Establishing Monitoring Programs for Travel Time Reliability (2014) / Chapter Skim
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12 C h a p t e r 2 This chapter presents two components of data gathering: a survey of existing travel time reliability monitoring systems (TTRMSs) and an assessment of user needs for information that might be produced by those systems.
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13 Tables 2.4 and 2.5 show what information is disseminated and how it is disseminated, respectively. Everything from work zone information to weather updates is disseminated, as well as travel content.
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14 Table 2.3. Data Collection by Select State DOTs Data Collection Method Rural Midsized Large WSDOT (I-90, I-5)
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15 five highway-oriented traffic websites in a single metropolitan area are common (and there may be additional public transportation websites)
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16 For this Chicago website, drilling down into the average travel time field yields a more detailed picture, and one that is useful in terms of travel time reliability. Figure 2.3 shows that for this freeway segment and direction, the current travel time is 10.88 minutes, the average is 13.17 minutes, the difference is -2.29 minutes, and the average is based on 186 sample days.
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17 A travel time website that directly addresses travel time reliability (i.e., consistency) is used in Seattle.
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18 Source: Travel Midwest (2013)
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19 Table 2.6. Travel Time Information for the Top 25 Metropolitan Areas Rank Metropolitan Area Population Website(s)
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20 Source: Washington State Department of Transportation (2013)
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21 • Skew statistic: Computed as the ratio of (90th percentile travel time minus the median) divided by (the median minus the 10th percentile)
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22 Several commercial companies provide travel time information for metropolitan areas throughout the country. The most common are Traffic.com, BeattheTraffic, Iteris, TrafficGauge, traffic.yahoo.com, and SmarTraveler.
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23 VMS disseminate similar types of travel time reliability information as radio broadcasts. Radio broadcasts are accessible throughout the service area of a particular radio station, but VMS are permanently located on specific roadways in the network.
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24 complicated ways. Anecdotal (experiential reports)
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25 Passenger Travelers The group of users comprising passenger travelers represents individual vehicle users who drive to work, recreational centers of activity, school, or other types of individual destinations. As Khattak et al.
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26 Table 2.7 summarizes the recommended performance measures for passenger travelers, grouped according to trip purpose for daily travel, and accompanied by a general assessment of the relative importance or severity of a reliability issue. Daily, constrained trips are those for which the user experiences day-to-day variability in travel time (due to recurring congestion and incident or nonrecurring congestion)
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27 costs. Furthermore, due to travel time uncertainty, travelers may not be able to properly plan their daily activities.
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28 Table 2.8 displays this classification scheme along with the criteria on which the classifications were made: (1) level of schedule flexibility, (2)
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29 unreliable travel conditions. This increases the cost of those deliveries, but at a lower cost to the carrier (and ultimately the shipper)
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30 have a direct impact on the day-to-day procedures of monitoring travel time reliability; however, the decisions made at the policy level regarding the focus of improvements and spending (e.g., improved safety versus increased efficiency) have a trickle-down effect on an agency's effectiveness when it comes to providing reliable travel times to users.
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31 and vehicle factors (e.g., driver distractions and equipment failure)
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32 and trips those agencies monitor. The following agencies were interviewed: • WSDOT; • TriMet (Portland, Oregon)
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33 Use Cases Based on all of the interviews conducted and the earlier L11 work, a set of 51 use cases was developed. These use cases were intended to form the functional specifications for a TTRMS and were designed to fit the template shown in Table 2.11.
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34 for individual vehicle travel times; TT-CDF refers to the travel time cumulative density function. Third, fairly technical information is presented for the results (e.g., TT-PDFs for the routes that might be selected)
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35 users, transit passengers, schedulers or operators, and freight customers or operators. Only one of the use case analysis procedures is described here in detail.
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36 weather) affect reliability so they can make investment decisions or formulate policies to help ensure system reliability will be acceptable.
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