Metro Transit Service Reliability Measures Assessment

Transcription

1 Metro Transit Service Reliability Measures Assessment Chen-Fu Liao Department of Civil, Environmental, and Geo- Engineering (CEGE) Senior Staff Meeting, 5/9/2017

2 Outline 1 Background & Objectives 2 Methodology & Measures 3 Analysis Results 4 Recommendations 5 Summary 2

3 Background Automatic data collection systems (AVL, APC etc.) have been deployed to improve operation management and provide real-time information to the public Metro Transit uses on time performance (OTP) to monitor service reliability In the literature, various methodologies have been developed to measure system performance and improve service reliability Alternative service reliability measures used by other transit agencies 3

4 Objectives Identify transit service reliability measures that may be applicable to bus and light rail services Expand the definitions of transit service reliability, determine which ones are applicable to Metro Transit s services Measure reliability of high-frequency service and explore different measures used for different type of service Assess identified measures that might be used effectively by Metro Transit Provide a proof of concept of how these measures could be applied using available operations data 4

5 Methodology Reviewed 18 service reliability measures used in the transit industry or found in the literature (e.g., schedule adherence, travel time reliability/delay, headway, and others) Refined the list to 8 performance measures to better understand the purpose and effectiveness of these measures based on the availability of existing operations data Finalized 4 service reliability measures for analysis on high frequency services 5

6 Service Reliability Measures On-Time Performance How often are trains/buses approximately on-time? Excess Wait Time How much longer than half the headway should I expect to wait for a trip I regularly ride? Gap Assessment How frequent are gaps in a service? Lateness How late are the late services? 6

7 Percentile On-Time Performance (OTP) 120.0% 100.0% 80.0% 60.0% 40.0% 20.0% Distribution of a Transit Departure Time at a Stop OTP Threshold Early OTP = 73% Late 0.0% 9:00 9:03 9:06 9:09 9:12 9:15 9:18 9:20 Time Schedule 9:04 7

8 Excess Wait Time Obs. n time Obs. 3 Obs. 2 time time Additional customer wait time computed from the coefficient of headway variations (i.e., ratio of headway standard deviation over the average headway) Obs. 1 time Schedule Headway 10 min 9:04 9:14 time Scheduled wait time = 5 min 8

9 Gap Assessment Gap 1 Gap 2 Gap 3 Actual Schedule Headway 1 Headway 2 Headway 3 time time For example, a service with 10-minute scheduled headway: Measures GAP20* GAP40 Assessment Criteria % of services with gaps less than 12 min. % of services with gaps less than 14 min. *GAP20 is used as a default measure for gap analysis in this presentation 9

10 Percentile Lateness 120.0% Distribution of a Transit Departure Time at a Stop 100.0% 80.0% 60.0% Early 90% of Late Services 40.0% 20.0% 90% lateness = 8 min Late 0.0% 9:00 9:03 9:06 9:09 9:12 9:15 9:18 9:20 Time Schedule 9:04 10

11 Results - Bus Route #5, #18 & #84 (All Day Average in Jan. 2016) Route OTP (%) Gap (%) Excess wait time (min) Lateness (min) 5 NB 87.9% 83.1% SB 85.5% 79.1% NB 82.7% 80.4% SB 75.6% 74.9% NB 94.7% 87.9% SB 95.3% 88.3%

12 Results - LRT Blue and Green Lines (All Day Average in Jan. 2016) Route OTP* (%) Gap (%) Excess wait time (min) Lateness (min) 901 NB 89.1% 93.3% SB 80.2% 89.2% EB 76.1% 86.5% WB 87.6% 88.2% *LRT within 1 minute early to 4 minutes late are considered as on-time. 12

13 Selection Criteria Is the service reliability measure easy to interpret? Is data available for both historical reporting and real-time applications? Can the metric provide a different perspective as compared to current OTP? Can the metric support best operational practices? 13

14 Recommendations List of Metrics Selected for Further Discussion On-Time Performance Excess Wait Time Gap Assessment 90 Percentile Lateness Rationale for Advancement or Abandonment for Analysis Advance current standard metric, helpful for providing context and comparison. This is the most well-understood reliability metric at Metro Transit. Abandon difficult to interpret the metrics because the computed results are based on ratios or coefficients that are not as easily understood as good or poor and the operations staff is not as confident what an appropriate threshold might be that can be aligned clearly with customer expectations or promises. Advance a simple measure to assess percentage of service that operates within a specific gap threshold that is aligned with existing operations standards for acceptable headway performance. Allows business to set a different gap threshold by service type, time of day, etc. It is particularly applicable for light rail and bus rapid transit service. Advance is a simple measure that helps staff understand how late is late? for those observations that do not meet the standard on-time threshold 14

15 Minutes Percentage Sample Results RTE #19 100% 95% 90% 85% 80% 75% 70% Route 19 (All Dir, All Day) Average OTP & Gaps Average OTP Average Gap Year/Month Route 19 (All Dir, All Day) Average Lateness Average Lateness (min) Year/Month 15

16 Lateness (min) OTP or Gap % 13 High-Frequency Buses 100% OTP and Gap by Time Period 90% 80% 70% AVG OTP (%) AVG Gap (%) 60% Early Morning AM Peak Mid Day PM Peak Late Evening All Day Time Period Lateness by Time Period Early Morning AM Peak Mid Day PM Peak Late Evening All Day Time Period AVG Lateness (min) 16

17 Summary Reviewed and identified 18 common service reliability measures Four service reliability measures were finalized for further evaluation: on-time performance (OTP), excess wait time, gap assessment, and the 90 th percentile of lateness Applied the finalized service reliability measures on 13 high frequency routes and 2 LRT lines using 38-months (Jan Feb. 2017) of transit operations data Applied selection criteria to evaluate how the selected measures are applicable to transit services and how they might be used most effectively by Metro Transit 17

18 Summary (cont.) In addition to OTP, gap assessment and the 90 th percentile lateness measures were recommended for implementation Metro Transit has already adopted the gap assessment measures into monthly Key Performance Indicators (KPI) report Gap assessment measures have been implemented for high-frequency buses and A Line Gap assessment for LRT will be implemented as soon as some data quality issues are resolved 18

19 Acknowledgement This project is sponsored by Metro Transit, a service of the Metropolitan Council, under contract #14I072 TAP committee members: John Levin, Rachel Dungca, Matthew Broughton, Joel Huting, Joey Reid, Kristin Thompson, Ellen Skog, Lisa Johnson, Edward Meyer, Ben Rajkowski, Sean Molloy, Katie Roth, Joseph Herron Center for Transportation Studies (CTS), UMN 19

20 Chen-Fu Liao University of Minnesota