Around 15% of the driven kilometers by bus operators in Amsterdam and Sydney are empty mileage kilometers. In less populous areas this percentage is even bigger and it is set to increase with more zero emission vehicles. The empty mileage trips are the trips from a depot to the first stop of a route, from the last stop from a route to a depot, or between the last stop from a route to the first stop of another route. So, the trips the bus has to make without transporting any passengers.
Current scheduling calculates the duration of empty mileage trips in a very naïve way by distance / average speed, not taking into account the fluctuating pattern of traffic over the day. As a substantial portion of the driven kilometers are from empty mileage trips, it is important to get a good insight in the travel times of empty mileage trips. When the estimated driving times are too high, this can lead to a schedule with more busses and/or drivers than necessary. On the other hand, when the driving times are too tight a bus doesn’t start in time, which can result in fines and reputation damage for the operators. In a lot of situations there is the actual historical driving times for all possible empty mileage trips is unknown. Lynxx has developed a model to estimate these driving times.
The empty mileage travel times are simulated using real world data, resulting in more accurate empty mileage kilometers. To do so a planning API for cars is used. The API is queried to get the driving times between all depots and termini (first and last stops of a route) in the network. To capture the fluctuating behavior of traffic this is done for different times e.g., morning peak, evening peak and interpeak and different day types e.g., a weekday, Saturday and Sunday. These driving times are then processed from driving times with a car for a certain route to driving times with a bus. For example, a bus cannot take certain roads, has a lower maximum speed or can cut off a part by taking a bus lane. Therefore, the data is adjusted using certain rules. In addition, a bus lane analysis is performed to see whether driving times need to be adjusted because a bus lane is being driven. The estimated driving times can than used as an input for the planning software used by the operator. At the moment the repositioning analysis is used in the operation of different bus operators in amongst others the Netherlands, Australia and New-Zealand, where the analysis has result into savings on mileage kilometers up to 2%, reducing the cost of fuel, maintenance and man-hours. Besides, the analysis is also used in different tenders. In the best-case scenario, this has saved up to 6 buses, costing 200k – 500k each.
