volatileendeavors-smithvu

Volatile Endeavors:

Negotiating Left Turns Along the SE Hawthorne Bike Corridor

Aaron Smith Helen Vu

[email protected] [email protected]

Portland State University

USP 565

Fall Quarter, December 2009

VOLATILE ENDEAVORS: NEGOTIATING LEFT TURNS Smith & Vu 2

Abstract

Intersections and left-turn maneuvers have been identified as having the highest rates for negative

bicycle and automobile interactions. Our study determines the need for additional transition and

left-turn facilities along the eastbound Hawthorne bike corridor to access northbound residential

feeder routes. The following questions framed our research: What are bicyclists’ perceptions of

safety and comfort when performing a left-hand turn? Are they employing the suggested north-

south bicycle route, if not, why? The data used in this study was collected from three bicycle counts

and responses from 118 intercept surveys of existing users on the bike corridor. Survey results reveal

that 61% of riders find merging across Hawthorne during peak traffic flows to be “very

challenging.” If left-turn treatments were added to the intersection at Southeast 7th and Southeast

Hawthorne, 71% would perceive an increase in their sense of safety, and 50% of cyclists traveling

north indicate that they would modify their route in order to use this facility. This illustrates high

user demand for left-turn treatments. The results of this study may be used to set priorities in the

creation of a low-stress bicycle network by city and transportation designers, planners, and

engineers.


Introduction

According to the Census Bureau’s American Communities Survey (2008), Portland, Oregon retains

the highest bicycle ridership in the country, with 6.4% of work commuters utilizing the bicycle as

their primary mode of transportation—a 52% jump from the prior year (as cited in “Portland Bike,

Pedestrian, and Transit,” 2009). These cycling rates in Portland have been achieved through the

city’s commitment to provide “low-stress, efficient, and comfortable facilit[ies].” The city reinforces

this idea in its action plan to “ensure all neighborhoods have adequate low-stress bicycle facilities

connecting to neighborhood commercial corridors and centers so that local residents can safely and

comfortably access them by bicycle or on foot” (Portland Bicycle Plan for 2030 [PBP 2030], 2009, p.

III & A-2).

The Hawthorne Bridge over the Willamette River serves as a primary gateway for bicyclists

traveling from downtown Portland into the city’s southeastern neighborhoods. At rush hour, as

cyclists journey eastward from the bridge along this designated bike corridor, commuters with

destinations to the north must merge across three lanes of heavy traffic in order to execute a left-

hand turn. This maneuver involves multiple points of conflict between bicyclists and motorists,

creating a potentially hazardous condition. This study examines the possible need for additional

transition facilities along the eastbound Hawthorne bike corridor (Hawthorne bridge to Southeast

12th Avenue) to allow safe access to northbound residential feeder routes, in keeping with the stated

goals of Portland’s Bicycle Plan for 2030.

In order to assess this need the following questions were posed: What are cyclists’ perceived

levels of ease and safety when navigating this corridor and performing a left-hand turn? Are these

cyclists employing the suggested north-south bike route that intersects this section of Hawthorne

and if not, where are they turning and why? How safe is the left-hand turn maneuver onto this

route? This study addresses these questions both through the perceptions of cyclists currently


commuting along this corridor and through quantitative observations of existing conditions. The

resulting data may be a valuable resource to planners and engineers in identifying the necessity of

and demand for improved level of service at this location, and by cycling advocates who may lobby

for such improvements.

Literature Review

To bolster the reasoning behind PBP’s focus on the creation of a low-stress bicycle network, this

review will focus on the high conflict area of intersections and the maneuvering of left-hand turns.

For the purposes of this study, the preceding topics will be examined through relevant data on

facility safety and treatment, and will be limited to the modal perspective of the basic cyclist. A

spotlight within these bounds will help to promote PBP 2030 objectives.

Hazard Measurements: Numerous studies have combined crash statistics, roadway conditions,

and user data in order to analyze leading points of conflict between cyclists and vehicles. A nine-year

study conducted by Wachtel and Lewiston (1994) indicated that the majority of bicycle-motor

vehicle accidents occurred at intersections. They found that intersections made up 74% of all

bicycle-vehicle collisions (Wachtel and Lewiston, 1994). Data from Oregon’s Traffic Crash

Summary (2009) support this finding. The 2008 Portland pedalcycle summary shows that 196 out of

265 crashes took place at intersections, accounting for 74% of incidents that year (Oregon

Department of Transportation, 2009, p. 82). This number becomes more astounding when one

considers that only 10-20% of bicycle crashes are severe enough to be reported to officials (Portland

Office of Transportation, 2007).

It’s no wonder that even in European cities, where there has been a long history of bicycling

ingrained in the culture of day-to-day living, that the European Conference of Ministers of

Transport (ECMT) identifies the crossings of intersections and executions of left turns as hazardous


to cyclists (ECMT, 2000, p. 28). Although it is not clear where crash reports and hospital trauma

statistics overlap, trauma records may provide greater insight on bicycle facility safety. In 2005,

Oregon hospitals had 297 patients from motor vehicle-pedalcyclist collisions; 3.7% of those patients

died from injuries sustained during the conflict (Trauma System and Patient Profile, 2005). As noted

in the Federal Highway Administration’s (FHWA) BIKESAFE, a 1996 study by Hunter et al. was

able to make a reliable distribution of bicycle crash types. Primary causes of automobile-bicycle

crashes were attributed to the following:

• A motorist failing to yield (21.7%)

• A bicyclist failing to yield at an intersection (16.8%)

• A motorist turning or merging into the path of the bicyclist (12.1%)

• A bicyclist failing to yield at midblock location (11.7%)

• A motorist overtaking a bicyclist (8.6%)

• A bicyclist turning or merging into the path of the motorist (7.3%) (as cited in

FHWA BIKESAFE, n.d.)

Contradicting measurements may be discovered when comparing various crash datasets. This is due

to the lack of uniformity of crash-reporting procedures across agencies. A January 2006 report from

the Portland Police Bureau implied that “cyclists merging into travel lanes” was the highest causal

factor of fatalities in bicycle-automobile crashes at 28% (Improving Bicycle Safety, 2007). Utilizing

methodologies to compute bicycle safety provides an additional option to gauge the cycling climate

of an area, and specifically an intersection. Rating models like the Bicycle Safety Index Rating and

Bicycle Level of Service have an intersection component, but fail to incorporate information about

crashes and conflicts. The FHWA also describes a more comprehensive rating tool, the Bicyclist

Intersection Safety Index (Bike ISI). This tool incorporates crash data, conflict and avoidance

maneuvers, and subjective intersection ratings in its rating of intersections (FHWA, n.d.).


Gains in Safety: Despite the number of injuries and fatalities reported by Oregon’s crash reports,

Portland’s overall bicycle crash rate is decreasing, likely due to the exponential surge in bicycle

ridership. Development of the bicycle network, in the form of intersection and left-turn facility

upgrades, are consistent with PBP 2030 goals. Birk and Gellar (2005) state that engineers and

planners must construct facilities to the highest standards in order to increase cyclist’s ease of use,

and to minimize negative bicycle-automobile interactions. They have also effectively coined

Portland’s “build it and they will come” approach to describe the city’s success in increasing bicycle

use (Birk & Gellar, 2005). It is reported that over half of Portland residents limit their bicycling due

to traffic safety concerns. Yet multiple studies have shown that increases in bicycling activity itself

create safer conditions. In Copenhagen’s Cycle Policy (2002-2012), the report specifies that a

“critical mass of cyclists decreases accident risk because motorists become more aware of cyclists,

but also because more cyclists are indicative of a well-developed cycling network” (Nelson &

Scholar, n.d., p. 14).

Development of the bicycle network becomes more significant when one considers the three

categories of cyclists: A—advanced, B—basic, and C—children. Group A cyclists (10% of overall

cycling population) are more skilled and therefore more willing to use streets with or without bicycle

facilities in their desire to travel on the most direct route. Group B cyclists (40% of biking

population) are moderately skilled, have basic knowledge, and tend to bike occasionally, but prefer

routes with bicycle facilities. For group C (10% of population), biking or public transportation is

often their only modes of transportation because they are too young to drive (Allen, Rouphail,

Hummer, & Milazzon, 1998, p. 29). This means that the greatest potential for new cyclists will come

from group B. In order to attract these new bicyclists, Portland’s bicycle network must continue to

improve bicyclists’ conflict areas. The “subjective feelings of comfort and safety will determine

stress levels experienced, as well as the likelihood of traveling on specific routes or using specific


travel modes” (Dewar & Olson, 2002, p. 597). Rietveld and Daniel found that overall perceptions of

bicycle facilities play a significant role in the decision to bicycle. Boslaugh et al. discovered an inverse

relationship between individual’s perceived safety risk and neighborhood bicycle ridership —the

higher the perception of risk, the lower the bicycling levels (as cited in Sener, Eluru, & Bhat, 2008, p.

2). This underscores the necessity to increase the safety of intersection and left-turn treatments.

Innovative Treatments: In their 2004 paper, “Safety Mega Issue,” the Institute of Transportation

Engineers (ITE) highlights the organization’s focus on the “design, construction, operation, and

maintenance of intersections for safety of all user groups.” By considering the needs of all users,

ITE’s improvements to intersection safety would contribute to making communities more livable

and sustainable. In order to produce this outcome and maximize resources, ITE stresses the

necessity for comprehensive research on the effectiveness of road countermeasures and bicycle

treatments (Safety Mega Issue, 2004). There are few bicycle treatments, and even less research,

which specifically address the challenge of intersections and left turns. The use of a colored bicycle

lane through an intersection is one technique to tackle this issue.

Colored bicycle lane marking through intersection

These brightly painted lanes guide cyclists’ movements through intersections and caution motorists

to conflicts with bicycle crossings. In a study of these treatments at intersections in Copenhagen,


Jensen concluded that crash rates were reduced by 10% at sites with one demarcated bicycle lane.

However, if more than one colored bike lane were present at an intersection crash rates would

increase (Weigand, 2008, p.3). This highlights the importance of balancing the needs of all users by

designing complete streets.

Portland’s Platinum Bicycle Master Plan Process identified the intersections of Southeast

Hawthorne and 7th, and Southeast Hawthorne and 11th, as two of Portland’s fourteen most difficult

intersections to navigate as a bicyclist. The plan targeted these cumbersome intersections for

immediate treatment (Improving Bicycle Safety, 2007). Examples of some possible designs to

remedy the difficulty of left-hand turns include:

• Two-Stage Signalized Left Turn: aka Copenhagen-left, or Jug-handle turn

In the Copenhagen-left treatment, cyclists turn right at intersecting street and position themselves in

front of traffic at cross street. On green light, they proceed straight. It is the “go right to turn left”

design (PBP 2030: Appendix D, 2009, p. 26). This provides a safe way for cyclists to turn left from

the right lane—this treatment is commonly found in European cities.


• Two Bike Lane Transition

This treatment decreases the number of merge maneuvers required to transition to the opposite

bikeway facility (San Francisco Department of Parking and Traffic, 2003). The use of color for the

left bike lane would warn motorists of high conflict points with left-turning cyclists, and would

designate preferred left-turn routes in the bicycle network.

• Streaming Bike Box/Advanced Stop Line (ASL)

(San Francisco Department of Parking and Traffic, 2003).


Pictured on the left: of SE 39th & SE Clinton, Portland, Oregon (Improving Bicycle Safety, 2007)

Pictured on the right: The Netherlands, bike box with marked turn lanes

Three studies in the UK; Allen, Bygrave et al., Wall, Davies et al., and Wheeler; found bike

boxes/ASLs effective for allowing bicyclists to position themselves in front of stopped vehicles at

signalized intersections. According to Allen et al. and Wall et al., this position reduces conflicts with

turning motorists. Cyclists perceived an increase in visibility and safety. Research in the UK and a

study in Eugene, Oregon, noted problems with vehicle encroachment in bike boxes, but hopefully

signage and education may remedy this issue (as cited in Weigand, 2008, p. 5).

• Bicycle Activated Signals: Scramble Traffic Light and Bicycle Only Signal Phase


This treatment stops all motor vehicle movement at the intersection, provides an exclusive phase for

bikes and pedestrians, and eliminates two-stage crossings (Walker, Tresidder, & Birk, 2009, p. 42 &

48). In Portland, Oregon, Wolfe et al. collected data before and after an intersection was installed

with a bicycle scramble light. Their results indicate the intersection had an increase of bicycle usage

after the treatment was installed. In addition, illegal intersection crossings dropped from 78.1% to

4.2% (as cited in Weigand, 2008, p. 8). In a study conducted in Davis, California, research showed

that integrating a bicycle-only phase into the existing intersection signal minimized conflicts amongst

bicyclists and motor vehicles. In a cost-benefit analysis, the study found that savings in crash

reductions paid for the cost of signal installation (Korve and Niemeir, 2002).

Methods

In order to comprehensively assess the Southeast Hawthorne bike corridor’s adequate facilitation of

left turns onto the Southeast 7th Avenue corridor, and thus determine the need and priority for

additional facilities, this study will analyze three significant indicators:

• Quantitatively evaluated safety of the bicycle left-hand turn maneuver from eastbound

Southeast Hawthorne onto northbound Southeast 7th Ave., including its merge component

(from right-hand bike lane to left lane).

• User comfort and perception of safety in performing this maneuver.

• Demand for additional left-hand turn facilities at this intersection.

The methods described hereafter were chosen to evaluate these indicators by synthesizing objective

data from traffic counts and an inventory of facility characteristics with qualitative data from user

intercept surveys, and supplementing these measures though existing statistical data where

appropriate.


Bicyclist Intersection Safety Index: Commonly referred to as “Bike ISI,” this tool consists of a

set of models developed in 2006 by the University of North Carolina’s Pedestrian and Bicycle

Information Center to rate the safety of approach legs and movements through intersections

(Carter, Hunter, Zegeer, Stewart, & Huang, 2006). Using extensively gathered crash data, behavioral

data (conflicts and avoidance maneuvers), and subjective ratings from expert users at 67 sites across

the U.S. (thirteen of which, incidentally, were in Portland), researchers developed a formula that

indexes safety to physical intersection characteristics (Carter et al., 2006). The calculation method for

Bike ISI, utilized in this study for a left turn from the right-hand bike lane of Southeast Hawthorne

onto Southeast 7th Ave., is described in Carter, Hunter, Zegeer, and Stewart’s Pedestrian and Bicyclist

Intersection Safety Indices: User Guide (2007). Inventory of the intersection will be taken from the

following geometric and operational characteristics (brackets indicate corresponding formula input

values):

• Presence of bicycle lane on main street (Hawthorne). [“presence”: 0=no, 1=yes; “absence”: 1=yes, 0=no]

• Average daily traffic volume on main street. [ADT in thousands]

• Number of through vehicle lanes on cross street (7th Ave.). [1, 2…]

• Number of traffic lanes bicyclists must cross to make left turn. [1, 2…]

• Speed limit on main street. [0=less than 35mph, 1=greater than or equal to 35mph]

• Presence of on-street parking on main street approach. [0=no, 1=yes]

• Presence of traffic signal at intersection. [0=no, 1=yes]

These data will then be plugged into the following formula:

Bike ISI = 1.100 + 0.025(main street ADT) + 0.836(bike lane presence) + 0.485(traffic signal presence) + 0.736(main street speed limit * bike lane presence) + 0.380(# of traffic lanes to cross * bike lane absence) + 0.200(on-street parking)

The calculated index value will occur on a range between 1 and 6, with 1 representing a relatively

safe intersection and 6 an unsafe intersection.


Bike ISI was chosen for this study as a quantitative measure of safety due in large part to its

unique ability to evaluate a specific approach and turn maneuver at a given intersection. Though

previously developed methodologies do exist for measuring the “bicycle friendliness” of a given

street or intersection (e.g. Bicycle Compatibility Index, Bicycle Level of Service), these all assume a

continuous and straight line of bicycle travel, with no specific attention given to approaches or turns

(Carter et al., 2006). Additionally, Bike ISI is the only model that incorporates crash data or

behavioral data into its calculations, significantly increasing its objectivity and accuracy in measuring

true safety. Though it possesses great advantages over other models of bicycle compatibility with

respect to this study, Bike ISI was developed primarily as a comparative tool for ranking an

intersection’s relative safety against others across a city (Carter et al., 2006). Applied only to an

isolated location, the index value loses its local comparative significance and therefore becomes

more abstract in its indication of favorability. However, Carter et al. surveyed an intentionally

diverse array of sites in their pilot study (2006), so its results should form a useful baseline for

general comparison. The results of that study were categorized for comparison according to right-

turn, left-turn, and straight-through movements. The ratings for right turn and straight-through

movements were clustered at the lower end of the scale in a tighter distribution than left turns,

which were grouped in the middle of the scale across a wider range, indicating a lower average level

of safety but greater variation between sites (Carter et al., 2006).

Demand for additional left-turn facilities at Southeast 7th Ave. will be estimated through a

combination of user preference survey and manual user counts along existing facilities. The user

count portion will quantify the number of cyclists currently performing a left turn at 7th Ave. and at

relatively interchangeable locations nearby. The likelihood of these other cyclists to use 7th Ave.

after a left-turn-friendly redesign at its intersection with Hawthorne will be demonstrated in the

responses of survey participants from that group when asked whether they would modify their route


to use 7th Ave. given such a redesign. A resulting estimation of demand emerges when these survey

responses are viewed in proportion to the number of cyclists observed turning after 7th. The

integration of observed data with user preference survey results is recognized in the Federal

Highway Administration’s Guidebook on Methods to Estimate Non-Motorized Travel: Overview of Methods

(1999) as significantly advantageous for predicting user behavior.

User Counts: A team of two data collectors will be stationed at the northeast corner of 9th and

Hawthorne, one facing westward and the other facing eastward. Each data collector will be given a

bicycle count form to record his or her observations (Appendix A). The westward-facing observer

will tally (by street) each left-turning bicyclist as they cross the observer’s sidewalk line of sight on

7th, 8th, and 9th Avenues. The eastward-facing observer will do the same for bicyclists turning left

onto 10th and 12th Avenues (11th being a one-way southbound). These observation points are

uniquely effective due to their relative lack of interference from car traffic (scanning across a

sidewalk as opposed to a street), and also to the fact that the heaviest bike traffic occurs on the street

furthest from the observer, maintaining a line of vision well-suited to the observation of multiple

streets. Three separate two-hour counts will be conducted during afternoon peak hours (4-6pm) on

a Tuesday, Wednesday, or Thursday, as these days are not shown to be statistically unique from one

another (Alta, 2009).

A number of logical assumptions constitute the rationale for the user count site selections.

Southeast 7th Ave. is the only designated north-south bike route intersecting the Hawthorne bike

route east of the bridge. Given that the intersection of these two streets is an acknowledged point of

difficulty for cyclist navigation (Portland Office of Transportation, 2007), and that the eastbound

Hawthorne bike corridor ends at 12th Ave., it stands to reason that cyclists encountering difficulty

with the left turn at 7th would likely turn instead at 8th, 9th, 10th, or 12th. It is also likely that a

significant number of Group A cyclists continuing their northward journey on 12th Ave. prefer this


route, given its status as an arterial, but the allowance of five additional blocks for merging left may

play a role in that decision. Manual user counts are a more sensible option for this study than

automated counts due to their higher level of accuracy and lower cost (Schneider, Patten, and Toole,

2005). The labor intensity of manual user counts can be a drawback in situations involving

numerous count locations, but this study’s need for only two observers working only three hours

each does not raise that concern.

The City of Portland conducts annual bicycle counts throughout the city and publishes their

aggregated results each year, along with a summary discussion of notable trends. Their counts are

performed by 24-hour automated means in some locations and manually using peak flow

extrapolation at many others, including the four main Willamette River bridges (Portland Bicycle

Counts, 2007). Their 2007 study utilized 60 volunteers to conduct 93 counts across the city, among

98 sites selected. With a scope this broad, they were able to analyze detailed bicycle usage trends on

many different scales, from individual intersections to the city on the whole. The 2007 study

concluded that Portland’s bicycle use is increasing rapidly, and doing so at an increasing pace.

User Intercept Survey: The quantitative measures of safety and demand outlined to this point

comprise the important empirical component of this study, but they do not paint a complete picture

without the incorporation of subjective user input. An intercept survey facilitates a targeted

evaluation of users’ perceived comfort and level of safety. Demand for additional facilities can be

gauged more precisely through the directly stated preferences of potential users. For this study a user

intercept study will be conducted among eastbound cyclists at the southeast corner of Southeast 6th

Ave. and Southeast Hawthorne, shortly before they would reach the intersection at Southeast 7th

Ave. In order to maximize the sample of these cyclists, a large sign will be placed in their line of

sight one block west of the survey point (at Southeast Grand Ave. and Southeast Hawthorne) urging

their participation. A second sign will be placed at the location of the survey, in clear view of cyclists


approaching in the bike lane. Given that the parallel parking strip between Hawthorne’s bike lane

and south curb does not allow parking on this portion of the block, it makes for a safe, highly

visible, and unobtrusive location for cyclists to dismount before receiving their questionnaires. There

is sufficient space here to accommodate a sizeable number of bicycles, and cyclists can transition to

this spot from the bike lane without facing bus or vehicular conflicts.

The user intercept survey method was selected for this study due to its effectiveness at

isolating and targeting the desired sample. Its time and day of occurrence will mimic that of the user

count in order to maximize the correspondence of their data sets. Depending on the number of

cyclists who choose to participate, attracting a sample size sufficient to achieve a maximum

acceptable sampling error of plus or minus 10% with a 95% confidence level may or may not require

more than one two-hour survey period. Ideally the survey will achieve a much lower sampling error

in one period, but due to the time and weather constraints surrounding this study, conducting the

sample across more than one period could be relatively burdensome. A tightly constrained sampling

error, however, is not necessary to adequately serve this study’s purpose of establishing a general

idea of demand.

An estimated count of daily peak-flow bicycle traffic near the survey location (population

size) will be used to calculate sampling error as represented in Table 8 of the Transportation

Cooperative Research Program’s TCRP Synthesis 63: On-board and Intercept Transit Survey Techniques

(2005). The Portland Department of Transportation recently observed a summer average of 7,379

bicycles per day on the Hawthorne bridge. Multiplying this count by a factor of 0.2 generally yields

an accurate 4-6pm peak-flow number (Geller, 2008), most of whom are presumably traveling east

and therefore exiting the bridge into our survey area. Certainly an unknown portion the bicyclists in

that count are traveling west, but this will only cause the actual sampling error to be lower than

calculated. The peak-flow number will be multiplied again by a factor of 0.5 to approximate the


difference between a summer bicycle count and a winter count (Geller, 2009), assuming ridership

levels on the survey date in November are similar to those during the winter. The high population

number generated by not excluding westbound cyclists will be offset to some degree if the number

of cyclists on the date of the survey is greater than that of an average day during the winter. By the

calculation method described here, the population size for the survey is estimated at 738.

Though effective in its ability to target a specific group of users for detailed questioning, the

principle weaknesses of the user intercept survey as it pertains to this study lie in the time and labor

intensity required to gather sufficiently accurate data, and the difficulty in estimating an accurate

population size from which to calculate sampling error.

In April 2006 a study seeking to understand cyclist use of off-road paths was undertaken in

Melbourne, Australia, taking the form of an intercept survey coupled with a postage-paid self-

completion questionnaire (Rose, 2007). Systematic sampling was used to select one out of every four

counted cyclists for an intercept interview, in which they were asked to answer a few brief questions

and given the take-home questionnaire to be returned via mail. In the end only one in seven actually

completed the interview process, but of these an impressive 77% completed and mailed back the

questionnaire. A detailed set of statistics on off-road trail use was gleaned from the survey’s


respondents, 85% of whom were commuters. The take-home-and-return questionnaire was

demonstrated here as a potentially effective way to augment the data gathered in an intercept survey.

The methodology outlined in this study for examining the question “Is there a need for

additional bicycle left-turn facilities at Southeast Hawthorne Blvd. and Southeast 7th Ave.?” matches

a pertinent selection of variables to a balanced set of established measurement techniques. A

synthesis of the resulting data will provide an appropriate indicator for evaluating this question.

Results and Interpretations

The data of primary interest in this study were gathered from the user intercept survey and are

augmented by the manual user counts and Bicyclist Intersection Safety Index. The user intercept

survey was conducted during the afternoon peak period of 4-6pm on two consecutive days, both

during relatively cold and overcast weather conditions. Daylight was present only during the first 30-

40 minutes of the survey period. Responses were collected from a total of 118 bicyclists out of the

estimated population size of 738, yielding a sampling error of ±8.3% at a 95% confidence level

(assuming a 50% sample proportion). Respondents were asked eleven questions, three regarding

bicycle usage characteristics, four regarding perception of safety and merge behavior in the study’s

location of interest, two determining the bicyclist’s current trip characteristics, and two regarding

attitudes toward a redesign of the intersection of Southeast 7th Ave. and Southeast Hawthorne. Five

of these questions were directed only at bicyclists turning left on their current trip, yet many others

still responded to them. Due to the questions of consistency that this raised, these responses were

removed from consideration.

volatileendeavors-smithvu

Documents

portland bike

negative bicycle

southeast hawthorne

foot portland bicycle

highest bicycle ridership

lowstress bicycle network

designated bike corridor

lefthand turn