Back Continue

HCMAG Home
Overview
Introduction
Getting Started
Problem 1
Problem 2
Problem 3
Problem 4
Problem 5
Problem 6
Problem Index
Datasets
Search

 

Sub-problem 1b - Page 9 of 9

ID# C201B09

Sub-problem 1b: Maxwell Drive PM Peak Hour - With Conditions

Uncertainty Issues
Estimating site-generated traffic is a challenge. Itís difficult to say with assurance how much traffic will be generated. Thus, a sensitivity analysis has value. It pays to look at variations in volume, both up and down from the projected numbers, to see what trends exist in cycle length, level of service, queue length, etc.

For this particular intersection, letís look at three situations: the base case (Dataset 10), a condition with 30% more site-generated traffic (Dataset 13), and a condition with 30% less site generated traffic (Dataset 14).

The results are presented in Exhibit 2-18. Itís interesting that increasing the site-generated volumes by 30% raises the cycle length substantially from 65 to 77 seconds. The delays also increase from an average of 28.7 seconds to 34.4 seconds. However, when the site-generated traffic is lower by 30% there isnít a significant change. The cycle length stays at 65 seconds, the average delay drops only marginally from 28.7 to 28.5 seconds.
 
Exhibit 2-18. Maxwell Drive Effects of Generated Traffic
Scenario Cycle Length Performance Measure EB WB NB SB OA
LT TH RT Tot LT TH RT Tot LT TH RT Tot LT TH RT Tot
Dataset 10 C-4 65.0 Delay 38.8 19.5 22.6 15.4 34.4 32.5 17.3 39.5 24.3 25.1 38.0 31.0 28.1 34.2 28.7
Queue 4.6 10.3 - 2.2 17.6 - 2.3 2.0 2.8 - 8.0 1.2 3.9 - -
Dataset 13 77.0 Delay 39.3 24.7 27.0 28.4 43.3 41.4 19.8 39.4 27.5 27.3 44.7 33.9 27.6 38.2 34.4
Queue 5.1 13.2 - 3.9 21.3 - 3.5 2.9 4.3 - 9.5 1.8 4.3 - -
Dataset 14 65.0 Delay 38.8 18.6 22.0 11.0 34.4 32.7 16.6 31.0 23.0 22.4 38.0 29.7 28.1 34.2 28.5
Queue 4.6 9.7 - 1.4 17.6 - 1.6 1.3 1.9 - 8.0 0.8 3.9 - -

Exhibit 2-19. Maxwell Drive Delay Patterns among Scenarios

Itís hard to see the trends in delays, etc. directly from the table. A graphic is useful. Exhibit 2-19 shows a radar plot of the delay trends. Each axis of the wheel is used to present the delay for a given movement. The lines and symbols show the delay for a given scenario. All five operational solutions discussed in Exhibit 2-17 and Exhibit 2-18 are included. If you look at the plots for C-4 (the base case) and Datasets 11 and 12, that trend is clear. The pattern for Dataset 11 is outside the pattern for C-4, which makes sense since the site traffic volumes for Dataset 11 are 30% greater than for C-4. The pattern for Dataset 12 is inside the pattern for C-4 for a similar reason. The site-related traffic is 30% less than in C-4. The patterns for scenarios C-7 and C-8 are different. Most notably, in both of those scenarios there are more lanes available for the northbound and southbound lefts. In C-7, weíve provided two left-turn lanes on both approaches. In C-8, there are three lanes being shared among the lefts, throughs, and rights, both northbound and southbound. As a result, the SL delays in particular, and the NL delays to a lesser extent, are noticeably smaller than they otherwise might be if the extra lane capacity had not been provided (i.e., the pattern in C-4 would have still applied).

[ Back ] [ Continue ] to Discussion