Analytical Procedures for Determining the Impacts of Reliability Mitigation Strategies (2012) / Chapter Skim
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50 C h a p t e r 4 Overview As discussed in Chapter 3, the research team took an empirical approach to the problem of reliability estimation. Before conducting the three main analyses (congestion by source, before-and-after studies of reliability improvements, and statistically based predictive relationships for reliability)
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51 Table 4.1. Travel Time Distribution Statistics: Atlanta Freeways, 2006 (4:00 to 7:00 p.m.)
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52 of the study corridor, the average travel times tend to be higher than those measured in the westbound direction. The eastbound traffic is frequently congested throughout the day, with substantial peaks in both a.m.
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53 entire distribution. Rather than relying on only one percentile calculation or one index, several must be documented to effectively track travel times.
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54 were in order. Based on the skewness of the travel time distributions, the median is a better central tendency statistic to use as a base value for travel time for indices.
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55 Figure 4.4. Peak hour travel time distribution, Atlanta, I-75 northbound, I-285 to SR 120 (2007)
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56 Data requirements for establishing reliability To allow sufficient time for the occurrence of the myriad of events (e.g., incidents, bad weather) that can affect travel times, reliability requires a fairly long history of travel times.
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57 Table 4.6 shows annual incident minutes on an 11-mile stretch of U.S. 101 southbound in California.
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58 Table 4.7) exhibited the same characteristics as the 95th percentile since its base is free-flow speed, which does not change.
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59 Year 2006 2007 2008 Section I-75 NB from I-285 to Roswell Roada TTI 2.046 2.026 1.665 Average TTI 11.271 11.162 9.177 95th Percentile TTI 16.934 17.507 14.800 Buffer Index 0.502 0.568 0.613 80th Percentile TTI 13.974 14.191 11.458 Skew statistic 0.942 1.087 1.514 Daily VMTb 691,399 689,628 N/A Section I-75 SB from I-285 to Roswell Roada TTI 1.312 1.369 1.293 Average TTI 7.665 7.994 7.552 95th Percentile TTI 10.139 10.517 9.868 Buffer Index 0.323 0.316 0.307 80th Percentile TTI 8.353 8.719 8.306 Skew statistic 1.524 1.515 1.461 Daily VMT 691,399 689,628 N/A Section I-75 NB from I-20 to Brookwood TTI 1.350 1.542 1.339 Average TTI 6.710 7.664 6.656 95th Percentile TTI 8.120 10.755 8.031 Buffer Index 0.210 0.403 0.207 80th Percentile TTI 7.097 8.112 7.015 Skew statistic 1.283 1.923 0.771 Daily VMT 616,038 620,959 595,034 Section I-75 SB from I-20 to Brookwood TTI 2.052 2.171 2.067 Average TTI 9.336 9.877 9.404 95th Percentile TTI 13.110 14.270 12.389 Buffer Index 0.404 0.445 0.317 80th Percentile TTI 10.805 11.416 11.042 Skew statistic 1.324 1.120 0.956 Daily VMT 616,038 620,959 595,034 Section I-285 EB from GA 400 to I-75c TTI 1.359 1.481 1.380 Average TTI 9.322 10.162 9.469 95th Percentile TTI 12.548 13.150 12.493 Buffer Index 0.346 0.294 0.319 80th Percentile TTI 10.505 11.382 10.849 Skew statistic 1.148 0.996 1.070 Daily VMT 584,487 588,442 572,211 Table 4.7. Trends in Reliability, Atlanta Freeways (2006–2008)
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60 Figure 4.12. I-75 northbound, I-285 to Roswell Road, peak period.
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61 Both the Buffer Index and the skew statistic indicate there was more spread in the distribution, but the worst travel times (the 80th and 95th percentiles) were decreased.
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62 Table 4.8. Peak Hour and Peak Period Definitions for L03 Study Sections Peak Hour Peak Period City Section Start Start End Length (h)
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63 congested period should not be sharply higher than the estimated demand rate for the second half of the congested period. It is sometimes necessary to smooth out the transition by assuming the congested period extends an additional 5-minute period.
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64 of congestion on the freeway, is quite a bit lower than the theoretical 2,000 vphpl capacity of the freeway (after converting from passenger car capacity to mixed-flow capacity)
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65 Figure 4.16. Volume and reliability on I-580 eastbound at multiple detectors.
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66 same freeway facility. In other words, the breakpoint volume does not appear to be a fixed ratio of the theoretical capacity of the subject section of the facility.
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67 An analysis was undertaken using data from the study sections in Seattle and Atlanta. For comparison with HCM terminology, the team defined SSR in terms of vehicles per hour per lane: • Data were available at 5-minute intervals in the two locations, so the first step was to aggregate the data to 15-minute time intervals; • For each 15-minute interval, an estimate of the corresponding vehicles per hour per lane value was made by multiplying the 15-minute volume by four and applying a peak hour factor of 0.95 (a more sophisticated version of this method would compute the peak hour factor directly from the data)
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68 Table 4.9. Distribution of SSR at Selected Locations (2007)
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69 I-405 693RN 1,599 167 1,961 1,851 1,794 1,767 1,702 1,630 1,417 1,349 992 I-405 694RN 1,574 178 1,961 1,889 1,820 1,763 1,687 1,596 1,368 1,296 961 I-405 696DN 1,927 48 1,961 1,961 1,961 1,961 1,961 1,927 1,892 1,892 1,892 I-405 696DS 1,615 221 1,961 1,953 1,866 1,835 1,769 1,674 1,349 1,186 920 I-405 698DN 1,586 151 1,961 1,961 1,805 1,771 1,693 1,571 1,414 1,349 1,091 I-405 698DS 1,607 185 1,999 1,938 1,866 1,813 1,721 1,630 1,383 1,292 1,087 I-405 704DN 2,032 276 2,398 2,383 2,337 2,272 2,204 2,105 1,714 1,497 992 I-405 706DN 1,615 541 1,961 1,961 1,961 1,961 1,961 1,892 992 992 992 I-405 708DN 1,811 175 2,124 2,105 2,010 1,995 1,919 1,843 1,630 1,467 1,201 I-405 708DS 1,788 222 2,117 2,094 2,048 2,003 1,934 1,839 1,528 1,440 954 I-405 709DN 1,930 222 2,322 2,208 2,158 2,139 2,060 1,961 1,740 1,550 866 I-405 709DS 1,933 293 2,379 2,364 2,223 2,174 2,117 1,995 1,588 1,307 783 I-405 710RN 1,778 229 2,132 2,086 1,999 1,961 1,904 1,824 1,592 1,292 714 I-405 710RS 1,926 239 2,318 2,288 2,177 2,124 2,056 1,951 1,786 1,600 673 I-405 711RN 1,776 179 2,060 1,999 1,959 1,934 1,877 1,820 1,617 1,427 946 I-405 711RS 1,877 427 2,504 2,402 2,310 2,250 2,174 2,048 1,205 920 688 I-405 716RN 1,891 256 2,291 2,227 2,139 2,098 2,041 1,930 1,661 1,349 817 I-405 716RS 1,979 291 2,409 2,345 2,280 2,200 2,128 2,025 1,775 1,455 509 I-405 717RN 1,830 246 2,284 2,124 2,067 2,041 1,972 1,877 1,581 1,330 692 I-405 717RS 1,940 215 2,333 2,307 2,236 2,147 2,060 1,959 1,754 1,653 1,068 I-405 720DS 1,498 272 1,961 1,923 1,820 1,775 1,695 1,554 1,180 984 540 I-405 722DS 1,512 209 1,961 1,892 1,744 1,710 1,642 1,539 1,296 1,060 817 I-405 726RS 1,629 334 2,333 2,291 2,128 2,029 1,900 1,585 1,345 1,007 638 I-405 730RN 1,572 313 2,044 2,044 1,961 1,923 1,843 1,568 1,243 882 585 I-405 730RS 1,641 218 1,961 1,961 1,892 1,851 1,744 1,661 1,490 1,258 570 I-405 731RN 1,564 309 1,972 1,972 1,921 1,870 1,816 1,695 1,094 1,056 654 I-405 731RS 1,459 220 1,961 1,961 1,824 1,718 1,623 1,482 1,224 1,140 654 (continued on next page) Table 4.9.
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70Table 4.9. Distribution of SSR at Selected Locations (2007)
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71 there is more excess capacity to buffer their effect, which is shown by the long tail to the left but no second peak for nonrecurring events. Sites with a bimodal distribution may also be upstream of a bottleneck.
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72 Figure 4.23. Distribution of SSR on I-405 in Seattle at Station 612DN.
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73 Figure 4.26. Orlando, Section 4, a.m.
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74 reliability of rural Freeway trips Figures 4.30 through 4.33 show the reliability of trips on the two study sections for 2006 and 2007 combined. The plots show the distribution of the actual travel times.
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75 Figure 4.31. I-45 southbound, Texas (length = 60.0 miles)
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76 facility began to be highly vulnerable to breakdown. On average days, there is little noticeable congestion, but on the worst days, congestion builds rapidly.
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77 • I-285 Northern Arc, from I-75 to I-85 (10.37 miles) –4 36 links eastbound, and –4 34 links westbound.
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78 Figure 4.37. Trip versus link reliability: mean TTI.
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79 their reliability metrics treated in the same way; that is, the reliability statistics of the nonfreeway links could be combined with the freeway links' reliability statistics. Finally, the trips used here were relatively short, even for urban conditions.
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