Public transport in New Zealand is facing significant challenges.
On one hand, continued growth is driving demand for additional capacity and coverage, particularly in new growth areas. On the other, NLTF funding constraints and targets for increasing the private share of public transport operating expenditure are pressuring Councils to find ways to increase revenue and reduce costs.
In this context, improving the efficiency of existing services has never been more critical. A key aspect of this is ensuring timetables are both reliable and optimised. Data-driven approaches offer an effective way to enhance timetable efficiency and improve the passenger experience while minimising costs.
Optimising bus timetables presents a compelling alternative to increasing fares or reducing service levels. By leveraging real-time and historical data, transport authorities can make evidence-based decisions that enhance network performance and passenger satisfaction.
Efficiency and Reliability
While improving reliability is often perceived as costly, many timetable optimisations can be achieved without increasing expenses. Some key strategies include:
- Reducing excessive dwell times at timing points – If dwell times at specific locations are unnecessarily long, they can be adjusted to reduce operating costs, shorten journey times, and increase patronage.
- Optimising for changing traffic conditions – Adjusting schedules to match traffic congestion patterns throughout the day ensures passengers receive a timetable that is both realistic and efficient. Faster schedules outside peak hours and improved reliability during congestion periods enhance the passenger experience.
- Ensuring runtimes are realistic and appropriate – Using statistical analysis, runtimes can be fine-tuned to strike a balance between operators meeting their KPIs and ensuring passenger expectations for reliability are met.
Optimising bus timetables can lead to reduced costs, improved passenger satisfaction, increased ridership, and higher farebox revenue. Lateness, uncertainty, and earliness of services all negatively impact passenger journey decisions, ultimately affecting patronage and revenue.
Collaboration for Data-Driven Optimisation
GPS data, such as that provided by Radiola’s Dynamis platform, gives Councils real-time insights into bus location and speed. Dynamis also stores rich datasets on historical on-time performance, which transportation authorities can use to optimise timetables effectively.
Radiola has partnered with Better Bus Planning to simplify the process of timetable optimisation. Better Bus Planning leverages historical data recorded by Radiola’s Dynamis Real-time System to support evidence-based optimisation. Together, we have developed a standardised format for sharing bulk schedule adherence data which allows for smooth data exchange, making it faster and more cost effective to optimise timetables effectively.
Conclusion
While funding constraints present challenges, leveraging Dynamis GPS data and investing in timetable optimisation has the potential to unlock significant efficiency gains without major expenditure. Better Bus Planning, a specialist New Zealand bus planning consultancy, can assist Councils in assessing potential benefits from timetable optimisation and provide expert support in implementing data-driven scheduling improvements.