Posted in May 2014

Improved public transport by data driven research

New promising Big Data sources are becoming available in the public transport industry. This data provides insights into both passenger flows and vehicle performance and is of great help to optimize public transport services. Traffic models are able to quickly process this data and to present it on a geographical layer. It enables to evaluate ridership and to compare it with the use of other modes as car and bike traffic. Finally, what-if predictions are available to gain insights into the expected level of cost coverage, service and ridership. These steps are of great support to optimize the public transport network and timetable design as well as its operations. This presentation reveals such opportunities for public transport systems.

Read more:Presentation seminar “Analytics and Scheduling in Public Transport”

How lightrail may enable enhanced service reliability

The introduction of lightrail in The Hague enabled a leap in service quality. The key challenge in other projects is how to incorporate these expected effects into decision making. In Utrecht we succeeded to calculate the expected service reliability impacts and incorporated them into the cost benefit analysis.

Read more: Presentation Danske Bane Konference

Quality improvement by implementing light rail: case RandstadRail

After the introduction of RandstadRail in The Hague, the level of service reliability increased substantially. An integrated package of planning and control instruments was designed and applied to achieve that objective.

Read: UITP Magazine p 1-2 and UITP Magazine p 3

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