Application of GPS

Simple beginnings We started with the basic premise of measuring legs and dwells We started with the principle of using all results within a SD of the mean

Data example 3866 different movements in a month in august from 1280 in January

First evolutions What more can we do with GPS If we can see where the norm, we can see where the Network fails to deliver If we can see the norm, we can see where things change. If we can measure the norm we can tell the impact of change

Impact of a speed restriction

Carrying the legacy

Improving Right time (to 10 sec’s) We know the exact time a train arrives We know the exact time a train departs We know the exact time a train passes We do challenge manual times We don’t challenge Auto times, we do challenge the associated attribution

Picking up cautionary aspects

SRT measurement

Dwells, Peak and Off peak

Berth offset variability TRUST reported a two minute dwell at a station. ARS logs show that CF1812 signal was not at red and the route from CF1806 was requested at 07:29:13,when 2K12 stepped from GW1816 to GW1814.The train ahead(1F62) was in berth CF804 at that time, so CF1806 should have gone to green. The initial step from GW approach to GW1818 took place at 07:25:49 with ARS reporting 2K12 had “sufficient route up to 1806” at that time

AEGIS- map the assets

AEGIS – pattern identification

Correcting what we find When we find an SRT issue we open up a can of worms Why is it deficient What's the solution Value vs journey time Resource impact/plan capability

Next stage Automated notification of change CIF/GENIUS headcode mapping Measurement of variance before/after RHTT Leg linking MySQL direct DB query interface