Evidence from GTFS-R that Bus Priority Lanes reduce Marginal Delay
Access status:
Open Access
Type
Working PaperAbstract
Bus priority measures such as bus lanes have been widely deployed in order to improve bus performance and attract ridership. The validation of these expected benefits has usually been done at the aggregate level with tolerances for acceptable delay. Newer data sources allow us to ...
See moreBus priority measures such as bus lanes have been widely deployed in order to improve bus performance and attract ridership. The validation of these expected benefits has usually been done at the aggregate level with tolerances for acceptable delay. Newer data sources allow us to track micro delays and relate them to spatially detailed bus priority data. Because schedules are adjusted to account for the benefit of bus priority measures, we hypothesise that bus lanes will result in small reductions in expected delay relative to the schedule even when assessed to the second and at the bus-stop-to-bus-stop level. We further hypothesise that the benefit of bus lane priority measures can be seen in the reduction in the variability of delay relative to the schedule. This study aims to use the GTFS arrival delay data for Sydney from June 2020 to March 2022 in order to analyse the effect of bus-stop-to-bus-stop route characteristics data on bus stop-to-stop marginal delay. This working paper shows the first result using GTFS arrival delay data from March 2021 (i.e. one month) only. The delays are modelled using panel regression with marginal delay and standard deviation of marginal delay as the dependent variables. The independent variables include the presence of priority measures, the traffic volumes, the number of traffic signals and the scheduled travel time. We find that the bus-taxi lanes and bus-HOV lanes are effective in reducing variation in the stop-to-stop marginal delay. The impact on marginal delay itself is mixed due to the interaction of demand, schedule adjustments and the priority measure. These findings quantify the benefits of bus priority measures at a microscale.
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See moreBus priority measures such as bus lanes have been widely deployed in order to improve bus performance and attract ridership. The validation of these expected benefits has usually been done at the aggregate level with tolerances for acceptable delay. Newer data sources allow us to track micro delays and relate them to spatially detailed bus priority data. Because schedules are adjusted to account for the benefit of bus priority measures, we hypothesise that bus lanes will result in small reductions in expected delay relative to the schedule even when assessed to the second and at the bus-stop-to-bus-stop level. We further hypothesise that the benefit of bus lane priority measures can be seen in the reduction in the variability of delay relative to the schedule. This study aims to use the GTFS arrival delay data for Sydney from June 2020 to March 2022 in order to analyse the effect of bus-stop-to-bus-stop route characteristics data on bus stop-to-stop marginal delay. This working paper shows the first result using GTFS arrival delay data from March 2021 (i.e. one month) only. The delays are modelled using panel regression with marginal delay and standard deviation of marginal delay as the dependent variables. The independent variables include the presence of priority measures, the traffic volumes, the number of traffic signals and the scheduled travel time. We find that the bus-taxi lanes and bus-HOV lanes are effective in reducing variation in the stop-to-stop marginal delay. The impact on marginal delay itself is mixed due to the interaction of demand, schedule adjustments and the priority measure. These findings quantify the benefits of bus priority measures at a microscale.
See less
Date
2022-08-22Faculty/School
School of Civil Engineering, The University of Sydney, AustraliaShare