1、Brief 9. How Commuting Influences Travel January 2015 Commuting in a merica 2013 The National Report on Commuting Patterns and TrendsAbout the AASHTO Census Transportation Planning Products Program Established by the American Association of State Highway and Transportation Officials (AASHTO) and the
2、 U.S. Department of Transportation (U.S. DOT), the AASHTO Census Transportation Planning Products Program (CTPP) compiles census data on demographic characteristics, home and work locations, and journey- to-work travel flows to assist with a variety of state, regional, and local transportation polic
3、y and planning efforts. CTPP also supports corridor and project studies, environmental analyses, and emergency operations management. In 1990, 2000, and again in 2006, AASHTO partnered with all of the states on pooled-fund projects to sup- port the development of special census products and data tab
4、ulations for transportation. These census transpor- tation data packages have proved invaluable in understanding characteristics about where people live and work, their journey-to-work commuting patterns, and the modes they use for getting to work. In 2012, the CTPP was established as an ongoing tec
5、hnical service program of AASHTO. CTPP provides a number of primary services: Special Data Tabulation from the U.S. Census BureauCTPP oversees the specification, purchase, and delivery of this special tabulation designed by and for transportation planners. Outreach and TrainingThe CTPP team provides
6、 training on data and data issues in many formats, from live briefings and presentations to hands-on, full-day courses. The team has also created a number of electronic sources of training, from e-learning to recorded webinars to downloadable presentations. Technical SupportCTPP provides limited dir
7、ect technical support for solving data issues; the pro- gram also maintains a robust listserv where many issues are discussed, dissected, and resolved by the CTPP community. ResearchCTPP staff and board members routinely generate problem statements to solicit research on data issues; additionally, C
8、TPP has funded its own research efforts. Total research generated or funded by the current CTPP since 2006 is in excess of $1 million. Staff Penelope Weinberger, CTPP Program Manager Matt Hardy, Program Director, Policy and Planning Jim Tymon, Chief Operating Officer/Director of Policy and Managemen
9、t Project Team Steven E. Polzin, Co-Author, Center for Urban Transportation Research, University of South Florida Alan E. Pisarski, Co-Author, Consultant, Falls Church, Virginia Bruce Spear, Data Expert, Cambridge Systematics, Inc. Liang Long, Data Expert, Cambridge Systematics, Inc. Nancy McGuckin,
10、 Data Expert, Travel Behavior Analyst Contact Penelope Weinberger, e-mail: pweinbergeraashto.org, phone: 202-624-3556; or CTPPinfoaashto.org 2015 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law. Pub Code: CA
11、09-4 ISBN: 978-1-56051-579-1 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.Commuting in America 2013: The National Report on Commuting Patterns and Trends Brief 9. How Commuting Influences Travel This
12、 brief is the ninth in a series describing commuting in America. This body of work, sponsored by American Association of State Highway and Transportation Officials (AASHTO) and carried out in conjunction with a National Cooperative Highway Research Program (NCHRP) project that provided supporting da
13、ta, builds on three prior Commuting in America documents that were issued over the past three decades. Unlike the prior reports that were single volumes, this effort consists of a series of briefs, each of which addresses a critical aspect of commuting in America. These briefs, taken together, compr
14、ise a comprehensive summary of American commuting. The briefs are disseminated through the AASHTO website (traveltrends.transportation.org). Accompany- ing data tables and an Executive Summary complete the body of information known as Commuting in America 2013 (CIA 2013). Brief 9 provides informatio
15、n on how the commute trip influences the overall pattern of travel. Part of the importance of commuting is that commuting travel influences the travel patterns of commuters for non-commute purposes. Additionally, the travel patterns of non-commuters are affected as they plan their travel in response
16、 to the times and locations of heavy travel by commuters. Specifically, someone commuting to an employment location for work has an explicit temporal constraint on when they can carry out other travel imposed by their work time commitment. In addition, the geographic locationmore specifically, the t
17、ravel corridor between home and workprovides an opportunity for that traveler to carry out other activities in proximity to that corridor. For example, a trip to eat during work is geograph- ically influenced by the work location. In addition, many errands carried out in conjunc- tion with travel to
18、 and from work are carried out within the commute corridor. Simple things such as picking up a gallon of milk or dropping off dry-cleaning are activities whose breadth of location options enables choosing a location conveniently located with respect to commute travel patterns. The regular commute tr
19、ip also increases the awareness of opportunities within the commute corridor that can influence the prospect of carrying out other activities in that geography. While commuting to work, a driver might notice a sale at a furniture store or a movie showing at a theater that might influence subsequent
20、travel destinations based on awareness of opportunities within the corridor. Commuting also influences the travel of non-commuters, as many individuals inten- tionally plan their trips to avoid competing with commuters on the roadway and transit sys- tem. It is common for individuals to avoid peak p
21、eriods for discretionary trips and to select destinations that are not in areas known to be subject to congestion caused by commuters. 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.4 Commuting in Amer
22、ica 2013: The National Report on Commuting Patterns and Trends Some of the relationships noted above can be described with quantitative data, and oth- ers simply are acknowledged behaviors but are not necessarily quantitatively documented. Trip Chaining Tables 2-1 and 2-2 in Brief 2 documented the i
23、mportance of commute travel in the realm of all household travel and roadway and transit system travel. Also in Brief 2, a series of figures added further detail (Fig- ures 2-12-7). In 2009, commuting consti- tuted 15.6 percent of person trips, 19.0 per- cent of person miles of travel, 18.8 percent
24、of person travel time, and 27.8 percent of vehicle miles of travel. These numbers, sig- nificant in their own right, under-represent the true influence of commuting due to the impacts noted above and the overall impact of commuting on our transportation system as discussed in Brief 1. One of the mos
25、t obvious ways in which commuting influences travel is via trip chaining, the process whereby individuals link additional activities to their trip to or from work. By creating chains of activities linked by travel between those activities versus carrying out each activity as a distinct trip from hom
26、e, travelers reduce overall travel re- quirements to carry out a given set of activities. Analysts have explored trip chaining in the context of commuting to and from work. Figure 9-1 shows the extent of trip chaining for work commuting by gender. The data indicate that the extent of trip chaining h
27、as remained relatively stable since 1995. There was a slight decline in commute trip stops for other purposes for 2009, perhaps contrary to what might be expected as analysts commonly assume that tight recession period budgets and high fuel prices would motivate increased trip chaining to reduce tra
28、vel. Defining Trip Chaining For purposes of defining trip chaining when analyzing National Household Travel Survey (NHTS) survey data, trips were defined as a “chain” if intervening activities consumed 30 minutes or less before resuming the trip to home or work. This under-represents the full ex- te
29、nt to which work trips are sequenced into trip tours, where longer-duration subsequent or prior activities are part of a sequence of activities all carried out since leaving from or before returning to home. This might include, for exam- ple, working a six-hour shift at a job, then traveling to a mo
30、vie before return- ing home. 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a violation of applicable law.5 Brief 9. How Commuting Influences Travel Figure 9-1. Transit Trip Chaining by Gender (Stops on Commute)Source: NHTS data se
31、ries, Trip Chaining file For work commuting in 2009, 84 percent of workers went directly to or from work without a chained trip, 12.5 percent of workers stop once, and 3.5 percent stop more than once. This level of stopping is quite modest, indicating that schedule or other factors dampen the motiva
32、tion to chain other activities with work trips. Often something as simple as a conveniently located coffee vendor accessible from the inbound travel lane is the motivation for a chained trip. Trip chaining varies modestly by gender. In 2009, more than 86 percent of males reported no stops on their t
33、rip to or from work versus approximately 81 percent of females. Similarly, females were more likely to have multiple stops on their commute trip. This is consistent with historical roles of females doing more household-/family-serving trips (646 per year for females versus 529 for males according to
34、 the 2009 NHTS) and shorter female commutes (9.72 miles for females versus 13.5 miles for males according to the 2009 NHTS). Figure 9-2 shows the trend in trip chaining by trip purpose. For all three surveys referenced, family and personal business trips are the large majority of trip purposes for c
35、hained trips. The second most common trip purpose is shopping. Work-related, church or school, social/recreation, and other trip purposes are all modest shares, below 10 percent of chained trips. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1995 2001 2009 MaleZero MaleOne MaleTwo or More FemaleZero F
36、emaleOne FemaleTwo or More While trip chaining would seem an attractive opportunity to carry out activities, the vast majority of workers84 percentdo not chain other activities with their trip to and from work on a given travel day. 2014 by the American Association of State Highway and Transportatio
37、n Officials. All rights reserved. Duplication is a violation of applicable law.6 Commuting in America 2013: The National Report on Commuting Patterns and Trends Figure 9-2. Trend in T rip Chaining by Trip PurposeSource: NHTS data series, Trip Chaining file Work travel also influences the timing and
38、perhaps location of other activities that are sequenced with trips to and from work into trip tours. NHTS data indicates that 21.6 per- cent of trips to work do not originate at home and 41.0 percent of trips from work do not go directly home. The difference between these numbers and the data shown
39、in Figure 9-1 represents tours of longer duration activities coordinated with work activities. Figure 9-3 itemizes the sequence of travel to and from work. This includes both short stops that constitute trip chains (activity duration of 30 minutes or less) as well as longer-duration stops, referred
40、to as trip tours. 0% 10% 20% 30% 40% 50% 60% 70% 1995 Commute Tours 2001 Commute Tours 2009 Commute Tours Work-Related Shopping Social/Recreational Family/Personal Business Other School or Church 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Dup
41、lication is a violation of applicable law.7 Brief 9. How Commuting Influences Travel Figure 9-3. Activities Integrated in Work Trip Chains and T ours Source: NHTS 2009. Note: Totals do not sum to 100% because 2.5% of trips do not have information about prior/subsequent activity. Activity-based model
42、s, with their inherent appreciation for the interrelationships between household travel decisions and activity decisions, have led to a growing interest in more fully understanding trip chaining and trip tour activities. With the greater avail- ability of GPS-based location data on travel activities
43、, analysts are beginning to evaluate the relationship between commuting and other activity geographic and temporal patterns. Ongoing research such as “ An Integrated Model of Residential Location, Work Location, Vehicle Ownership, and Commute Tour Characteristics” 1and “Exploring the Influence of Ur
44、ban Form on Travel and Energy Consumption: A Tour-based or Trip-based Analysis?” 2reflect the growing attention to further understanding trip chaining and trip tour behaviors in the context of commuting. 1Rajesh Paleti, Chandra R. Bhat, and Ram M. Pendyala, 92nd Annual Meeting of the Transportation
45、Research Board, 2013. 2Chao Liu and Frederick W . Ducca, 91st Annual Meeting of the Transportation Research Board, 2012. 75.9% 2.2% 1.2% 0.9% 0.4% 4.5% 1.0% 0.6% 6.3% 4.1% 0.4% 56.5% 2.3% 4.5% 0.7% 1.1% 11.8% 4.3% 1.9% 4.7% 9.2% 0.5% 0% 10% 20% 30% 40% 50% 60% 70% 80% HomeWork Work-Related School/Re
46、ligious Activity Medical/Dental Services Shopping/Errands Social/Recreational Family Personal Business/Obligations Transport Someone Meals Other Reason From work to: To work from: 2014 by the American Association of State Highway and Transportation Officials. All rights reserved. Duplication is a vi
47、olation of applicable law.8 Commuting in America 2013: The National Report on Commuting Patterns and Trends Aspects of trip chaining remain to be researched, such as how much circuity is added to the home-to-work trip to carry out trip-chaining or trip-tour activities. GPS provides a tool to provide
48、 the information to answer this question. Emerging GPS and cell phone tracking data, for example, can help validate actual trip chaining behavior relative to survey responses. The Influence of Commuting on Other Trip Departure Times In addition to influencing travel for other purposes via trip chain
49、ing, the work trip and time at work influence the ability of the traveler to accomplish activities during those occu- pied times and, hence, influence the overall temporal distribution of travel. Workers travel for other purposes has to be coordinated with, or planned around, their commute travel. Figure 9-4 shows the temporal pattern of travel for workers on weekdays for the approxi- mately 42 percent of the adult population (ages 16 and older) that is in the workforce and worked on the travel day that was surveyed. These workers may hav
