Computing and Improving Passenger Punctuality Dennis Huisman 1,2 1. - - PowerPoint PPT Presentation

Computing and Improving Passenger Punctuality

Dennis Huisman1,2

• 1. Econometric Institute & ECOPT, Erasmus Univ. Rotterdam
• 2. Process quality & Innovation, Netherlands Railways

Dutch Railway System

Dense railway system Passenger trains (93%) Cyclic timetable (1 hr) NS operates the main lines until 2025 (85% of the passenger train km) >1 million passenger trips/day >17 billion passenger km/yr Infrastructure management and operations are split

Traditional definitions of (passenger) punctuality

Traditional definitions (1)

• Train punctuality: percentage of arrivals which were on time

compared to the planning. ProRail measures this indicator at 35 large stations. Cancelled trains and renumbered trains are not considered in this indicator.

• Operated trains: percentage of trains which were actually
• perated (possibly renumbered) compared to the planning.
• Note: Two major KPIs in the concession agreement 2005-2014

Traditional definitions (2)

• Traditional passenger punctuality: weighted average of the

train punctuality at 35 large stations. The weights are based

• n forecasted amount of passengers. Cancelled trains and

some predefined transfers are taken into account as well.

• Note: KPI since 2011 for NS next to train punctuality,

major KPI in concession agreement 2015-2024 for NS and ProRail

New method to compute passenger punctuality

Passenger punctuality 2.0

• Passengers assume to arrive according to the advice from

the travel planner, where they ask for a trip from station A to station B at a certain time

• Passenger delay can be computed as the difference

between the “actual” arrival time of the passenger and the expected arrival time according to the travel advice

Passenger punctuality 2.0 - Example

Passenger punctuality 1.0

• Only 1 transfer taken into account (Rotterdam Centraal)
• Punctuality measured in Rotterdam Centraal, Gouda,

Utrecht Centraal, Amersfoort & Zwolle. Passenger trip counts 5 times.

• Passenger trip is “4/5th successful”

Passenger punctuality 2.0

• Both transfers taken into account (Rotterdam Centraal,

Zwolle)

• Punctuality is measured as trip from Rotterdam Zuid to
• Akkrum. Passenger trip only counts once.
• Passenger trip is “not successful”

+10

disruption

Improving missed connections (Delay Management)

Delay Management

• To improve the reliability of the connections, the operator can

decide to delay connecting trains slightly in case of a delayed feeder train.

• Delay management decides which connections to drop and which

to maintain.

• With good delay management, one can have short connections

that are reliable at the same time!

Delay Management - definition

Given

• a planned timetable,
• a set of source delays,
• the passengers’ travel plans

determine

• a new timetable,
• and new travel plans for the passengers,

such that the total delay for the passengers is as small as possible.

Modeling the passenger delay

• The main difficulty in modeling the delay management problem, is

to determine the delay for the passengers.

• If all connections for a passengers are maintained, this delay

equals the delay of the last train.

• If a passenger misses a connection, the travel plan for that

passenger has to be adjusted. The delay will depend on this new travel plan.

Classical Delay Management

• Schöbel (2001, 2006) gave an integer programming formulation for

the Delay Management Problem.

• If a passenger misses a connection, he will wait for the next

train that departs one cycle time later.

• The delay equals
• the delay of the last train if all connections on the path are

maintained;

• exactly one cycle time if a connection is dropped.

Delay Management with Rerouting

• Dollevoet, Huisman, Schmidt and Schöbel (2012) introduced the

concept of passenger rerouting.

• We determine a route through the railway network for each OD pair

explicitly by assuming that the passengers select the fastest path to their destination.

Example wait-depart decision Den Bosch (1)

Example wait-depart decision Den Bosch (2)

Example wait-depart decision Den Bosch (3)

• Applying optimal wait-depart decisions would result in 30%

less passenger delays then having no waiting time rule at all

Disadvantages of this approach

1. Complex mathematical model resulting in too high computation times for real-time rescheduling 2. For every situation a different decision This led to the question if with simple rules-of-thumb a near-optimal solution can be achieved?

• Master thesis Nicole de Lugt (2013)
• Develop rules-of-thumb for wait-depart decisions

Simple rules-of-thumb

• In this example, 2 intervals results based on the median value in

a solution of less than 1% from the optimal solution

To summarize …

• Passenger punctuality can be measured accurately via smartcard

data

• Passenger punctuality will be very important in the coming years
• Passenger punctuality can be improved by less delayed trains,

less cancelled train and less missed connections

• For the latter, exact delay management models or rules-of-thumb

derived from these models could be used

Put Passengers First!