2011 New Jersey Pedestrian Safety Tracking Report Final

8/3/2019 2011 New Jersey Pedestrian Safety Tracking Report Final

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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



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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.



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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


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).


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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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.


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


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%


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.


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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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


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.



18/31

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



20/31


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2003 2004 2005 2006 2007 2008 2009 2010

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0 1 20.5

Miles

Crashes within 150ft radius

!(

One crash every two years!( One crash every year



Pedestrian Vehicle crashes 2003 - 2010Elizabeth

8095 83 86 90 85

69 77

0

50

100

2003 2004 2005 2006 2007 2008 2009 2010

Elizabeth Number Crashes

0

4

01

24

32

0

5

2003 2004 2005 2006 2007 2008 2009 2010

Elizabeth Fatalities


22/31


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COUNTY

616

US

206

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US2

06

0 2 41 Miles

Crashes within 150ft Radius





Pedestrian Vehicle crashes 2003 - 2010Hamilton

27 16 2635 25 15 16 210

50

2003 2004 2005 2006 2007 2008 2009 2010

Hamilton Number of

Crashes

1 10

3

1 1 1 10

2

4

2003 2004 2005 2006 2007 2008 2009 2010

Hamilton Fatalities


23/31


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HUDSONCOUNTY603

HUDSONCOUNTY66

8HUDSONCOUNTY617

0 1 20.5Miles




!(Two crashes a year


Pedestrian Vehicle crashes 2003 - 2010Jersey City

332 313251 220 255 197 239

1130

200

400

2003 2004 2005 2006 2007 2008 2009 2010

Jersey City Number Crashes

62 2 2 2 1 1

40

5

10

2003 2004 2005 2006 2007 2008 2009 2010

Jersey City Fatalities


24/31


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OUNTY6

28

OCEANCOUNTY31

OCEANCOUNTY30

0 2 41Miles






Pedestrian Vehicle crashes 2003 - 2010Lakewood

48 30 25 44 36 32 34

134

0

50

100

150

2003 2004 2005 2006 2007 2008 2009 2010

Lakewood Number Crashes

31 0

51 1

3 20

5

10

2003 2004 2005 2006 2007 2008 2009 2010

Lakewood Fatalities


25/31


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ROUTE5

08

ROUTE510

0 1 20.5

Miles


!(

One crash every two years!( One crash every year



Pedestrian Vehicle crashes 2003 - 2010Newark

383 350 331215 139

270 263 287

0

200

400

600

2003 2004 2005 2006 2007 2008 2009 2010

Newark Number Crashes

4 5 4 59

6 7 7

0

5

10

2003 2004 2005 2006 2007 2008 2009 2010

Newark Fatalities


26/31


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I-80 NJ20

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US46

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ROUTE507

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I-80

SECOND

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NJ20

SECONDARY

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NTY649

NJ19SECONDARY

NJ2

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SECO

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PASSAICCOUNTY647

PASSAIC

COUNTY633

PASSAICCOUNTY648

NJ4

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TY628

BERG

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76

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AIC

COUNT

Y657

PASSAIC

COUNTY

662

BERG

ENCO

UNTY

78

0 1 20.5 Miles





!( 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

50

100

150

200

2003 2004 2005 2006 2007 2008 2009 2010


27/31


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NJ37

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5 49

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NJ37 SECONDARY

NJ166

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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

4

1 1

43 3

10

5

2003 2004 2005 2006 2007 2008 2009 2010

Toms River Fatalities


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Pedestrian Vehicle crashes 2003 - 2010Trenton

93 100 84 65 79 65 49 61

0

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2003 2004 2005 2006 2007 2008 2009 2010

Trenton Number Crashes

21 1 1 1 1

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0

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2003 2004 2005 2006 2007 2008 2009 2010

Trenton Fatalities


29/31


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0 1 20.5Miles






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


30/31



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Rutgers,TheStateUniversityofNewJersey

Documents

2011 New Jersey Pedestrian Safety Tracking Report Final