Pedestrian Countdown Signals: What Impact on Safe Crossing?

doi:10.4236/ojce.2013.33B007

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Open Journal of Civil Engineering, 2013, 3, 39-45

http://dx.doi.org/10.4236/ojce.2013.33B007 Published Online September 2013 (http://www.scirp.org/journal/ojce)

Pedestrian Countdown Signals: What Impact

on Safe Crossing?

Janusz Supernak, Vinay Verma, Iga Supernak

Department of Civil, Construction and Environmental Engineering, San Diego State University, San Diego, USA

Email: [email protected]

Received July 2013

ABSTRACT

This paper examines safety impacts of a Pedestrian Countdown Signal (PCS) installed on a busy downtown intersection

in San Diego, California. Crossing episodes of over 5000 pedestrians were videotaped and analyzed using multivariate

statistical methods. Details of timing of pedestrian crossing as well as information about vehicular traffic and signal

timing were carefully coded for each pedestrian. Significant safety benefits of the PCS system were found on the long

crossings over a street with high vehicular volumes: most pedestrians were able to effectively increase their walking

speed to complete their crossing without committing the exit violation —even if they have already committed the entry

violation. However, on the short crossing with light vehicular traffic, PCS was generally ineffective in preventing the

entry violations from becoming exit violations. Over there, many pedestrians felt safe enough to walk over a short

crossing with no apparent vehicular traffic in sight instead of waiting for a green signal. The length of crossing and vo-

lume of interfering vehicu lar traffic were consistently found the most significant variables affecting the crossing viola-

tion rates of different categories of pedestrians. Crossing violation rates were the highest for runners, bicyclists and old-

er males. Crossing violation charac teristics were found to be consistent over time.

Keywords: Pedestrian Safety; Countdown Signals; Multivariate Analysis; Safety Impacts

1. Introduction

PCS systems aim at improving pedestrian safety at the

intersections: information about the number of seconds

remaining for a safe crossing should help pedestrians to

make a correct decision whether to start crossing or to

wait for the next Steady Walk (SW) signal. It could also

alert them to speed up their walking to safely complete

their crossing maneuver in time and avoid any conflict

with the vehicular traffic.

Generally, PCS systems proved to bring tangible bene-

fits in terms of reducing the percentage of finishing of

the pedestrian crossings on Don’t Walk (DW) signal (il-

legal exit). However, several studies indicated that PCS

may actually increase the percentage of pedestrians who

start crossing on Flashing Don’t Walk (FDW) signal (il-

legal entry) as they may realize that they still have

enough time to complete their crossing safely. A large

San Francisco, CA study [1] found that PCS brought an

impressive 52% reduction in pedestrian injury as well as

statistically significant decrease in exit violations and in

running or aborting crossing. At the same time, there was

a slight (and statistically not significant) increase in the

entry violations. The observed vehicle-pedestrian con-

flicts decreased but not to the statistically significant le v-

el. P edestrians were found to increase their speed to clear

intersection in time. Similar positive results were re-

ported in the Monterey, CA [2] and Las Vegas, NV [3]

studies. But in the Montgomery County, study [4], the

PCS performance was found to be somewhat mixed: only

three out of five intersections studied found decrease in

the exit violations. Even less impressive are results from

the Lake Buena Vista, FL study: PCS installation re-

sulted in more rather than less exit and entry violations

there [5]. A before-after study performed at the city-first

PCS-equipped intersection in downtown San Diego

found that the new system brought a statistically signifi-

cant decrease in percentage of illegal exits but also in-

crease (although not statistically significant) in illegal

entries [6].

International studies generally confirm the benefits of

the PCS systems. For example, in Shanghai, China, PCS

installation dramatically increased the proportion of suc-

cessful crossing; the resulting safety improvement was

experienced primarily by the older people [7]. A study

from Auckland, New Zealand, concluded that PCS sys-

tems favorably affect pedestrian crossing behavior if

placed at suitable locations but may lead to increase in

risky crossing behavior at some unsuitable locations [8].

J. SUPERNAK ET AL.

Most commonly, PCS installations begin the count-

down procedure on the start of FDW interval rather than

on the SW interval. However, some cities follow the op-

posite procedure. Although there may be still discussion

on which version of the PCS system may be preferred by

the pedestrians, it is quite clear by now that the pede-

strians overwhelmingly favor intersections equipped with

PCS systems over those without PCS.

Review of the literature indicates some diversity of

conclusions reflecting not only any potential differences

in pedestrian behavior over the wide range of local cir-

cumstances but also some methodological issues related

to study design and the actual analytical methods applied.

This paper reports on an effort undertaken at San Diego

State University (SDSU) to better understand the pede-

strian crossing behavior at an intersection equipped with

a PCS system [9]. Availability of the newly installed

PCS system in downtown San Diego created not only an

incentive to study its effectiveness but also created an

opportunity to look into the core “anatomy” of the pede-

strian crossing behavior through careful recording and

coding of over 5000 crossing episodes made by a diver-

sified gr oup of pedes trians.

2. Study Objectives

The main goal of the SDSU study reported in this paper

was to evaluate the long term effect of pedestrian count-

down signals on the intersection crossing behavior of

various groups of pedestrians in the context of pedestrian

safety. Data collection was conducted using a video

camera. The relevant data from each individual crossing

episode were extracted from the video tapes and coded

into a spreadsheet format suitable for analysis. Finally,

the data were analyzed using statistical methods to sys-

tematically study the pedestrian behavior at that PCS-

equipped intersection.

The following research questions were posted: 1) How

common are pedestrian crossing violations? 2) Who are

the violators? 3) Where do the violations happen? 4)

When do the violations happen? 5) Are violations af-

fected by the geometry of the crossing? 6) Are vio lations

affected by the vehicular traffic? 7) Are violations con-

sistent over time? 8) Do PCS systems reduce the most

dangerous violation: illegal exit? 9) Do pedestrians use

PCS displays to adjust their walking behavior to com-

plete their intersection crossing in time?

3. The Venue

The selected intersection is located at Broadway and

Second Avenue in the downtown San Diego. It is sur-

rounded by Westgate Hotel building, San Diego City

Hall, NBC San Diego, Speckles Theater, and several

stores and restaurants. A major trolley station is nearby.

The study intersection has high pedestrian traffic vo-

lumes during the day. The vehicular traffic volumes are

high on Broadway but light on the Second Avenue. The

study intersection is not equipped with pedestrian push

buttons. The pedestrian crossing cycles are activated

once per traffic cycle. Data was collected in the morning

peak period time 8:00 to 10:00. One crosswalk was se-

lected for one specific day. Video recording was done for

three weeks from Monday to Thursday. Pedestrian video-

tape records were examined carefully to properly code

the behavior of each pedestrian on Excels spreadsheets.

To assure privacy, no specific person was ever targeted

or identified.

Broadway Street is almost two times wider than the

Second Avenue. The Broadway crossing distance is 25.8

m (86 feet) whereas the Second Avenue crossing dis-

tance is 14.4 m (48 feet). At the time of the videotaping

in August 2009, the c ycle length on the study inter se ction

was c = 70 seconds. Cycle phasing for pedestrians was

set as follows:

Broadway Crossing:

Walk: 7 sec; FDW: 21 sec and DW: 42 sec; Total: 70

sec.

Second Avenue Crossing:

Walk: 20 sec; FDW: 10 sec and DW: 40 sec; To tal: 70

sec.

Assuming the conservative walking speed standard of

1.0 m/sec (3.5 ft/sec), a pedestrian would need almost 26

seconds to cross Broadway; a person who starts crossing

at the beginning of the SW indication will have just 28

seconds to complete his/her crossing. If the 1.2 m/sec

(4.0 ft/sec) speed standard was applied, the pedestrian

would need 21.5 second s to cros s. This mean s that a slow

walking pedestrian who enters legally at the end of his/

her SW phase may have difficulty to exit on time since

the FDW signal is just 21 seconds long.

The pedestrian timing plan for the Second Avenue

crossing appears problematic. Assuming the 1.0 m/sec

walking speed, a pedestrian would need almost 14

seconds to cross Second Avenue but the FDW phase

there was only 10 seconds long. Thus, a pedestrian who

starts crossing legally at the end of the SW indication

may not have enough time to exit legally. Even if 1.2

m/sec standard was applied, the pedestrian would need

12 seconds to cross, more than the duration of the FDW

phase. This problematic timing plan on the Second Ave-

nue design (too long SW phase and too short FDW phase)

may well be one of the contributing factors to Exit viola-

tions on that crossing.

4. Pedestrian Data Organization

4.1. Pedestrian Crossing Situations

Every pedestrian’s intersection crossing behavior can be

J. SUPERNAK ET AL.

classified as one of the four following situation s :

Situation 1: Non Violation; Legal E ntry and Le gal Exit.

Situation 2: Illegal Entry but Legal Exit.

Situation 3: Legal Entry but Illegal Exit.

Situation 4: Illegal Entry and Illegal Exit.

In order for the Entry to be legal, it has to start on

Steady Walk (SW) signal. In order for the Exit to be le-

gal, it has to be completed on Steady Walk (SW) or

Flashing Don’t Walk (FDW) signal.

4.2. Definition of Crossing Violations

In order to effectively record and process the observed

incidents of intersection crossing done by each individual

pedestrian, the raw data was organized on a spreadsheet

to record for each pedestrian the following pieces of in-

formation : 1) date; 2) cycle number; 3) crossing identi-

fication (Broadway or Second Avenue); and 4) person

category number.

The following crossing-related information was ex-

tracted from the video for each pedestrian P:

Tw = duration of the Steady Walk (SW) phase (sec).

Tfdw = duration of the FDW phase (sec).

to = time gap between the start of SW phase and the

moment pedestrian P started his/her crossing (sec).

t1 = time used by pedestrian P to reach the median of

the intersection (sec).

t2 = time used by pedestrian P to traverse the distance

between the intersection median and the intersection end

(sec).

The following condition constitutes the Illegal Entry

by pedestr i an P:

Tt0−<

(1)

The following condition constitutes the Illegal Exit by

pedestrian P:

( )

wfdw0 1 2

TTttt 0+− ++<

(2)

If pedestrian P is increasing his/her speed as his/her

intersection crossing progresses, the following condition

is expected to be met:

tt0−<

(3)

In order to examine the effect of PCS on safe crossing,

there is a need to identify those pedestrians who have

already committed Entry Violation (entered on FDW)

and were heading for the Exit Violation if their speed

was not adjusted (increased).

For this particular subset of pedestrians the condition

t0 > Tw needs to meet the following additional condition:

01w fdw

t 2t TT+>+ (4)

If their speed was not adjusted, the original time t1

would be repeated on the second half of the intersection.

However if the speed increase had sufficiently reduced t2,

the Exit Violation could be avoided.

Analysis of the intersection crossing episodes made by

various categories of pedestrians at the study intersection

in downtown San Diego proved that the vast majority of

them crossed the intersection with a speed much faster

than the design speed of 1.0 m/sec (3.5 feet/sec). Thus,

despite the rather tight timing plan, Situation 3: legal

entry yet illegal exit proved to be a very rare case. Dur-

ing the three weeks of videotaping of 5504 crossing epi-

sodes, this situation was encountered only once. For that

reason, Situation 3 was not analyzed as a separate case.

Thus, the study intersection exhibited only two distinct

violation cases, consistently used in the analysis pre-

sented in this paper:

1) Entry Violation: Illegal Entr y bu t still Legal Exit.

2) Exit Violation: Illegal Exit following Illegal Entry.

5. Analysis

5.1. Initial Definition of Pedestrian Ca t egories

Twelve pedestrian categories were arbitrarily defined

based on pedestrians’ age (below 18; 18 - 40; 40 - 65,

above 65), gender (male, female) and their specific status

(handicapped, runners, bicyclists). Their crossing beha-

vior was videotaped and coded. Representations of the

defined categories are quite uneven: for example, the

Younger Males Category amounts for a half of all pede-

strians in the sample. Categorization according to age

and handicap was done consistently, based on the best

possible i nt erpreta t ion of the vi deo data.

5.2. Comparison of Violation Proportions for the

Twelve Pedest rian Categories

A total of 5504 pedestrians were observed and classified

into 12 categories. The three performance outcomes:

Non-Violation; Entry Violation; and Exit Violation pro-

portions were examined for the following variables: pe-

destrian categories; time-of-day periods (peak/off-peak);

days of the week (M, Tu, W, and Th); weeks (1, 2, and 3);

length of crossing (short/long) and corresponding vehi-

cular traffic (light, heavy) as well as corresponding tim-

ing plans for the two crossings (short FDW/long FDW).

The starting analysis was performed for the initial

twelve categories of pedestrians to identify similarities

and differences among them in terms of their intersection

crossing behavior. A pair-wise comparisons of the entry

and exit violation proportions was made to evaluate

whether the performance measures between different

those groups are statistically significant. The null hypo-

thesis tested in all cases is that there is no difference be-

tween groups, with the a lter native hypothesis that there is

a statistically significant difference among them.

01 2

Hp p

=: (5)

J. SUPERNAK ET AL.

Hp p

a≠:

(6)

A two-tailed z test was performed at a confidence level

of 95% with the corresponding critical z value (zα/2) of

1.96. Various groups of pedestrians were stratified ac-

cording to several variables, and pair-wise proportion

comparisons were performed to have preliminary know-

ledge about the significance of those variables in de-

scribing variations in Entry and Exit Violations propor-

tions. The z-test brought the following initial results:

1) With both crossings analyzed jointly, older males

were committing the Entry Violation more frequently

than their younger male counterparts and that difference

was significant. The same was also true for the Exit Vi-

olation: older males were exiting illegally with higher

frequency than their younger male counterparts but this

difference was not significant. It is likely that younger

males were able to adjust their walking speed more ef-

fectively than their older counterp arts.

2) Persons performing sports activities (runners, bi-

cyclists) were committing both Entry and Exit Violation

more frequently than their “regular” pedestrian counter-

parts.

3) For both Entry and Exit Violations, there was a sta-

tistically significant difference in their frequency be-

tween short and long crossing. The length of crossing is

just one of the differences between those two crossings.

There are two more differences:

a) The long pedestrian crossing on Broadway is against

heavy vehicular traffic whereas the short crossing over

the Second Avenue has a very light vehicular traffic; and

b) The FDW phase over Broadway is long whereas

FDW phase over the Second Avenue is short.

4) Both Violation types are more frequent during the

peak period (8 - 9 am) than during the off peak period (9

- 10 am), as expected. Rushing to work may be the rea-

son for more frequent violations during the pea k pe riod.

5.3. Comparison of Violation Proportions for the

Six Pedestrian Categories

Initial statistical analysis: comparison of violation pro-

portions for the twelve pedestrian categories helped to

identify those categories of pedestrians who were the

most common violators. However, some of the categories

were not represented with enough observations despite

the relatively long (three weeks) observation period. For

example, people with handicap amounted to just one case

out of 5504 observations; a much larger observation pe-

riod and a larger sample would have been needed to ob-

tain statistically valid results concerning this group of

pedestrians at the study intersection.

For the purpose of the further analysis, some of the

“old” categories 1 through 12 were merged to create six

“new” categories A through F. A common sense judg-

ment was used to create this new categorization of pede-

strians. Definitions of the new categories and respective

Entry and Exit Violation proportions are presented in

Table 1 and can be summarized as follows:

1) Pedestrians crossing the study intersection in down-

town San Diego were predominantly younger males and

females: they accounted for 88% of the entire sample of

pedestrians.

2) The overall Entry Violation proportions were quite

high (around 30%) for both crossings. The highest Entry

Violation rates were for the runners and bicyclists, and

for older males, particularly on the short crossing.

3) The overall Exit Violation proportions were quite

small (around 6%) on the long crossing but remained

substantial on the short crossing (ar ound 20%).

4) On the long crossing, 78% of the Entry Violations

did not lead into consequent Exit Violations. But on the

short crossing, this number was only 34%.

5) Significant reduction in Violation frequency be-

tween the intersection entry and the exit on the long

crossing may be partially attributed to the PCS system;

more detailed analysis follows to test this hypothesis .

5.4. Chi-Square Analysis

Chi-square analysis was performed on the new categories

to evaluate whether pedestrian behavior represented by

the proportions among the three possible outcomes (No

Violation, Entry Violation, Exit Violation) varied with

different pedestrian categories, weeks, time of the day,

day of the week or length of crossing. The null hypothe-

sis tested in all cases is that there is no difference in pro-

portions between the strata, with the alternative hypothe-

sis that there is a statistically significant difference be-

tween the strata:

Table 1. Crossing violation proportions for six person ca-

tegories.

Pedestrian Long crossing Short crossing

Category Entry Exit Ent ry Exit

Violation Violation Violation Violation

A. Children 30.8% 0.0% 8.5% 5.1%

B. Younger Males 29.5% 7.8% 30.0% 20.4%

C. Younger Females 20.6% 3.3% 30.0% 18.6%

D. Older Males 34.1% 3.9% 42.7% 28.9%

E. Older Females 26.1% 4.3% 34.5% 23.8%

F. Runners, Bicyclists

31.6% 5.3% 61.3% 48.4%

Overall 26.6% 5.8% 31.0% 20.6%

J. SUPERNAK ET AL.

01 2

Hp p=

: (7)

Hp p

a≠:

(8)

Results of chi-square analysis are shown in Table 2.

Results that are significant at the 5% level are labeled S,

and not significant are labeled N. The results of the chi

square analysis presented in Table 2 show that o ut of the

five variables studied: pedestrian categories, weeks, days,

time of day, crossing length—only “weeks” variable ap-

pear consistently not significant at the 95% confidence

level.

All other variables show statistical significance for at

least some situations listed in the first column. “Length

of crossing” (and related difference in vehicular traffic

and in signal timing) appears to be a strong discriminat-

ing variable. “Person categories” differences also appear

important except for the case when distinction is made

between the Entry Violation and Exit Variation propor-

tions only. “Time of day” is the third significant variable.

Chi-square analysis shows that there is a statistically

significant difference in crossing behavior related to

those three variables when they are analyzed separately.

The next research question is how significant would

those variables be if analyzed jointly. Analysis of va-

riance (ANOVA) is a suitable statistical technique for

this type of analysis.

5.5. Analysis of Variance (ANOVA)

Analysis of variance (ANOVA) analysis was performed

on the new six categories. This test was performed to

evaluate whether the differences in violation proportions

between different categories are statistically significant

when analyzed together with the following variables: the

type of crossing, weeks, day of the week, and time of the

day. All possible 2-way ANOVA calculations were per-

formed separately for the Entry Violation and Exit Viola-

tion cases.

Results of analysis of variance for the Entry and Exit

Violations are presented in a summary way in Table 3

and Table 4, respectively. Differences in proportions that

are significant at the 95% level of confidence are labeled

Table 2. Summary of chi-square analysis results.

Proportion scenarios 1F 2F 3F 4F 5F

VN/VNE/VXE S S N S S

VN/VNE S S N S S

VN/VXE S S N N S

VNE/VXE N S N N S

NV = non-violation proportion; ENV = entry violation proportion; EXV =

exit violation proportion; F1 = pedestrian categories; F2 = crossing length;

F3 = week s; F4 = days; F5 = peak/off-peak; S = signif ican t at 5% level; N =

not significant at 5% level.

Table 3. Entry violation ANOVA significance summary.

srotcaF 1F 2F 3F 4F 5F

1F N S N N

2F S N N N

3F N N N N

4F N N N N

5F N N N N

F1 = pedestrian cate gories ; F2 = crossing length; F3 = weeks; F4 = days; F5

= peak/off-peak; S = significant at 5% level; N = not significant at 5% level.

Table 4. Exit violation ANOVA significance summary.

srotcaF 1F 2F 3F 4F 5F

1F N S S S

2F S S N N

3F N N N N

4F N N N N

5F N N N N

F1 = pedestrian cate gories ; F2 = crossing length; F3 = weeks; F4 = days; F5

= peak/off-peak; S = significant at 5% level; N = not significant at 5% level.

S and those not significant are labeled N.

The main conclusions from the results summarized in

Tables 3 and 4 are as follows:

• Two variables show explanatory power to explain

differences in proportions of the Entry Violation be-

havior (entering illegally). Variable “categories” are

significant when analyzed together with variable

“weeks”; and type of crossing is significant only if

analyzed together with variable “categories”. This

result would imply that Entry Violation happens rela-

tively independently of the other variables analyzed.

• Exit Violation behavior is quite different than the

Entry Violation behavior. The “category” variable is

significant when analyzed together with variables:

“weeks”, “peak/off peak” and “days” variables (but

only when recorded on the short crossing). The

“crossing” variable is significant when analyzed to-

gether with the “category” and “weeks” variables;

• Three remaining variables: weeks, days, time-of-day

do not show explanatory power if analyzed with other

variables. This result sugges ts that pedestr ian cro ssing

behavior is quite consistent over time.

5.6. Impact of PCS on Walking Speed

Some studies indicated that PCS systems may be able to

make pedestrians to adjust their speed of crossing to

avoid the dangerous Exit Violation. Equation (4) identi-

J. SUPERNAK ET AL.

fies those pedestrians who committed Entry Violation

(entered on FDW) and were heading for the Exit Viola-

tion if their speed was not adjusted (increased).

Out of 5402 pedestrians studied, 1084 of them (252 on

Broadway and 832 on the Second Avenue) were those

who committed the Entry Violation and were on track to

also commit the Exit Violation.

One hundred and fifty two (152) out of the 252 pede-

strians (60.3%) who made a long crossing across Broad-

way (high volume of auto traffic), and started late

enough to potentially commit Exit Violation, had in-

creased their speed by observing PCS display and com-

pleted their crossing in time before the steady DW indi-

cation.

Potential for speed adjustment was also studied for the

pedestrians on short crossing (Second Avenue). But in

that case, only 77 pedestrians out of 832 (9.3%) who

committed Entry Violation were able to effectively adjust

their speed to avoid Exit Violation and finish their cross-

ing on time. Two reasons were likely responsible for that:

1) light vehicular traffic that made the short crossing ep-

isode look safe even if it is illegal, and 2) problematic

signal design that offered a very short crossing time for

pedestrians who entered on the Flashing Don’t Walk or

even late on the Steady Walk phase.

5.7. Impacts of Other Fa ctors

5.7.1. Effect of Vehicular Traffic

Pedestrian behavior is naturally affected by the vehicular

traffic density. High vo lume of veh icular traffic may lead

into dangerous pedestrian-vehicle conflicts, and reason-

able pedestrians would try to avoid them. This may be

one of the reasons why pedestrians were committing Exit

Violation on the short Second Avenue crossing more

frequently than on the long and busy Broadway crossing .

Videotape analysis clearly revealed that auto traffic was

much more intense on Broadway than on the Second

Avenue. Gaps between consecutive cars were short on

Broadway, potentially discouraging pedestrians from

making risky crossing decisions. But on the Second Ave-

nue, auto traffic was very light with much larger gaps

between consecutive automobiles. Cars were counted on

the Second Avenue to determine time gaps between them

during the pedestria n FDW and DW phases, and revealed

that 41% of auto gaps there were longer than 8 seconds.

This means that almost every second cycle had zero cars

interfering with the pedestrians on that short crossing.

5.7.2. Enforcement Issue

During the three weeks of the videotaping, there was no

indication of any enforcement action against those who

jaywalked. Lack of enforcement may have been a con-

tributing factor to the magnitude of crossing violations at

the study intersection.

5.7.3. Pl atooning

Some pedestrian crossing violations may be caused by

platooning. When a large group of pedestrian is trying to

cross, some pedestrians may actually block other pede-

strians, delay them and potentially contribute to their

crossing violations. However, no episode of pedestrian

platoon-related delay was observed on either Broadway

or Second Avenue crossing.

6. Summary of Findings

1) Pedestrian Countdown Signals (PCS) appear effec-

tive in reducing exit violations where there is a long

crossing with a long Flashing Don’t Walk phase count-

down (the Broadway case in this study). In case of short

crossing with a short FDW phase, they appear to be ra-

ther ineffective (the Second Avenue case in this study).

Auto traffic may also effect the violations among pede-

strians: for the higher volume auto traffic on the long

crossing fewer violations were recorded as compared to

lighter traffic on the short crossing.

2) The exit violations proportions are greatly reduced

on the long crossing over a major arterial (Broadway).

This reduction is much smaller on the short crossing over

a street with a low traffic volume (Second Avenue).

3) PCS system is proved to influence speed adjustment

of pedestrians who can effectively avoid the consequen-

tial exit violation; this is primarily observed on the long

crossing where 2/3 of pedestrians heading for the exit

violation are effectively able to avoid it and exit the in-

tersection timely.

4) Pedestrian population is heterogeneous in term of

its intersection crossing behavior, and proper market

segmentation appears useful in understanding differences

in violation frequencies among various groups of pede-

strians. In downtown San Diego, the groups with the

highest crossing violation rates are runners and bicyclists

as well as older males.

5) Pedestrian violations are more frequent during the

rush hours than outside that period but this difference is

not statistically significant. Pedestrian intersection cross-

ing behavior is consistent from day to day and from week

to week.

6) Pedestrian behavior is affected by multiple factors

such as composition of the population, intersection geo-

metry, traffic intensity and signal design. In order to

properly capture those various effects, multivariate ana-

lysis is useful.

7) Analysis based on videotaping and detailed coding

of the relevant elements of the intersection crossing of

every individual is a tedious but effective procedure to

better understand subtleties of pedestrian intersection

crossing behavi or.

8) More studies of the same kind would be needed to

verify validity of those findings at some other sites, par-

J. SUPERNAK ET AL.

ticularly at locations with higher percentage of such

groups like: children and adolescents or elderly and han-

dicapped pedestrians.

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