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13 Introduction While the pattern differs in degrees among the regions studied, TNCs appear to primarily serve core urban areas for shorter trips, with peak TNC demand in a few specific areas at times when activity is high, but transit service is infrequent. TNCs seem to be used in a way that differs from traditional commute modes. At peak commute hoursâthe time when the roads and highways are most congested and public transit ridership is at its highestâthe total volume of TNC usage does not match that seen on Friday and Saturday nights. In fact, the total volume of peak-hour TNC usage across the entire week (six hours a day across five weekdays) makes up only around half of the proportion of TNC trips taken on Friday and Saturdays. Findings on Trip-Making Characteristics Weekend nights dominate usage. In each region for which TNC data was provided, the single busiest hours fall on Saturday nights at 9 p.m. or 10 p.m., while the lowest volume hours uniformly fall on early weekday morn- ings. Table 3 summarizes the highest and lowest hours of TNC usage for the six study regions. In the city of San Francisco, Friday at 7 p.m. was the highest ridership hour. Friday and Saturday together account for 38% to 45% of TNC trips in all regions in this study, compared to a range of 20% to 27% of trips for all weekday peak hours combined (see Table 2). TNC usage takes place in communities of all income levels. Individual TNC trips are widespread across the five TNC study regions, suggesting that TNCs are used to some degree by communities across the socioeconomic spectrum. Almost every ZCTA in the core counties of the study regions serve as ride origins (Table 4), and destinations cover an even wider area. See Appendix B for maps and profiles of the five regionsâSan Francisco is not included because of its different data source. At least two-thirds of the ZCTAs in each of the five regions have trips originating in them and more than half of the ZCTAs have signifi- cant flows (i.e., TNC flows for which a relative volume can be calculatedâsee Appendix A for description of the data). Destination ZCTAs cover an even wider part of the five regions. Nearly every ZCTA in the five study regions shows at least some TNC trips both starting and ending in that ZCTA. Maps for origins and destinations in the Los Angeles region are shown in Figures 6 and 7. Similar maps for the five study regions are in Appendix B. The greatest levels of TNC use are concentrated in core areas and near airports. Despite the breadth of trip-making activity in each of the five study regions, it appears to take place at a low level across most of the metropolitan area, with high levels of activity taking place C H A P T E R 3 Trip-Making Characteristics
Region Maximum TNC Volume (day, hour) Minimum TNC Volume (day, hour) Chicago 4350 (Saturday, 10 p.m.) 65 (Wednesday, 2 a.m.) Washington, D.C. 3460 (Saturday, 10 p.m.) 25 (Wednesday, 2 am) Los Angeles 8146 (Saturday, 9 p.m.) 54 (Tuesday, 2 a.m.) Nashville 698 (Saturday, 9 p.m.) 6 (Thursday, 2 a.m.) Seattle 2395 (Saturday, 9 p.m.) 43 (Tuesday, 2 a.m.) San Francisco* 17,350* (Friday, 7 p.m.) 505* (Tuesday, 3 a.m.) Note: Volumes are in terms of signiÂicant observations only (i.e., origin-destination Âlows for which a volume proportion is supplied, which are cut off at the low end between 0 and 2%). *San Francisco data is from SFCTA modeling, and those volume Âigures refer to modeled pickup counts for trips entirely within the City of San Francisco. Source: TNC trip data, SFCTA modeled TNC data. Table 3. Highest and lowest hourly TNC volumes in each region. Region Possible unique origin ZCTAs Origin ZCTAs with lows Origin ZCTAs with lows (% of total) Origin ZCTAs with signi icant lows Origin ZCTAs with signi icant lows (% of total) Unique destination ZCTAs Chicago 188 169 90 96 51 311 Washington, D.C. 225 156 69 152 68 336 Los Angeles 416 359 86 335 81 547 Nashville 37 32 86 29 78 61 89 135Seattle 73 82 72 81 Source: TNC trip data. Table 4. Count of unique ZCTAs with actual and significant flows. Figure 6. TNC trip origins by zip code, Los Angeles region. Source: TNC trip data.
Trip-Making Characteristics 15 within limited areas. Across the five study regions, a plurality of trips take place within just a few core areas. The top five ZCTAs in each region, whether origin or destination, account for one-quarter to three-quarters of the total count of flows, representing a high concentration of TNC trips (Table 5).5 At least four of the same ZCTAs are among both the top five origins and top five destinations in the study regions. The highest volume of TNC trips is generally within a single ZCTA, between nearby ZCTAs, or to or from a ZCTA containing an airport. Short trips dominate overall usage in the study regions. TNC trips shown by the data are generally short. The top ten TNC origin-destination pairs, by total volume, are shown in Table 6. More than half of the top ten TNC trip flows (shown in bold in the table) take place within single ZCTAs. All the flows have estimated distances under 2.5 miles in length. Each of the TNC trip flows sees a mean hourly volume between about one-quarter and one-third of the single highest volume flow in that market. The meaning and calculation of the volume index, as well as the method for estimating and comparing distances, are explained in Appendix A. 5âVolumeâ refers to the aggregated TNC volume index for all hourly ZCTA pairs for which these numbers are provided (i.e., only those with a volume index greater than 2). âFlow countâ refers to a simple count of all hourly ZCTA pairs (i.e., all nonzero flows, regardless of whether a volume index is provided for a given hour). Figure 7. TNC trip destinations by zip code, Los Angeles region. Source: TNC trip data.
16 Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles Region Top Origin ZCTAs Proportion of Regional Origin Volume (%) Proportion of Regional Origin Flow Count (%) Top Destination ZCTAs Proportion of Regional Destination Volume (%) Proportion of Regional Destination Flow Count (%) Chicago 60614, 60611, 60657, 60622, 60647 41.4 29.9 60611, 60614, 60657, 60654, 60647 39.1 27.7 Washington, D.C. 20001, 20009, 20002, 20007, 20005 42.6 27.8 20001, 20009, 20002, 20007, 22202 42.0 28.4 Los Angeles 90028, 90046, 90024, 90069, 90045 22.9 15.6 90028, 90045, 90046, 90069, 90026 23.5 17.0 Nashville 37203, 37206, 37214, 37212, 37201 73.1 62.2 37203, 37206, 37214, 37201, 37212 76.2 66.8 Seattle 98122, 98101, 98109, 98105, 98121 54.9 40.3 98122, 98101, 98109, 98105, 98104 51.6 36.7 Note: ZCTAs are listed in order of descending volume within each region, with those that appear in both the top Âive origins and top Âive destinations set in bold, and those containing major airports underlined. Source: TNC trip data. Table 5. Top five TNC trip origin and destination ZCTAs by volume, and proportion of regional totals for volume and flow count. Region Start zip End zip Total weekly volume index Mean hourly volume index Distance (miles) Chicago 60614 60614 4908 31 1.7 Seattle 98105 98105 4547 27 2.4 Los Angeles 90024 90024 4356 27 1.3 Los Angeles 90028 90028 4203 25 1.1 Washington, D.C. 20001 20001 4103 26 1.4 Washington, D.C. 20001 20002 3860 24 1.9 Washington, D.C. 20001 20009 3850 24 1.2 Chicago 60614 60657 3822 24 1.2 Washington, D.C. 20002 20002 3781 23 2.1 Chicago 60657 60614 3695 24 1.2 Note: Single-ZCTA Âlows are in bold. Source: TNC trip data.6 Table 6. Top origin-destination TNC trip pairs, by total weekly volume. Typical TNC trips are under approximately 3 miles. Across the five study regions, the median TNC trip length (Table 7) varies between 2.2 and 3.1 miles, with the shortest trips in Washington, DC, and the longest in Nashville. Maximum TNC trip lengths range between about 20 and 30 miles depending on the regions, but most trips are shorter.7 Though Los Angeles had the longest TNC trips at the high end (a function of its extensive, largely low-density urbanized area, which includes several unusually large ZCTAs), 6The TNC trip length estimation is based on the straight-line distance between the center points of the origin and destination ZCTAs, or in the case of a single-ZCTA trip, half of the longest possible trip between any two points within that ZCTA. The method for calculating these distances is detailed in Appendix A. 7The minimum, median, and maximum TNC trip length measure is based only on TNC flows for which a significant volume was supplied (i.e., those with a volume index greater than 2%). A few isolated, very long trips, in some cases across one or more state lines, appeared in the data for all five study regionsâfor instance, from Los Angeles to Las Vegas, Nevada, or from Chicago to Detroitâbut these were uniform for flows with insignificant volumes (between 0 and 2%).
Trip-Making Characteristics 17 the more typical estimated trip lengths there were in the middle of the pack compared with the other regions included in this study. Though the survey conducted for this study did not ask about trip distance in a way that is directly comparable (in part because these trip lengths are estimates derived from the odd-shaped ZCTA geographies), the most common trip length on both TNCs and public transit was reported by survey respondents to be one between 1 and 5 miles; bus trips tended to be shorter than train trips, and typical TNC trips were at roughly the midpoint between the two transit modes. The bulk of TNC trips are short in each of the five study regions, but there is much variation among regions in typical trip lengths throughout the day and week. The range of TNC trip lengths for every hour of the week is shown in Figure 8. In that figure, the vertical lines show the central 50% of trip distances for each hour, centered on a point rep- resenting the median, while the points above and below the lines indicate the maximum and minimum, respectively. The data underlying this figure only represent TNC trip flows in the five regions for which a volume was provided. Chicago, Los Angeles, and Seattle all show distinctive peaks in typical trip lengths in the early morning hours (2 a.m. to 5 a.m.), meaning that longer trips make up a greater portion of the trips at those times. In Chicago and Seattle, the median trip in this period is often more than 10 miles long. Nashville shows the same effect to a lesser degree, though trips there tend to be longer to begin with. The Washington, D.C., region shows little of this early morning phenomenon. This pattern is likely driven partly by airport trips (see discussion in section on airports), as well as the general unavailability of frequent public transit services in the early morning hours. Trips within a single zip code represent a substantial proportion of TNC trip volumes and, though their greatest volume is concentrated, these trips occur widely across each of the study regions. In each of the five study regions, the single top origin-destination TNC trip flow is within a single ZCTA (Table 6), and 11 of the top 20 flows by volume are within a single ZCTA. The average proportion of single-zip trips ranges from 14% (Chicago) to 29% (Nashville) of total TNC trip volume (Table 8). At a given hour, this proportion ranges from a low of 4% to a high of nearly 70%, again in Chicago and Nashville, respectively. This proportion is at both its lowest and its highest during the midweek early mornings across all five study markets, although the low point occurs later in the morning than the high point. Beyond this, there is Region Minimum Median Maximum Average Transit Trip Chicago 0.4 2.3 21.4 4.4 Washington, D.C. 0.2 2.2 28.0 4.8 Los Angeles 0.4 2.4 30.7 4.9 Nashville 0.3 3.1 20.4 5.4 Seattle 0.7 2.4 21.5 4.9 Source: TNC trip data.8 Table 7. Range of regional TNC trip lengths for significant flows, and average regional transit trip length (miles). 8Average regional transit trip lengths calculated from ratio of passenger miles to unlinked passenger trips on the major transit agencies of the region, excluding commuter rail. Source: 2016 APTA Factbook, Appendix B.
18 Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles Figure 8. Range of TNC trip lengths. For each hour, vertical lines show the 25th to 75th percentiles, with a gap at the median; points above and below represent maximum and minimum values. Source: TNC trip data. little temporal pattern to these proportions more generally, either in relation to peak commute hours or the late-night peaks that are obvious in the volume overall: for the most part, the hourly proportions vary fairly randomly around the average values. In short, the single-ZCTA TNC trips happen widely at all hours of the day. As noted earlier, just a few ZCTAs account for a large proportion of the total TNC trip volume, and the same is true for these shortest trips in volume terms. However, looking only at the geo- graphic distribution of these short trips without regard for volume, single-zip TNC trips occur
Trip-Making Characteristics 19 widely across the five metro areas, taking place in at least three-quarters of the ZCTAs in each region (far right column of Table 8). Airports appear to be the major non-core areas of TNC trip activity in almost every study region. In each of the five TNC study regions, the ZCTAs containing or adjacent to major airports9 are among the highest volume TNC trip origins and destinations. In fact, the ZCTAs containing Los Angeles International and Reagan National Airport are the first and fifth most frequent destinations in the entire TNC dataset, respectively, in terms of flow count. While we cannot know definitively that trips to and from these ZCTAs are trips to or from the airports, the relative isolation of these ZCTAs from other areas of TNC activity in many of the regions and the fact that the trips happen to and from these places from across all five study regions make this a reasonable assumption. The Shared Mobility Survey did not ask specifically about airport trips, but in the Four Agency Survey, between 5% and 11% of TNC trips overall were to or from the airportâand a quarter of the trips substituting for BART trips were airport trips. Airport trips are also a factor in early morning peaks in travel distance in several cities in this study, described above and visible in Figure 7. The number of airport trips at an otherwise low- volume period seems to be increasing typical TNC trip lengths in the early morning throughout the weekâin Chicago, especially, this peak is most pronounced early on weekday mornings and the same is true to a lesser degree in Los Angeles and Seattle. All three regions have one or more major airports at least 15 miles from the downtown core. The central location of the Washington, DC, regionâs Reagan National Airport, in comparison with more outlying airports in the other regions, likely helps keep ride distances closer to the typical ranges at other times of day. Reports from cities throughout the United States that track TNC activity at airports show that TNC trips are a growing portion of airport ground transportation, including in regions that have rail links to their airports. A 2015 study commissioned by the San Francisco and Oakland International Airports found that 22% of respondents who rode TNCs to the airports would have used BART or public buses before TNCs were permitted; taxicabs made up 50% of the forgone uses, and private vehicles 18% (ACRP Synthesis 84, 2017). Region Mean Single- ZCTA Trip Volume as Proportion of T otal TNC Trip Volume (%) Single-ZCTA TNC Trips: Minimum Proportion (%) (day, hour) Single-ZCTA TNC Trips: Maximum Proportion (%) (day, hour) Count of ZCTAs with Single-Zip TNC Trips (% of total origin ZCTAs) Chicago 14 4 (Monday, 3 a.m.) 41 (Tuesday, 1 a.m.) 74 (79%) Washington, D.C. 18 7 (Monday, 3 a.m.) 53 (Tuesday, 2 a.m.) 104 (80%) Los Angeles 20 5 (Wednesday, 4 a.m.) 41 (Tuesday, 2 a.m.) 274 (85%) Nashville 29 11 (Tuesday, 3 a.m.) 70 (Wednesday, 2 a.m.) 19 (73%) Seattle 15 4 (Tuesday, 3 a.m.) 26 (Wednesday, 1 a.m.) 52 (79%) Source: TNC trip data. Table 8. Characteristics of TNC trips within a single zip code. 9Medium or large commercial hubs, as defined by the Federal Aviation Administration; these classifications are defined in terms of proportion of total annual scheduled passenger boardings (greater than 0.25% and 1%, respectively), and thus vary from year to year. In 2015 the minimum activity for the medium and large categories were 2 million and 8 million annual boardings, respectively (FAA Calendar Year 2015 Revenue Enplanements at Commercial Service Airports, 2016).
20 Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles TNCs are changing the mix of airport-related transportation revenues (e.g., parking charges; rental car, taxi, van, and TNC fees; and fare surcharges on dedicated public transit links) and spatial requirements (e.g., pickup/dropoff locations, staging lots, and parking for personal vehicles). While the net impacts of this changing landscape are not yet clear, the economics of capital-intensive projects financed by ground transportation revenues, such as airport rail spurs or express trains, appear to be much different than they were even a decade ago (ACRP Synthesis 84, 2017; ACRP Report 146, 2015). Areas with more service industry jobs generate more TNC trips than areas dominated with office jobs. To the degree than commercial land uses can be discerned at the ZCTA level, service-oriented districts (which would include areas with many restaurants or bars) tend to generate higher TNC volumes than office-oriented districts: the zip codes where most TNC trips take place tend to be areas with higher proportions of service industry jobs. Of the top 25 zip codes in the sample, 16 have greater proportions of service industry jobs than office jobs. This accords with the findings from both the Shared Mobility Survey and the Four Agency Survey described in the next section, which found that recreational trips form a larger proportion of TNC trips than commutes or work-related trips. It is possible that many of the TNC trips to and from service-oriented dis- tricts are work-related trips by service industry workers, putting the trips outside of traditional peak commute hours.