QR Customers from Darra, Chelmer to Benefit from Extra Train Services During Peak Times

Photo Credit: TravellerQLD [CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0)] / Wikimedia Commons

Beginning 13 May 2019, customers of Queensland Rail coming from Darra Station, Chelmer stand to benefit from the extra train services that will be added to the Springfield line and six other train lines to carry more passengers during the busy hours.

The additional weekly train services was announced ahead of timetable improvements planned this 2019. These changes will be available in the TransLink Journey Planner beginning mid-April.

The extra 32 weekly services to the Redcliffe Peninsula, Cleveland, Springfield, Shorncliffe​, Ferny Grove​,Gold Coast, and Airport lines would add 14,000 seats during peak hours in the morning and afternoon.

number works n' words Ad

​Monday to Friday additions

Line ​Departing station ​Departure time ​Arrival station​Arrival time
​Redcliffe Peninsula ​Kippa-Ring station7.10am ​Central station8.05am
​Cleveland​Cleveland station
6.39am ​Central station7.34am
​ClevelandCentral station5.09pm Cleveland station6.05pm

​Monday to Thursday additions to the services already running on a Friday

Line ​Departing station ​Departure time ​Arrival station​Arrival time
​Springfield​Springfield Central station6.51am ​Central station7.32am
Shorncliffe ​Shorncliffe station
7.39am ​Central station8.16am
Shorncliffe Central station6.58am Shorncliffe station7.35am

​Friday additions to the services already running Monday to Thursday

Tower Ad
Line ​Departing station ​Departure time ​Arrival station​Arrival time
​Ferny Grove​Ferny Grove station7.25am ​Central station ​7.56am
​Gold Coast​Varsity Lakes station5.55am ​Central station ​7.14am
Airport Central station7.16am ​Domestic Airport station7.40am
Airport ​Domestic Airport station7.49am ​Central station8.13am
​ClevelandCentral station5.32pm Cleveland station6.35pm

The additional train services is Queensland Rail’s response to customer feedback, and was the result of analyzing patronage data, wait times, and operational efficiencies.