Guidebook on Methods to Estimate Non-Motorized Travel: Supporting Documentation
of Oregon. Making the Land Use Transportation Air Quality Connection:
Volume 4A, The Pedestrian Environment. Portland, OR, 1993. Available
at http://www.telepport.com/~friends/ Lutraq2/Docs.htm
between the Pedestrian Environment Factor used in modeling and various travel
behavior characteristics such as mode split and vehicle-trips per household.
Includes basic correlations as well as regression modeling to account for
effects of socioeconomic and accessibility characteristics.
Cathy L., Nonmotor Travel in the 1990 Nationwide Personal Transportation
Survey. Transportation Research Record 1502, 1995.
||Analysis of NPTS
data to contrast the characteristics of travelers and of trip characteristics
by non-motorized vs. motorized modes (i.e., distribution of trip purposes
by mode; distribution of income categories by mode; etc.)
|Ashley, Carol A. and Chris Banister. Cycling to Work from Wards in a Metropolitan Area. Traffic Engineering and Control,
Vol. 30 Nos. 6-8, June - September 1989.
||This is a study using UK census data which (1) evaluates factors influencing cycling to work; (2) develops a model to
predict the proportion of residents in a ward cycling to work; and (3) tests the model. A variety of factors are tested including personal
characteristics, trip distance, availability of other modes, traffic levels, and local climate/topographical factors.
The authors conclude that "while it is possible to isolate some factors in the form of a model for particular areas, when the model is applied
elsewhere the fit is not so good" and that there are significant difficulties involved with developing a transferable model.
|Aultman-Hall, Lisa, Fred L. Hall and Brian B. Baetz. Analysis of Bicycle Commuter Routes Using GIS - Implications
for Bicycle Planning. Presented at the 1997 Transportation Research Board Annual Meeting, Paper #970168, January 1997.
||This analysis makes use of a GIS network data base to determine the characteristics of 397 routes used by commuter cyclists in
Guelph, Ontario, and to compare them to the shortest path routes between each origin and destination. The analysis provides useful insight for
understanding factors affecting travel behavior such as grades, intersections, etc. The study recommends different priorities for improving
conditions for existing cyclists and for attracting new cyclists to the network.
Bicyclists Evaluate Their Environment: Some Results. M.Sc. Thesis,
Department of Civil and Environmental Engineering, University of Wisconsin,
development of discrete choice models, based on stated-preference surveys,
to determine preferences of bicyclists for various route characteristics.
and Smith, R.L. Bicyclist Link Evaluation: A Stated-Preference Approach.
In Transportation Research Record 1085, 1986.
and L.H. Immers. Bicycle Ownership and Use in Amsterdam. Transportation
Research Record 1441, 1994.
of Amsterdam were interviewed about their ownership and use of a bicycle.
Questions included reasons for not owning a bicycle; reasons for using/not
using a bicycle; and use by trip purpose and facilities/incentives provided.
and B. Patel. A Method for Estimating Pedestrian Volume in a Central
Business District. Transportation Research Record 629, 1977.
study to model pedestrian volumes in the Milwaukee CBD as a function of
land use characteristics. Regression models are developed to relate block-level
land use data (square feet by type of use) to pedestrian volumes. These
models can be used to estimate pedestrian volumes in areas where counts
do not exist, and to forecast future volumes as a result of land use changes.
and Bruce Burgess. Warwick Bicycle Transportation Plan: Trip Generation
Draft Report. Prepared by the Bicycle Federation of America for the Rhode
Island Department of Transportation, Washington, DC, 1997.
estimated trip generation for traffic analysis zones adjacent to the alignment
of potential bicycle routes, based on employment, school enrollment, and
total population. Composite trip generation scores were then attributed
to network segments within the areas of influence of trip generators. The
results of this analysis were compared to the existing designated bicycle
route network. Alternative route designations were suggested where undesignated
roadway links' potential scored higher than a parallel or adjacent designated
route. The results of this sketch planning effort served as the basis for
final facility improvement recommendations.
|Beltz, Mike, and Herman Huang. Bicycle/
Pedestrian Trip Generation Workshop:
Summary. Sponsored by: Federal Highway
Administration, Washington, DC,
|Summarizes results of a workshop held to discuss
data sources on bicycle and pedestrian trip-making and to summarize the
state-of-the-practice in bicycle and pedestrian demand modeling.
|Betz, Joe; Jim Dustrude; and Jill Walker.
Intelligent Bicycle Routing in the United States. Transportation
Research Record 1405, 1994.
||Discusses the use of Intelligent Transportation
System (ITS) technology for bicycle routing.
|Botma, Hein. Method to Determine Level
of Service for Bicycle Paths and Pedestrian-Bicycle Paths. Transportation
Research Record 1502, 1995.
||Describes Level of Service (LOS) measures for
pedestrians and bicyclists on shared paths. LOS is based on the perceived
hindrance to users, as a function of volumes of both types of users, path
width, and speeds.
|Botma, Hein; Hans Papendrecht. Operational
Quality of Traffic on a Bicycle Path. Institute of Transportation Engineers
(ITE) 1993 Compendium of Technical Papers, ITE; Delft University of Technology,
pp. 81-85, 1993.
||See Botma (1995).
|Bovy, Piet H.L. and Mark A. Bradley. Route
Choice Analyzed with Stated-Preference Approaches. Transportation Research
Record 1037, 1986.
||The authors use stated-preference surveys to develop
a discrete route choice model. Route factors include facility type, surface
quality, traffic level, and travel time (each described qualitatively at
|Bowman, John L. and Moshe Ben-Akiva.
Activity-Based Travel Forecasting. Massachusetts Institute of Technology,
Cambridge, MA; unpublished paper for the Travel Model Improvement Program,
sponsored by the U.S. Department of Transportation and the Environmental
Protection Agency, 1996.
||Overview of activity-based travel forecasting.
At least some of the models documented include non-motorized travel modes,
but methods and implications of activity-based forecasting for non-motorized
travel are not explicitly discussed.
|Brog, Werner and ERL Erhard. Potential
of the Bicycle as a Substitute for Other Modes of Transportation. Transportation
Research Record 909, 1983.
||Discusses characteristics of trips and trip-makers
to identify the extent to which trips could be taken by bicycle instead
of other modes.
|Burgess, Bruce; Bruce Landis, and Michael
Beltz, NFTC Regional Bikeway Implementation Plan. Prepared by the
Bicycle Federation of America for the Niagara Frontier Transportation Committee,
Buffalo, NY, 1998.
||This study uses the Bicycle Level of Service
(BLOS) to rate roadway conditions for 800 miles of roads in the Buffalo,
NY area. Through public involvement and consultant recommendations, target
levels of accommodation were designated: minimum LOS C for all links and
LOS B for certain priority routes and where opportunities exist.
|Caldwell, Erin. Modal Shift in the Boulder
Valley: 1990 to 1996. City of Boulder, Center for Policy and Program
Analysis, March 1997.
||Analysis of changes in travel patterns in
the Boulder Valley area based on biennial household travel surveys conducted
between 1990 and 1996. Purpose is to assess 1989 Transportation Master Plan's
objectives of progressively decreasing SOV use. Data suggest that initial
goals have been exceeded but that decrease in SOV use has leveled off. (Bicycle
and pedestrian mode splits are analyzed but changes are not statistically
|Cambridge Systematics and Barton Aschman Associates.
Travel Survey Manual. Prepared for U.S. Department of Transportation
and U.S. Environmental Protection Agency, 1996.
||A guide to conducting household and other
types of travel surveys that are used in the development of travel demand
|Cambridge Systematics, Inc. Modeling Non-Motorized
Travel (Work Plan). Cambridge, MA; unpublished draft prepared
for Federal Highway Administration, 1996.
||Sets forth research and development priorities
for incorporating non-motorized travel in travel demand modeling efforts.
|Cambridge Systematics, Inc. Short-Term
Travel Model Improvements, Travel Model Improvement Program. U.S. Department
of Transportation; DOT-T-95-05, October 1994. (1994a)
||Recommends short-term improvements to travel
models. Discussion of non-motorized travel includes an overview of non-motorized
environment factors and mode choice in the Portland, OR, and Montgomery
Co., MD, travel models, as well as issues associated with modeling non-motorized
|Cambridge Systematics. The Effects of Land
Use and Travel Demand Management Strategies on Commuting Behavior. Prepared
for the Travel Model Improvement Program, U.S. Department of Transportation;
DOT-T-95-06, October 1994. (1994b)
||Using site surveys and statistical analysis,
examines relationships between site design variables, Travel Demand Management
measures, and commuter mode choice at a variety of workplaces in Southern
Research and Contract Standardization in Civil Engineering - The Netherlands,
Sign up for the Bike: Design Manual for a Cycle-friendly Infrastructure.
Bicycle Master Plan, record 10, The Netherlands, ISBN 90-6628-158-8,
for the Bike is a thorough design manual for creating an infrastructure
conducive to use of the bicycle. The report first presents the design requirements
necessitated by cyclists and then explores various ways those needs can
be met through traffic and urban infrastructure planning.
and Roger Gorham. Commuting in Transit Versus Automobile Neighborhoods.
Journal of the American Planning Association, Vol. 61, No. 2,
compares travel behavior (including non-motorized mode split and trip generation
rates) in "transit"-vs. "auto"-oriented
neighborhoods in the San Francisco and Los Angeles areas. Transit and auto
neighborhoods are selected in matched pairs to control for density, income,
etc. Transit and non-motorized trip rates and mode shares are higher in
Bay Foundation, Environmental Defense Fund, et al. A Network of Livable
Communities: Evaluating Travel Behavior Effects of Alternative Transportation
and Community Designs for the National Capital Region. Washington, DC,
non-motorized travel and influencing factors are included in travel modeling
to analyze alternative development scenarios. The PROMO (Proximity Mode
Choice Model) is a pivot-point logit sketch model which interacts with the
official Metro Washington model to evaluate the effects of pedestrian and
bicycle friendliness strategies on travel behavior.
|City of Portland,
OR, Office of Transportation. Identifying Priorities for Pedestrian Transportation
Improvements. Pedestrian Master Plan Project Development: Final
Report, June 30, 1997.
development of two indices to aid in prioritizing pedestrian projects:
the Pedestrian Potential Index and Deficiency Index. The Pedestrian
Potential Index highlights the locations where pedestrian activity is likely
to be greatest, based on land use and pedestrian environment conditions.
The Deficiency Index rates the quality of existing pedestrian infrastructure
to identify areas which are most deficient.
|Clark, David E. Estimating Future Bicycle
and Pedestrian Trips From A Travel Demand Forecasting Model. Institute
of Transportation Engineers, 67th Annual Meeting, 1997.
||Describes a process to adjust vehicle trip tables
in a travel demand model to account for future increases in bicycle and
pedestrian trips. Existing trips are stratified by length and purpose, and
adjustment factors which represent a potential percent increase in bicycle
and pedestrian trips as a result of future improvements to the bicycle and
pedestrian network are applied to reduce the number of vehicle trips. The
adjustment factors vary by trip purpose, length, and mode and are based
on local judgment.
|Clarke, Andy. Bicycle-Friendly Cities:
Key Ingredients for Success. Transportation Research Record 1372,
||Describes key factors that lead to high levels
of bicycling in certain cities.
|Cynecki, M.J., G. Perry, and G. Frangos. Study
of Bicyclist Characteristics in Phoenix, Arizona. Transportation Research
Record 1405, 1993.
||Describes characteristics of bicyclists in the
Phoenix area based on local surveys.
|Davies, D.G., M.E. Halliday, M. Mayes, and
R.L. Pocock. Attitudes to Cycling: A Qualitative Study and Conceptual
Framework. TRL Report 266: Transport Research Laboratory, Crowthorne,
Berkshire (UK), 1997.
||Examines attitudes towards cycling and factors
which would influence people to cycle, based on interviews, focus groups,
and stated-preference surveys. Introduces a conceptual framework for promoting
cycling based on concepts from the public health and social marketing fields,
which focus on identifying and changing behavior in stages. Also includes
a review of previous attitudinal studies in the UK.
|Davis, Scott E., L. Ellis King and
H. Douglas Robertson. Predicting Pedestrian Crosswalk Volumes.
Transportation Research Record 1168, 1991.
||The authors describe a method to measure and predict
pedestrian crosswalk volumes for the evaluation of traffic signal requests
and for the compilation of hazard indices data. The method uses short-term
counts of five to 10 minutes and is more cost effective than performing
|Deakin, Elizabeth A. Utilitarian Cycling:
A Case Study of the Bay Area and Assessment of the Market for Commute Cycling.
University of California, Berkeley, ITS Research Report, 1985.
||The author defines a demographic target group
for San Francisco Bay Area commuter cycling, based on data from the Bay
Area Travel Survey, a review of the literature, and interviews with local
and state officials. Her market is defined as: employed full-time;
under 40 years old; travel less than 11.2 km one-way to work; drives alone
during the peak-period; and owns a bike suitable for commuting. She then
uses these criteria to estimate a reasonable upper bound on the size of
the potential bicycle commuter market.
|Demetsky, Michael J. and David Morris.
Structuring an Analysis of Pedestrian Travel. Highway Research Record 467,
||Sets forth a framework for analyzing the demand
for pedestrian travel. This demand is hypothesized as a function of four
factors: functional class of the trip, trip characteristics, characteristics
of the trip maker, and quality of the walking environment. Desired data
include relative preferences for accommodations (by type of pedestrian)
as determined by attitudinal surveys; existing data on walking behavior
in different environments; and field evaluations of walking environments.
|Department of Transport. Traffic Advisory
Leaflet 8/95: Traffic Models for Cycling. London, UK, 1995.
||Overview of application of QUOVADIS-BICYCLE to
|DeRobertis, Michelle and Alan Wachtel. Traffic
to Encourage Bicycling. 1996 Compendium of Technical Papers, Institute
of Transportation Engineers 66th Annual Meeting, pp. 498-502, 1996.
||Discusses the compatibility of various traffic
calming measures with bicycling and recommends approaches to implementing
traffic calming in a bicycle-friendly manner.
|DHV Environment and Infrastructure. QUOVADIS-BICYCLE
Manual. Amersfoort, Netherlands (no date).
||Documentation for the QUOVADIS-BICYCLE network
|Dillman, D. Mail and Telephone Surveys:
The Total Design Method. Wiley-Interscience: New York, 1978.
||While somewhat dated, a generally excellent resource
for anyone interested in designing and conducting an attitudinal survey
of existing or potential bicyclists and pedestrians.
|Dixon, Linda. Adopting Corridor-Specific
Performance Measures for Bicycle and Pedestrian Level of Service. Transportation
Planning, city of Gainesville, Fla. Traffic Engineering Department, pp. 5-7,
||Describes the development and application of bicycle
and pedestrian level of service measures in Gainesville, FL.
|Eddy, Nils. Developing a Level of Service
for Bicycle Use, Pro Bike Pro Walk 96: Forecasting the Future, Bicycle
Federation of America/Pedestrian Federation of America, pp. 310-314,
||Describes the development of a bicycle level of
service measure to rate the suitability of roadway facilities for bicycling.
|Epperson, Bruce. Bicycle Transportation
Planning: A Quantitative Approach, DRAFT, pp. 1-42, January 15, 1996.
||Includes, among other items, a discussion of the
traditional travel demand forecasting process and its possibilities and
limitations with respect to bicyclists; a literature review of existing
quantitative approaches to bicycle travel; and potential future developments
for modeling of bicycle travel.
|Epperson, Bruce. Demographic and Economic
Characteristics of Bicyclists Involved in Bicycle-Motor Vehicle Accidents.
Transportation Research Record 1502, 1995.
||Examines demographic and economic characteristics
of bicyclists involved in bicycle-motor vehicle accidents. Accidents are
regressed against census tract characteristics to predict total and per-capita
accidents and to identify factors associated with accident risk.
|Epperson, Bruce. Evaluating Suitability
of Roadways for Bicycle Use: Toward a Cycling Level-of-Service Standard.
Transportation Research Record 1438, 1994.
||Reviews recent work to determine Level of Service
indicators for bicyclists and discusses factors to be considered in future
refinement of such indicators.
|Epperson, Bruce. On the Development of
a Roadway Level of Service Standard For Bicycles: A History and Discussion.
Miami Urbanized Area Metropolitan Planning Organization, 1994.
||See Epperson (Transportation Research Record,
|Epperson, Bruce, Sara J. Hendricks, and
Mitchell York. Estimation of Bicycle Transportation Demand from Limited
Data. University of South Florida (no date).
||Attempts to predict bicycle travel based on four
types of available data: (1) accident rates; (2) census data -
Category 1 Transportation Disabled population; (3) census data -
bicycle work trip percentage; and (4) bicycle trip rates as a function
of demographic data, based on the 1990 NPTS. Predictions from the
four methods do not correlate well. However, bicycle counts and analysis
in five neighborhoods suggest that simplified methods can be reasonably
predictive if (1) they are combined with specific information about
geography and demographics, and (2) recreational and utilitarian trip-making
|Ercolano, James M., Jeffrey S. Olson,
and Douglas M. Spring. Sketch-Plan Method for Estimating Pedestrian
Traffic for Central Business Districts and Suburban Growth Corridors. New
York State Department of Transportation; in Transportation Research Record 1578,
||Presents a sketch-plan method for estimating pedestrian
traffic at intersections and mid-block locations of commercial areas. The
method applies access-egress mode trip generation and applies peak vehicle
per hour turning movements, transit vehicle or passenger counts, and walk/bike
counts or projections to produce peak pedestrian-per-hour trips.
|Erickson, Michael. The Potential for Bicycle
Transportation in Chicagoland. Proceeds of the Velo 1992 conference
(Perspectives Mondiales Sur le Velo; The Bicycle: Global Perspectives,)
||Estimates the potential market for bicycle
commuting in Chicago, based on demographic data and data on trip characteristics
from travel surveys. Uses market potential analysis techniques based on
|Evans, John E., IV, Vijay Perincherry,
and G. Bruce Douglas, III. Transit Friendliness Factor: An
Approach to Quantifying the Transit Access Environment in a Transportation
Planning Model. Presented at the 1997 Transportation Research Board
Annual Meeting, Paper #971435, January 1997.
||Describes the development of a "transit
friendliness factor"to indicate the quality of the environment for pedestrian access to transit
|Federal Highway Administration (Stewart A.
Goldsmith). Case Study No. 1: Reasons Why Bicycling and
Walking Are Not Being Used More Extensively As Travel Modes. National
Bicycling and Walking Study, U.S. Department of Transportation (FHWA), Publication
No. FHWA-PD-92-041, 1992.
||Includes a literature review and interpretation
of (1) factors influencing individual choices to bike or walk; (2) aggregate
levels of bicycling and walking based on area characteristics; (3) non-motorized
data collection efforts; and (4) analytic methods for determining non-motorized
|Federal Highway Administration. A Compendium
of Available Bicycle and Pedestrian Trip Generation Data in the United States,
A Supplement to the National Bicycling and Walking Study. U.S. Department
of Transportation (FHWA), October 1994.
||Reviews bicycle and pedestrian counts and
mode choice studies in a number of communities and on a variety of facility
types. Information was gathered by reviewing selected literature and contacting
individuals in U.S. communities known to have active bicyclist and pedestrian
|Federal Highway Administration. Selecting
Roadway Design Treatments to Accommodate Bicycles. U.S. Department of
Transportation, FHWA, Turner-Fairbank Highway Research Center: McLean,
VA, January 1994.
||Provides guidance to assist transportation
planners and engineers in selecting roadway design treatments to accommodate
|Federal Highway Administration. Development
of the Bicycle Compatibility Index: A Level of Service Concept (Final
Report). U.S. Department of Transportation, FHWA, Turner-Fairbank Highway
Research Center: McLean, VA, Publication No. FHWA-RD-98-072,
||This paper seeks to establish a methodology to
determine how compatible a roadway is for allowing the efficient operation
of both bicycles and motor vehicles. The authors develop a method for evaluating
urban and suburban roadway segments via the use of their Bicycle Compatibility
Index (BCI). The BCI seeks to assess those variables used by cyclists to
determine the "bicycle
friendliness"of a roadway by measuring the geometric and operational characteristics
of a variety of roadways. Specifically, the BCI is determined based on an
equation which includes various factors pertaining to the space available
for the cyclist and the characteristics (volume, vehicle size, etc.) of
the roadway. Ultimately, this index could be used to evaluate and design
|Frank, Lawrence D. An Analysis of Relationships
Between Urban Form (Density, Mix, and Jobs: Housing Balance) and Travel
Behavior (Mode Choice, Trip Generation, Trip Length, and Travel Time).
Washington State Department of Transportation, Olympia, WA, 1994.
||See Frank et al (1997).
|Frank, Lawrence D.; Brian Stone, Jr. and Eric
Matthew Pihl. A Methodology to Measure Land Use Relationships With Travel
Behavior and Vehicle Emissions. DRAFT, July 1997.
||For the Puget Sound area, trip generation by mode,
travel time and distance, and modal choice (including non-motorized) per
household are related using regression analysis of tract-level land use
variables (density, mix, and pedestrian connectivity), transit level of
service, and household demographic variables. Data are taken from a regional
travel survey, a land use database, and the census.
|Garder, Per. Rumble Strips or Not Along
Wide Shoulders Designated for Bicycle Traffic? Transportation Research
Record 1502, 1995.
||Discusses the use of rumble strips to alert inattentive
drivers who stray from the traffic lane and onto wide shoulders used by
|Goldsmith, Stuart. Estimating the Effect
of Bicycle Facilities on VMT and Emissions. DRAFT, Seattle Engineering
Department (no date).
||Describes the development and application of a
sketch-plan method to estimate the number of users of a bicycle facility
under development, and to estimate the impact of the facility on reducing
motor-vehicle miles traveled and emissions.
|Handy, Susan. Urban Form and Pedestrian
Choices: Study of Austin Neighborhoods. Transportation Research Record 1552,
||Explores the relationships between urban form
(traditional, early modern, or late modern neighborhood) and the choice
to make pedestrian trips. Based on a study of six neighborhoods in Austin,
TX, examines correlation between personal, attitudinal, and environment
factors and the propensity to walk for recreation or for shopping. The data
suggest that certain aspects of urban form can play an important role in
encouraging walks to a destination but that the savings in travel from the
substitution of walking for driving is likely to be small.
|Harkey, David L., and J. Richard
Stewart. Evaluation of Shared-Use Facilities for Bicycle and Motor Vehicles.
Presented at the 1997 Transportation Research Board Annual Meeting,
Paper #970840, January 1997.
||Evaluates the safety and utility of shared-use
bicycle facilities based on observations of bicyclists and motorists interacting
on different types of roadways.
|Hass, R.C.G. and J.F. Morrall. Circulation
Through a Tunnel Network. Traffic Quarterly, April 1967.
||Describes a survey of pedestrian tunnels between
all major buildings and parking lots of Carleton University in Ottawa, Canada.
The objective was to develop a pedestrian demand model for future design
criteria. Data were collected using an origin-destination questionnaire
survey, and the model was calibrated using screen-line counts and walking
time-distance surveys. Trips were assigned to a network system by a computer
assignment program based on results of the survey. (Referenced in Behnam
and Patel, 1977)
|Hoekwater, J. Cycle Routes in the Hague
and Tilburg. Published in Cycling as a Mode of Transport: Proceedings
of a Symposium held at the Transport and Road Research Laboratory, Crowthorne,
U.K. (TRRL Supplementary Report 540), October 1978.
||Documents a study comparing cycle traffic
before and after the addition of cycle lanes in the Netherlands. Counts
are also performed on parallel facilities to attempt to estimate diversion
vs. new riders. In one location, cycle counts increased by 30 to 60 percent
on the route with a slight increase on parallel routes. For a different
location, cycle traffic on the route also increases but there is some decrease
on parallel facilities; the authors conclude that roughly two-thirds of
the increase in cycle traffic comes from parallel routes and one-third from
P. and M. Wardman. Evaluating the Demand for New Cycle Facilities.
Transport Policy Vol. 3, 1996.
techniques are used to obtain valuations of improvements to cycle facilities,
forecast the effects of such facilities on route choice, and provide a partial
cost-benefit analysis of alternate cycle routes.
Overview of Three Roadway Condition Indexing Models for Bicycle Transportation.
Pro Bike Pro Walk 96: Forecasting the Future, Bicycle Federation of
America/Pedestrian Federation of America, pp. 303-309, September 1996.
compares the pros and cons of three roadway compatibility measures for bicyclists:
the Roadway Condition Index developed by Davis (1987), the Bicycle Stress
Level developed by Sorton and Walsh (1994), and the Interaction Hazard Score
developed by Landis (1996).
Using GIS for Transit Pedestrian Access Analysis. Presented at the
1997 Transportation Research Board Annual Meeting, Paper #970157, January 1997.
uses GIS techniques to analyze pedestrian accessibility to transit in Orange
County, CA, using the actual street network and population information by
Census Tract. Among other things, the technique can be used to estimate
the impacts on catchment population (and potentially mode choice) of improvements
to the pedestrian network.
A Multimodal Simultaneous Equilibrium Travel Forecasting Model for Congested
Urban Areas. Maryland-National Capital Park and Planning Commission,
Silver Spring, MD (no date).
development of a travel model for Montgomery County, MD. The model includes
zone-level indices of bicycle and pedestrian friendliness.
Selecting Bicycle Commuting Routes Using GIS. Berkeley Planning Journal
10, U.C. Berkeley, pp. 75-90, 1995.
application of GIS techniques to planning bicycle routes.
and J.E. Abraham. Influences on Bicycle Use. Submitted for presentation
at the 1998 Transportation Research Board Annual Meeting, July 1997.
route choice model was developed based on a hypothetical-choice stated-preference
survey of cyclists in Edmonton, Canada. Facility factors included time spent
cycling on three different facility types and the availability of showers
and secure bicycle parking. Socioeconomic data and indicators of experience
and comfort level were also used in model development.
A.T. Brownlee, and L.P. Doblanko. Design and Calibration of the Edmonton
Transport Analysis Model. Presented at the 1998 Transportation Research
Board Annual Meeting, Paper #981076, January 1998.
travel model for the Edmonton, Canada region which includes bicycle and
walk as mode choices. Bicycle mode choice uses a "bicycle
equivalent travel time"which weights travel time by facility type (bike path, bike lane, or mixed
traffic) based on results of a stated-preference survey (Hunt and Abraham,
1997). The model uses aggregate nested logit models at each step (generation,
destination, time of day, and mode choice) and feeds composite utilities
from each step to the previous step.
|Hunter, William W.
and Herman F. Huang. User Counts on Bicycle Lanes and Multi-Use
Trails in the United States. Transportation Research Record 1502,
patterns in the number of bicycle trips along bicycle lanes and trails,
at various locations throughout the United States.
Norikazu Suzuki and Yoji Takahashi. Modeling Bicycle Route Choice Behavior
on Describing Bicycle Road Network in Urban Area. Presented at the 1998
Transportation Research Board Annual Meeting, Paper #980353, January 1998.
bicycle route choice model in which facility characteristics (e.g., road
width or sidewalk) affect the impedance function in route choice. Development
of the model is based on a survey of bicyclists in which they are asked
to map their trip on a network. Parameters are estimated based on actual
versus minimum-path routes, using the Genetic Algorithm method.
Using GIS to Address Pedestrian Issues. City of Seattle; Presented
at the 1997 National Pedestrian Conference, Washington, DC, September 1997.
||The City of
Seattle has created inventories of its pedestrian facilities using GIS.
This information is being matched to locations of elementary schools, neighborhood
service, and neighborhood business districts to prioritize pedestrian facility
and Mark Gommers. Innovative Approaches to Regional Traffic Forecasting
Models in the Netherlands. ITE 1993 Compendium of Technical Papers,
ITE; Dutch Ministry of Transport, pp. 244-247, 1993.
overview of the Dutch Regional traffic forecasting Model System (RMS). Walk/cycle
mode choice is included in the model, but the method of incorporation is
not described here.
W.G. Scott, and U.P. Avin. A Pedestrian Planning Procedures Manual.
Prepared for the Federal Highway Administration, Report Nos. FHWA-RD-79-45,
FHWA-RD-79-46, and FHWA-RD-79-47 (3 Volumes), 1978.
outlines a formal Pedestrian Planning Process (PPP), including a demand
modeling phase and a design and evaluation phase. The PPP includes a comprehensive
evaluation of existing and forecast pedestrian travel patterns and movement
requirements. Demand modeling procedures are similar to standard transportation
modeling procedures and include trip generation, trip distribution, and
Demand for Bicycle Use: A Behavioral Framework and Empirical Analysis
for Urban NSW, Doctoral Thesis, The Graduate School of Business, The
University of Sydney, Sydney, NSW, Australia, December 1996.
commuter bicycle use is modeled in two steps: (1) the choice to participate
(bicycle) is modeled (through factor analysis and logit regression) based
on attitudes and personal characteristics; and (2) mode choice is modeled
through discrete choice (logit) models which include attitudes, personal
characteristics, and structural factors (cost, distance, etc.). Bicycle
facility measures include bicycle cost, trip distance, availability of showers
and parking at the trip end, and percent of trip on a bike path. Elasticities
for the bicycle mode are -0.88 for trip distance, +0.58 for percent of trip
on bike path, and +0.26 for car cost. Inclusion of attitudinal factors is
found to significantly improve model fit. Data are based on telephone and
in-person surveys and choice experiments. An extensive discussion and literature
review of the behavior modeling issues and techniques relevant to bicycle
travel modeling is also included.
Modeling Bicycle Demand as a Mainstream Transportation Planning Function.
Transportation Research Record 1502, 1995.
quantitative techniques for modeling bicycle travel; argues for greater
consideration of bicycle travel in formal transportation planning models.
|Khan A. M.,
and A. Bacchus. Bicycle Use of Highway Shoulders. Transportation
Research Record 1502, 1995.
research on opportunities and issues in the use of highway shoulders for
bicycle routes, including design factors and safety and economic benefits.
Evaluating Community Livability Using a Core Set of Bicycle and Pedestrian
Facilities as Indicators, Draft Report, University of Maryland, August 1997.
establishes a framework for developing a set of bicycle and pedestrian facility
indicators which can be used to evaluate community livability.
Patricia L. Mokhtarian, and Laura Laidet. A Micro-Analysis of Land Use
and Travel in Five Neighborhoods in the San Francisco Bay Area. Transportation
Vol. 24 No. 2, May 1997.
conduct stated-preference surveys to determine the relative influence of
socioeconomic, attitudinal, and neighborhood characteristics on travel behavior.
Discrete choice models are developed to predict mode choice and total number
of trips by mode. Facility variables include presence of sidewalks and bike
paths as well as perceptions of whether streets are pleasant for walking
Richard, TIGER: A Primer for Planners. Planning Advisory Service
Report Number 436, American Planning Association, Chicago, Illinois,
the use of Census TIGER files.
Kara Maria. Travel Behavior as a Function of Accessibility, Land Use
Mixing, and Land Use Balance: Evidence from the San Francisco Bay Area.
Thesis, Department of City and Regional Planning, University of California
at Berkeley, 1996.
miles of travel (VMT), auto ownership, and mode choice to various land use
descriptors, accessibility measures, and socioeconomic characteristics at
the census tract level, based on Bay Area data. Includes an aggregate walk/bike
mode choice model (no facility descriptors). GIS is used extensively for
William Hyman and Bruce Aunet. Wisconsin Work Mode-Choice Models Based
on Functional Measurement and Disaggregate Behavioral Data. Transportation
Research Record 895, 1982.
mode choice models are developed for four sets of metropolitan areas in
Wisconsin based on the results of stated and revealed-preference surveys.
Bicycle and walk are included as separate mode choices. Bicycle facility
variables include distance to work, lane (yes or no), street surface (smooth
or rough), and traffic (busy or quiet). Pedestrian facility variables include
distance to work, presence of sidewalks, and season (summer or winter).
W. Bicycle Interaction Hazard Score: A Theoretical Model. Transportation
Research Record 1438, 1994.
||Describes a theoretical
model to estimate bicyclists' perception of the hazards of sharing roadway
segments with motor vehicles.
W. Bicycle System Performance Measures. ITE Journal, February 1996.
||Describes how the
Interaction Hazard Score and Latent Demand Score developed by the author
can be used to evaluate, test, and prioritize on-road bicycle projects.
W. NFTC Regional Bikeway Implementation Plan: Scoring Methodology Report,
Sprinkle Consulting Engineers, Inc., Tampa, FL, March 1997.
||Describes the application
of the Bicycle Level of Service to rate the quality for bicycling of existing
streets in the Buffalo, NY, area.
|Landis, Bruce W.
and Venkat R. Vattikuti. Real-Time Human Perceptions: Toward
a Bicycle Level of Service. Sprinkle Consulting Engineers, Inc., September 1996.
||Describes the development
of a Bicycle Level of Service (BLOS) based on earlier work to develop an
Interaction Hazard Score and new research.
and Jennifer Toole. Using the Latent Demand Score Model to Estimate Use.
Pro Bike Pro Walk 96: Forecasting the Future, Bicycle Federation of
America/Pedestrian Federation of America, pp. 320-325, September 1996.
||Describes an application
of the Latent Demand Score.
Buckley and James E. Kirk, Central Massachusetts Rail Trail Feasibility
Study, Central Transportation Planning Staff, Boston, MA, April 1997.
bicycle/pedestrian facility and its surrounding population are compared
with a proposed facility and its surrounding population to estimate potential
usage levels on the proposed facility.
J. Obstacles and Potentions (sic) for Replacing Car Trips by Bicycle
Trips. Proceeds of the Velo 1992 conference (Perspectives
Mondiales Sur le Velo; The Bicycle: Global Perspectives), 1992.
survey in the Netherlands asking people about obstacles to bicycling and
willingness to change behavior. Respondents are asked to record all car
trips for a week, and to note whether the trip could have been made by bicycle
(impossible, only with much trouble, or possible). These estimates are used
to develop a range of potential mode shift from car to bicycle. Different
impediments are identified for trips of each degree of replaceability.
David R. Pedestrian Access to Transit: A Model of Walk Trips and
their Design and Urban Form Determinants Around BART Stations. Presented
at the 1997 Transportation Research Board Annual Meeting, Paper #971424,
choice model of transit mode choice access is developed based on passenger
surveys and station area characteristics for the Bay Area Rapid Transit
system (BART) in San Francisco. Urban design and station area characteristics
are found to be secondary to individual characteristics in determining the
choice to walk. (Station area variables include nearby arterials and freeways;
grid pattern; population density; and type and mix of land uses. Descriptors
are developed using GIS techniques.)
(http://www.caliper.com), Caliper Corporation.
capabilities of Maptitude GIS software.
Mercer. If We Build it, Will They Come? (Forecasting Ped. Use and Flows).
Pro Bike Pro Walk 96: Forecasting the Future, Bicycle Federation of
America/Pedestrian Federation of America, pp. 315-319, September 1996.
trips in a corridor are estimated using existing land use and mode split
data and estimates of pedestrian trips from various types of trip generators
(land uses, transit, etc.) The method is used for prioritizing corridors/locations
for pedestrian improvements.
|Mescher, Phillip J. and Reginald R. Souleyrette.
Use of an Internet-Based Delphi Technique and Geographic Information
System for Bicycle Facility Planning. Paper written for the 1996 Geographic
Information Systems for Transportation Symposium, 1996.
||The authors use a GIS to assign bicycle condition
index (BCI) values to the city street network of Ames, Iowa. The BCI was
developed using the Delphi technique, using the internet to coordinate expert
panelist responses. The authors then develop an optimal route-planning tool,
using a shortest-path FORTRAN algorithm, that minimizes the sum of (negative)
link scores between two identified nodes. The outputs of the optimal route
calculations are then compared to existing bicycle routes.
|Metropolitan Transportation Commission. San
Francisco Bay Area 1990 Travel Model Development Project: Compilation of
Technical Memoranda (Volumes II-VI). Oakland, CA, 1995-1997.
||Describes the development of the various trip
generation, trip distribution, and mode choice models which are used in
the San Francisco Bay Area travel models. The current status and history
of Bay Area modeling efforts are also described, and Volume VI includes
a description of current home-based work trip mode choice models developed
by other MPOs which include non-motorized travel.
|Meyer, Michael D. A Toolbox for Alleviating
Traffic Congestion. Institute of Transportation Engineers; Prepared
for the Federal Highway Administration, Washington, DC, 1997.
||Contains some basic information and references
on bicycle trip characteristics, benefits and costs, and implementation
guidelines for bicycling as a Transportation Demand Management (TDM) strategy.
|Milam, Ronald T. and Michael G.
Jones. Engineering A Bikeway Master Plan. Fehr & Peers Associates,
Inc., Prepared for the 1995 ITE District 6 Annual Meeting, Denver,
Colorado, August 9, 1995.
||Methods and issues to consider in developing a
bicycle master plan.
|Montgomery County Planning Department. Travel/2:
A Simultaneous Approach to Transportation Modeling (Draft). Montgomery
County, MD, February 1993.
||Describes the development of a travel model for
Montgomery County, MD. The model includes zone-level indices of bicycle
and pedestrian friendliness.
|Moritz, William E. A Survey of North
American Bicycle Commuters - Design and Aggregate Results. University
of Washington; Presented at the 1997 Transportation Research Board Annual
Meeting, Paper #970979, January 1997.
||Documents a survey of 2,374 bicycle commuters
in the United States and Canada. Includes socioeconomic and demographic
information, commuting habits/trip characteristics, accidents, equipment
and facilities used, "relative
danger"by type of street, and motivation.
Vernez, Paul Hess, Mary-Catherine Snyder, and Kiril Stanilov. Effects
of Site Design on Pedestrian Travel in Mixed-Use, Medium-Density Environments.
Presented at the 1997 Transportation Research Board Annual Meeting, Paper #971360,
tests the hypothesis that pedestrian network connectivity is an important
factor in determining pedestrian activity levels. Selecting 12 sites in
the Puget Sound area to control for population density, income, and land
use mix, intensity, and distribution, the study finds that areas with direct
pathways and a complete system of pedestrian facilities have significantly
higher rates of pedestrian travel (as measured by counts).
Calculating Multi-Mode Levels-of-Service, (abridged). International
Bicycle Fund, http://www.halcyon.com/
fkroger/bike/los.htm, August 1997.
development of a level-of-service (LOS) measure referred to as "Pedestrian,
Bicycle, Auto, Transit Level of Access" (P-BAT LOA). The purpose is to establish
a multimodal level of service measure as an alternative to traditional LOS
measures, which do not consider bicycle, pedestrian or transit modes.
Cycle Model Study, Final Report, prepared for Leicestershire County
Council, Contract No. 02/C/1428, October 1995.
development and application of a cycle network model for the Leicester,
England area. The model distributes future cycle trips given a network of
existing and proposed roads and cycle facilities. Cycle trip tables are
developed based on existing trip tables for motorized travel in conjunction
with cycle trip length distributions. The model does not forecast future
levels of cycling, but rather uses an assumed level of future cycle traffic
under ideal conditions and distributes it to a future-year network.
C., and David Allen. If You Build Them, Commuters Will Use Them:
Cross-Sectional Analysis of Commuters and Bicycle Facilities. City
Planning Program, Georgia Institute of Technology; Presented at the 1997
Transportation Research Board Annual Meeting, Paper #970132, January 1997.
analysis of 18 U.S. cities to predict work trip bicycle mode split (census
data) based on weather, terrain, number of college students, and per capita
miles of bikeway facilities. A positive association is found.
J.F. Morrall, and B.G. Hutchinson. An Analysis of Central Business District
Pedestrian Circulation Patterns. Highway Research Record 283, 1969.
applies the gravity model technique to forecast pedestrian volumes in the
Toronto area. The CBD is divided into office zones, linked by pedestrian
facilities. Trip generation rates are measured for office zones and transportation
terminals, and are used in conjunction with a set of friction factors and
minimum-path walking trees as inputs to a gravity-type distribution model.
The minimum path is calibrated on the basis of walking time, waiting time
at intersections, street attractiveness, and a turn penalty. (Referenced
in Behnam and Patel, 1977)
and G.S. Rutherford. Non-Motorized Transportation, 1990 NPTS Special
Report. Report FHWA-PL-94-019, FHWA, U.S. Department of Transportation,
and pedestrian trip characteristics and demographic characteristics of travelers
in the 1990 National Personal Transportation Survey.
Longitudinal Analysis of Bicycle Count Variability: Results and
Modeling Implications. ASCE Journal of Transportation Engineering, American
Society of Civil Engineers, May/June 1996.
to count bicycle traffic volumes; discusses issues which may affect counts,
such as commuter vs. recreational bicycling patterns and the effects of
B. Perceived Risk and Modal Choice: Risk Compensation in Transportation
Systems. Accident Analysis and Prevention, Vol. 27 No. 4,
and Kunreuther, 1995 (same study, greater focus on safety aspects).
B. and Howard Kunreuther. Short-Run and Long-Run Policies for Increasing
Bicycle Transportation for Daily Commuter Trips. Transport Policy,
Vol. 2 No. 1, 1995.
logit models are developed which relate use of a mode to perceptions of
risk and convenience of that mode (perceptions of cost, comfort, and relevant
personal variables are also included). Modes include auto, transit, bicycle,
and walk. Risk and convenience perceptions are measured based on surveys
of bicyclists and of the general population. The model is used to evaluate
the general effect of policy variables on mode split. Elasticities are developed
with respect to bicycle convenience, comfort, parking availability, competency,
and lack of shoulders, as well as auto cost, convenience, and comfort. "Short-run"and "long-run"elasticities and mode splits are developed, which assume that many people
do not have a choice of modes in the short run, but that in the long run
different urban form policies and residential location decisions could allow
everyone a choice of modes.
University Traffic Institute. Pedestrian and Bicycle Considerations in
Urban Areas - An Overview. Training course developed for the U.S.
Department of Transportation, Federal Highway Administration, in cooperation
with Barton-Aschman Associates. (no date; est. late 1970s).
sketch-planning approach to estimating potential bicycle trips based on
population, employment, school trip activity, and other factors. Approach
appears similar to that used by Ohrn (1976), who was also with Barton-Aschman
at the time of his article.
E. Predicting the Type and Volume of Purposeful Bicycle Trips. Transportation
Research Record 570, 1976.
potential number of bicycle trips in the Minneapolis-St. Paul area,
assuming that adequate facilities are provided, based on existing trip lengths
and frequencies by purpose and on estimated maximum diversion by length
and purpose, given ideal conditions.
de Dios, Andres Iacobelli and Claudio Valeze, Estimating Demand for A
Cycleway Network, Department of Transport Engineering, Pontificia Universidad
Catolica de Chile (no date).
||A travel survey
including stated choice experiments for potential bicyclists was conducted
in Santiago, Chile. A logit model is constructed to predict "willingness
to cycle"under the assumption of a dense network of segregated cycleways and parking
facilities, and a mode choice model is subsequently developed. Based on
total trips and travel attributes for each origin-destination (O-D) pair
of the regional travel model, the number of potential bicycle trips is estimated
for each O-D pair and overall.
Planning Commission, Survey of Users on the Norwottuck Rail Trail,
Federal Highway Administration, July 19, 1996.
survey of users of the Norwottuck Rail Trail in central MA, including trip,
access, and user characteristics.
Research, Inc., Report on a Telephone Survey Conducted in the Route One
Corridor of New Jersey, February 5, 1997.
provides the processed data from a phone survey of 500 households along
the Route One Corridor in New Jersey. The survey explored the respondents'use of the corridor and their opinions towards infrastructure improvements
to make the corridor more bike and pedestrian friendly. Almost three-quarters
of respondents replied that they strongly support policies that encourage
development supportive of walking and bicycling. This survey was commissioned
by the Bicycle Federation of America.
Boris and Jeffrey M. Zupan. Pedestrian Travel Demand. Highway Research
Record 355, 1971.
of this article study the nature of pedestrian flow in the central business
district of midtown Manhattan. Their survey analyzed the number and kinds
of pedestrians and the nature of their trips, including trip times and distances.
Regression analysis is used to relate pedestrian volumes to adjacent land
uses. The study provides several methodologies ranging from aerial photography
to street-side surveys to collect data.
Inside the Black Box: An Insider's
Guide to Transportation Models. Pro Bike Pro Walk 96, Bicycle Federation
of America/Pedestrian Federation of America, pp. 276-280, September 1996.
travel modeling for laypersons, including how non-motorized travel can be
Integrating Pedestrian and Bicycle Factors into Regional Transportation
Planning Models: Summary of the State-of-the-Art and Suggested Steps
Forward. Environmental Defense Fund, July 20, 1995.
and critiques current non-motorized modeling practices, and suggests future
D. Generating Fine Levels of Detail from a Regional Modeling Package.
ITE 1994 Compendium of Technical Papers, ITE; Fehr & Peers Associates,
pp. 425-429, 1994.
large area traffic network models can be used to generate fine-level details
such as intersection turning movements, link-specific zonal contribution
estimates, and parcel-level trip allocations.
D. Projecting Bicycle Demand: An Application of Travel Demand
Modeling Techniques to Bicycles. 1995 Compendium of Technical Papers,
Institute of Transportation Engineers 65th Annual Meeting, pp. 755-785,
theoretical development of a bicycle-specific travel model, based on traditional
travel modeling principles, and its application to the city of Berkeley,
California. Bicycle trips are currently assigned based on travel distances;
link attributes could potentially be included. Problems were encountered
in predicting bicycle mode split at a Census Tract level based on available
Surveying Actual Roadway User Characteristics. Pro Bike Pro Walk
96: Forecasting the Future, Bicycle Federation of America; Pedestrian Federation
of America, pp. 307-309, September 1996.
argues for the importance of conducting user surveys to accurately assess
pedestrian and bicycling conditions and demands. The author shows various
ways that traditional methods of counting users may be inexpensively yet
productively enhanced. Hard data, Ronkin argues, is essential to making
|Rossi, Thomas, T. Keith Lawton and Kyung Hwa
Kim. Revision of Travel Demand Models to Enable Analysis of Atypical
Land Use Patterns. Cambridge Systematics, Inc. and Metropolitan Service
District, May 1993.
||Describes revision of travel models in the Portland,
OR, area to include (among other things) non-motorized mode choice as a
function of local land use and environment variables.
|Shafizadeh, Kevan and Debbie Niemeier. Bicycle
Journey-to-Work: Travel Behavior Characteristics and Spatial Attributes.
Transportation Research Record 1578, 1997.
||Analyzes characteristics of commuter cyclists,
including travel time by income, age, gender, and proximity to bicycle trail,
based on surveys of commuters on CBD bike lanes and on the Burke-Gilman
trail in Seattle.
|Sharples, Rosemary. "Think
Bike! - TRIPS Goes Cycling,"The MVA Consultancy, Manchester, TRIPS Software News, August 1996.
||See MVA (1995).
|Sorton, Alex; Thomas Walsh. Bicycle Stress
Level as a Tool to Evaluate Urban and Suburban Bicycle Compatibility.
Northwestern University Traffic Institute; Transportation Research
Record 1438, 1994.
||Describes the development of a bicycle stress
level measure to evaluate the suitability of roadway facilities for bicycling.
|Stein, William R. Pedestrian and Bicycle
Modeling in North America's
Urban Areas: A Survey of Emerging Methodologies and MPO Practices.
Thesis: Master of City Planning and Master of Science, Georgia Institute
of Technology, March 1996.
||Overview of the state of non-motorized modeling
at major U.S. MPOs. Also includes a literature review of non-motorized user
characteristics and preferences and level-of-service measures.
|Stein, William R. Summary of Bicycle Modeling
Efforts at Portland Metro. Metro Travel Forecasting Section, Portland,
OR, November 22, 1996.
||One-page description of current non-motorized
modeling efforts and future plans.
|Stutts, Jane C. Development of a Model
Survey for Assessing Levels of Bicycling and Walking. University of
North Carolina, Highway Safety Research Center, November 1994.
||The purpose of this study is to develop a model
survey for states and local communities to use to assess current levels
of bicycling and walking. Includes a review and assessment of a variety
of existing surveys which either focus on or include non-motorized travel.
and Hani Mahmassani. Analysis of Stated-Preferences for Intermodal Bicycle-Transit
Facilities. Transportation Research Record 1556, 1996.
choice model is developed based on a hypothetical-choice stated-preference
survey to assess preferences for work-trip mode choice (auto, park-and-ride,
or bike-and-ride). Facility factors include on-street bicycle facility type,
bicycle parking facility type, and access distance to transit. Only relative
utilities are reported -- the model is not used to predict changes
in total mode use as a result of facility changes.
W. and Ph. Ambrosius. Potential Demand for Bicycle Traffic in Relation
to Existing Bikeway Networks. In Research for Transport Policies in
a Changing World: Proceedings of the World Conference on Transport
Research, Hamburg, Germany, April 1983.
develop a measure of quality of bicycle network access to a destination
and relate it to the likelihood of using a bicycle to access the destination.
The authors find an "S-shaped"relationship, where there is a minimum level of bicycle use even with a
poor network and a maximum level which relates to a good network. A slight
improvement to a poor network has little effect until a certain minimum
standard is achieved. The authors also look at reasons for not bicycling
based on survey data, including the influence of route characteristics.
Bicycle Case Studies: A Review of Planning Guidelines and Design
Standards for Bicycle Facilities. Institute of Transportation Engineers
66th Annual Meeting, pp. 504, 1996.
review of planning guidelines and design standards for bicycle facilities.
Urban Transportation Planning in the United States: An Historical Overview
(Fifth Edition). Publication DOT-T-97-24, U.S. Department of Transportation,
evolution of transportation planning methods in the United States, including
the four-step regional travel model approach known as the "Urban Transportation
and Phil Madsen. Perception and Preference Models for Motorized and Non-Motorized
Travel, Barton-Aschman Associates, Inc., pp. 1-69, August 1979.
of this work was to develop mode perception and preference models based
on attitudinal data as obtained from surveys. Modes included auto, transit,
walk, and bike. Sophisticated statistical and modeling techniques are used,
but the applicability of methods and results to other areas is unclear.
Follow-up studies were performed to carry the techniques further into predicting
Design and Pre-Testing of a Survey Instrument to Measure Pedestrian Levels
of Safety and Comfort: A Case Study of the Channelized Cut-Off from Laurier
Avenue East to Nicholas Street South, Ottawa, Ontario, Submitted to
the Mobility Services Division, Regional Municipality of Ottawa-Carleton
(RMOC), Department of Geography, University of Ottawa, Ottawa, Ontario,
of this study was twofold. First, the study was to gauge the effectiveness
of pedestrian improvements to a specific Ottawa intersection. Second, the
study was commissioned to create and pre-test a survey instrument for evaluating
the concerns of pedestrians in relation to traffic intersections in general.
The methodology used was to send researchers to the intersection to conduct
tape-recorded surveys of pedestrians. The tape-recorded data was then transcribed
to a written survey form. The study concluded that there were concerns about
vehicles not yielding to pedestrians. The researchers were very pleased
with the effectiveness of this survey method.
Anthony Richardson and Paris Brunton. Simplified Estimation of Demand
for Non-motorized Trails Using GIS. Presented at the 1998 Transportation
Research Board Annual Meeting, Paper #981203, January 1998.
application of GIS techniques to compare usage on two non-motorized trails
Associates. Non-Motorized Access to Transit: Final Report. Prepared
for Regional Transportation Authority, Chicago, IL, July 1996.
estimates the effects on transit mode choice access of various improvements
to bicycle and pedestrian facilities in station areas. Methodology is based
on estimation of a discrete mode choice model from both revealed-preference
and stated-preference survey data.