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2011 PEDESTRIAN SAFET
TRACKING REPORT
SUBMITTED TO:
STATE OF NEW JERSEY
Department of Transportation
1035 Parkway Avenue
P.O. Box 600
Trenton NJ 08635-0600
SUBMITTED BY:
ALAN M. VOORHEES
TRANSPORTATION CENTER
Edward J. Bloustein School of
Planning and Public Policy
Rutgers, The State University of
New Jersey
33 Livingston Avenue
New Brunswick NJ 08901
New Jersey Bicycle and Pedestrian Resource Cen
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2011 Pedestrian Safety Tracking Report
Rutgers,TheStateUniversityofNewJerseyEdwardJ.BlousteinSchoolofPlanningandPublicPolicy
AlanM.VoorheesTransportation Center33 Livingston Ave New Brunswick, New Jersey 08901 T 732.932.6812 F 732.932.3714 http://policy.rutgers.edu/vtc
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Table of Contents
Introduction! 1Total Pedestrian Fatalities and Injuries! 2Gender! 2Age! 3Pedestrian Crashes by Road Type! 4Pedestrian Crashes by Time of Day! 6Pedestrian Crashes by Day of the Week! 6Pedestrian Crashes by Month! 7Pedestrian Crashes by Weather Condition! 7Pedestrian Crashes and Alcohol Consumption! 8Pedestrian Crashes by County! 9Pedestrian Crashes for 10 Largest New Jersey Municipalities! 11Conclusions and Implications! 12Appendix A Pedestrian Crashes in New Jerseys Ten Largest Municipalities! 14
2011 Pedestrian Safety Tracking Report
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IntroductionThis report is intended to extend and update the information provided in the 2010 Pedestrian Safety
Tracking Report. Data presented in this report were collected from a variety of sources, but focus on the
Plan4Safety database of reported crashes in the State of New Jersey. This database is maintained by the
Center for Advanced Infrastructure and Transportation (CAIT) at Rutgers, The State University of New
Jersey. The data in the Plan4Safety database are compiled from police records and verified by New Jersey
Department of Transportation. This report updates the 2010 report with data from 2009 and 2010, while
also increasing the accuracy of previously reported data through a more robust data extraction.
The primary purpose of this report is to continue to track crashes involving pedestrians. This report
refines the previous work done, and provides more detailed analysis of the patterns of pedestrian
fatalities and injuries on New Jersey's highways and roads. We have specifically expanded this year's
analysis to include some new spatial information on counties and municipalities. It is our expectation that
this spatial data and more sophisticated visual representations of existing data will be incorporated into
future updates to make the presentation of this material more accessible and useful for policy makers.
Another ongoing goal of this research is to collect and compile information on safety improvements and
investments. These efforts are underway, reflected in a separate three-corridor analysis report entitled
Pedestrian Safe Corridors: Memorandum. We expect to improve this effort in subsequent years as we are able
to collect more data on specific improvements and combine those data with the Plan4Safety data.
The primary findings of this report show a continuation of the highly variable number of pedestrian
fatalities on New Jersey streets, even while the overall numbers of crashes involving pedestrians have
modestly declined in the most recent years. Demographic analysis shows a higher risk for men and older
adults, especially over the age of seventy-five. New analysis techniques have also uncovered a significant
outlier in terms of overall pedestrian safety: Atlantic County. Home to popular tourist destinations that
attract many pedestrians to the region, Atlantic County has a much higher rate of crashes involving
pedestrians than any other New Jersey county when population density is controlled. One explanation is
that most of the county is tourist-oriented, which inflates the number of pedestrians compared to the
native population during certain times of year. Nevertheless, Atlantic County (and to a lesser extent
Ocean County) is more fatally dangerous than other areas of the State.
The data extracted from the Plan4Safety database limited the type of crashes under investigation. Like the
previous years study, the 2011 Pedestrian Safety Tracking Report only examined crashes involving
pedestrians, which were also reported to result in injury or fatality. We omitted crashes that only resulted
in property damage. Data were merged from both the pedestrian reports and the crash reports to create a
2011 Pedestrian Safety Tracking Report 1
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single dataset containing all pedestrian (individual) and crash site variables. When possible, pedestrian-
level data were used to calculate injury and fatality counts. In some cases, crash counts were used in place
of pedestrian level data for analysis.
The rest of this report provides detailed sections analyzing trends in pedestrian safety. The report aims to
inform decision makers and therefore does not explicitly engage in policy discussions or make
recommendations. The concluding section does discuss some implications of the findings, but does not
suggest any strategies for addressing pedestrian safety. The concluding section also summarizes the
methodological challenges in analyzing pedestrian safety data.
Total Pedestrian Fatalities and Injuries
During the eight-year study period, 2003-2010, a total of 1003 pedestrian fatalities occurred due to
vehicle-pedestrian crashes, or an average of 125 per year. During the same eight-year period, a total of40,150 pedestrian injuries occurred due to such crashes at an annual rate of 5,019 injuries. Fatalities have
stayed nearly constant over the period, but injuries show a large drop between 2005 and 2006 and then
again between 2008 and 2010. During the latter period, vehicle-miles-traveled have also fallen, which may
be one explanation for the decline in pedestrian injuries.
nnual Pedestrian Fatalities and Injurie in New Jersey, 2003-2 10
Injury Fatal Daily Vehicle Miles Traveled
Pedestrian Fatalities per 1
million Daily VMT
Pedestrian Injuries per 1
million Daily VMT
2003
2004
20052006
2007
2008
2009
2010
Total
5,817 126 195,237,000 0.6 29.8
5,785 120 199,119,000 0.6 29.1
5,658 147 203,076,000 0.7 27.94,805 124 207,131,000 0.6 23.2
4,721 125 208,419,000 0.6 22.7
4,704 108 200,051,000 0.5 23.5
4,549 133 199,586,000 0.7 22.8
4,111 120 N/A N/A N/A
40,150 1003
Gender
One of the more striking details about these data is the differences in injuries and fatalities among men
and women. Though men are very slightly overrepresented in injurious crashes, fatal crashes show atroubling difference. Men represent 65 percent of the pedestrian fatalities in New Jersey crashes. One
reason may be that men walk more frequently at night when more fatal crashes occur. Men's proportion
of nighttime fatalities is 67 percent; that proportion drops to 59 percent during daylight hours. Because
most fatal crashes occur in nighttime hours, the overall percentage is skewed heavily toward the
nighttime percentage.
2011 Pedestrian Safety Tracking Report 2
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Pedestrian fatalities have varied over the last eight years. Between 2008-2010, a higher proportion of men
have been killed than in three of the previous five years. This increase corresponds to a general decline in
pedestrian fatalities over this same period. The proportion of injuries occurring to males has remained
nearly constant throughout the entire study period.
Age
Data for 2003-2010 show age as an interesting indicator in crash occurrences. In this analysis we
compared both injuries and fatalities to the overall population shares in ten different age categories. For
pedestrian injuries, the 10-17 and 18-24 year-old categories are significantly over-represented. This likely
reflects both the propensity of younger people to walk and their risk-taking behavior when walking. The
0-9 year-old category is the only category underrepresented, likely due to their dependence on adults. Allother age categories track closely to the overall population share for pedestrian injuries.
Pedestrian fatalities tell a slightly different story, though. First, pedestrian under 18 years old are
significantly underrepresented compared to their population share. This contrasts the injury data and is
difficult to explain; some hidden explanatory factor must be omitted from our data. One explanation may
be that younger people are in better physical condition and can survive major injuries more often than
2011 Pedestrian Safety Tracking Report 3
0%
25%
50%
75%
100%
2003 2004 2005 2006 2007 2008 2009 2010
Percent male by severity
Injury
Fatal
0
25
50
75
100
2003 2004 2005 2006 2007 2008 2009 2010
Pedestrian Fatalities by Gender and Year
Female
Male
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older adults. Pedestrians over the age of 44 become more likely to be involved in a fatal pedestrian crash
and that propensity increases with each age category. The older one gets, the more likely it seems
pedestrian crashes will be fatal.
Pedestrian Crashes by Road Type
During the years 2003-2010, the largest number of pedestrian fatalities occurred on state highways (380),
followed by county roads (268), and municipal roads (220), respectively. However, when normalized by
miles of roadways in each class, fatalities are far less frequent on county and municipal roads (52 and 10
per 1,000 miles, respectively) than state highways (198 per 1,000 miles). A moderate increase in pedestrian
fatalities on Interstate highways from 2008-2010 (19 per year versus 10 per year in 2003-2007) has pushed
the normalized average fatalities for Interstate highways (104) into the same range as other high-speed
roadways like state highways (198) and toll roads (119).
These data indirectly indicate that speed is an important factor in pedestrian fatalities. This is highlighted
by the county road injury data. County roads have the highest normalized injury rate (1,797 per 1,000
road miles), yet as previously mentioned, do not result in nearly as many fatalities as the higher speed
highways.
Although municipal roads account for only a modest number of pedestrian fatalities compared to state
highways, half of the pedestrian injuries occur on these roads. These roads, however, account for 70
percent of the total road miles in the state.
Pedestrian fatalities for each road type have remained fairly constant over the eight year study period.
Injurious crashes have also remained nearly constant, except for at the municipal level. Municipal
roadways have seen a steady decline in reported injuries during the entire study period (2,956 injuries in
2003 to 2,153 in 2010).
2011 Pedestrian Safety Tracking Report 4
0%
5%
10%
15%
20%
0-9 10-17 18-24 25-34 35-44 45-54 55-64 65-74 75-84 85+
Proportions of population and fatal crashes by age
Pop %
Fatal %
Injury %
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2011 Pedestrian Safety Tracking Report 5
0
50
100
150
200
2003 2004 2005 2006 2007 2008 2009 2010
Fatal crashes by road type, 2003-2010
Interstate State Authority County Municipal Park Private Property Other
0
1500
3000
4500
6000
2003 2004 2005 2006 2007 2008 2009 2010
Injurious crashes by road type, 2003-2010
Interstate State Authority County Municipal Park
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Pedestrian Crashes by Time of Day
Combined data for the eight-year study period show that most pedestrian fatalities (65 percent) occur at
night. This statistic illustrates the importance of visibility in pedestrian safety. In contrast, however, mostpedestrian injuries (64 percent) occur during daylight hours. The relatively high proportion of injuries
during the daytime is due to greater pedestrian presence. Most pedestrian activities occur during the day,
thus putting more pedestrian on the streets at risk of traffic crashes.
One potential explanation of higher rates of pedestrian fatalities at night might be the increased use of
alcohol in those types of crashes. At night, 23 percent of fatal crashes involved alcohol compared to 6
percent during daylight hours. It seems there is evidence among these data of alcohol as a contributing
factor in more pedestrian fatalities at night.
Although darkness is often attributed to crashes, when the pedestrian injuries and fatalities are classified
by availability of streetlights, it appears only a small proportion (7 percent) of nighttime injuries occur in
areas with no streetlights. Fatalities, however, far outpace the proportion of injuries in unlit areas at 20
percent of all nighttime pedestrian deaths. To understand the true impact of streetlights on pedestrian
crashes, a more detailed research approach would be needed.
Hourly data of the eight-year period show that pedestrian injuries predominately occur in the afternoon/
evening period. This can be directly related to activities and road usage by individuals.
Pedestrian Crashes by Day of the Week
Aggregate data for the 2003-2010 period show that pedestrian fatalities and injuries vary only modestly
between the days of the week. Both fatalities and injuries are highest on Fridays. The higher frequency ofcrashes on Fridays may be due to a combination of various factors, including greater traffic volumes,
greater traffic and pedestrian volumes after dark, and alcohol consumption. Despite lower traffic volumes
on weekends, Saturdays have the second most fatalities. Sundays also have a large fatality-to-injury
discrepancy. Lower injury rates and higher fatality rates on weekends suggests that higher speeds due to
lower traffic volume may be a contributing factor to these higher weekend fatality rates.
2011 Pedestrian Safety Tracking Report 6
Crashes by light condition
Dark Dawn Daylight Dusk Total
Fatalities
%
Injuries
%
635 13 314 21 983
65% 1% 32% 2%
11705 392 23398 1030 36525
32% 1% 64% 3%
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Pedestrian Crashes by Month
The largest number of pedestrian crashes occurs during the October-December period. Aggregate data
from the 2003-2010 period show that both fatalities and injuries peak in the month of December. The
reason for a large number of crashes in December may be a combination of weather, high volumes of
holiday traffic, alcohol consumption, and unfamiliarity with driving in winter weather conditions. It is
worth noting that a large number of injuries occur in May and June, which may be due to higher
pedestrian volumes and academic breaks.
Pedestrian Crashes by Weather Condition
During the eight-year study period, 66 percent of pedestrian fatalities occurred during clear conditions,
while 12 percent occurred during rain or snow. Seventy percent of pedestrian injuries occurred during
clear conditions; twelve percent of injuries occurred during rain or snow. Most pedestrian crashes occur
during clear conditions because pedestrians tend to avoid activity during inclement weather. Taking into
account weather conditions is a difficult procedure due to the variety of ways one could measure
2011 Pedestrian Safety Tracking Report 7
0
50
100
150
January February March April May June July August S eptember October November December0
1250
2500
3750
5000Crashes by month, fatal and injurious
Fatal
Injury
0%
5%
9%
14%
18%
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Crashes by day of week
FatalitiesInjuries
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weather-related impacts. One way to control for variation in weather with easily accessible data is to use
total annual precipitation. Normalizing for this factor on an annual basis reveals that 2007 and 2008
seemed to have an unusually high number of pedestrian fatalities in rain or snow conditions compared to
the annual precipitation figures. In 2004, 2009, and 2010, rain/snow fatalities were much lower when
compared with annual rainfall. These anomalies are difficult to explain, but may be worth future research
to detect these differences more accurately.
Pedestrian Crashes and Alcohol Consumption
It is widely acknowledged by researchers that alcohol consumption by motorists and pedestrians is often
a contributing factor in crashes. Between 2003 and 2010, alcohol was involved in 17 percent of totalpedestrian fatalities. Alcohol is a much smaller factor in pedestrian injuries; only 6 percent of pedestrian
injuries reported during the period involved alcohol. This relationship is highly correlated with the
daytime/nighttime crash statistics reported earlier. More fatal crashes occur at night, when alcohol is also
more likely to be involved, than during the day. These data do not infer, however, who was under the
influence of alcohol and pedestrian alcohol consumption is likely to be underreported because it is not
necessarily illegal to walk when under the influence of alcohol.
Cra hes inv lving alcohol2003 2004 2005 2006 2007 2008 2009 2010
Fatal Alcohol
No alcohol
% alcohol
Injury Alcohol
No alcohol
% alcohol
31 24 28 37 20 20 38 20
116 122 136 145 132 141 134 112
21% 16% 17% 20% 13% 12% 22% 15%
386 377 341 326 305 305 299 272
5575 5586 5429 5121 5128 5090 4990 4481
6% 6% 6% 6% 6% 6% 6% 6%
2011 Pedestrian Safety Tracking Report 8
0%
5%
9%
14%
18%
2003 2004 2005 2006 2007 2008 2009 20100
15
30
45
60
Percent rain/snow conditions by year versus annual statewide preciptation
% Rain & Snow Precipitation
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Pedestrian Crashes by County
The data reported to the Plan4Safety database allow a certain degree of spatial analysis. In this section we
briefly highlight some of the county-level variation in crash statistics during the eight year study period.In general, urban and northern counties have lower rates of pedestrian crashes when controlling for
population density than suburban and southern counties. Three significant outliers are present in the
population density analysis: Atlantic, Ocean, and Burlington Counties. Both Atlantic and Ocean Counties
are shore counties with large tourism economies. They tend to attract visitors who are likely to walk more
often than other places, and who are unfamiliar with the areas. The visitors to these places are also likely
to consume alcohol and walk at night. Burlington County, on the other hand, is a large suburban county
on the Delaware River. Detecting reasons why Burlington has a high fatality rate normalized by
population density is difficult.
Controlling for population only (omitting land area) yields slightly different results. Smaller, northern
counties (Essex, Hudson, Passaic, and Union) have much higher total crash rates when only population is
controlled. Atlantic also remains high. Burlington drops to near the bottom, suggesting that it's large land
area might be a larger factor in the density analysis above. In terms of fatal crashes, Atlantic remains an
outlier in fatal crashes when only population is controlled. Both Ocean and Burlington drop back to the
rest of the counties in the fatal crash analysis. Union is the only other outlier and is difficult to explain
with the available data.
2011 Pedestrian Safety Tracking Report 9
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
MorrisOcean
Passaic
Salem
Somerset
Sussex
Union
Warren
0 50 100 150
Fatal crashes by county
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
MorrisOcean
Passaic
Salem
Somerset
Sussex
Union
Warren
0 2000 4000 6000 8000
Injurious crashes by county
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2011 Pedestrian Safety Tracking Report 10
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
OceanPassaic
Salem
Somerset
Sussex
Union
Warren
All crashes controlling for pop density, by county
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
OceanPassaic
Salem
Somerset
Sussex
Union
Warren
All crashes per 100,000 people by county
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
OceanPassaic
Salem
Somerset
Sussex
Union
Warren
Fatal crashes controlling for population density, by county
Atlantic
Bergen
Burlington
Camden
Cape May
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
OceanPassaic
Salem
Somerset
Sussex
Union
Warren
Fatal crashes per 100,000 people by county
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Pedestrian Crashes for 10 Largest New Jersey Municipalities
As a supplement to the county-level analysis, we visualized the crash data for New Jersey's ten largest
municipalities. Each of the maps in Appendix A shows a visual representation of crash data over theentire eight-year study period. Crash locations are aggregated based on proximity to each other, and
larger dots represent clusters of frequent crashes. The maps show a spatial pattern of crashes along major
transportation corridors. These are typically the highest traffic locations with the most retail and service
businesses to attract high volumes of both automobiles and pedestrians. Relatively suburban
municipalities like Toms River and Hamilton clearly show clustering along corridors and at major
intersections of multiple corridors. Denser urban municipalities like Jersey City and Newark show much
more distributed (but high density) crash locations. This reflects the high pedestrian volumes in these
cities.
Another measure of pedestrian safety at the municipal level is the Pedestrian Danger Index (PDI). This
index uses the percent of workers walking to work (as reported to in the American Community Survey)
as a rough estimate of pedestrian exposure within municipalities.1 This measure was developed by the
Surface Transportation Policy Partnership in the 1990s and has been applied by a number of research
groups as a best available practice to estimating pedestrian exposure. We have adapted the data for our
use by adding PDI measures associated with both fatal crashes and total crashes. The data from New
Jerseys ten largest municipalities show a pattern of high pedestrian danger in suburban locations like
Edison, Woodbridge, and Toms River. These three municipalities have a much lower rate of pedestrian
exposure (measured by workers walking to work). Among the other municipalities, Jersey City and
2011 Pedestrian Safety Tracking Report 11
1 PDI is computed by dividing the average annual fatalities (or crashes) by the percent of workers walking to work.
For convenience, the PDI - Crashes measure is divided by 100. PDI - Fatalities and PDI - Crashes are not comparable.
AverageAnnualPedestrianDeathsper
100,000(2003-2010)AverageAnnual
PedestrianCrashesper100,000(2003-2010)
PercentofWorkersWalkingtoWork(ACS2005-2009)
PedestrianDangerIndex-
Fatalities
PedestrianDangerIndex-
Crashes
JerseyCityPaterson
Lakewood
Elizabeth
Newark
Trenton
Edison
Woodbridge
TomsRiverHamilton
1.0 96.9 8.2% 12 12
0.9 90.4 5.9% 16 15
2.2 51.6 9.8% 22 5
1.6 66.5 6.5% 25 10
2.1 100.7 7.5% 28 13
1.9 87.7 5.3% 36 16
2.0 30.4 2.0% 101 15
2.6 31.4 2.5% 104 12
2.5 32.9 1.1% 215 29
1.3 25.6 N/A N/A N/A
Pedestrian Danger Index 10 Largest New Jersey Municipalities
Note: American Community Survey data for Hamilton Township not available.
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Paterson are safest, while Trenton and Newark are less safe. These results show little correlation among
pedestrian deaths and pedestrian exposure among this small sample of cities. Comparison with PDI -
Total Crashes shows some similarities and differences. Toms River is still an outlier when taking into
account total crashes; it seems much more dangerous than the other municipalities listed by both
measures. Toms River has the lowest pedestrian walking rate of all the municipalities listed, so that may
be influencing the results. When taking into account all crashes, suburban Edison and Woodbridge fall
roughly into the same category as the other municipalities listed. Elizabeth and Lakewood both seem
significantly safer than other municipalities when measuring based on total pedestrian crashes. In future
work, we plan to expand this analysis to include all available municipalities in New Jersey.
Conclusions and Implications
The analyses in this report provide some useful information on pedestrian crashes in New Jersey by
focusing on fatalities and injuries from 2003-2010. New Jersey is a state characterized by predominately
urban and suburban land use patterns, along with a ubiquitous network of Interstate highways, tollways,
and state highways. It's relatively small land area also means that it has the highest population density
among all states. The combination of high overall population density and automobile-oriented land use
patterns contributes to a high degree of exposure to unsafe automobile traffic for pedestrians. Although
overall traffic fatalities in New Jersey are modest in comparison to many other states, the state ranks fairly
high in the northeastern region. This should be a concern for all transportation planners and policy
makers in the state.
The analyses in this report provide some key information on pedestrian crashes in the state:
First, far more men become casualties of pedestrian crashes than women. This is presumably
because of exposure since men walk more frequently and take more risks than women (in
darkness and in unsafe conditions).
Second, age is an important indicator. Young people seem to take more risks resulting in higher
injury rates, but older people are more prone to be killed in crashes compared to their respective
shares of the population.
Third, most pedestrian injuries occur in the daytime when pedestrian activity is higher, but
pedestrian fatalities are skewed heavily toward darkness hours. To understand this relationship
more fully, a comprehensive pedestrian study should be conducted.
Fourth, most pedestrian crashes occur on municipal roads, but these also tend to be less fatal.
State highways, county roads, and Interstates have higher proportions of traffic fatalities because
speed kills.
2011 Pedestrian Safety Tracking Report 12
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Fifth, pedestrian crashes follow temporal patterns. More crashes tend to occur in the late Autumn,
with a second spike during the early Summer. Factors contributing to these increases could be
academic cycles and changing climate conditions (including shorter daytime hours), which take
time to adjust to each year.
Sixth, alcohol use continues to be a factor in pedestrian crashes. Nighttime crasheswhere the
results are more often fatalare more often correlated with alcohol involvement than daytime
crashes, a very troubling relationship.
In order to make policy recommendations regarding pedestrian safety issues, cause-and-effect
explanations are important. Identifying the causes of crashes in a scientific manner using the limited data
collected by CAIT in the Plan4Safety database is limited. The Plan4Safety database has no measure for
pedestrian volumes or exposure, so controlling for volumes of pedestrian activity is not possible.
Pedestrian volume counts are costly to collect and are generally not readily available except in very small
geographic samples and for very limited durations. The Plan4Safety data are also devoid of any
information on land uses in the areas where crashes occur. We can only infer characteristics of land use by
looking at the types of roads (state highways, county roads, municipal arterials, etc). In the absence of
adequate information on pedestrians' exposure and micro-area land use characteristics, it is difficult to
identify specific strategies to address pedestrian crashes.
We have begun the process of examining the Plan4Safety data on a spatial scale. We hope to expand this
effort in future updates to this report and other work. We will continue to seek more sources of data to
include alongside the Plan4Safety data in these analyses to help establish new understandings of thepatterns of pedestrian crashes in the State of New Jersey.
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Appendix A Pedestrian Crashes in New Jerseys Ten Largest Municipalities
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2011 Pedestrian Safety Tracking Report
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Pedestrian Vehicle crashes 2003 - 2010Edison
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Edison Number of Crashes
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24
21
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2003 2004 2005 2006 2007 2008 2009 2010
Edison Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
21/31
2011 Pedestrian Safety Tracking Report
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Pedestrian Vehicle crashes 2003 - 2010Elizabeth
8095 83 86 90 85
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2003 2004 2005 2006 2007 2008 2009 2010
Elizabeth Number Crashes
0
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Elizabeth Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
22/31
2011 Pedestrian Safety Tracking Report
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Pedestrian Vehicle crashes 2003 - 2010Hamilton
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Hamilton Number of
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1 10
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2003 2004 2005 2006 2007 2008 2009 2010
Hamilton Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
23/31
2011 Pedestrian Safety Tracking Report
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Pedestrian Vehicle crashes 2003 - 2010Jersey City
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Jersey City Number Crashes
62 2 2 2 1 1
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2003 2004 2005 2006 2007 2008 2009 2010
Jersey City Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
24/31
2011 Pedestrian Safety Tracking Report
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Lakewood Number Crashes
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2003 2004 2005 2006 2007 2008 2009 2010
Lakewood Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
25/31
2011 Pedestrian Safety Tracking Report
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2003 2004 2005 2006 2007 2008 2009 2010
Newark Number Crashes
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0
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2003 2004 2005 2006 2007 2008 2009 2010
Newark Fatalities
-
8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final
26/31
2011 Pedestrian Safety Tracking Report
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Crashes within 150ft radius
!( One crash every two years
!( One crash every year
!(Two crashes a year
!( More than two crashes a year
Pedestrian Vehicle crashes 2003 - 2010Paterson
Paterson Fatalities
0
21
3 3
1 100
2
4
2003 2004 2005 2006 2007 2008 2009 2010
Paterson Number Crashes
167 162131 140 131
84120 122
0
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200
2003 2004 2005 2006 2007 2008 2009 2010
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2011 Pedestrian Safety Tracking Report
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Pedestrian Vehicle crashes 2003 - 2010Toms River
34 33 2642 41
22 20 220
20
40
60
2003 2004 2005 2006 2007 2008 2009 2010
Toms River Number Crashes
0
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1 1
43 3
10
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2003 2004 2005 2006 2007 2008 2009 2010
Toms River Fatalities
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Crashes within 150ft Radius
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!( One crash every year
!(Two crashes a year
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Pedestrian Vehicle crashes 2003 - 2010Trenton
93 100 84 65 79 65 49 61
0
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Trenton Number Crashes
21 1 1 1 1
42
0
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2003 2004 2005 2006 2007 2008 2009 2010
Trenton Fatalities
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2011 Pedestrian Safety Tracking Report
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Crashes within 150ft Radius
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Pedestrian Vehicle crashes 2003 - 2010Woodbridge
3443
26 38 31 22 35 210
20
40
60
2003 2004 2005 2006 2007 2008 2009 2010
Woodbridge Number Crashes
3 4 25
02
410
5
10
2003 2004 2005 2006 2007 2008 2009 2010
Woodbridge Fatalities
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Rutgers,TheStateUniversityofNewJersey