Western Cascadia Border Operations: delay and the impact on supply chains Anne Goodchild April 23, 2008 Assistant Professor Civil and Environmental Engineering University of Washington

Graduate Students Li Leung Susan Albrecht

Previous Research Impact of border crossing time variability on regional supply chains –On average delays are modest for FAST approved vehicles –Delays are more problematic for nonFAST vehicles –Carriers are very knowledgeable about average and standard deviation of delay –2 standard deviations used as expected variability and built into schedule –Very long delays (> 2 hours) are very disruptive –The cost of variability is low Regional industry is not tightly scheduled due to commodity profile, typical distances and ability to predict travel times Data from Pacific Highway Crossing, GPS data, interviews with carriers and existing sources TT

Delay increases cost beyond average delay Responses to variability –Buffer time –Terminal time Cost is a function of the Pacific Northwest market –Schedules are designed to about 4 hour accuracy –More significant for scheduled or time sensitive industries such as fresh seafood and air freight DS

4 of top 5 crossings in Ontario Source: BTS

Southbound Routes ORIGINS West Lower Mainland Rest BCAlberta East Lower Mainland Whatcom West Canada East Canada TOTAL DESTINATIONS Alaska 0.1% 0.2% East Canada 0.1% Whatcom 10.5%0.6%0.2%0.1% 11.6% Puget Sound 34.9%0.7%0.8%0.2% 0.4%37.1% West WA 4.4%0.2%0.1% 4.8% East WA 3.2% West USA 28.4%1.7%0.7%0.1% 31.0% Rest USA 11.6%0.4% 12.1% TOTAL 93.2%3.7%1.9%0.4%0.2%0.1%0.5% Seattle to Vancouver ~ 150 miles Source: WCOG AP

Border Crossing Time Distribution 4 hours20 minutes Carriers had different responses to border delay than urban congestion delay.

Disruptions off-hours Some of the largest delays occur off-peak

Long delays are not infrequent

What is the cause of 2 hour delays? Compare truck arrival data from BCMOT to delay data from probe vehicles If the patterns are consistent we expect that demand is driving the delay If they are not consistent we expect it is a supply side or operational problem

If served at non-FAST rate If all served at FAST rate

If served at non-FAST rate If all served at FAST rate

Arrival Pattern - All Spring Mondays

Delay Pattern – All Spring Mondays

Summary Variability: –Delay incurs cost beyond the average –The economic cost of this is low at Blaine due to the characteristics of regional trade –Significant cost from very long delays Western Cascadia has a unique profile of trade –Typical travel distances –Commodity profile –Consistent pattern of truck arrivals Very Long Delays: –A significant proportion of the delay is from secondary sources –Supply and demand side delay patterns can be observed in many cases –We are currently exploring these phases and summarizing observations

Dataset Comparison (Southbound) FAST vehicle distributions match in the two datasets, therefore we assume the nonFAST data for June 2006 is reasonably representative of average nonFAST crossing times. The average wait time for nonFAST vehicles is distinctly longer than for FAST vehicles, but the standard deviation is not. Over the three day period the average arrival rate per lane for the WCOG data is the same for FAST and non- FAST (21.5 vehicles per hour) but FAST service rates are shorter (86 seconds compared to 119, 121 for the two non-FAST lanes), so differences in wait time are due to differences in service rates rather than differences in arrival rates. ProbeWCOG Average wait time FAST 23 minutes 22 minutes Standard deviation FAST 24 minutes 21 minutes 90 th Percentile FAST 47 minutes Average wait time nonFAST 1 hour 23 minutes Standard deviation nonFAST 26 minutes

Seasonal Variation Some of the largest delays occur off-season