Скачать или смотреть Route optimisation for community and non-emergency medical transportation

This video focuses on the challenges of implementing a route optimisation algorithm to automatically generate and optimise efficient routes and schedules for community transport, paratransit, non-emergency medical transport (NEMT / NEPT) and other patient transport planning problems.

Many factors are involved in planning and automated dispatching for NEMT. Passengers may have target pickup or drop-off times (e.g. doctor’s appointment), ridesharing is common and certain drivers may be preferred (particularly for matching outbound and return journeys). There are limits on onboard time (i.e. total journey time), picking up or dropping off late, and passengers having to wait onboard a stationary vehicle for another passenger’s pickup or dropoff time. These limits cannot always be met, meaning we need to trade-off the different factors to keep within KPIs as much as possible.

Most commercial route optimiser engines can’t solve these problems for one simple reason – it can be more efficient to delay a pickup rather than serving it as soon as the driver can, and they can’t model this. The ODL Live optimiser has Pickup Time Optimisation – which means it can delay a pickup to minimise onboard journey time and waiting onboard time, whilst balancing this against other factors like lateness.

The ODL Live algorithm does the following - (1) assigns passengers to drivers, (2) determines the sequence of pickups and drop-offs, (3) decides when drivers should take breaks and (4) determines the best pickup times for passengers to maximise KPIs. Using ODL Live for optimising patient or passenger transportation greatly reduces the workload for human planners, and enables automated realtime control, where new ad-hoc jobs are automatically scheduled, and jobs are re-assigned from late running drivers. Better control boosts efficiencies, helping to reduce CO2 emission, and leads to a more reliable service, increasing customer satisfaction.