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Trip Generation Characteristics of Discount Supermarkets


OVER THE PAST SEVERAL YEARS, many grocers have attempted to create a niche market by selling high-quality goods, creating in-store brand names, selling products in bulk and/or selling products at discounted prices. As these trends have continued, building sizes typically have increased and the trip generation profile of grocers has evolved. Two elements are of particular concern in assessing the transportation impacts and needs of grocers: trip generation and trip type. The trip generation profile of a typical store is important because it is necessary to determine the on-site and off-site transportation impacts associated with that store. Trip type is important both in understanding trip origins and modal split and in enabling better planning of site access and parking to prevent spillover into residential neighborhoods. This feature provides a summary of a trip generation study prepared for a major discount supermarket company located in the western United States.



The Institute of Transportation Engineers' (ITE) Trip Generation typically is used to estimate the number of site-generated trips associated with a given land use.1 The Trip Generation Handbook is used to determine trip type.2 Both publications include data for two land uses commonly employed to study large grocers: supermarkets (ITE Land Use Code 850) and discount supermarkets (ITE Land Use Code 854). In addition to these two land uses, data for shopping centers (ITE Land Use Code 820) sometimes are used to evaluate the transportation impact of grocers when they are part of a larger shopping center development. ITE Land Use Code 850 characterizes supermarkets as typically being "free-

standing retail stores selling a complete assortment of food, food preparation and wrapping materials and household cleaning and servicing items. Supermarkets may also contain facilities such as money machines, photo centers, pharmacies and video rental areas." ITE trip generation data for the supermarket land use represent average store sizes ranging from approximately 27,000 square feet to 53,000 square feet, with most of the data points based on the smaller store sizes. By comparison, ITE Land Use Code 854 characterizes discount supermarkets as typically being "free-standing retail stores selling a complete assortment of food (often in bulk), food preparation and wrapping materials and household cleaning and servicing items at discounted prices." The store sizes associated with the ITE discount supermarket database range from less than 10,000 square feet to more than 125,000 square feet. ITE specifically cautions Trip Generation users to employ discount supermarket data carefully because of the small data sample size (daily trip rate data are not available). For this reason, some jurisdictions will not accept trip generation projections based on ITE discount supermarket data, even though the proposed land use may not correlate well with ITE's supermarket definition.


Currently, a segment of the grocer market is focused on volume delivery of standard grocery products at discounted prices. One of the major grocers on the west coast of the United States follows this business practice while serving customers 24 hours per day and 7 days per week. The stores feature a full line of groceries as well as in-store departments that include a bakery, a pizza shop with madeto-order pizza, quantity bulk foods, a delicatessen, a seafood department, a fresh



Table 1. 24-hour traffic counts/trip generation potential.

24-hour traffic volumea (vehicles per day) Site number 1 2 3 4 5 6 7 8 9 10 Average Location Antelope, CA, USA Chico, CA, USA Elk Grove, CA, USA Yuba City, CA, USA Eugene, OR, USA Hillsboro, OR, USA Salem, OR, USA Reno, NV, USA Clark County, WA, USA Vancouver, WA, USA Store size (square feet) 80,147 79,324 80,147 79,097 79,097 74,630 71,717 79,771 79,336 70,085 77,335 Tuesday to Thursdayb 8,960 7,760 7,220 6,630 6,960 6,720 7,280 5,480 7,430 8,910 7,330 Saturday 12,200 9,450 8,920 8,780 10,830 8,470 8,710 7,060 9,360 9,990 9,380 Sunday 10,440 8,980 8,490 7,900 8,980 8,290 7,110 9,020 8,650 24-hour trip generation rate (trips per 1,000 square feet of gross floor area) Tuesday to Thursdayc 111.8 97.8 90.0 83.8 88.0 90.0 101.5 68.7 93.7 127.1 95.2 Saturday 152.3 119.1 111.3 111.0 136.9 113.5 121.5 88.5 117.9 142.6 121.5 Sunday 130.2 113.2 105.9 99.8 113.5 115.5 89.1 113.7 110.1

* Note: Traffic volumes shown are based on calibrated road tube counts. Shaded areas indicate that data are not available. a Volume numbers represent the total number of trip ends (one-way trips) counted during the identified 24-hour period. b Provides a mid-week average daily trip generation. c Provides a mid-week average daily trip generation rate.

meat department, a fresh produce department, organic products and a health and beauty aids department. The stores typically sell the same type and size of brand name products as conventional supermarkets but have the lowest prices of any competitor in the trade area in which they operate. As a result, the stores' annual sales volume far exceeds that of typical supermarkets. While sales volume is higher than at other supermarkets, it has been hypothesized that actual store trip generation on a square-foot basis is lower due to the comparatively large store size and the higher volume of groceries purchased per customer. Typical modernday supermarkets range in size from 45,000 to 60,000 square feet; the typical supermarket building in the company under study is between 70,000 and 90,000 square feet. This unique characteristic leads to the perceived need to better identify trip generation, trip characteristics and subsequent transportation impacts associated with existing and future company stores.


activities. Data collection at the study sites included: · A traffic count program to obtain weekday p.m. peak-hour trips; 24hour weekday, Saturday and Sunday trips; and mid-day peak-hour trips on a Saturday. · A customer survey program to identify the various trip types made by customers (primary, pass-by and diverted) and mode split. Specific elements of the data collection activities included 24-hour road tube counts at the site-access driveways for a full week as well as manual peakhour traffic counts (entering/exiting) on mid-week days at the road tube locations. Customer surveys to differentiate between types of trips were completed on mid-week days during the evening peak period (4:00 p.m. to 6:00 p.m.). The customer surveys were completed at nine of the 10 study sites by interviewing shoppers as they arrived at the stores.


Ten study sites operated by the company were selected for data collection


Data collected at the 10 stores under study were examined to evaluate the trip profile of each store. Table 1 presents

the average daily trip generation rate per 1,000 square feet of gross floor area for each site on a typical mid-week day, Saturday and Sunday. All trips shown in Table 1 have been rounded to the nearest 10 trips. As shown in Table 1, the daily trip generation for the store sites was highest on Saturday. Sunday volumes fell between typical Saturday and weekday volumes. Table 2 presents a summary of the average peak-hour trip generation profile of the 10 study sites. All trips shown in Table 2 have been rounded to the nearest five trips. The weekday trip data in Table 2 represent the peak hour of the individual stores between 7:00 a.m. and 9:00 a.m. and between 4:00 p.m. and 6:00 p.m. These values were derived by first selecting the highest four consecutive peak 15-minute periods between 7:00 a.m. and 9:00 a.m. (and between 4:00 p.m. and 6:00 p.m.) for each day at each store. The average weekday a.m. and p.m. peak-hour volume of each store then was determined by calculating the average of the one-hour peak period traffic volumes collected on each of the three days of data collection.


Table 2. Peak-hour traffic counts/trip generation potential.

Volumea Site number 1 2 3 4 5 6 7 8 9 10 Average a.m. peak 335 220 275 220 260b 215b 245b 165b 190b 235b 230 p.m. peak 750 730 495 655 640 665 740 505 725 790 670 Saturday peak 945b 885b 800b 710b 1,000b 785b 740b 645b 800b 840b 815 Trip rate (trips per 1,000 square feet of gross floor area) a.m. peak 4.2 2.8 3.4 2.8 3.3 2.9 3.4 2.1 2.4 3.3 3.1 p.m. peak 9.4 9.2 6.2 8.3 8.1 8.9 10.3 6.3 9.2 11.3 8.7 Saturday peak 11.8 11.2 10.0 9.0 12.6 10.6 10.3 8.1 10.1 12.0 10.6 a.m. peak (percent) 48 / 52 57 / 43 65 / 35 64 / 36 60 / 40 55 / 45 43 / 57 56 / 44 48 / 52 63 / 37 56 / 44 Directional split (in/out) p.m. peak (percent) 43 / 57 49 / 51 59 / 41 50 / 50 48 / 52 51 / 49 49 / 51 58 / 42 50 / 50 49 / 51 51 / 49 Saturday peak (percent) 40 / 60 46 / 54 55 / 45 52 / 48 59 / 42 47 / 53 49 / 51 50 / 50 52 / 48 57 / 43 51 / 49

a Volume numbers represent the total number of trip ends (one-way trips) counted during the identified peak-hour period. b Reported volume is based on calibrated road tube counts. All other volumes reported are based on manual turning movement count data.

Table 3. Summary of customer survey results.

Site number 1 2 3 4 5 6 7 8 9 Total/average Number of participating customers 617 798 538 547 637 786 827 478 884 6,112 Private automobile 97.1 97.6 97.6 98.8 96.3 99.5 96.2 98.8 97.7 97.7 Travel mode (percent) Public transit Walk 0.3 0.8 1.2 0 0.8 0.1 1.0 0.4 0.7 0.6 0.4 0.9 0.6 0.2 1.1 0.2 0.2 0 0 0.4 Trip type (percent) Bicycle 2.3 0.8 0.7 1.0 1.9 0.1 2.6 0.8 1.6 1.3 Primary 67.8 57.9 52.2 64.5 51.7 39.6 50.9 43.5 39.3 51.9 Pass-by 11.7 19.8 25.3 14.9 12.8 33.1 31.5 38.0 33.6 24.5 Diverted 20.4 22.3 22.5 20.6 35.5 27.2 17.6 18.5 27.2 23.6

The data presented in Table 2 represent the Saturday peak hour of the individual stores, which varied between store locations but typically occurred between 1:00 p.m. and 5:00 p.m. Similar to the weekday morning and evening peak-hour analysis, the average value was derived by averaging the highest four consecutive peak 15-minute periods between 12:00 p.m. and 5:00 p.m. for each store. Truck counts were not performed at the sites. However, based on information provided by the company, the stores receive an average of 10 tractor-trailer deliveries per day. In addition, 10 to 15 single-unit trucks provide deliveries on a daily basis.



Table 3 summarizes travel mode and trip type data derived from more than 6,100 customer surveys completed at nine of the study sites. No surveys were completed at the Vancouver, WA, USA, site. As shown in Table 3, the vast majority of trips to the study sites were made via private vehicle. This travel pattern largely reflects the volume sales pattern offered by the grocer, which typically would require a private vehicle to transport comparatively large grocery cargos. The mode split also reflects the typical location of the stores in suburban market areas that may not have convenient access to transit service.

Three types of trips were evaluated in the study: primary trips, pass-by trips and diverted trips. ITE defines primary trips as trips made for the specific purpose of visiting the generator.3 Pass-by trips are made as an intermediate stop on the way from an origin to a destination without a route diversion. Diverted linked trips, as defined by ITE, are attracted from the traffic volume on a roadway within the vicinity of the generator but require a diversion from that roadway to another roadway to gain access to the site. With respect to trip type, on average, 52 percent of the trips generated by the supermarket stores were primary trips.


Table 4. Comparison of estimated trip generation rates (trips per 1,000 square feet).

Analysis period Daily trip rate a.m. peak-hour trip rate In/out p.m. peak-hour trip rate In/out Saturday trip rate Saturday peak-hour trip rate In/out ITE supermarket (ITE Land Use Code 850) 111.5 3.3 61 percent / 39 percent 11.5 51 percent / 49 percent 177.6 12.3 51 percent / 49 percent ITE discount supermarket (ITE Land Use Code 854) 1.7 70 percent / 30 percent 9.8 48 percent / 52 percent 10.1 50 percent / 50 percent Field data 95.2 3.1 56 percent / 44 percent 8.7 51 percent / 49 percent 121.5 10.6 51 percent / 49 percent

* Note: Shaded areas indicate that data are not available.

The remainder was a combination of pass-by and diverted trips, with some variation between the pass-by and diverted percentage based on the location of the store. Five of the nine study sites had a pass-by trip percentage of at least 25 percent. Some locations, such as the Eugene, OR, USA, store, were on a lower level collector roadway that required a diversion from a nearby highway to reach the site, resulting in a relatively high diverted trip rate. As a group, the California-based stores exhibited a comparatively higher primary trip rate than stores in any of the other states studied. The higher primary trip rate can be attributed to the location of the stores in comparatively smaller population centers (where drivers are more likely to make a primary trip as opposed to a linked trip on the way to another destination).


Table 5. Comparison of weekday trip types.

Trip type Primary Pass-by Diverted ITE supermarket (ITE Land Use Code 850) 34 percent 36 percent 38 percent ITE discount supermarket (ITE Land Use Code 854) 9 percent Field data 52 percent 24 percent 24 percent

* Note: Shaded areas indicate that data are not available.

Table 4 provides a side-by-side comparison of the trip generation rates provided in Trip Generation and the average results obtained from the field studies. Table 5 provides a side-by-side comparison of the applicable trip types provided in Trip Generation and the results obtained from the field studies. The shopping center comparison was not included because it did not pertain to any of the sites studied. Overall, the field-measured daily trip rate was approximately 15 percent lower than the ITE supermarket rate on a


weekday and approximately 32 percent lower on a Saturday. When compared to the ITE discount supermarket, the field data trip rate was higher on a weekday a.m. peak-hour basis and lower on a p.m. peak-hour basis. There was no applicable comparison between field data and the ITE shopping center land use data because the shopping center trip rate is tied to the overall shopping center site where the store is located. Equally as important as trip generation rates are trip characteristics. Trip characteristics differentiate between the net amount of new trips on the roadways and the existing trips on the roadways that may or may not be rerouted. Table 5 shows a comparison of weekday trip types. As shown in Table 5, the pass-by rate associated with the field data was smaller than the comparable ITE trip rate for the supermarket land use. However, the passby trip rate associated with the field data was significantly larger than the ITE trip rate for the discount supermarket land use (which is based on 33 surveys at one 50,000 square-foot store).

The new data suggest that trips to the stores studied in the field data collection were more destination-oriented than trips to other land uses such as typical full-service supermarkets (for example, a grocery store consisting of less than 60,000 square feet).


The purpose of these studies was to collect site-specific data for each of the variables typically used by traffic engineers and other review agencies in assessing traffic impacts and related traffic impact fees and system development charges. Based on the findings, the trip rate and trip type associated with a major discount supermarket company were found to be generally significantly lower than that of the standard ITE supermarket. The data presented in this study should be added to ITE's database of discount supermarkets, thereby broadening the database available for estimating the transportation impacts of modern grocers. The transportation community would benefit from additional studies of grocers to update both


the supermarket and the discount supermarket databases further.



Goods Movement Council

ITE Coordinating Council Summary Report-- Key Projects to be Completed in 2003

Committee Title Type Committee Chair

Alan Danaher; 407-540-0555; [email protected] Marsha Anderson Bomar; 770-813-0882; [email protected] Carol Walters; 817-277-5503; [email protected] Alan Danaher; 407-540-0555; [email protected] John Corbin; 608-266-0459; [email protected] Jon Obenberger; 202-366-2221; [email protected] NCHRP synthesis project ITE Journal article on truck trip generation ITE Journal special issue on goods movement ITE Journal article Truck trip generation study Survey Enhancement of Traffic Incident Management Committee Web site 2004 National Meeting of Transportation Management Center (TMC) Managers-- "Managing Travel for Planned Special Events" 2003 National Meeting of TMC Managers Parking generation report Informational library development National bicycle and pedestrian documentation program Transportation professional's role in public agencies Signal activation procedures New technology part 1 (in-roadway signs and in-pavement flashing markers) New technology part 2 (in-roadway signs and in-pavement flashing markers) New technology part 3 (public agency experience with school flasher systems) Agency self-assessment Transportation agencies' role in economic development Update of Guidelines for Prohibition of Turns on Red Central business district vitality Speed zoning issues Neighborhood Street Design Guidelines Benefits of retiming traffic signals Traffic Signal Timing Advisory Committee--Identification of key national traffic signal timing issues Transit council membership A joint teleconferencing effort on transit security issues Bicycles and transit Recommended practice on traffic impact studies update Graduate transportation programs directory ASCE Policy 465 University course syllabi directory Student chapter manual Expert Witness Information Notebook Annual meeting/international conference sessions and briefing Update of site impact analysis recommended practice Success stories on congestion management Travel demand management strategies during reconstruction Impact study database Graduated driver licensing laws Council newsletters Web site Conference

The authors appreciate the insight and peer review guidance offered by Mojie Takallou, Ph.D., P.E. and Mark Kennedy, Ph.D., P.E., professors at the University of Portland School of Engineering, in developing the trip generation study documented in this feature. References

1. Trip Generation, Sixth Edition. Washington, DC, USA: Institute of Transportation Engineers (ITE), 1997. 2. Trip Generation Handbook: An ITE Recommended Practice. Washington, DC: ITE, 2001. 3. ITE, note 2 above.

Intelligent Transportation Systems Council

Parking Council* Pedestrian and Bicycle Council

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Conference Jon Obenberger; 202-366-2221; [email protected] Informational report Randy McCourt; 503-243-3500; [email protected] Web Shawn Turner; 979-845-8829; [email protected] Charlie Zeeger; [email protected] Recommended Michael Jones; 415-482-8660; [email protected] practice Survey Nazir Lalani; 805-654-2080; [email protected] Pat Noyce; [email protected] Recommended Nazir Lalani; 805-654-2080; [email protected] practice Survey Frank Markowitz; 415-252-4696; [email protected] Survey Survey Informational report Roundtable discussion Recommended practice Informational report Brochure Proposed recommended practice Brochure Informational report Brian Van De Walle; 512-416-3375; [email protected] John Runiks; 702-633-1267; [email protected] Doug Wiersig; 713-837-7274; [email protected] Jim Helmer; 408-277-4945; [email protected] Steven Gayle; 607-778-2443; [email protected] Bill Savage; 517-339-3933; [email protected] Daniel Rathbone; 703-764-0512; [email protected] Rick Staigle; 713-270-8145; [email protected] Martin Bretherton; 770-822-7412; [email protected] Srinivas Sunkari; 979-845-7472; [email protected] W. Scott Wainwright; 202-366-0857; [email protected]

CHRISTOPHER L. BREHMER, P.E., is a senior engineer with Kittelson & Associates Inc. and serves as the development services manager for the firm's Portland, OR, USA, office. His areas of interest include traffic operations and design and highway/railroad crossing issues. He received his master's and bachelor's degrees in civil engineering from Texas A&M University and Clarkson University, respectively. He is a member of ITE. MARC A. BUTORAC, P.E., PTOE, is a principal engineer with Kittelson & Associates Inc. and serves as the public works manager for the firm's Portland office. His interests include public and private development work and access management issues. He received his master's and bachelor's degrees in civil engineering from Texas A&M University and the University of Idaho, respectively. He is a member of ITE.

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Tom Ryden; 214-819-1780; [email protected] Cynthia Gilliland; 972-406-6970; [email protected] Informational report Eva Lerner-Lam; [email protected] Survey Informational report John Overman; 817-462-0516; [email protected] Steve Hofener; [email protected] Technical project support Web ITE Journal article Web-based directory Manual Informational report Sponsored sessions Recommended practice Informational report Gary B. Thomas; 979- 458-3263; [email protected] Martin Lipinski; 901-678-3279; [email protected] Michael Kyte; 208-885-6002; [email protected] Gary B. Thomas; 979-458-3263; [email protected] Ronald Eck; 304-293-3031 ext. 2627; [email protected] Joe Champagne; 914-576-6543; [email protected] Richard Hawthorne; [email protected] Ed Papazian; [email protected] Brian Betlyon; 410-962-3743; [email protected]

Transit Council** Transportation Consultants Council*** Transportation Education Council

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Informational report Tad Widby; 916-567-2501; [email protected] Informational report Ahmad Al-Akhras; [email protected] Stein Lundebye; 202-458-0148; [email protected] Policy and ITE Journal article Angie Christo; 614-543-7030; [email protected] Newsletter

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