Tracking with ETA update

HERE Route Matching v8 continuously computes routes while the vehicle is travelling, to update the ETA. After the initial route planning, call the router again, for example, every few minutes, providing the GPS trace, to get an updated ETA.

Activate this feature by &routeMatch=2 and put the trace into the POST body.

Basic Scenario

Vehicle keeps sending its planned route + its GPS trace so far.

The service responds with an updated ETA.

Driven for 3 hours

• Route Matching confirms no rest taken
• No via point reached or skipped
• No rest sequences learned or matching along this path/time

Route from current location to the destination

• Consider truck restrictions, real time traffic + traffic patterns
• Consider legal driver rest times
• Consider driver is already in service for 3 hours
• Go through all via points to the destination
• Consider (and optimize for) the country truck bans, rest during truck bans, rest on ferries …

ETA Predition Levels

Breaks & rest times taken in reality

Country regulations enforce periodical breaks & rests

• After hours driven or in service
• Short breaks and nightly rests

In reality, drivers take earlier/different and longer rest times

• At their favorite truck stops or restaurants
• At their logistics company hubs
• Unload or load freight (partial truck load jobs)
• Change drivers, trailers ...
• Sometimes not directly along the planned route

They may have special situations

• 2 drivers, swapping instead of resting
• Special permissions or restrictions/rules of the logistics company

For the ETA it is important to learn/predict the real rest times/locations

Route Matching can automatically learn real rest behavior

• Customers can choose the learning granularity
• Per start+destination and/or per arrival time slot, or per driver, truck, weekday ...

Driver took break/rest

Route Matching detects legally applicable rest(s) taken

• Checks whether this rest location/duration is prefix of a learned sequence

If not, then route from current location to the destination...

• Consider legal driver rest times, driving time used until next legal rest, remaining via points ... If prefix of (one of the) learned stop sequences
• If currently resting then plan the learned remaining rest time right here
• Switch off legal driver rest times
• Instead plan intermediate stops with the learned rest locations/times

Driver took another break/rest (or not)

Route Matching detects that the taken rest location/time doesn‘t fit to a learned sequence (anymore)

• Or another learned sequence now fits better

Or detects that the next expected (from learning) rest didn‘t happen

• If no other learned stop sequences match the behavior so far
• Then continue like „no learned sequences available“

Driver met or skipped a via point

Route Matching detects which of the planned via points have already been taken or skipped

• By comparing the actually driven path with the planned route

Route using only the remaining via points

• From current position
• No change on learning or rest time behavior

Driver has switched off tracking device

Often drivers activate the tracking very late

• minutes or hours after start, or after resuming from rest

Often drivers switch off tracking during a rest

Sometimes drivers switch off tracking for a while

• Due to netowrk coverage gaps, roaming/cost issues, empty battery, privacy concern..

Route Matching tries to bridge such gaps

• For missing pieces at the start assume one of the learned rest sequences have taken place
• For gaps during driving figure out whether it was just a rest, just driving, or a mix
• Can met/skipped via points still be detected?
• If possible then continue on the best matching learned stop sequence

Arrival

Driver (or shipper) confirms arrival

Route Matching analyzes the drive trace & actual rest sequence taken

If (despite gaps at start/intermediate/end) the rest sequence can be used for learning

Then check similarity to an existing learned stop sequence, if match

• then increase likelihood for this stop sequence for the future
• And adjust the location/duration/time along route for the existing learned sequence from the new observation
• This incremental learning automatically adjusts obsolete or outlier observations over time (self adjusting, self healing)

If no match then learn it as a new sequence

• Likelihood to apply learned stop sequences depends on number of observations
• Likelihood also means: At the start of a journey Route Matching assumes the stop sequence with the most observations ...
• ... until actual stops (or expected stops not taken) make Route Matching reconsider the best applicable sequence