future dispatching bill cumpston and jason lawrie

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Future Dispatching Bill Cumpston and Jason Lawrie

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Page 1: Future Dispatching Bill Cumpston and Jason Lawrie

Future DispatchingBill Cumpston and Jason Lawrie

Page 2: 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

Page 3: Future Dispatching Bill Cumpston and Jason Lawrie

OPTIMISE Minimize Distance

Page 4: Future Dispatching Bill Cumpston and Jason Lawrie

OPTIMISE Current Rules

Page 5: Future Dispatching Bill Cumpston and Jason Lawrie

OPTIMISE Time

Page 6: Future Dispatching Bill Cumpston and Jason Lawrie

Various algorithms – zone, distance, cover

Fleets have different requirements

Explanations are complicated

Not yet perfect

Dispatch is Complicated

Page 7: Future Dispatching Bill Cumpston and Jason Lawrie

Pickup Addresses

Destination Addresses

Requested Pickup Time

ASAP or Pre-Booking

Requested Vehicle Attributes (WAT, etc.)

Our Current Algorithm Inputs

Page 8: Future Dispatching Bill Cumpston and Jason Lawrie

Preferred vehicle or driver

Current passenger wait time

Relative priority of attributes (must do maxi)

Driver plotting

Vehicle vacant time

Blacklist preferences

Our Current Algorithm Inputs

Page 9: Future Dispatching Bill Cumpston and Jason Lawrie

Driving time from current position

Time criticality (e.g. meeting a train)

Current driver earnings per hour

Driver rewards earned

Driver penalties incurred

It will not be getting simpler!

Page 10: Future Dispatching Bill Cumpston and Jason Lawrie

Driver end of shift time and location

Distribution (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 ….

Page 11: Future Dispatching Bill Cumpston and Jason Lawrie

Customer experience vs. Cost Reduction?

Driver fairness vs. rewards and penalties?

Many things are Trade-offs

Page 12: Future Dispatching Bill Cumpston and Jason Lawrie

High level categories provide a guide

This is combined with an “input” weighting

Add reward or penalty scores

Car or job with highest score wins

Weighting Based Algorithm

Page 13: Future Dispatching Bill Cumpston and Jason Lawrie

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?

Page 14: Future Dispatching Bill Cumpston and Jason Lawrie

“Their Score”

Will increase over time until they get a job

Rewards or penalties will affect their scores

In a localised region (e.g. rank) the highest score in a similar vehicle will get job first

What will drivers see?

Page 15: Future Dispatching Bill Cumpston and Jason Lawrie

Click “Explain” on any offer

Get scores for every vehicle for that offer

Can explain to drivers if needed

Can be used to tweak weighting

But why did .….. get job …… ?

Page 16: Future Dispatching Bill Cumpston and Jason Lawrie

THANK YOU!

Questions?