Development of bus driving cycles using a cost effective data collection approach

Hing Yan Tong*, Ka Wai Ng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Driving cycles are important for vehicle performance evaluations including emissions and fuel/energy consumption estimations. The franchised bus services are currently being extensively used in Hong Kong, however, no driving cycle has been developed specifically for buses. Therefore, this study has developed a set of bus driving cycles using a cost effective data collection approach. On-road bus speed data were collected using the built-in GPS function of smartphones Based on an analysis of the structure of the franchised bus route network and the statistical properties of the collected bus speed data, five significantly different bus driving patterns in Hong Kong were identified. Separate driving cycles were then developed for each identified pattern namely Pattern I(a): Inter-districts; Pattern I(b): Within a District; Pattern II(a): Peaks; Pattern II(b) Off Peak (Day); and Pattern II(c): Off Peak (Night). These patterns indicated significantly longer idling and more aggressive acceleration/deceleration characteristics as compared to other international bus driving cycles. Bus operators and regulating authorities can select appropriate cycles for traditional/electric bus emission and/or energy consumption estimations under specific bus driving patterns. The developed cycles can also fill the knowledge gap in providing a representative platform for the bus emissions testing in Hong Kong.

Original languageEnglish
Article number102854
Number of pages19
JournalSustainable Cities and Society
Early online date16 Mar 2021
Publication statusPublished - Jun 2021

Bibliographical note

© 2021, Elsevier Ltd. This accepted manuscript version is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


  • Bus driving behaviours
  • Bus driving characteristics
  • Bus driving patterns
  • Driving cycles
  • GPS data collection
  • Vehicle Specific Power (VSP)


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