Within Pitane Mobility version 10, much attention was paid to the new automatic car planning. After all, for many companies the planning of cars is a complex matter that has to take into account many factors such as the range of the car, break and service times of the driver and the use of the right equipment to meet the expectations of the traveler.
In the past period the automatic car planning was further developed and tested on the work floor at the traffic control of Trevvel. This Rotterdam-based company processes more than 6,000 journeys per day and uses Pitane Mobility version 10.
Dynamic planning with checking current traffic information
Because this often also concerns 'last-minute' changes, it was decided to wait until the last moment to select the right car for the assignments. All factors that play a role in determining the right car for a route or trip assignment for travelers such as low-entry, wheelchair transport, boarding via the lift, use of aids, etc. are checked during the dynamic planning.
Different methods to use as a planning system
With group transport, and certainly with school transport, in most cases there is no question of using automatic planning systems for the car because the car and driver are usually already locked in for a longer period.
For target group transport where it is usually possible to order up to 1 hour prior to transport, the software provides a number of possible planning methods, the most striking of which may be the start-up planning. This start-up schedule is relatively easy to determine based on the location of the car in the morning, such as the driver's home address or the base point or garage of the car.
Still getting used to for the planner ...
It becomes more complex when we receive thousands of journey orders during the day that are combined into optimal routes and must be automatically assigned to the right vehicles. Pitane Mobility offers dynamic car planning with control of current traffic information.
For the planner it takes some getting used to and especially figuring out why the machine chose a different car than what he had in mind for the same journey. Further investigation often shows that current traffic information was the reason for the choice made. Other choice elements are then monitoring of the break and scheduling times and the range of the car.