate

    1Brent, Daniel A., and Austin Gross. "Dynamic Road Pricing and the Value of Time and Reliability (Revised June 2017)." DEPARTMENT OF ECONOMICS WORKING PAPER SERIES2016, no. 07 (June 2017): 3-4. Accessed June 02, 2017. http://faculty.bus.lsu.edu/papers/pap16_07.pdf.2Patterson, Tyler. Personal Interview: On Dynamic Pricing in WSDOT. June 19, 2017. Personal interview to discuss experiences with dynamic pricing in WSDOT's system, Kapsch TrafficCom, Austin.

    http://faculty.bus.lsu.edu/papers/pap16_07.pdf

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    Get It Right, Out of the Gate

    Using price to control traffic flow and capacitySimulationAcceptance testingGo Live! May entail period of human monitoring and controlling…

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    We Had It Right…Don’t expect “set it and forget it”

    Reasons to adapt: Patrons change behavior – long-term

    adaptation Incidents – short-term adaptation Politics

    The importance of flexibility: Adaptation strategy: conservative or

    aggressive? Manual adaptation Automation Agility

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    AdaptationFlexibility for successFlexibility for success

    Manual overrides and response: important, but not our topicObjective: automation that is Flexible: can be configured to adapt

    to changes in elasticity of price Insightful: reacts well under both

    expected and unexpected conditions

    Reactive: able to respond to the real world

    Effective: provides predictable influence over traffic patterns, without excessive jitter or manual intervention

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    Accomplishing the GoalApproach for an adaptive algorithm

    Practical exampleRatio of ML:GP occupancy Low ratio expected during non-

    peak Ratio 0.6 - 0.8 peak during

    high-demand

    Short-term & long-term data horizon

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    Set Points

    Set points provide a target for occupancy

    30-Minute Ratio of ML to GP

    Time0

    .2

    .8

    5-Minute Sample Rate

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    30-Minute Ratio of ML to GP

    Time0

    .2

    .8

    Actual traffic

    Minimum toll

    Set Points

    Managed traffic chases set points

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    30-Minute Ratio of ML to GP

    Time0

    .2

    .8Current slice, calculate • Error (∆Current state – set point)

    • Rate of change ( )

    • Integral (stored over time for comparison)

    Set Points

    Application of information from current sample, in real-time

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    Determine Price Change

    ↓↓↓ ↓↓ ↓ 0↓↓ ↓ 0 ↑↓ 0 ↑ ↑↑0 ↑ ↑↑ ↑↑↑

    ErrorCurrent ratio - setpointD

    erivative (rate of change)

    Low error High error

    1. Fuzzy logic lookup2. Integral informs effectiveness of change: short-term impact to elasticity of price demand3. Determine change in price4. Store integral for historic reference – effectiveness

    Error decreasing

    Error Increasing

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    Adaptation PointsProxies for Changing Behavior

    Fuzzy logic output – how much change for each cell?

    Elasticity of price demand impact: Small integral over time == toll rate effective.

    No change needed Large positive integral over time == larger toll

    changes needed. Large negative integral over time == smaller

    toll changes needed.

    Storage of integral informs need to adapt across long-term

    Integral can be used: Direct impact to fuzzy logic result

    As a factor in a PID controller

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    Adaptation PointsFlexibility of Blending Models

    Models can break down: Low traffic

    Low traffic punctuated by spikes

    Technology should have ability to blend algorithms: Over time

    As a ratio

    Different segments or trips

    Time-of-day

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    What About Incidents?Accident in the Managed Lane:

    Upstream traffic slows

    Ratio of ML:GP gets larger; derivative large

    Price increases rapidly in response, limiting new entrants into the ML system

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    What About Incidents?Accident in the General Purpose Lane:

    Upstream traffic slows

    Ratio of ML:GP gets smaller; derivative large

    Price decreases rapidly in response, encouraging new entrants into the ML system.

    Increased utilization of the ML, helping to manage overall traffic flow

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    Flexible Algorithms

    “Sweet spot” of utilization and traffic flow in MLImportant to consider both ML & GPAbility to adapt as consumers adapt ensures performanceEconomical, practical, predictable, and effective

    Graphs courtesy of WSDOT I-405 Express Lanes

    Practical results of adaptability

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    Importance of Simulation

    Support of simulation which incorporates value of time is keyRun scenariosPost-release, use to validate simulator logic

    Hypothesize, test, validate

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    Future StepsMachine learning

    Better traffic & incident prediction: Refined expert systems Neural networks

    Better price determination: Markov decision process Neural networks

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    Conclusion

    Correct utilization of adaptive algorithms can: Improve long-term managed lane performanceReact effectively to short- and long-term behavior changesPerform in a cost-effective and predictable manner compared to

    active human management

  • Thank youfor your attention.John MillerVice President, Back Office Solution Management

    Kapsch TrafficCom

    Kapsch TrafficCom211 E 7th St Ste 800Austin, TX 78701 USAPhone: +1 512 450 6305E-Mail: [email protected]

    Please Note:The content of this presentation is the intellectual property of Kapsch AG and all rights are reserved with respect to the copying, reproduction, alteration, utilization, disclosure or transfer of such content to third parties. The foregoing is strictly prohibited without the prior written authorization of Kapsch CarrierComAG. Product and company names may be registered brand names or protected trademarks of third parties and are only used herein for the sake of clarification and to the advantage of the respective legal owner without the intention of infringing proprietary rights.

    Dynamic PricingDynamically Priced Managed LanesGet It Right, Out of the GateGet It Right, Out of the GateWe Had It Right…AdaptationAccomplishing the GoalSet PointsSet PointsSet PointsDetermine Price ChangeAdaptation PointsAdaptation PointsWhat About Incidents?What About Incidents?Flexible AlgorithmsImportance of SimulationFuture StepsConclusionThank you�for your attention.