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Evaluation of Travel Time Methods to Support Mobility Performance Monitoring:
Zaragoza Bridge (Page 2 of 3)

Data Collection Details

The City of El Paso Street Department, Zaragoza Bridge provided hourly outbound border crossing statistical data for the three days of collection and the U.S. Customs Management Center (CMC) provided daily inbound data for the 3 days. The City of El Paso also provided daily Zaragoza truck crossing data for the period August 2000 through July 2001 and the CMC provided monthly data for that period. These data were evaluated for an assessment of the variability in travel conditions at the Zaragosa Bridge. The goal of this analysis process is to obtain statistically useful data with as few data collection days as possible. In order to customize the data collection activities at the Zaragosa Bridge, the following steps were conducted:

  • Define significant "seasonal" variations,
  • Define significantly different days of the week,
  • Identify traffic streams that experience significantly different conditions, and
  • Estimate the number of days needed for the data collection survey.

As shown in Table 3, there is some variation in the commercial traffic by month. Due to project constraints, data collection needed to occur between late May and early September 2001. From Table 3, the two months with the greatest average volumes during this data collection window were June and August.

Table 3. Monthly Traffic Distribution of Outbound Commercial Vehicles
Month 1998 1999 2000 1998-2000 Average
January 28,622 24,077 30,457 27,719
February 31,928 24,958 31,742 29,543
March 34,434 29,682 34,606 32,907
April 31,296 26,982 27,816 28,698
May 31,849 26,624 34,120 30,864
June 29,351 32,169 35,072 32,197
July 27,804 26,987 32,600 29,130
August 27,107 29,700 38,989 31,932
September 26,754 30,885 32,084 29,908
October 29,889 29,979 32,144 30,671
November 25,483 30,742 32,905 29,710
December 23,709 28,860 29,535 27,368
Total 350,224 343,644 394,070 362,646

Source: Data collected from U.S. Customs and compiled by the Texas Center for Border Economic and Enterprise Development

Tables 4 and 5 show that there is a significant difference in commercial traffic between weekdays and weekends and, further, there is a significant difference between Monday and Friday and the three mid-week days. Weekend traffic is 8 percent of typical weekday traffic and Monday/Friday traffic is 76 percent of typical Tuesday/Wednesday/Thursday traffic. It was determined that collecting three days of data, from Tuesday through Thursday, would provide an adequate number of data samples to represent "typical" conditions.

Table 4. Sample Month – Daily Traffic Distribution of Commercial Outbound Vehicles for June 2001
Day Day of Week Outbound
1 Friday 1,369
2 Saturday 514
3 Sunday 0
4 Monday 1,203
5 Tuesday 1,304
6 Wednesday 1,349
7 Thursday 1,418
8 Friday 1,480
9 Saturday 490
10 Sunday 0
11 Monday 1,281
12 Tuesday 1,360
13 Wednesday 1,282
14 Thursday 1,326
15 Friday 1,349
16 Saturday 392
17 Sunday 0
18 Monday 1,229
19 Tuesday 1,349
20 Wednesday 1,266
21 Thursday 1,192
22 Friday 1,294
23 Saturday 423
24 Sunday 0
25 Monday 1,190
26 Tuesday 1,243
27 Wednesday 1,179
28 Thursday 1,150
29 Friday 1,274
30 Saturday 368
Total empty cell 29,274

Source: City of El Paso Street Department, Zaragoza Bridge

Table 5. Averages for Sample Month – Daily Traffic Distribution of Outbound Commercial Vehicles for June 2001
Day of Week Week 1 Week 2 Week 3 Week 4 Week 5 Average
Sunday empty cell 0 0 0 0 0
Monday empty cell 1,203 1,281 1,229 1,190 1,225.75
Tuesday empty cell 1,304 1,360 1,349 1,243 1,314.00
Wednesday empty cell 1,349 1,282 1,266 1,179 1,269.00
Thursday empty cell 1,418 1,326 1,192 1,150 1,271.50
Friday 1,369 1,480 1,349 1,294 1,274 1,352.20
Saturday 514 490 392 423 368 437.40

Source: City of El Paso Street Department, Zaragoza Bridge

From discussions with U.S. Customs, we learned that backups at the Zaragoza Bridge typically did not occur on the U.S. side and, when they did, they did not grow very long. However, on the Mexican side, backups occurred more frequently, which reflected the more stringent U.S. Customs inspection methodology.

Data Collection Procedures

The data collection stations selected for the crossing were chosen because of the particular actions that occur at each site. Segments defined by the data collection stations were used to determine the commercial vehicle travel times and freight delay. As illustrated in Figures 2, 3, 6 and 8, the data collection sites could be located at:

  • An advance station located upstream of the commercial vehicle queue – IB-1 and OB-1.
  • The import station (primary inspection booths before detailed, or secondary, inspection) – IB-2 and OB-2.

Data collection was conducted by recording commercial vehicle license plates as vehicles crossed fixed points within the data collection sites. Survey individuals or teams, were placed at each of the four data collection sites to record commercial vehicle license plate data. The various photographs in this report display the facilities on both sides of the border, including station locations and major and secondary points of inspection.

Collectors at these locations would record the last five characters of the front, lower-left license plate of as many trucks as possible that passed their location. When trucking firms register many vehicles at once, they often get assigned sequential license plate numbers. Using the last five characters helps to ensure that as different trucks operated by the same firm travel across the bridge that they are uniquely identified. License plate information was entered into Handspring Visor PDAs (handheld computers) with a special application designed for this project. Each entry was time-stamped with the current date and time. Prior to each day's collection, all PDAs were synchronized to the same time. Prior experience indicated that recording the entire license plate was too time-consuming and that entering only the last four characters did not provide adequate distinction between different vehicles, so the project team chose to record the last five characters.

The team frequently had difficulty reading two common types of license plates at this crossing. One was from the city of Chihuahua and the other was from the state of Chihuahua. One was difficult to read because of its bright yellow color, the other because of an image on the plate that overlays one of the readable digits and partially obscures it.

On the U.S. side, the queue of Outbound trucks crossing the border did not extend beyond the vicinity of the tollbooths during our collection. However, on the Mexican side, the Inbound queue would extend out to the feeder road where trucks enter from the Juarez street system. When this occurred, the data collector at the starting location would have to move further from the initial checkpoint to a point beyond the end of the queue. In this way, they could continue to record trucks before they began their wait at the end of the line. When this or any other event of interest occurred, the collectors would use an "EVENT" feature of the PDA software to record it.

For the IB-1 starting location, the supervisor would record the distance from any data collection point other than the original position (which would be in the Customs area near the original checkpoint). During post-processing, the data from all locations nearer to the bridge than the farthest location would be adjusted to include the additional travel time from the farthest location to the original location. The travel time would be computed at free-flow speeds, since there would have been no queue at the times that the data were collected at these closer locations. In this way, the data all would appear to be collected from the same location, the one most distant from the bridge.

Data Collection Sample Size

Sample sizes are typically not a concern with videotape or handheld data entry devices, because the data collection includes a large number of vehicles. However, minimum sample sizes should be verified with variability values from field data. Early research found that sample sizes from 25 to 100 license matches were necessary for a given roadway segment and time period (Turner, et. al.). In general, there were sufficient records each day to meet this requirement.

Data Collection Equipment

As outlined in the "Data Collection Procedures" section above, Handspring Visor PDAs were used as the data entry device and proved adequate to the task. Low-end models with 2MB of storage capacity were selected as the application and data size were projected to be well below this limit. The Handspring Visors use the Palm OS (operating system) and have faster processing speeds (at least in side-by-side comparison with this application) and larger screen sizes than comparable models from Palm Computing.

A custom application was developed for the Palm OS that allowed the data collectors to identify their locations (e.g., IB-1, OB-2), the number of open booths (primarily used for the customs inspection booths), special events or other comments, and license plate information. A screen shot of the application interface is shown in Figure 11.

Photo of Handspring Visor PDA data collection device and software application.
Figure 11. Data Collection Device and Software Application

The data were downloaded via a serial cable directly from the application into a text file on the field laptop computer, which was a Dell Latitude CPx H running with a 500 MHz Pentium III processor.

Data Collection Summary

Table 6 shows the number of commercial vehicle license plates recorded for each of the stations on each of the data collection days. Table 7 shows the average daily traffic volume as recorded by the El Paso Street Department International Bridges tollbooth operations (Outbound direction) and U.S. Customs (Inbound direction). (Mexican Customs combines hourly traffic for all three bridges: Zaragoza, Cordova, and Santa Theresa, so a particular bridge's hourly volumes from that source were not distinguishable). Hourly volumes are used in the calculation of delay; those are shown with the delay calculations in Tables 8 through 19.

Table 6. Number of Commercial Vehicle License Plates Collected
Station 6/26/01 6/27/01 6/28/01
IB-1 870 981 988
IB-2 999 1,044 1,037
OB-1 837 821 826
OB-2 965 959 955
Total 3,671 3,805 3,806

Table 7. Average Daily Traffic at the Zaragoza Bridge
Direction 6/26/01 6/27/01 6/28/01
Inbound 1,171 1,066 1,015
Outbound 1,243 1,179 1,150
Total 2,414 2,245 2,165

Data Quality Steps

At the end of each day of data collection, the supervisor would collect the PDAs and download the data into the field laptop computer where it was stored on the hard drive. The data would be examined for any anomalies and transferred across the Internet to a secondary location for backup purposes. The IB-1 and IB-2 data would be merged together and license plates from the two locations would be "matched" using a spreadsheet developed in Microsoft Excel. As it is easy to mistake certain characters, particularly letters that looked like numbers, the license plate data was pre-processed. All 'I's were replaced with '1's; all 'O's, 'D's, and 'Q's were replaced with '0's; all 'S's were replaced with '5's; and all 'Z's were replaced with '2's. In addition, the data collectors were instructed to always use '1's for 'I's and '0's for 'O's (i.e., to use the digit, rather than the letter).

Occasionally, collectors would be unsure about a license plate and would append "QQQ" to their entry. This would typically occur when several trucks passed the collector in rapid succession or if one truck blocked the license plate of another and he or she could only manage a quick glimpse. This would allow the supervisor to search the downloaded data for a potential match by using the travel times of other trucks that were recorded in the same general time frame. During this process, the supervisor could identify the few records in which the data collector forgot to press "ENTER" after recording a license plate before recording the next one. These ten-character entries could be split into two and the time for the first interpolated from the adjacent entries if they were less than a minute or so apart.

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