ITS Canada Annual Conference and General Meeting. May 2013

Transcription

1 Evaluation of Travel Time Data Collection Technologies: An Innovative Approach for a Large- Scale Network ITS Canada Annual Conference and General Meeting May 2013

2 Study Steps Obtain the traffic data from data providers for the selected freeways, arterials, and ramps of the Province of Ontario; Calculate travel time measures for each road segment in the study area for each data source; Compare alternative technologies with the benchmark (previous MTO Travel Time Studies in 2010);and Recommend the preferred technologies. 2

3 Data Processing (Bluetooth) A two-phase filtering approach was used to clean-up the dataset Phase 1 Ramps: All the matched ID with a Travel Time higher than 3.5 times the Free Flow Travel Time are eliminated Arterials: An approximate travel time range is defined for each segment based on: Free flow travel time Average travel time during peak hours Number of intersections between two consecutive Bluetooth receivers Traffic signal timing 3

4 Data Processing (Bluetooth) Phase 2 An innovative statistical methodology proposed by Dion and Rakha (2006) is used to detect Bluetooth travel time outliers This algorithm works for both freeways and arterials. The algorithm detects outliers that falls outside a validity range, that is determined based upon: Expected average and variance of travel time Number of consecutive data points either above or below the validity range Variability in interval times within an analysis interval 4

5 Travel Time (min) Data Processing (Bluetooth) Time of Day a) Raw travel time data before filtering Travel Time (min) Time of Day b) 5 Travel time data after application of phase 1

6 Data Processing (Bluetooth) Observed Travel Time Min 35 Travel Time (min) Time of Day a) Application of the algorithm 25 Travel Time (min) Time of Day 6 b) Processed travel time data Max

7 Data Processing (TomTom and INRIX) A. Spatial Matching Matching the road section between two consecutive interchanges or intersections (referred to as road Segments) of each data provider with the benchmark 7 a) Continous links through an interchnage b) Broken links at the interchange B. Temporal Matching Establishing a one-to-one correspondence between the data collection days in the benchmark and the days of weeks for TomTom and INRIX data for direct comparison (AM and PM peaks)

8 Evaluation Criteria for evaluation of each data provider against the benchmark: Accuracy Coverage Number of observations Special facilities (Express vs. Collector, HOV vs. GPL) 8

9 Accuracy (Bluetooth) F-test and T-test are conducted to evaluate the Bluetooth technology against GPS data collection F-test: Test for equality of two variances T-test: Test for equality of two means either the variances are equal or different Example of Bluetooth and GPS data comparison (95% significance level) Road type Week # Time of Day F-value F-critical F-test result T- Value T-critical T-test results Ramp 1 AM peak PM peak 1.7E Variances are different Variances are the same Mean are the same 9

10 Accuracy (Bluetooth) Bluetooth Benchmark Average Travel Time (min) Average Travel Time (min) SB to 401 EB 404 SB to 401 WB 404 SB to 401 WB 401 EB to 404 NB (GPL) (HOV) (Exp/Coll) Ramps Bluetooth a) AM Peak Benchmark 400 SB to 401 EB 404 SB to 401 WB 404 SB to 401 WB (GPL) Ramps (HOV) 401 EB to 404 NB (Exp/Coll) Visual Comparison between Bluetooth and GPS for Ramps Segments b) PM Peak 10

11 11 Accuracy (TomTom and INRIX)

12 Accuracy (TomTom and INRIX) Average travel time omethodology: Trajectory method (Izadpanah, 2010) o Description: Building a trajectory of a typical vehicle based on the reported average link speeds for each road segment Variance of travel time omethodology: The sum of variances of links which constitute the road segment Average speed and variance of speed omethodology : Proposed by Hayya et al. (1975) odescription: Estimating average speed and variance of speed based on average travel time and variance of travel time calculated for the road segment 12

13 Accuracy (TomTom and INRIX) Benchmark In Vehicle Navigation System Mobile Phone Probes with GPS Cumm mulative Travel Time (min) Distance (Km) Cumulative Travel Time for Don Valley Parkway Northbound During AM Peak Period 13

14 Accuracy (TomTom and INRIX) 120 Benchmark In Vehicle Navigation System Mobile Phone Probes with GPS 100 Speed (Kph) Distance (Km) Speed Profile for Don Valley Parkway Northbound During AM Peak Period 14

15 Accuracy (Results) Technology/ Data provider Road segment type Highways Arterials Ramps In-Vehicle Navigation Systems (TomTom) 90% 98% 100% Mobile Phone Probes with GPS (INRIX) 91% 98% 100% Bluetooth N/A 100% 100% 15

16 Accuracy - Challenge Travel Tim me (Sec) Run_1 Run_2 Run_3 Run_4 Run_5 Run_6 Run_7 Run_8 Run_9 Run_10 MTO TomTom INRIX Distance (km) 16 Speed for the QEW WB PM Peak Period

17 No of Observation Ave. No. of Obs. per Peak period Mobile Phone Probes with GPS Bluetooth In-Vehicle Navigation System AM PM Benchmark (GPS Equipped Probe Vehicles ) Arterial Ave. No. of Obs. per Peak period Mobile Phone Probes with GPS Bluetooth In-Vehicle Navigation System Benchmark (GPS Equipped Probe Vehicles ) AM PM Highway 17 Average Observations per Peak Period for Highway and Arterial Sections

18 Coverage Missing traffic data for each vendor and road type Technology/ Data provider Length of segments with missing data for each road type (km) Highways Arterials Total length (km) In-Vehicle Navigation Systems (TomTom) Mobile Phone Probes with GPS (INRIX) Bluetooth

19 Special Facilities Express and Collector lanes (e.g. Highway 401 in Ontario) TomTom and INRIX are able to separate traffic data High Occupancy (HOV) versus General Purpose Lanes (GPL) All data sources (TomTom, INRIX, Bluetooth) failed to provide separate traffic data HOV and GPL Express and Collector Lanes 19

20 Conclusions Three data sources (Bluetooth, TomTom, and INRIX) were used to obtain wireless traffic information over a large-scale area within the GTA in Ontario. Based on accuracy evaluation results, there is no evidence to suggest that for 90% of road segments, Bluetooth, TomTom, and INRIX data are statistically different from the benchmark. INRIX provides significantly more observations than Bluetooth and TomTom. Bluetooth ranked second and TomTom third. All three vendors provided more observations than the benchmark. All three data providers had an acceptable coverage. TomTom and INRIX were able to differentiate between express and collectors. All three vendors failed to differentiate between HOV and GPL. 20

21 Acknowledgements Ministry of Transportation Ontario (MTO) for the financial support 21

22 Questions? 22