future dispatching

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Future Dispatching. Bill Cumpston and Jason Lawrie. REQUIREMENTS . TAXIS As many bookings as possible Wait times not major consideration Driver not normally relevant. HIRE CARS, WATS Control numbers of bookings Wait times critical for hire cars, important for WATs. Driver often relevant. - PowerPoint PPT Presentation

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Future DispatchingBill Cumpston and Jason Lawrie

REQUIREMENTS

TAXISAs many bookings as possibleWait times not major considerationDriver not normally relevant

HIRE CARS, WATS

Control numbers of bookingsWait times critical for hire cars, important for WATs.Driver often relevant

OPTIMISE Minimize Distance

OPTIMISE Current Rules

OPTIMISE Time

Various algorithms – zone, distance, coverFleets have different requirementsExplanations are complicatedNot yet perfect

Dispatch is Complicated

Pickup AddressesDestination AddressesRequested Pickup TimeASAP or Pre-BookingRequested Vehicle Attributes (WAT, etc.)

Our Current Algorithm Inputs

Preferred vehicle or driverCurrent passenger wait timeRelative priority of attributes (must do maxi)Driver plottingVehicle vacant timeBlacklist preferences

Our Current Algorithm Inputs

Driving time from current positionTime criticality (e.g. meeting a train)Current driver earnings per hourDriver rewards earnedDriver penalties incurred

It will not be getting simpler!

Driver end of shift time and locationDistribution (E.g. “trip” run fairness)Pre-allocation (E.g. private jobs)Distribution to sub-networks or “friends”Changes for peak or normal periods

And that’s not all ….

Customer experience vs. Cost Reduction?Driver fairness vs. rewards and penalties?

Many things are Trade-offs

High level categories provide a guideThis is combined with an “input” weightingAdd reward or penalty scoresCar or job with highest score wins

Weighting Based Algorithm

Can we eliminate zones?Perhaps have some “special” regions (ranks)All distance calculations based on actual directions (including current time of day)

Who Likes Zones and Layering?

“Their Score”Will increase over time until they get a jobRewards or penalties will affect their scoresIn a localised region (e.g. rank) the highest score in a similar vehicle will get job first

What will drivers see?

Click “Explain” on any offerGet scores for every vehicle for that offerCan explain to drivers if neededCan be used to tweak weighting

But why did .….. get job …… ?

THANK YOU!

Questions?

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