The Impact of 

Automated Transit, Pedestrian, 

and Bicycling Facilities on 

Urban Travel Patterns 

The Exploratory Advanced Research Program

Summary 
Foreword

Full usage of rapid transit systems that serve major urban areas can reduce road congestion and greenhouse 

gas emissions. One obstacle to greater use of available rapid transit systems is the distance between the 

rapid transit station and the traveler’s origin or destination, termed the last-mile problem. To address 

the last-mile problem, the investigators of this research project, sponsored by the Federal Highway 

Administration’s Exploratory Advanced Research Program, asked whether the use of rapid transit might 

be increased by implementing an automated, high-frequency community shuttle service to the transit 

station and improving urban design near the stations to accommodate pedestrians and cyclists. The 

investigators surveyed residents of four metropolitan Chicago neighborhoods, all served by rapid transit 

but differing in levels of population density and affluence. By drawing on the survey data and by using 

agent- and activity-based modeling developed by the research team, the investigators found that a 

significant shift of commuters from automobiles to rapid transit might be achieved with implementation 

of the potential shuttle service and design improvements. The investigators also explored how perceptions of cost, safety, and time affect travelers’ choice of mode. 

Replication of this study, validation of its forecasts, and refinement of the research models are now 

needed to understand significant shifts in travel and mode choice. Although the deployment of automated 

vehicles is approaching technological feasibility, research is also needed to understand and address associated public policy and institutional issues, particularly with regard to public transit applications. The 

results of this project suggest that further research is indeed warranted.

Joseph I. Peters

Director, Office of Operations Research 

and Development

Federal Highway Administration

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for 

the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential 

to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. 

Standards and policies are used to ensure and maximize the quality, objectivity, utility, 

and integrity of its information. FHWA periodically reviews quality issues and adjusts its 

programs and processes to ensure continuous quality improvement.

Cover background image: © shutterstock.com. All other cover images: © University of Michigan.

Debra S. Elston

Director, Office of Corporate Research, 

Technology, and Innovation Management

Federal Highway Administration
Technical Report Documentation Page 

i

Summary	
  Report:	
  Automated	
  Shuttle DRAFT 3/4/2015

EAR	
  Program	
  Project:	
  University	
  of	
  Michigan iii

Technical	
  Report	
  Documentation	
  Page	
  

1. Report No.

FHWA-HRT-15-015

2. Government Accession No. 3. Recipient’s Catalog No.

4. Title and Subtitle

Impact of Automated Transit, Pedestrian, and Bicycling 

Facilities on Urban Travel Patterns: Summary Report

5. Report Date

June 2015

6. Performing Organization Code: 

7. Author(s)

Jonathan Levine and Tom Morton

8. Performing Organization Report No. 

9. Performing Organization Name and Address

University of Michigan

2000 Bonisteel Boulevard, Ann Arbor, MI 48109

University of Illinois at Chicago

2035 W. Taylor Street, Chicago, IL 60612

Woodward Communications

1420 N Street, NW., Suite 102, Washington, DC 20005

10. Work Unit No.

11. Contract or Grant No.

DTFH61-09-C-00013

DTFH61-09-F-00027

12. Sponsoring Agency Name and Address

U.S. Department of Transportation

Federal Highway Administration

Office of Operations Research and Development

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered 

Summary Report 

September 2009–August 2013

14. Sponsoring Agency Code 

HRTM-30

15. Supplementary Notes

FHWA’s Contracting Officer’s Task Manager (COTM): Zachary Ellis, HRTM-30

Technical Contact: Robert A. Ferlis, Technical Director, Office of Operations Research and Development

16. Abstract

Researchers conducted a survey in four metropolitan Chicago neighborhoods served by commuter rail to explore 

how residents’ travel preferences might change with the potential addition of (1) an automated community transit 

(shuttle) service to and from the station and (2) a package of streetscape improvements to facilitate walking and 

bicycling to the station. The neighborhoods differ in levels of population density, current rail use, land use, and 

affluence. By using a telephone and mail survey to determine residents’ current travel patterns and preferences 

with the potential improvements, agent-based modeling, and activity-based modeling, the researchers forecast a 

possible overall decrease in car use of 39 percent and an increase in commuter rail use of 34 percent with the 

improvements. The shuttle service produced greater changes in lower density neighborhoods, with forecast of 

transit use doubling in the lowest density neighborhood. Travelers’ perceptions of cost, time, and safety are 

explored, and the differences among communities’ responses to the improvements and their implications for the 

relative effectiveness of each potential improvement are discussed. This report summarizes the Exploratory 

Advanced Research Program project “Effects of Automated Transit and Pedestrian/Bicycling Facilities on 

Urban Travel Patterns.” The final project report is available at https://taubmancollege.umich.edu/faculty/

faculty-publications/effects-automated-transit-pedestrian-and-bicycling-facilities-urban. 

17. Key Words

Automated transit, automated vehicles, 

neighborhood shuttles, bicycling facilities, public 

transit, cycling, last-mile problem, pedestrians, 

transit shuttle, urban travel patterns. 

18. Distribution Statement

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

20

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
ii
iii

Table of Contents

INTRODUCTION v

THE STUDY NEIGHBORHOODS AND TRANSIT STATIONS 1

Village of Skokie 2

Town of Evanston 2

Town of Cicero 3

Neighborhood of Pilsen 3

POTENTIAL IMPROVEMENTS DESCRIBED IN THE SURVEY 4

Transportation Improvements 4

Design Improvements 4

METHODS 6

Household Survey 6

Modeling and Simulations 9

RESULTS 10

Differences by Land-Use Density 10

Differences by Improvements 10

Differences by Level of Use 11

CONCLUSIONS AND RECOMMENDATIONS 13

REFERENCES 14
List of Figures

Figure 1. Locations and household density of the four metropolitan Chicago 

neighborhoods on which the study was based. 1

Figure 2. Land-use map of the buffer zone centered around Pilsen’s Hoyne/

Damen transit station. 2

Figure 3. Example of the illustrated improvements. 5

Figure 4. Sample worksheet with illustration of transportation improvements 

at the West Cullerton Street and South Damen Avenue approach to Pilsen’s 

Hoyne/Damen CTA Station. 8

Figure 5. Combined model results using the neighborhood best fit coefficients 

comparing and testing the effect of community transit. 11

List of Tables

Table 1. Neighborhood selection scheme. vi

iv
v

This report summarizes the results of a Federal Highway Administration (FHWA) Exploratory 

Advanced Research (EAR) Program research project that explored the potential of a hypothetical 

driverless vehicle to improve access to and use of available rapid-transit rail service. The distance 

between a traveler’s origin or destination and the nearest public transit station is often time-consuming, 

inconvenient, or unsafe to travel and may discourage potential transit riders from using the system. This 

distance, known as the “last-mile problem,” impedes full usage of existing transit systems, particularly 

in outlying suburban and exurban areas. 

Walking, cycling, driving or being driven, or riding a station feeder bus line are the usual options for 

reaching the nearest station. In some public transit systems, community shuttle buses or vans supplement 

existing feeder bus lines to improve residents’ access to commuter rail stations, but the challenge in 

providing community shuttles is the high cost of labor, fuel, and equipment, particularly in neighborhoods 

with low population density. In these areas, the cost per rider for shuttle service can be prohibitively high, 

whether in the form of rider fares or tax-supported 

subsidies. Automated vehicles would eliminate the 

cost of operator labor from this equation, possibly 

lowering costs sufficiently to make high-frequency 

service feasible and offering a solution to the last-mile 

problem. Recent rapid advances in automated vehicle 

technology have brought the driverless vehicle within 

reach, potentially within the next decade for lowspeed neighborhood travel. 

Whether the availability of an innovative transit 

shuttle service would be incentive enough to attract 

large numbers of people to public transit is an open question, however. In this project, the University of 

Michigan and the University of Illinois at Chicago conducted an initial inquiry into the potential impact of 

three types of neighborhood improvements on residents’ use of transit: 

•	 Automated, high-frequency community shuttle service to and from commuter rail stations.

•	 Cycling facilities.

•	 Urban design improvements in the vicinity of the transit station to facilitate walking and cycling.

The researchers also explored the effect of changes in the costs of parking and driving on public 

transit use. 

Introduction

The full final report of this project, Effects of 

Automated Transit, Pedestrian, and Bicycling 

Facilities on Urban Travel Patterns (September 2013), is available on the University of 

Michigan Web site: https://taubmancollege.

umich.edu/faculty/faculty-publications/

effects-automated-transit-pedestrian-andbicycling-facilities-urban.
This project was not a feasibility study; rather, the research design was a “best-case” approach to help 

assess whether the concept of using automated vehicles as transit shuttles holds promise for further 

research and development. The project’s purpose was to inform discussions on policy choices regarding 

this option. Of specific interest was the relative capacity of the potential improvements to generate changes 

in travel behavior, that is, to shift trips from automobile to other modes of transportation and to increase 

use of regional public transit based on improved station access.

The best-case assumptions for the research included no congestion on local streets, no limitations due 

to weather or nighttime conditions, and unrestricted ability to alter rights-of-way to make transit and environmental improvements. Because the researchers examined whether the frequency and quality of service 

deemed possible with automated neighborhood shuttles might increase transit use and did not evaluate 

the feasibility, practicability, or acceptability of deploying the shuttles, the driverless aspect of the shuttles 

was not discussed with the research participants. 

The study had several related elements:

•	 A literature review to identify urban design improvements shown to have a positive effect in promoting

multimodal travel.

•	 An inventory and selection of sites and station approaches in four metropolitan Chicago neighborhoods,

including mapping a 1.5-mi (2.4-km) buffer zone around the selected station by using geographical 

information system data (rights of way, land use, and census data).

•	 Preparation of photographs and illustrations of station approaches and potential improvements.

•	 A mail and telephone survey of households located within about1.5 mi(2.4 km) of the station.

•	 Simulations using activity-based and agent-based modeling.

The research focused on four Chicago-area neighborhoods—Evanston, Skokie, Pilsen, and Cicero, 

Illinois. All are first-ring suburbs or, in the case of Pilsen, within Chicago city limits, and all are served by 

Chicago Transit Authority (CTA) rapid transit lines with capacity for increased use. The researchers 

selected the neighborhoods to represent different combinations of housing density and affluence, as shown 

in table 1. 

Table 1. Neighborhood selection scheme.

 Lower Income Higher Income

More Auto-Oriented Cicero Skokie

Less Auto-Oriented Pilsen Evanston

The following sections discuss the characteristics of the four neighborhoods and transit stations and the 

neighborhood improvements that were the basis for the research.

vi
The Study Neighborhoods and Transit Stations

The research team selected the four neighborhoods in the study to represent two broad conditions of land-use mix and population 

density and two broad conditions of household 

income to ensure that the research findings could 

be generalized to a variety of urban conditions. 

Each neighborhood was served by at least one CTA 

station, with service frequencies in the range of 7 to 

15 minutes. See figure 1 for the location and housing 

density of each neighborhood.

Figure 1. Locations and household density of the four metropolitan 

Chicago neighborhoods on which the study was based. 

Within each neighborhood, the research team 

selected a transit station and mapped a buffer zone 

of 1.5-mi (2.4-km) radius around it. This zone provided the population for the simulations. Within 

the buffer zone, the researchers chose two smaller 

focus areas within 0.5 mi (0.8 km) of the station, A 

and B, on which to base the project’s survey. The A 

and B focus areas surround two different 

approaches to the CTA station to facilitate planning, designing, and illustrating the potential 

improvements. Each station approach included a 

street intersection close to the station that became 

the site of the transit, cycling, and urban design 

improvements that were described and illustrated 

in survey materials. An example of a land-use map 

with buffer zone and focus area demarcated is 

1

© University of Michigan
2

shown in figure 2, with the two approaches 

numbered “01” and “02.” The following sections 

provide a brief description of each neighborhood. 

The research team obtained the neighborhood 

demographic information from publicly available 

sources and survey responses.

Village of Skokie 

The Skokie/Morton Grove neighborhood, served 

by the Yellow Line, is an area with predominantly 

low-density residential land use and socioeconomic composition of primarily middle-to-high 

income, ranking high on measures of suburban living quality. The area has a complete street network, 

although some fragmentation is introduced by 

highways and railroads. The Skokie station offers 

connections with four bus lines, indoor bike parking, and a park-and-ride facility, and it also serves 

as the Greyhound bus terminal. Service frequency 

varies between 10 and 15 minutes during weekdays 

from 5 a.m. to 11:15 p.m. On weekends, frequency is 

every 15 minutes between 6:30 a.m. and 11:15 p.m. 

There are no other stations within the buffer zone 

around the station, and residents are highly dependent on cars for transportation.

Figure 2. Land-use map of the buffer zone centered around Pilsen’s 

Hoyne/Damen transit station. [NOTE: The highlighted area contains 

the A and B focus areas included in the survey, and the station area 

improvement sites are marked “01” and “02.”] 

Evanston Demographics

Average family size, 3–3.5 members

Vehicles per household, 1.0–2.0

Average annual family income, $75,000 

(northwest subarea, $55,000)

Current travel mode share to Chicago’s inner 

central area: Train, 65.4%, Bicycle, 2.3%, 

Bus, 1.8%, Driving, 30.5%

Skokie Demographics

Average family size, 3 members

Vehicles per household, 1.5–2.5

Current travel mode share to Chicago’s inner 

central area: Train, 39.5%, Bicycle, 0.6%, 

Bus, 1.7%, Driving, 58.1%

Town of Evanston 

Evanston, served by the Purple Line, is a mixed-use 

area with a socioeconomic composition of primarily middle-to-high income. Evanston has a fully 

connected street network. The focus area covers 

both low-density residential areas toward the 

south and a more mixed-use and high-density 

downtown area around the Davis station, a downtown stop on the Purple Line that was selected for 

the study. Service frequency varies from 7 to 14 

minutes. The station offers connections with seven 

bus lines and was one of four test sites for the Active 

Transit Station Signs program, which provides 

real-time transit and traffic message signs that 

display travel time, next departing train, delay, fare, 

and other CTA-programmed information. The 

buffer zone around the CTA Davis station includes 

six other stations on the Purple Line as well as a 

Metra commuter rail stop. The two focus areas 

selected were a residential neighborhood and a residential neighborhood with an institutional anchor.

© University of Michigan
3

Town of Cicero 

Cicero, served by CTA’s Pink Line, is an area with 

predominantly residential land use and a socioeconomic composition of low-to-middle income. Like 

Pilsen, Cicero is fragmented by industrial sites, but 

its residential areas are lower in density. The focus 

CTA station, 54th/Cermak, is the last stop on the 

Pink Line and offers connections with five bus 

lines, indoor bike parking, and a park-and-ride 

facility. Service frequency varies from 7.5 to 15 minutes. The focus area is dominantly residential and 

excludes the industrial areas and the higher income 

neighborhoods to the west. The surroundings of 

the 54th/Cermak station are more residential compared with those of the three other stations located 

in the buffer zone.

Neighborhood of Pilsen 

Located in the lower west side of Chicago and 

served by the CTA Pink and Blue Lines, Pilsen is a 

mixed-use area with a socioeconomic composition 

of low-to-middle income. Pilsen has high-density 

residential areas and large industrial areas traversed only by major arterial roads. The focus CTA 

station in Pilsen, Hoyne/Damen on the Pink Line, 

has indoor bike parking and connects with two 

CTA bus lines. Service frequency varies from 8 to 

15 minutes. The buffer zone around the station 

includes five other stations on the Pink Line and 

one on the Blue Line. An industrial area on the 

south and a university-related area of development 

in the northeast were not part of the focus area.

Cicero Demographics

Average family size, 3.5–4 members

Vehicles per household, 2.0–2.5

Average annual family income

Near station, $45,000–$55,000

Toward the east, >$75,000

Toward the west, <$45,000

Current travel mode share to Chicago’s inner 

central area: Train, 32.0%, Bicycle, 2.3%,

Bus, 9.8%, Driving, 56%

Pilsen Demographics

Average family size, 3.5–4 members

Vehicles per household:

Near station, 0–1.0

Not near station, 1.0–1.5

Average annual family income, $45,000

(northeast subarea, $65,000–$75,000)

Current travel mode share to Chicago’s inner 

central area: Train, 24.6%, Bicycle, 4.8%,

Bus, 32.6%, Driving, 38.0%
4

Potential Improvements Described in the Survey

The researchers designed potential transportation (shuttle and biking facilities) and urban design (streetscape changes) improvements 

for each station approach (two for each transit 

station), and they described and illustrated the 

improvement changes in materials that were 

distributed in the neighborhood surveys. For 

each approach, seven illustrations were prepared 

that showed: 

•	 The streetscape with no changes.

•	 The streetscape as it would be changed by transportation (shuttle and cycling) improvements at 

three levels of use (e.g., current level of users, a 

few more users, and a lot more users).

•	 The streetscape as itwould be changedwith both

the transportation improvements and additional 

streetscape features, also at three levels of use. 

The transportation and streetscape design improvements are described in the following sections.

Transportation Improvements

The primary hypothesis in the study was that an 

automated high-frequency community shuttle service would increase transit use and reduce driving. 

The shuttle vehicle would circulate frequently 

through the neighborhood, delivering passengers 

to and from the regional rail station, on a fixed route 

and a fixed schedule. Illustrations in the survey 

materials showed the shuttle vehicle near spacious, 

covered transit stops with seating. 

Bicycle facilities were the second transportation 

improvement and included well-marked, dedicated 

bicycle lanes; bicycle traffic signals; and bicycle 

stands. Illustrations in the survey showed the 

brightly colored bicycle lanes located, where possible, between the street curb and parked cars.

Design Improvements

The design elements illustrated in the survey 

materials target safety, density of users, and attractiveness of surroundings to users near the station. 

Some of the elements that have been shown to 

increase use of alternatives to driving include the 

presence of pedestrians, shops and businesses, 

benches and other places to sit, a friend or neighbor using the same route, and traffic control devices 

that aid pedestrians.(1) For bicyclists, bicycle lanes, 

bicycle signals, and bike racks near public transit 

are important.(2,3,4) Transit riders value sheltered, 

well-lit waiting areas and safe access to vehicles.(5,6)

Although diversity of land use and density of the 

built environment have also been shown to improve 

walkability, this research was focused on assessing 

environmental improvements that did not require 

changes in land use; therefore, no alterations to the 

built environment were shown in the illustrations. 

The improvements illustrated in the community 

survey included the shuttle and bicycle facilities 

described previously and an assortment of streetscape features: widened and brightened sidewalks, 

pedestrian crosswalks, a generous tree canopy and 

continuous plantings, signs, public art, magazine and 

newspaper dispensing boxes, trashcans, light poles, 

and sign posts. The survey illustrations also represented different levels of use with the addition of 

pedestrians, cyclists, and transit users in the vicinity 

of the intersections. For an example, see the illustrations prepared for Site 2 at the Hoyne/Damen station 

in Pilsen in figure 3. A photograph of the unchanged 

area is shown first. Three images follow with transportation improvements (shuttle vehicle and bicycle 

facilities) at increasing levels of use. The final three 

images show both the transportation and the urban 

design improvements at increasing levels of use.
5

Figure 3. Example of the illustrated improvements. [Note: The seven graphics depict site 2, the Damen Avenue 

approach to Pilsen’s Hoyne/Damen CTA station.] 

Current State

Transportation Improvem.

Current level of users

Transportation Improvem.

Few more level of users

Transportation Improvem.

Much more level of users

Transportation Improvem.

Current level of users

Transportation Improvem.

Amenities

Few more level of users

Transportation Improvem.

Amenities

Much more level of users

CTA Station Hoyne/Damen (Pilsen, Chicago)

Site 2: Intersection of S Damen Av. and W21st St.

0

A

B

C

D

F

G

vegetation (shade)

★Improvements

improved

pedestrian crossing

co
ee shop

transit shop

community

transit 

bike lanebike lane

vegetation

(shade & bu
er)

vegetation

(shade & bu
er)

© University of Michigan
6

Methods

The research team used three analytical 

approaches in the study: a mail and telephone 

survey; activity-based modeling of respondents’ choice of travel modes, based on the survey 

results; and agent-based modeling of commuters 

and their preferences regarding cost, travel time, 

and safety considerations. The agent-based model, 

calibrated with data from the four neighborhoods, 

was developed by first using parameters from the 

travel behavior literature and then incorporating 

parameters from the study’s activity-based model. 

Commuters in the model choose transportation 

options based on their preferences, characteristics 

of the environment, and the travel modes available 

to them.

Household Survey

The research team conducted a survey of at least 

150 respondents in each of the four neighborhoods. 

Respondents lived within 1.5 mi (2.4 km) and 

worked within 3 mi (4.8 km) of a CTA rail station. 

The research team designed the household survey 

to collect information about the household, the 

respondent’s current travel behavior, mode preferences under the potential transportation and 

design improvements, and perceptions of mode 

cost, convenience, time, and safety. 

Staff from the Survey Research Laboratory at 

the University of Illinois at Chicago used a multimode design for the household survey. The staff 

used address-based sampling from the Delivery 

Sequence File constructed by the U.S. Post Office to 

obtain an initial 7,700 addresses within the A and B 

focus areas of the four neighborhoods. The staff 

divided sampling equally among the neighborhoods, and carried out recruitment in eight repetitions of the same experimental conditions during 

March–April 2012. Because of the low responses in 

Cicero, Pilsen, and Skokie, the survey staff added 

an additional 8,998 addresses in those neighborhoods in two additional samplings, with recruitment occurring during May–June and December 

2012. Thus, 16,698 households received the initial 

recruitment contact. 

The team conducted the survey in three steps:

1. Recruitment mailing to random sample:

•	 Advance letter describing the survey and

inviting participation.

•	 Response form and postage-paid return

envelope.

2. Study packet mailing to eligible respondents:

•	 Cover letter and consent information form.

•	 Travel diary covering 1 day, to be completed

on a randomly assigned weekday. 

•	 Booklet containing seven color images illustrating the status quo and potential improvements (customized to the address of the 

respondent) accompanied by six worksheets 

to be used in the telephone interview.

3. Telephone interview (30 minutes):

•	 To elicit the respondent’s modal preferences

through a process of completing the six 

illustrated survey worksheets and to elicit 

perceptions of cost, safety, quickness, and 

convenience.

The recruitment mailing asked for participation 

in the study and offered a cash incentive to eligible 

respondents who completed the written survey 

and the followup telephone interview. Anyone living in the household and over the age of 18 who 

spoke either English or Spanish (interviews and 

survey materials were available in either language) 

was eligible to return the response form, which 
7

asked whether the respondent works or goes to 

school outside the home, his or her work or school 

address, and how many times during the week the 

person travels to his or her nearest CTA rail station 

or within a half-mile (0.8 km) of that station. 

The survey team used a screening process to 

eliminate respondents who did not work or go to 

school outside the home, did not travel at least once 

a week to their CTA rail station area, or did not 

work or attend school within 3 mi (4.8 km) of the 

CTA system. The team sent the survey study packet 

containing the travel diary and booklet only to 

respondents deemed eligible. At least 1 day after 

the date assigned to the respondent to complete 

the travel diary, the survey team telephoned to 

conduct the followup interview.

The overall returns to the recruitment mailings 

were 10.1 percent, and the final participation rate—

respondents who completed the telephone interview—was 3.8 percent and ranged from 2.0 percent 

in Cicero to 9.2 percent in Evanston. 

Travel Diary

The travel diary centered on the respondent’s travels 

on a randomly selected weekday. The questionnaire 

devoted three pages to the main tour of the day (e.g., 

the series of trip segments between home and a destination or from a destination to home), with up to 

three segments, and contained space to add additional tours. Questions involved destination, travel 

times, travel modes, length of trip, and number of 

stops. The travel mode options offered were private 

vehicle as driver, private vehicle as passenger, bus, 

train, walking, cycling, and car-sharing. Questions 

also included any costs for parking or highway tolls.

Survey Booklet and Telephone Interview

The telephone interview had four parts: 

•	 Collecting information about the household.

•	 Collecting the travel diary entries, which represented the respondent’s current travel behavior

•	 Gathering the respondent’s perceptions of

the safety, convenience, quickness, and cost 

of the main trip with and without potential 

improvements.

•	 Recording the respondent’s travel preferences

under the six potential levels of transportation 

and design improvements.

The survey booklet that was mailed as part of 

the study packet contained six worksheets covering the transit station approach with which the 

respondent’s address was associated. Each worksheet was illustrated with one of six “improved” 

scenarios (a sample is shown in figure 4). These 

worksheets were completed one by one during 

the telephone interviews, which were conducted 

by using CASES, the Computer-Assisted Survey 

Execution System Program, version 5.4.(7) The 

interviewer supplied travel times and costs for 

each travel mode based on the times, starting point, 

and destination data for the main trip in the respondent’s travel diary. Survey software generated the 

values for the interviewer. The interviewer then 

asked the respondent to reflect on the worksheet 

information and image and select the mode of 

transportation that they would prefer to use for the 

trip recorded in the diary. 

Limitations of the Survey

Although the survey team sent the initial recruitment mailing to a random sample within the 

defined geographic areas, the survey respondents 

were a self-selected sample, and their participation likely reflects a greater interest in transit, 

cycling, and walking as alternatives to driving 

than that of the general population. As a result, 

the survey results cannot be used to make population inferences. The assumed positive bias, 

however, is in line with the mission of the study, 

which was to estimate a best-case scenario for the 

community shuttle.
8

Figure 4. Sample worksheet with illustration of transportation improvements at the West Cullerton Street and 

South Damen Avenue approach to Pilsen’s Hoyne/Damen CTA Station. 

© University of Michigan
9

Modeling and Simulation

Data from the neighborhood surveys were the basis 

of the activity-based model. The survey incorporated 

both the respondents’ current travel patterns and 

their stated preferences after potential implementation of the improvements, as described and illustrated in the survey materials. The stated preference 

portion of the data was used to estimate an activitybased model of mode choice. Utilities from this 

model were then used to revise initial parameters 

used in the agent-based model. In this way, the 

empirical estimation of the activity-based model was 

combined with the capacity of the agent-based 

model to simulate changes over time.

In the stated-preference survey, respondents 

chose from five travel modes:

•	 Drive.

•	 Community shuttle to the transit station.

•	 Walk to the transit station.

•	 Cycle to the transit station.

•	 Cycle to destination.

Information presented about the travel options 

included travel time to the CTA station by shuttle, 

time between shuttles, driving time to the destination, parking cost at the destination, CTA train 

frequency, station-to-station travel time, and fare. 

Some variables changed according to the residential location of the respondent but did not vary 

among the hypothetical scenarios. These variables 

included: walk time to the CTA station, cycle time 

to the CTA station, cycle time to the destination, 

CTA travel time from station to station, and CTA 

train frequency. The respondents’ actual choices 

were compared against their stated preferences.

The research team built a prototype agent-based 

model to represent commuters living within a 

1.5-mi (2.4-km) radius of a transit station in their 

neighborhood and work or study in the downtown 

area, making transit a feasible commuting choice. 

As part of a larger metropolitan area, commuters 

have a choice of various transportation modes, and 

they base their decisions on their preference for 

travel time, transportation cost, and perceived 

safety. The neighborhoods, commuting modes, and 

parameters were modeled after the four Chicago 

neighborhoods in the study. The agent-based 

model incorporated parameters from the activitybased model, and the simulations were run on this 

integrated model.

A permanent link to the agent-based last 

mile commuter behavioral model is available 

at www.openabm.org/model/4055/version/

1/view http://www.openabm.org/model/4055/

version/1/view. The model is built on NetLogo 

5.0.2 and works on multiple operating 

systems.
10

Results

Results from the integrated model showed that 

the presence of the community transit and 

urban-design improvements had a marked 

effect on the sample population. Modeling with and 

without community transit and a set of urban amenities resulted in noticeable reductions in driving, as 

shown in figure 5. The decrease in the percentage of 

travelers who drove cars on their commuting trips 

varied between 7 percent and 29 percent, with the 

largest percentage-point reductions seen in the more 

auto-oriented areas of Cicero (16 percent) and Skokie 

(29 percent). Auto-use reductions were also significantly lower in areas with greater transit use to begin 

with; specifically Pilsen (8 percent) and Evanston 

(7 percent). The increase in the percentage of travelers who used the train varied between 9 percent 

and 28 percent, with more auto-oriented Skokie 

(28 percent) and Cicero (23 percent) exceeding the 

denser Pilsen (12 percent) and Evanston (9 percent). 

CTA mode shares among the modeled population 

increased from 24 percent to 52 percent in Skokie, 

46 percent to 55 percent in Evanston, 52 percent to 

75 percent in Cicero, and 52 percent to 64 percent in 

Pilsen. Across all neighborhoods, the results indicated that community transit might possibly decrease 

car use for these trips from the current 36 percent to 

22 percent and increase CTA share from its current 

50 percent to 67 percent. Community transit was 

shown to produce the greatest change in the lower 

density areas of Skokie and Cicero. 

Differences by Land-Use Densit

One of the most robust findings in the project was 

that the community shuttle produced greater change 

in the lower density areas of Skokie and Cicero. 

These less dense neighborhoods were more sensitive 

to higher parking costs, streetscape improvements, 

and the shuttle service than were the denser and 

more pedestrian-oriented neighborhoods (Pilsen 

and Evanston). Results from the stated-preference 

survey questions suggest that the shift from car to 

transit would be even greater if supported by policy 

changes that affect the cost of driving.

In contrast, where environments are more 

urban in character with walkable neighborhoods, 

more accessible transit, and higher parking costs, 

fewer gains may be realized with a community 

shuttle. For example, Evanston was the least 

responsive to the shuttle service—bus service to 

its CTA and Metra stations is already quite good. 

The higher density in central Evanston would also 

explain why the community shuttle service and 

street improvements seem to serve different 

populations: Shuttles would likely target residents 

living further away but close to shuttle routes, 

whereas streetscape improvements target commuters who have to spend more time walking 

across the neighborhood. As a result, the effects of 

applying each policy independently add up in the 

combination scenario. 

Differences by Improvements

The first level of improvements represented in the 

survey was the community shuttle with a bicycle 

lane; the shifts in respondents’ mode choices 

occurred at this level. The second level of improvements, urban design improvements with the shuttle 

and bicycle facilities, showed minimal further shifts. 

Running the model with and without 

community transit for each neighborhood 

shows that adding shuttles can lead to 

noticeable reductions in driving.
11

Figure 5. Combined model results using the neighborhood best fit coefficients comparing and 

testing the effect of community transit.

Extensive urban design improvements beyond the 

bike lane were tested, and none of them had a 

measurable impact on mode choice in the study. As 

a result, although there is support in the modechoice literature for the potential of urban design 

improvements to reduce driving, this research did 

not generate additional empirical evidence for that 

hypothesis. Streetscape improvements tended to 

support transit use for residences closer to train 

stations. Results from the activity-based model suggest that of the design variables, the frequency of the 

shuttle service had the greatest influence on its use.

Differences by Level of Us

The researchers also asked whether the presence 

of pedestrians, cyclists, and other transit users in 

greater numbers would affect traveler’s perceptions 

and shift mode choices to transit. Three levels of 

use were represented in the survey images for 

the transportation and urban design improvements. This hypothesis was tested in agent-based 

and activity-based modeling, and neither found 

an effect.

© University of Michigan

13

Conclusions and Recommendations

The purpose of this EAR Program project 

was to aid in an assessment of whether 

automated vehicle technologies deployed 

as community shuttles to transit stations hold 

promise for further research and development. 

The research was conducted within a best-case 

framework and adopted best-case assumptions. 

The research team explored the potential of transportation and urban streetscape improvements to 

increase transit use within cities and suburban 

neighborhoods without significant changes to the 

built environment. The specific improvements 

included an automated high-frequency, fixed-route 

community shuttle serving the transit station; 

bicycle lanes, paths, racks, and signals; and 

streetscape changes, such as more trees, wider 

sidewalks, and better lighting. The project used 

three forms of analysis—survey research, activitybased modeling, and agent-based modeling—as a 

check against one another and ultimately combined them into a single model to explore the 

impact of the potential improvements.

The project results suggest that high-frequency 

transit shuttles could trigger significant shifts from 

driving to public transit. Shifts to public transit 

may be larger in low-density neighborhoods that 

are more automobile-oriented and in neighborhoods where bus service is unavailable, unreliable, 

or infrequent. Streetscape improvements targeting 

areas near transit stops may reinforce these shifts, 

as may policies that modify other aspects of travel. 

The strong response to cycling improvements in 

particular suggests that there is considerable 

growth potential for this mode with installation of 

the appropriate facilities. 

The research suggests that greater shifts can be 

expected in urban and close-in suburban neighborhoods that are less transit-oriented. 
14

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About the EAR Program

Federal legislation establishes an Exploratory Advanced Research (EAR) Program to address longerterm, higher-risk, breakthrough research with the potential for dramatic long-term improvements to 

transportation systems—improvements in planning, building, renewing, and operating safe, congestionfree, and environmentally sound transportation facilities. The Federal Highway Administration’s (FHWA) 

EAR Program secures broad scientific participation and extensive coverage of advanced ideas and new 

technologies through stakeholder engagement, topic identification, and sponsored research. 

For more information, please visit the program Web site at http://www.fhwa.dot.gov/advancedresearch/

index.cfm. 
Office of Operations Research and Development

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

Publication No. FHWA-HRT-15-015

HRTM-30/06-15(WEB)E