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TRAFFIC CRASH FACTS FOR CHAMPAIGN-URBANA
SELECTED CRASH INTERSECTION LOCATIONS 2005-2009
June 2011
Champaign Urbana Urbanized Area Transportation Study A program of the Champaign County Regional Planning Commission
1
TABLE OF CONTENTS LIST OF TABLES ................................................................................................................... 2
LIST OF FIGURES ................................................................................................................. 3
Executive Summary ............................................................................................................... 4
1.0 Introduction………………………………………………………………………………………..6
2.0 Crash Data .................................................................................................................. 8
2.1 Data Source ................................................................................................................ 8 2.2 Data Limitations and Errors ........................................................................................... 8 2.3 Data Reduction ............................................................................................................ 9
3.0 Vehicle Crash Analysis Methodology .............................................................................. 10
3.1 Intersection Type Classification .................................................................................... 10 3.2 Volume Based Classification ....................................................................................... 10 3.3 Average Crash Frequency ........................................................................................... 10 3.4 Average Crash Rate ................................................................................................... 11 3.5 Crash Severity Method ................................................................................................ 12
3.5.1 Crash Severity ..................................................................................................... 12 3.5.2 Equivalent Property-Damage-Only (EPDO) Method ............................................... 13
3.6 Critical Intersection Prioritization .................................................................................. 14
4.0 Traffic Crash Trends and Facts for Champaign-Urbana .................................................. 15
4.1 Traffic Crash Fatalities ................................................................................................ 18 4.2 Traffic Crash Injuries ................................................................................................... 21 4.3 Corridor Crash Analysis………………………………………………………………………24 4.4 Additional Traffic Crash Facts for 2005-2009 .............................................................. 24
4.4.1 Day of the Week Analysis ..................................................................................... 28 4.4.2 Time of the Day Analysis ...................................................................................... 29 4.4.3 Collision Types.................................................................................................... 30 4.4.4 Weather Conditions……………………………………………………………………..31 4.4.5 Roadway Surface Condition ................................................................................. 32 4.4.6 Roadway Lighting Condition ................................................................................ 33 4.4.7 Driver Condition ................................................................................................. 34 4.4.8 Driver Age and Gender ....................................................................................... 35 4.4.9 Traffic Control .................................................................................................... 37
5.0 Pedestrian and Bicycle Crashes .................................................................................... 38
5.1 Pedestrian Crashes ..................................................................................................... 38 5.1.1 Pedestrian Age and Gender ................................................................................. 38
5.2 Bicycle Crashes .......................................................................................................... 42 5.2.1 Bicyclist Age and Gender ..................................................................................... 42
5.3 Pedestrian & Bicycle Crashes in the University District .................................................... 45
6.0 Selected Critical Intersection Locations (2005-2009) ........................................................ 48
6.1 Intersection Locations with Fatal Crashes .................................................................. 51
7.0 Conclusions ............................................................................................................... 53
REFERENCES ..................................................................................................................... 55
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LIST OF TABLES Table 1: Volume Based Classification .................................................................................... 10 Table 2: Crash Frequency Criteria ......................................................................................... 11 Table 3: Crash Rate Criteria ................................................................................................. 11 Table 4: EPDO Criteria ........................................................................................................ 13 Table 5: Priority Levels .......................................................................................................... 14 Table 6: Crash Data Summary (1985-2009) .......................................................................... 15 Table 7: VMT and Total Crash Rate for Champaign-Urbana ................................................... 17 Table 8: Crash Injury Levels (2005-2009) .............................................................................. 21 Table 9: Crashes along Major Corridors in Champaign-Urbana (2005-2009)…………………..24 Table 10: Severe Crashes along Major Corridors by Year…………….………………………...…25 Table 11: Fatal Crashes along Major Corridors by Year .......................................................... 25 Table 12: Different Vehicle Collision Types ............................................................................. 30 Table 13: Traffic Crashes in Different Weather Conditions ....................................................... 31 Table 14: Crashes by Roadway Lighting Condition ................................................................. 33 Table 15: Driver Condition Information ................................................................................. 34 Table 16: Driver and Passenger Injuries in Champaign-Urbana ............................................... 34 Table 17: Crashes Based on Traffic Control ........................................................................... 37 Table 18: Pedestrian Crashes in Champaign-Urbana ............................................................. 38 Table 19: Bicycle Crashes in Champaign-Urbana................................................................... 42 Table 20: Pedestrian and Bicycle Crashes in the University District ........................................... 48 Table 21: Critical Signalized Intersections (2005-2009) .......................................................... 48 Table 22: Critical Unsignalized Intersections (2005-2009) ...................................................... 49
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LIST OF FIGURES Figure 1: Different Steps Followed in the Study ......................................................................... 7 Figure 2: Total Crashes in Champaign-Urbana ...................................................................... 16 Figure 3: Total Injury Crashes in Champaign-Urbana ............................................................. 16 Figure 4: Total Crashes per 100 Million VMT ......................................................................... 17 Figure 5: Traffic Fatalities in Champaign-Urbana ................................................................... 18 Figure 6: Traffic Fatalities per 100 Million VMT ...................................................................... 19 Figure 7: Fatal Crash Locations in Champaign-Urbana .......................................................... 20 Figure 8: Crash Injury Levels in Champaign-Urbana ............................................................... 21 Figure 9: Severe Injury per 100 MVMT in Champaign-Urbana ................................................ 22 Figure 10: Type “A” Injury Crash Locations in Champaign-Urbana .......................................... 23 Figure 11: Fatal and Severe Crashes along Major Corridors in Chamapign-Urbana ................. 26 Figure 12: Pedestrian and Bicycle Crashes along Major Corridors in Champaign-Urbana ......... 27 Figure 13: Crashes by Day of the Week ................................................................................. 28 Figure 14: Time of the Day Analysis ....................................................................................... 28 Figure 15: Percent Distribution of Crashes by Collision Types .................................................. 30 Figure 16: Percent Distribution of Crashes by Weather Condition ............................................ 31 Figure 17: Crashes by Road Surface Condition ...................................................................... 32 Figure 18: Percent Distribution of Crashes by Roadway Lighting Conditions .............................. 33 Figure 19: Percent Distribution of Impaired/Distracted Driving Crashes .................................... 34 Figure 20: Age Distribution of Motor Vehicle Drivers involved in Traffic Crash ........................... 35 Figure 21: Total and Severe Injuries for Different Age Groups ................................................. 35 Figure 22: Crash Frequency Comparision between Male and Female Drivers ........................... 35 Figure 23: Percent Distribution of Crashes based on Traffic Control ......................................... 35 Figure 24: Pedestrian Age Distribution ................................................................................... 39 Figure 25: Pedestrian Age and Gender Distribution ................................................................ 39 Figure 26: Pedestrian Crash Locations in Champaign-Urbana ................................................. 40 Figure 27: Bicyclist Age Distribution ....................................................................................... 43 Figure 28: Bicyclist Age and Gender Distribution .................................................................... 43 Figure 29: Bicyclist Crash Locations in Champaign-Urbana ..................................................... 43 Figure 30: Bicycle and Pedestrian Crash Locations in the University District ............................... 46 Figure 31: Bicycle and Pedestrian Crash Severity in the University District ................................. 47 Figure 32: Selected Critical Intersection Locations (2005-2009) .............................................. 50 Figure 33: Fatality Intersection Locations and Selected Critical Intersection Locations (2005-2009)
................................................................................................................................... 52
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Executive Summary This report summarizes the traffic crash facts in the Champaign-Urbana area based on traffic crash data for 2005-2009. According to the Unified Technical Work Program (UTWP) of the Champaign Urbana Urbanized Area Transportation Study (CUUATS), a study has to be completed every two years to identify critical crash intersection locations in the Champaign-Urbana area. Identification of these intersection locations is a vital component of safety improvements. The intersections in Champaign-Urbana were analyzed utilizing methods such as crash frequency, crash rate, and crash severity. The methodology used to identify the Selected Crash Intersection Locations (SCIL) is presented in the report. Additional data analyses were performed to highlight the trend in crashes over the 5-year period, from 2005 to 2009. The data was analyzed based on the time & day of the crash, crash conditions, and the driver characteristics. The crashes along the key east-west and north-south corridors in Champaign-Urbana were also summarized. Important findings of the report include:
The number of crashes in the study area showed a decreasing trend from 2005 to 2009. The crashes in 2009 reduced 22% from 2008 and 31% from 2005.
The vehicle miles traveled in Champaign-Urbana remained relatively constant, while the crashes per 100 million vehicles miles traveled (MVMT) decreased from 385 in 2005 to 256 in 2009. The crash rates per year in the study area remained consistently lower than the statewide crash rates (per 100 MVMT).
The total fatalities increased from 2005 to 2008 and decreased from 2008 to
2009. The traffic fatality rates from 2005 to 2009 in Champaign-Urbana were less than 1.0 fatality per 100 million VMT. The study area fatality rates remained lower than the statewide fatality rates and the target rates proposed by IDOT’s Highway Safety Performance Plan (HSPP), for each study year.
The total injuries steadily decreased from 2005 to 2008. There was a marginal increase in the number of total injuries in 2009 from 2008. The traffic crash injuries reduced by 19% from 2005 to 2009. The severe injury crashes (Type A) increased from 134 in 2008 to 178 in 2009. About 20% of the crashes every year were severe injury crashes.
The severe injury rates (per 100 million VMT) for Champaign-Urbana in 2005, 2006, and 2007 were more than the statewide rates. The severe injury rates in 2008 and 2009 were less than the statewide severe injury rates and significantly below the proposed statewide HSPP goals.
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The University Avenue and Prospect Avenue corridors had about 1,000 crashes over the five year period which is the highest among the major corridors in the Champaign-Urbana area. The maximum number of severe crashes along the key corridors occurred in 2009.
Additional data analysis showed the following trend in crashes from 2005 to 2009:
o Majority of the crashes occurred between 12:00 PM and 6:00 PM. o Rear-end, turning, and angle crashes are the predominant crash types
in Champaign-Urbana. o Majority of the crashes were under clear weather conditions (80%),
during daylight (70%) and on dry roadway pavement surface (71%). o Majority of the impaired/distracted driving crashes were alcohol related
(71%).
Drivers between the ages of 15-29 were involved in 46% of the total crashes reported in Champaign-Urbana. The highest number of severe injuries and fatalities were reported in crashes involving drivers aged between 20 and 24.
About 43% of the crashes were at intersections controlled by a traffic signal or stop sign/flasher.
Eleven pedestrians and one bicyclist were killed from 2005 to 2009 in traffic crashes. Pedestrian and bicyclist deaths account for about 40% of the total traffic crash related fatalities in Champaign-Urbana over the five year analysis period (2005-2009).
Almost all the pedestrian and bicycle crashes resulted in an injury. Also, a significant number of pedestrians were severely injured (26% of injured pedestrians had a Type A injury).
A significant number of pedestrians (51%) and bicyclists (58%) involved in
traffic crashes between 2005 and 2009 were under 25 years of age.
Twelve signalized and twenty-three unsignalized intersections were identified as critical intersections. Different priority levels were assigned to the critical intersections based on the crash frequency, crash rate, and crash severity values.
Seven fatal crashes occurred at intersections in Champaign-Urbana from 2005 to 2009.
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1.0 Introduction Traffic crashes are one of the leading causes of death in the United States. In 2009, 33,808 lives were lost in traffic crashes in the U.S.1 Illinois recorded 911 fatalities and 89,090 injuries in 20092. Roadway intersections have been the predominant locations of traffic crash occurrences in urban areas. More than 50 percent of all traffic crashes in urban areas and more than 30 percent of crashes in rural areas nationally are intersection related3. Intersections are locations where two or more roadways join or cross one another. Various maneuvers (e.g., crossing and turning maneuvers) that occur at intersections create opportunities for vehicle-vehicle, vehicle-pedestrian, and vehicle-bicycle conflicts, which may result in traffic crashes. The Federal Highway Administration (FHWA) notes that 20.8% of the total fatalities (7,043) nationwide in the year 2009 were intersection related4. About 59% of the injury crashes in the United States in the year 2009 were intersection related5. Approximately 26% of the fatal crashes in Illinois in 2009 occurred at intersections2. The FHWA has identified intersection safety as one of four high-risk areas. The American Association of State Highway and Transportation Officials (AASHTO) added improving the design and operation of highway intersections as a key emphasis area in its 2005 Strategic Highway Safety Plan (SHSP). According to the Unified Technical Work Program (UTWP) of the Champaign Urbana Urbanized Area Transportation Study (CUUATS), a study has to be completed every two years to identify critical crash intersection locations in the Champaign-Urbana area. Identification of these intersection locations is a vital component of safety improvements. This report summarizes the Selected Crash Intersection Locations (SCIL) for 2005 to 2009. Figure 1 details the different steps followed in this study. The Local Accident Reference System (LARS) data was obtained from the Illinois Department of Transportation (IDOT). CUUATS staff decoded the data and identified the Selected Crash Intersection Locations (SCIL) following CUUATS’ crash data analysis methodology. The report presents the summary of crashes in the Champaign-Urbana area and compares it against the various goals established by IDOT to reduce fatalities and injuries on the Illinois roadways. The report also identifies the measures of effectiveness addressed in the CUUATS 2035 Long Range Transportation Plan (LRTP) regarding transportation safety. The measures of effectiveness include the total crashes per 100 Million Vehicle Miles Travelled (MVMT), total fatalities per 100M VMT, total severe injuries per 100M VMT, total pedestrian crashes, and total bicycle crashes. This report quantifies and helps achieve the LRTP goals by identifying the problem crash locations and crash trends in the region. The LRTP transportation safety goals include reducing the total number of crashes in Champaign-Urbana by 5% between 2009 and 2014; reducing the total number of fatalities and severe injuries in Champaign-Urbana by 25% between 2009 and 2014; and reducing the total number of crashes involving bicyclists and pedestrians in Champaign-Urbana by 15% by 2014.
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Figure 1: Different Steps Followed in the Study The summary includes all crashes in the region (including intersection and mid-block crashes). The pedestrian and bicycle crashes in the Champaign-Urbana area are also analyzed.
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2.0 Crash Data Crash data is observed and collected in the field. A reported crash is recorded in the field by law enforcement agencies. Any error in observation affects the quality of the data. Furthermore, there is a chance of making errors while coding the data. Crash data has to be carefully studied to identify the errors. The errors have to be corrected and any flawed data has to be excluded from further analysis. Better quality and a higher level of information from the crash data will help engineers better understand the crash patterns and identify the cause(s) for the crashes. This understanding is very important in order to come up with recommendations for improving the safety of the intersections. It should be noted that the law regarding the reporting threshold for property damage crashes has changed effective January 1, 2009. If all the drivers involved in the crash are insured, the amount of damage to the property that must be reported increased from $500 to $1500. The threshold remains at $500 if any of the drivers involved in the crash are not insured2.
2.1 Data Source CUUATS used the crash data available from the Local Accident Reference System (LARS) produced by the Illinois Department of Transportation (IDOT). The LARS database is compiled every year from the local and state police crash records submitted to the IDOT Division of Traffic Safety. The LARS data is coded numerically based on standard coding rules and is distributed in an electronic database. The data includes the street code, day, time, number of persons injured or killed, road feature, road surface condition, light condition, type of collision, crash severity information, direction, maneuvers and type of vehicle for up to four vehicles involved in a crash.
2.2 Data Limitations and Errors The data used in this study had the following limitations:
Data does not include unreported crashes. Minor property damage (below the qualifying value), lack of willingness to report, crashes on private properties, etc., are major causes of unreported crashes.
Some crash records were incomplete.
Also, a few crash records in the LARS list had errors in coding. Coding errors make it difficult to identify the location or the type of collision and may lead to contradictions between the different elements of the same crash record.
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2.3 Data Reduction The numerically coded LARS data was decoded and then checked for any errors (e.g., wrong coding). Erroneous and/or incomplete data was removed. The LARS data includes crashes from all kinds of road features (including mid-block, intersections, freeways, etc.). From this mixture of data, the intersection crashes were extracted. The data was grouped into different coverage areas (Champaign and Urbana) so that individual municipalities could track what occurs in their jurisdictions. The crashes were grouped again by intersection. From this grouped data, the number of crashes at each intersection was obtained and analyzed to identify the critical intersections.
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3.0 Vehicle Crash Analysis Methodology This study utilized specific methods: crash frequency, crash rate, and crash severity to identify critical intersections. The final list of SCILs was produced using an enhanced combination of the above methods approved by the Champaign Urbana Traffic Engineering Committee (CUTEC). The CUTEC criteria used for identifying Critical Intersection Locations include the following:
Intersection Type Classification Volume Based Classification Average Crash Frequency Average Crash Rate Average Crash Severity
3.1 Intersection Type Classification All crash intersections should be classified into two groups (signalized and unsignalized) based on existing traffic control types.
3.2 Volume Based Classification Each intersection should be classified based on its total entering volume per day. Roadway ADT information is generally obtained from IDOT traffic maps and an in-house traffic count database. Table 1 shows intersection classifications based on daily entering traffic.
Table 1: Volume Based Classification
3.3 Average Crash Frequency For this criterion, the average crash frequency and its standard deviation for each volume class of signalized and unsignalized intersections are calculated. Crash data over a period of five years or more are analyzed for determining the average crash frequency of each intersection.
Intersection Class
Daily Entering Traffic
A ≥20,000 B 10,000-19,999 C 5,000-9,999 D 2,000-4,999 E ≤1,999
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An intersection’s crash frequency should be termed as “very high”, “high”, or “above mean” as per the criteria shown in Table 2.
Table 2: Crash Frequency Criteria
Intersection Crash Frequency
Very High High Above Mean
Signalized ≥ Fsavi + 2Ssfi ≥ Fsavi + Ssfi > Fsavi
Unsignalized ≥ Fuavi + 2Sufi ≥ Fuavi + Sufi > Fuavi
Where; Fsavi = Average Crash Frequency of all Signalized Intersections in Volume Class i. Ssfi = Standard Deviation of Crash Frequencies of all Signalized Intersections in
Volume Class i. Fuavi = Average Crash Frequency of all Unsignalized Intersections in Volume Class i. Sufi = Standard Deviation of Crash Frequencies of all Unsignalized Intersections in
Volume Class i.
3.4 Average Crash Rate The average crash rate method is applied to each volume class of signalized and unsignalized intersections. Crash data over a period of five years or more are analyzed for determining the average crash rate of each intersection. The standard deviation of average crash rates for each volume class of signalized and unsignalized intersections is also calculated. An intersection’s crash rate should be termed as “very high”, “high”, or “above mean” as per the criteria shown in Table 3.
Table 3: Crash Rate Criteria
Intersection Crash Rate
Very High High Above Mean
Signalized ≥ Rsavi + 2Ssri ≥ Rsavi + Ssri > Rsavi
Unsignalized ≥ Ruavi + 2Suri ≥ Ruavi + Suri > Ruavi
Where; Rsavi = Average Crash Rate of all Signalized Intersections in Volume Class i. Ssri = Standard Deviation of Crash Rates of all Signalized Intersections in
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Volume Class i. Ruavi = Average Crash Rate of all Unsignalized Intersections in Volume Class i. Suri =Standard Deviation of Crash Rates of all Unsignalized Intersections in Volume Class i.
3.5 Crash Severity Method In this method, crashes or injuries judged as more severe are given more relative importance/weight than those judged as less severe.
3.5.1 Crash Severity The National Safety Council (NSC) and the American National Standards Institute (ANSI) provided the following standard definitions of severity of crashes and injuries7: Fatal: One or more deaths (commonly signified by K). A-level Injury: Incapacitating injury preventing victim from functioning normally (e.g., paralysis, broken/distorted limbs, etc.). B-level Injury: Non-incapacitating but visible injury (e.g., abrasions, bruising, swelling, limping, etc.). C-level Injury: Probable but not visible injury (e.g., stiff neck, muscle pain). PDO: Property-damage only. IDOT also defines the severity of crashes and injuries in a similar way. IDOT’s definitions of crash severities and injuries are the following: Fatal Crash: A fatal crash is a motor vehicle crash (single or multiple) that results in the death of one or more persons. Injury Crash: Any motor vehicle crash that results in one or more non-fatal injuries.
A-Injury (Incapacitating Injury): Any injury, other than a fatal injury, which prevents the injured person from walking, driving, or normally continuing the activities he/she was capable of performing before the injury occurred. Type “A” crashes includes severe lacerations, broken limbs, skull or chest injuries, and abdominal injuries. B-Injury (Non-incapacitating Injury): Any injury other than a fatal or incapacitating injury, which is evident to observers at the scene of the crash. Includes lump on head, abrasions, bruises, minor lacerations.
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C-Injury (Possible Injury): Any injury reported or claimed which is not either of the above injuries. It includes momentary unconsciousness, claims of injuries not evident, limping, complaint of pain, nausea, and hysteria.
PDO: Property-damage only crash (property damage in excess of $1500 for crashes insured drivers and $500 for crashes involving un-insured driver(s)).
3.5.2 Equivalent Property-Damage-Only (EPDO) Method
In this method, weights of fatal and injury crashes are determined against a baseline of property damage only crashes. Each of the injury levels (as described above) is given a specific weight that is compared against property-damage-only crashes, which is given a weight of 1. IDOT’s EPDO calculation formula8 is as follows: (50)*(# of FA) + 50*(# of AA) + (5)*(# of BA) + (2)*(# of CA) + (# of PDO) (3-1) Total Crashes Where, FA=Fatal crashes AA=Crash where most severe injury is an A injury BA=Crash where most severe injury is a B injury CA=Crash where most severe injury is a C injury PDO=Property Damage Only Crash Equation 3-1 is used to calculate EPDO values of crash intersections of each volume class for signalized and unsignalized intersections. Crash data over a period of five years or more should be analyzed for determining the EPDO of each intersection. An intersection’s EPDO should be termed as “high severity” or “moderate severity” as per the criteria shown in Table 4.
Table 4: EPDO Criteria
Intersection Crash Severity
High Severity Moderate Severity
Signalized ≥ EPDOsavi + Ssei ≥ EPDOsavi
Unsignalized ≥ EPDOuavi + Suei ≥ EPDOuavi
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Where; EPDOsavi = Average EPDO of all Signalized Intersections in Volume Class i. Ssei = Standard Deviation of EPDO values of all Signalized Intersections in Volume Class i. EPDOuavi = Average EPDO of all Unsignalized Intersections in Volume Class i. Suei = Standard Deviation of EPDO values of all Unsignalized Intersections in Volume Class i. IDOT used the EDPO calculation formula to identify the five percent critical highway locations in Illinois for the 2006 FHWA Highway Safety Improvement Plan (HSIP) – Five Percent Report10. The crash weighing scheme used by IDOT to calculate the equivalent crash severity for the HSIP-Five Percent Report was changed in 200811. As per the FHWA requirement for the HSIP report, the analysis focuses only on the most severe crashes. The recommended weighting structure is 25 times a fatal crash, 10 times an A-type injury crash, and equivalent to a B-type injury crash. The IDOT EPDO calculation formula is used to identify the critical locations in Champaign-Urbana which includes the C-injury and PDO crashes in the analysis.
3.6 Critical Intersection Prioritization All the SCIL intersections identified through the above mentioned procedures are prioritized according to their crash frequency, crash rate, and crash severity levels. Table 5 shows the priority levels of SCIL intersections.
Table 5: Priority Levels
Priority Level Crash Frequency Crash Rate Crash Severity
Priority 1 Very High Very High High Severity
Priority 2 High Very High High Severity
Priority 3 High High Moderate Severity
Priority 4 Above Mean Above Mean N/A
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4.0 Traffic Crash Trends and Facts for Champaign-Urbana Table 6 shows the crash data summary in the Champaign-Urbana area from 1985 to 2009. The information summarized in Table 6 includes all the crashes in Champaign-Urbana, not just at intersections.
Table 6: Crash Data Summary (1985-2009)
There were 2,264 reported crashes in Champaign and Urbana in 2009. This reflects a 21.5% decrease in the total number of crashes from the previous year (2008) and a 31.3% decrease change from 2005. The sudden decrease in the crashes from the year 2008 to the year 2009 is partly due to the change in the Illinois Department of Transportation (IDOT) crash reporting threshold, effective January 1, 2009. Figure 2
1985-2009
Year
Total Crashes Persons Injured
Average Injuries
per Crash
Fatalities
Champaign Urbana Total Champaign Urbana Total Champaign Urbana Total
1985 2,429 1,058 3,487 957 415 1,372 0.39 3 3 6
1986 2,543 1,027 3,570 1023 427 1,450 0.41 4 2 6
1987 2,589 1,011 3,600 1186 434 1,620 0.45 8 3 11
1988 2,375 924 3,299 973 342 1,315 0.4 1 2 3
1989 2,232 943 3,175 869 321 1,190 0.37 3 0 3
1990 2,410 926 3,336 915 344 1,259 0.38 3 4 7
1991 2,218 866 3,084 788 299 1,087 0.35 2 4 6
1992 2,264 802 3,066 973 276 1,249 0.41 1 1 2
1993 2,295 881 3,176 938 368 1,306 0.41 0 0 0
1994 2,363 893 3,256 1045 347 1,392 0.43 0 0 0
1995 2,482 780 3,262 995 285 1,280 0.39 2 0 2
1996 2,579 910 3,489 907 323 1,230 0.35 3 2 5
1997 2,154 892 3,046 802 265 1,067 0.35 0 0 0
1998 2,292 790 3,082 760 291 1,051 0.34 5 0 5
1999 2,250 817 3,067 802 224 1,026 0.33 1 0 1
2000 2,075 764 2,839 644 212 856 0.3 3 1 4
2001 2,032 767 2,799 605 170 775 0.28 1 1 2
2002 2,135 868 3,003 635 185 820 0.27 3 2 5
2003 2,241 873 3,114 621 214 835 0.27 3 0 3
2004 2,345 1,009 3,354 685 232 917 0.27 5 3 8
2005 2,345 950 3,295 651 221 872 0.26 4 1 5
2006 2,167 795 2,962 582 230 812 0.27 5 1 6
2007 2,192 862 3,054 562 201 763 0.25 4 3 7 2008 2,074 809 2,883 532 166 698 0.24 5 3 8
2009 1,626 638 2,264 509 201 710 0.31 0 4 4
Total 56,707 21,855 78,514 19,959 6,993 26,939 - 69 40 109
Average/yr 2,268 874 3,141 798 280 1,078 0.34 3 2 4
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and Figure 3 show the trend of the total crashes and total injury crashes in the Champaign-Urbana area from 2005 to 2009, respectively.
0
500
1,000
1,500
2,000
2,500
3,000
3,500
2005 2006 2007 2008 2009
Total Champaign Urbana
Figure 2: Total Crashes in Champaign-Urbana
2005 2006 2007 2008 2009
Champaign 651 582 562 532 509
Urbana 221 230 201 166 201
Total 872 812 763 698 710
0
100
200
300
400
500
600
700
800
900
1000
To
tal
Inju
ries
Figure 3: Total Injury Crashes in Champaign-Urbana
Figure 3 shows that the total number of injuries per year has been decreasing from 2005 to 2008. Even though the number of injuries decreased in the City of
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Champaign in the year 2009, the rise in the number of injuries in the City of Urbana contributed to the marginal overall increase (1.7%) of total injuries in Champaign-Urbana from year 2008 to 2009. Table 7 shows Vehicle-Miles of Travel (VMT) information for the Champaign-Urbana area. The VMT data was obtained from the “Illinois Travel Statistics”6 published annually by IDOT. Table 7 and Figure 4 show that the crashes per million VMT have been decreasing in Champaign-Urbana since the year 2005 and have also been consistently lower than the statewide crash rate (per 100 MVMT).
Table 7: VMT and Total Crash Rate in Champaign-Urbana
Champaign-Urbana
Ill inois
2005 2,345 855.9 385.0 390.82006 2,340 854.1 346.8 382.62007 2,335 852.3 358.3 393.62008 2,368 864.3 333.4 386.52009 2,426 885.5 255.7 276.2
YearDaily VMT
(Thousands) Yearly VMT (Mill ions)
Crashes/100MVMT
0
50
100
150
200
250
300
350
400
450
2005 2006 2007 2008 2009
Cra
hes
/100
MV
MT
Champaign-Urbana Illinois
Figure 4: Total Crashes per 100 Million VMT
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4.1 Traffic Crash Fatalities Figure 5 shows the traffic crash fatalities in Champaign and Urbana from 2005 to 2009. The graph shows that the total fatalities increased from the year 2005 to 2008 and decreased in the year 2009. No fatalities were reported in Champaign in the year 2009. Two fatal crashes in the year 2008 which occurred at the edge of the city municipal boundaries were not included in the LARS data as Champaign-Urbana crashes. The two crashes (on I-57, south of I-74 and on IL 130, south of Washington Street) were entered as Champaign County unincorporated area crashes in the LARS database. These crashes are included in the crash analyses performed to prepare this report. Apart from the crashes recorded within the City of Urbana and City of Champaign municipal boundaries, four additional fatal crashes were reported in the Champaign-Urbana-Savoy-Bondville urbanized area, two of which were in the Village of Savoy.
0
1
2
3
4
5
6
7
8
9
2005 2006 2007 2008 2009
Champaign Urbana Total
Figure 5: Traffic Fatalities in Champaign-Urbana
Figure 6 shows fatalities per 100 million VMT from 2005 to 2009 in Champaign-Urbana and in the state of Illinois. The graph also presents the statewide goal for
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fatalities per million VMT proposed by IDOT’s Division of Traffic Safety in the Highway Safety Performance Plan (HSPP).
0
0.2
0.4
0.6
0.8
1
1.2
1.4
2005 2006 2007 2008 2009
Fat
alit
ies/
100M
VM
T
Champaign-Urbana Illinois HSPP Target
Figure 6: Traffic Fatalities per 100 Million VMT As shown in Figure 6, fatalities per 100 million VMT in Champaign-Urbana were well below the state of Illinois rates. The Illinois Highway Safety Performance Plan (HSPP) for FY 20099 proposed a goal of reducing the statewide fatality rate (per 100 million VMT) from 1.16 in year 2007 to 1.04 by year 2008 and 1.00 by December 31, 2009. The number of fatalities per 100 million VMT in the year 2009 has decreased since 2008 by 34%, while the annual VMT increased by 2.4%. The Illinois Highway Safety Performance Plan (HSPP) for FY 201110 set up a new goal to reduce the statewide traffic fatality rate per 100 million VMT to 0.76 by December 31, 2011. Traffic fatality rates for 2005 to 2009 in Champaign-Urbana were, in fact, less than 1.0 fatality per 100 million VMT. Figure 7 shows the fatal crash locations in Champaign-Urbana from 2005 to 2009.
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Figure 7: Fatal Crash Locations in Champaign-Urbana
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4.2 Traffic Crash Injuries The traffic crash injuries in Champaign-Urbana are a major concern. Table 8 provides the number of different levels of crash injury in Champaign-Urbana from 2005 through 2009. The IDOT’s Division of Traffic Safety categorizes injury severity levels as: “A” (most severe), “B” (moderate severity) and “C” (least severe).
Table 8: Crash Injury Levels (2005-2009)
2005 2006 2007 2008 2009
A Injury 157 158 143 134 178
B Injury 367 366 352 311 277
C Injury 348 288 268 253 255
Total 872 812 763 698 710
Injury Type
Year
Table 8 shows that the number of injuries has decreased 19% from 872 in the year 2005 to 710 in the year 2009. The severe injuries in Champaign-Urbana have increased from 157 to 178 over the five-year time period. Even though the total number of crashes decreased from the year 2008 to 2009, the “A” injuries or the severe injuries increased from 134 to 178. Figure 8 shows percentages of traffic crash injury severity levels in Champaign-Urbana from 2005 through 2009 with “A” being the most severe and “C” being the least severe injury. The percent split of the three crash injury levels was observed to be similar for each analysis year.
20%
43%
37%
A Injury B Injury C Injury
Figure 8: Crash Injury Levels in Champaign-Urbana
22
Figure 9 shows severe injury rates per 100 million VMT in Champaign-Urbana for 2005 to 2009. The severe injury rates are compared to the actual statewide severe injury rates and the statewide goal established by IDOT’s Division of Traffic Safety.
0
2
4
6
8
10
12
14
16
18
20
2005 2006 2007 2008 2009
Severe Injuries/100MVMT
Champaign‐Urbana Illinois HSPP Target
Figure 9: Severe Injury per 100 MVMT in Champaign-Urbana The IDOT’s HSPP goal for Calendar Year (CY) 2003-2009 was to reduce statewide severe injury rate (per 100 million VMT) from 16.70 in year 2006 to 15.95 by December 31, 20096. As shown in Figure 9, severe injury rates (per 100 million VMT) for Champaign-Urbana in 2005, 2006 and 2007 were higher than the statewide rate. The severe injury rates for the years 2008 and 2009 were lower than the observed statewide rates and the projected targets. Type “A” injury (severe) crash locations in Champaign-Urbana from 2005 to 2009 are shown in Figure 10.
23
Figure 10: Type “A” Injury Crash Locations in Champaign-Urbana
24
4.3 Corridor Crash Analysis Identifying and analyzing the crashes along the key corridors in the region is important to help increase corridor safety and promote efficient traffic flow. The traffic crashes along the seven major east-west and north-south corridors in Champaign-Urbana are summarized. Table 9 provides the total number of crashes, injuries, fatalities, and the number of injury crashes along the major corridors. Table 10 and Table 11 show the change in the number of Type “A” severe crashes and fatal crashes on the corridors over the five year study period. Figure 11 shows the fatal crash locations and severe crash locations along the corridors. Figure 12 presents the bicycle and pedestrian crash locations along the study corridors.
Table 9: Crashes along Major Corridors in Champaign-Urbana (2005-2009)
Bradley Avenue 827 279 1 55 71 72
University Avenue 1,267 400 1 64 127 92
Springfield Avenue 1,116 335 2 51 96 102
Kirby Avenue/Florida Ave 760 220 1 34 67 65
Windsor Road 344 132 1 15 43 37
Mattis Avenue 883 291 0 54 80 64
Prospect Avenue 1,240 340 1 46 85 117
Neil Street 1,122 330 0 45 108 90
Lincoln Avenue 753 204 0 29 76 63
Cunningham Ave/Vine St 667 192 0 25 80 48
High Cross Road/IL 130 91 34 1 7 13 6
Tota l 9,070 2,757 8 425 846 756
East-West Corridors
North-South Corridors
B-Injury Crashes
C-Injury Crashes
Roadway Crashes InjuriesA-Injury Crashes
Fatalities
University Avenue and Prospect Avenue had the highest number of crashes among the major corridors in the Champaign-Urbana area.
25
Table 10: Severe Crashes along Major Corridors by Year
Bradley Avenue 11 15 12 5 12
University Avenue 11 10 14 11 18
Springfield Avenue 15 13 6 10 7
Kirby Avenue/Florida Ave 7 4 4 7 12
Windsor Road 5 3 1 1 5
Mattis Avenue 10 10 10 8 16
Prospect Avenue 10 8 9 11 8
Neil Street 7 13 11 6 8
Lincoln Avenue 7 7 6 5 4
Cunningham Ave/Vine St 2 4 5 4 10
High Cross Road/IL 130 1 1 2 0 3
Total 86 88 80 68 103
2008
North-South Corridors
East-West Corridors
2009Roadway 2005 2006 2007
Table 10 shows that University Avenue, Mattis Avenue, and Bradley Avenue are the corridors with the highest number of severe crashes in the Champaign-Urbana area. Table 11 shows the maximum number of fatal crashes along the key corridors between 2005 and 2009.
Table 11: Fatal Crashes along Major Corridors by Year
Bradley Avenue - - 1 - -
University Avenue - - - - 1
Springfield Avenue 1 1 - - -
Kirby Avenue/Florida Ave - - 1 - -
Windsor Road - - 1 - -
Mattis Avenue - - - - -
Prospect Avenue - - - 1 -
Neil Street - - - - -
Lincoln Avenue - - - - -
Cunningham Ave/Vine St - - - - -
High Cross Road/IL 130 - - - 1 -
Total 1 1 3 2 1
East-West Corridors
North-South Corridors
Roadway 2005 2006 2007 2008 2009
26
Figure 11: Fatal and Severe Crashes along Major Corridors in Champaign-Urbana
27
Figure 12: Pedestrian and Bicycle Crashes along Major Corridors in Champaign-Urbana
28
4.4 Additional Traffic Crash Facts for 2005-2009 Additional analysis has been performed to highlight some important facts associated with the crash data in the City of Champaign and City of Urbana from 2005 to 2009.
4.4.1 Day of the Week Analysis Figure 13 shows the number of crashes that occurred by day of the week. As can be seen in Figure 13, Friday was the most hazardous day of the week.
0
100
200
300
400
500
600
700
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Cra
sh
Fre
qu
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2005 2006 2007 2008 2009
Figure 13: Crashes by Day of the Week
29
4.4.2 Time of the Day Analysis Crashes during different hours of the day are shown in Figure 14. As can be seen in Figure 14, the majority of the crashes occurred between 12:00 PM and 6:00 PM.
0
50
100
150
200
250
300
350
Cra
sh
Fre
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Time of Day
2005 2006 2007 2008 2009
Figure 14: Time of the Day Analysis
30
4.4.3 Collision Types Table 12 shows a summary of different collision types for 2005-2009. As shown in Figure 15, rear-end, turning, and angle crashes are the predominant crash patterns for Champaign-Urbana. The crash analysis shows that the majority of the crashes at intersections are rear-end, turning, and/or angle crashes.
Table 12: Different Vehicle Collision Types
2005 2006 2007 2008 2009 Angle 558 502 508 489 385 2,442 16.9% Animal 34 14 16 15 16 95 0.7% Fixed object 307 260 298 307 230 1,402 9.7% Head on 12 21 11 13 11 68 0.5% Other non collision 14 15 14 15 8 66 0.5% Other object 18 11 12 9 11 61 0.4% Overturned 33 22 28 20 19 122 0.8% Parked Motor Vehicle 320 298 334 297 257 1,506 10.4% Pedalcyclist 58 63 53 54 60 288 2.0% Pedestrian 50 44 44 37 38 213 1.5% Rear end 908 789 871 841 653 4,062 28.1% Sideswipe opp. direction 26 21 23 18 17 105 0.7% Sideswipe same direction 235 240 212 227 133 1,047 7.3% Train 0 0 0 1 0 1 0.0% Turning 708 662 630 538 426 2,964 20.5%
Crash TypeTotal
Crashes% of Total Crashes
Year
Angle16.9%
Animal0.7%
Fixed object9.7%
Head on0.5%
Other non collision0.5%
Other object0.4%
Overturned0.8%Parked Motor
Vehicle10.4%
Pedalcyclist2.0%Pedestrian
1.5%
Rear end28.1%
Sideswipe opp. direction0.7%
Sideswipe same direction7.3%
Turning20.5%
Figure 15: Percent Distribution of Crashes by Collision Types
31
4.4.4 Weather Conditions Figure 16 shows a summary of crashes during different weather conditions. The majority of the crashes occurred in clear weather conditions. The percentages of crashes in different adverse weather conditions were similar every year from 2005 through 2009.
Clear80%
Fog/Smoke/Haze1%
Rain12%
Snow/Sleet/Hail4%
Other/Unknown3%
Figure 16: Percent Distribution of Crashes by Weather Condition
Table 13 provides the number of crashes during different weather conditions in Champaign-Urbana from 2005 through 2009.
Table 13: Traffic Crashes in Different Weather Conditions
2005 2006 2007 2008 2009 Clear 2,676 2,371 2,465 2,188 1,762 11,462 79.3% Fog/Smoke/Haze 24 18 26 23 8 99 0.7% Rain 350 444 336 350 350 1,830 12.7% Snow/Sleet/Hail 154 42 160 259 96 711 4.9% Other/Unknown 81 87 67 61 48 344 2.4%
Weather Conditions
Year % Total Crashes
Total Crashes
32
4.4.5 Roadway Surface Condition Figure 17 shows the crashes occurring on different roadway surface conditions. About 71% of the crashes over the five year period were on dry pavement conditions. Around 25% of the crashes occurred on snowy, icy, or wet pavement. The main contributory factors for wet pavement crashes are slippery pavement (reduced friction), water ponding on the roadway, and inadequate retroreflectivity of pavement markings. The number of crashes in each roadway surface condition category has decreased or remained consistent from 2005 to 2009, except for the “Snow/Slush/Ice” condition. There was a significant drop in the crashes “Snow/Slush/Ice” in 2006, but the number of crashes rose back up again in 2007 and 2008.
Dry Snow/Slush/Ice Wet Other/Unknown
2005 2,460 210 524 91
2006 2,255 26 594 87
2007 2,135 305 523 91
2008 1,933 367 505 76
2009 1,539 200 481 44
0
500
1,000
1,500
2,000
2,500
3,000
Cra
sh
Fre
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enc
y
Figure 17: Crashes by Road Surface Condition
33
4.4.6 Roadway Lighting Condition The relation of intersection crashes to the roadway lighting conditions was analyzed. Table 14 and Figure 18 show that the majority of the crashes occurred during the daytime. About 70% of the crashes occurred during daylight and 28% of the crashes occurred during poor lighting conditions (Dawn, Dusk, Darkness, & Darkness with Lighted Road).
Table 14: Crashes by Roadway Lighting Condition
2005 2006 2007 2008 2009 Daylight 2,331 2,065 2,152 2,063 1,572 10,183 70.5% Dawn 22 18 15 15 10 80 0.6% Dusk 61 56 61 49 45 272 1.9% Darkness 279 238 284 245 225 1271 8.8% Darkness, Lighted Road 513 521 483 452 376 2345 16.2% Unknown 79 64 59 57 36 295 2.0%
Lighing ConditionsYear Total
Crashes% Total Crashes
Daylight70%
Dawn1%
Dusk2%
Darkness9%
Darkness, Lighted Road16%
Unknown2%
Figure 18: Percent Distribution of Crashes by Roadway Lighting Conditions
34
4.4.7 Driver Condition Table 15 summarizes the driver condition information for the crashes in Champaign-Urbana. The driver condition is likely to contribute to crashes in Champaign-Urbana, and increase the severity of the crashes. The majority of the injuries (85%) occurred during normal driving conditions. Figure 19 shows that the majority of the impaired/distracted driving crashes (71%) were alcohol related.
Table 15: Driver Condition Information
2005 2006 2007 2008 2009
Alcohol Impaired 94 84 80 81 75 414 96 4.1% 19 4.1%
Asleep/Fainted 12 11 6 9 10 48 21 0.9% 7 1.5%
Drug Impaired 8 9 12 6 3 38 7 0.3% 4 0.9%
Fatigued 6 8 5 7 6 32 8 0.3% 2 0.4%
Had Been Drinking 25 21 34 9 16 105 23 1.0% 6 1.3%
Illness 7 2 9 8 8 34 13 0.6% 5 1.1%
Normal 5,318 4,843 4,954 4,702 3,639 23,456 2,104 89.3% 393 85.1%
Other/Unknown 500 458 437 396 300 2,091 84 3.6% 26 5.6%
Driver Condit ionTotal
Crashes
Total Injured
Percent of Total Injured
Total A Injury
Percent of Total A Injury
Year
Alcohol Impaired
57%
Asleep/Fainted
12%
Drug Impaired4%
Fatigued5%
Had Been Drinking
14%Illness8%
Figure 19: Percent Distribution of Impaired/Distracted Driving Crashes
35
4.4.8 Driver Age and Gender
Figure 20 shows age distribution of motor vehicle drivers involved in crashes. The graph shows that drivers aged between 20 and 24 were the most vulnerable to being involved in a traffic crash (21%), followed by drivers between the ages of 15 and 19 (13%). Drivers between the ages of 15-29 were involved in 46% of the total crashes reported in Champaign-Urbana. Figure 21 shows the total injuries and severe type “A” injuries for each age group.
0
200
400
600
800
1000
1200
1400
Cra
sh F
req
uen
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Age Group
2005 2006 2007 2008 2009
Figure 20: Age Distribution of Motor Vehicle Drivers involved in Traffic Crash
0
50
100
150
200
250
300
350
400
450
Cra
sh
Fre
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Age Group
Total Injuries Severe (A) Injuries
Figure 21: Total and Severe Injuries for Different Age Groups
36
Table 16 shows the driver and passenger injuries in the study region. About 41% of the total injuries in Champaign-Urbana involved individuals of ages between 15 and 29. Figure 22 shows crash frequency comparisons between male and female drivers of different age groups from 2005-2009. As shown in Figure 22, female drivers were involved in a higher number of crashes in all age groups.
Table 16: Driver and Passenger Injuries in Champaign-Urbana
Female Male Female Male Female Male Total % 0-9 0 0 69 58 69 58 127 3.8%
10-14 0 2 44 30 44 32 76 2.3% 15-19 145 101 94 66 239 167 406 12.3% 20-24 218 206 83 64 301 270 571 17.2% 25-29 160 133 55 35 215 168 383 11.6% 30-34 120 112 42 28 162 140 302 9.1% 35-39 115 82 30 13 145 95 240 7.2% 40-44 107 78 37 11 144 89 233 7.0% 45-49 94 94 31 13 125 107 232 7.0% 50-54 100 72 21 13 121 85 206 6.2% 55-59 71 50 20 4 91 54 145 4.4% 60-64 50 40 18 4 68 44 112 3.4% 65-69 40 36 18 2 58 38 96 2.9% 70-74 20 16 8 2 28 18 46 1.4% 75-79 19 26 13 6 32 32 64 1.9% 80-84 11 12 9 5 20 17 37 1.1% 85 + 13 4 6 12 19 16 35 1.1%
Total InjuriesAge
Driver Passenger
0
500
1,000
1,500
2,000
2,500
3,000
Cra
sh
Fre
qu
en
cy
Age Group
Male Female
Figure 22: Crash Frequency Comparison between Male and Female Drivers
37
4.4.9 Traffic Control Table 17 and Figure 23 present the percent distribution of crashes based on traffic control. About 43% of the crashes were at intersections controlled by a traffic signal or stop sign/flasher.
Table 17: Crashes Based on Traffic Control
Lane Use Marking 246 182 233 189 217 1,067 7.4%
No Control 1,537 1,400 1,441 1,330 1,057 6,765 46.8%
Other Warning Sign 22 14 23 12 14 85 0.6%
Stop Sign/Flasher 537 481 464 443 366 2,291 15.9%
Traffic Signal 876 811 820 870 578 3,955 27.4%
Other 39 50 45 20 22 176 1.2%
Unknown 28 24 28 17 10 107 0.7%
2009Total
Crashes% Total Crashes
Traffic Control 2005 2006 2007 2008
Lane Use Marking
7%
No Control47%
Other Warning Sign
%
Stop Sign/Flasher
16%
Traffic Signal27%
Other1%
Unknown1%
Figure 23: Percent Distribution of Crashes based on Traffic Control
38
5.0 Pedestrian and Bicycle Crashes Pedestrians and bicyclists are the most vulnerable road users; collisions with motor vehicles often result in serious injury or death. In 2009, 4,092 pedestrians and 630 bicyclists were killed in the United States12. National statistics show that 36% of the bicycle fatalities in 2009 occurred at intersections13. 37% of pedestrian deaths among people 60 and older occurred at intersections, compared with 22% for those younger than 6013. The following sections analyze the pedestrian and bicycle crashes in Champaign-Urbana over the five year study period. All the bicycle and pedestrian crashes reported between 2005 and 2009 involved at least one motor vehicle.
5.1 Pedestrian Crashes Table 18 shows the pedestrian crash information in the City of Champaign and City of Urbana between 2005 and 2009.
Table 18: Pedestrian Crashes in Champaign-Urbana
A B C2005 34 30 3 6 19 52006 27 27 0 12 9 62007 32 30 2 5 14 112008 27 27 0 6 15 62009 26 26 0 6 11 8
2005 17 17 0 5 11 12006 23 22 1 5 11 62007 15 14 1 7 5 22008 11 10 1 5 5 02009 19 19 2 4 8 4
City of Champaign
YearTotal
CrashesTotal
In juriesKilled
Injury Severity
City of Urbana
As can be seen in the table, almost all of the pedestrian crashes resulted in injuries. The 11 pedestrian fatalities accounted for 36% of the total fatalities in Champaign-Urbana over the five year period. Also, a significant number of pedestrians were severely injured (26% of injured pedestrians had a type A injury).
5.1.1 Pedestrian Age and Gender Figure 24 shows the age distribution by year of pedestrians involved in traffic crashes in 2005-2009. As can be seen in the figure, a significant number of pedestrians (51%) involved in traffic crashes were under age 25.
39
0
2
4
6
8
10
12
14
16
Below 4 5‐9 10‐14 15‐19 20‐24 25‐29 30‐34 35‐39 40‐44 45‐49 50‐54 55‐59 60‐64 65‐69 70 plus
Fre
qu
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Age Group
2005 2006 2007 2008 2009
Figure 24: Pedestrian Age Distribution
Figure 25 shows age distribution by gender of pedestrians involved in traffic crashes in 2007.
0
5
10
15
20
25
30
Fre
qu
en
cy
Age Group
Females Males
Figure 25: Pedestrian Age and Gender Distribution
40
Pedestrian crash locations in Champaign-Urbana from 2005 to 2009 are shown in Figure 26. The pedestrian crash frequency shows the number of crashes at a particular location.
41
Figure 26: Pedestrian Crash Locations in Champaign-Urbana
42
5.2 Bicycle Crashes Table 19 shows the bicycle crash information in Champaign-Urbana between 2005 and 2009. In 2009, there was a bicycle fatality on Green Street in Urbana. Almost all the bicycle crashes resulted in injuries.
Table 19: Bicycle Crashes in Champaign-Urbana
A B C2005 34 34 0 4 20 102006 46 46 0 9 22 152007 34 34 0 4 20 102008 27 27 0 6 15 62009 39 38 0 8 22 8
2005 24 24 0 2 16 62006 17 17 0 1 12 42007 20 21 0 1 16 32008 15 10 0 2 5 32009 21 20 1 5 9 6
City of Urbana
City of Champaign
YearTotal
CrashesTotal
In juriesKilled
Injury Severity
5.2.1 Bicyclist Age and Gender Figure 27 shows the age distribution by year of bicyclists involved in traffic crashes in 2005-2008. The age and gender distribution for bicyclists was not available for 2009. As can be seen in the figure, a majority of bicyclists (58%) involved in traffic crashes were under the age of 25.
43
0
2
4
6
8
10
12
14
16
18
Below 4 5‐9 10‐14 15‐19 20‐24 25‐29 30‐34 35‐39 40‐44 45‐49 50‐54 55‐59 60‐64 64‐69 70 plus
Cra
sh
Fre
qu
en
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Age Group
2005 2006 2007 2008
Figure 27: Bicyclist Age Distribution Figure 28 shows the age distribution by gender of bicyclists involved in traffic crashes in 2007. In addition, male bicyclists were more likely to be involved in crashes than female bicyclists. Bicycle crash locations in Champaign-Urbana from 2005 to 2009 are shown in Figure 29.
0
5
10
15
20
25
30
35
Below 4 5‐9 10‐14 15‐19 20‐24 25‐29 30‐34 35‐39 40‐44 45‐49 50‐54 55‐59 60‐64 64‐69 70 plus
Fre
qu
en
cy
Age Group
Female Male
Figure 28: Bicyclist Age and Gender Distribution
44
Figure 29: Bicycle Crash Locations in Champaign-Urbana
45
5.3 Pedestrian & Bicycle Crashes in the University District The University of Illinois District in Urbana-Champaign accommodates thousands of pedestrians and bicyclists each year during regular academic sessions. Table 20 presents the number of crashes and the severity level information of the reported pedestrian and bicycle crashes in the University District from 2005-2009. Figure 30 shows the location of bicycle and pedestrian crashes in the University District. Figure 31 shows the severity level of the bicycle and pedestrian crashes in the University District.
Table 20: Pedestrian and Bicycle Crashes in the University District
A B C
2005 15 14 1 3 10 1
2006 16 17 0 3 8 5
2007 15 16 0 3 7 4
2008 11 11 0 4 6 1
2009 12 12 0 2 7 3
2005 26 25 0 2 15 8
2006 18 19 0 5 10 3
2007 17 17 0 1 11 5
2008 19 16 0 2 9 5
2009 24 22 1 6 10 6
Bicycle Crashes
Pedestrian Crashes
YearTotal
CrashesTotal
In juriesFatality
Injury Severity
46
Figure 30: Bicycle and Pedestrian Crash Locations in the University District
47
Figure 31: Bicycle and Pedestrian Crash Severity in the University District
48
6.0 Selected Critical Intersection Locations (2005-2009) Based on the critical intersection selection and prioritization procedures (described in Chapter 3), the following signalized intersections were identified as critical in Champaign-Urbana. Different priority levels were assigned to the critical intersections based on the crash frequency, the crash rate, and the crash severity values. As can be seen in Table 21, there were no signalized intersections in the Priority 1 or Priority 2 lists. Eight signalized intersections were identified as critical in Champaign-Urbana.
Table 21: Critical Signalized Intersections (2005-2009)
1st St & Green St A 13 1.5 4.8
Cunningham Ave/Vine St & University Ave A 23 1.6 4.8
Mattis Ave & Bradley Ave A 17 1.2 9.1
Mattis Ave & Springfield Ave A 16 1.1 6.5
Neil St & Green St A 14 1.2 4.5
Neil St & Kirby Ave A 16 1.1 4.6
Neil St & Windsor Rd A 15 1.1 4.2
Prospect Ave & Bloomington Rd A 21 1.4 4.5
Neil St & Columbia Ave B 10 1.5 5.0
Randolph St & Church St B 8 1.5 5.1
4th St & Peabody Dr C 3 0.6 7.0
Moreland Blvd & Marketview Dr C 2 0.4 10.9
Intersect ionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
Priority 1
Priority 2
Volume Class
Volume Class
Priority 3
Intersect ionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
Volume Class
Intersect ionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
Table 22 lists critical unsignalized intersections in Champaign-Urbana. Twenty-six un-signalized intersections were identified as critical in Champaign-Urbana. Figure 32 shows the selected critical intersection locations for 2005 through 2009.
49
Table 22: Critical Unsignalized Intersections (2005-2009)
Lincoln Ave & Main St A 5 0.6 6.3
5th St & Washington St C 4 1.7 10.5
Crescent Dr & Kirby Ave A 4 0.5 11.1
Vine St & Water St A 7 0.4 4.8
McKinley Ave & Bradley Ave A 4 0.9 5.9
Prospect Ave & Hill St A 4 0.4 3.7
Prospect Ave & Park St A 4 0.4 4.3
3rd St & Springfield Ave B 6 0.9 5.8
5th St & Green St B 6 0.9 4.7
5th St & Springfield Ave B 5 0.8 4.9
Maple St & University Ave B 11 0.9 4.1
Prospect Ave & John St B 4 1.4 4.4
State St & Clark St B 2 0.9 4.5
Anthony Dr & Marketview Dr C 3 0.8 5.2
Broadway Ave & County Club Road C 3 0.9 10.9
Coler Ave & Green St C 3 0.8 6.2
Elm St & University Ave C 3 0.9 4.7
High Cross Rd/IL 130 & Washington St C 3 0.7 4.9
Market St & Olympian Dr C 3 0.9 17.4
Smith Rd & Main St C 3 0.7 6.0
State St & Columbia Ave C 3 0.8 14.1
State St & Washington St C 2 1.0 5.7
Broadway Ave & Illinois St D 4 0.8 15.1
IntersectionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
Priority 3
Volume Class
Volume Class
IntersectionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
Priority 1
Priority 2
Volume Class
IntersectionAverage Crash
Frequency
Average Crash Rate
Average EDPO Index
50
Figure 32: Selected Critical Intersection Locations (2005-2009)
51
6.1 Intersection Locations with Fatal Crashes A total of 28 fatalities were recorded in Champaign-Urbana from 2005 to 2009. Of the 28 fatalities, seven were intersection related. Fatalities were recorded at the following intersections over the five year period: Champaign
Market Street and Olympian Drive McKinley Avenue and Springfield Avenue Prospect Avenue and Healey Street Sixth Street and Chalmers Street State Street and Eureka Street
Urbana
Carle Avenue and Florida Avenue Orchard Street and University Avenue
Figure 33 shows the intersection fatality locations in Champaign-Urbana over the five year analysis period.
52
Figure 33: Fatality Intersection Locations and Selected Critical Intersection Locations (2005-2009)
7.0 CONCLUSIONS Crash data is an invaluable tool for traffic safety analysis. This report analyzed five years of crash data (2005-2009). Important findings of the report include:
The number of crashes in the study area showed a decreasing trend from 2005 to 2009. The crashes in 2009 reduced 22% from 2008 and 31% from 2005.
The vehicle miles traveled in Champaign-Urbana remained relatively constant, while the crashes per 100 million vehicles miles traveled (MVMT) decreased from 385 in 2005 to 256 in 2009. The crash rates per year in the study area remained consistently lower than the statewide crash rates (per 100 MVMT).
The total fatalities increased from 2005 to 2008 and decreased from 2008 to
2009. The traffic fatality rates from 2005 to 2009 in Champaign-Urbana were less than 1.0 fatality per 100 million VMT. The study area fatality rates remained lower than the statewide fatality rates and the target rates proposed by IDOT’s Highway Safety Performance Plan (HSPP), for each study year.
The total injuries steadily decreased from 2005 to 2008. There was a marginal increase in the number of total injuries in 2009 from 2008. The traffic crash injuries reduced by 19% from 2005 to 2009. The severe injury crashes (Type A) increased from 134 in 2008 to 178 in 2009. About 20% of the crashes every year were severe injury crashes.
The severe injury rates (per 100 million VMT) for Champaign-Urbana in 2005, 2006, and 2007 were more than the statewide rates. The severe injury rates in 2008 and 2009 were less than the statewide severe injury rates and significantly below the proposed statewide HSPP goals.
The University Avenue and Prospect Avenue corridors had about 1,000 crashes over the five year period which is the highest among the major corridors in the Champaign-Urbana area. The maximum number of severe crashes along the key corridors occurred in 2009.
Additional data analysis showed the following trend in crashes from 2005 to 2009:
o Majority of the crashes occurred between 12:00 PM and 6:00 PM. o Rear-end, turning, and angle crashes are the predominant crash types
in Champaign-Urbana. o Majority of the crashes were under clear weather conditions (80%),
during daylight (70%) and on dry roadway pavement surface (71%). o Majority of the impaired/distracted driving crashes were alcohol related
(71%).
Drivers between the ages of 15-29 were involved in 46% of the total crashes
reported in Champaign-Urbana. The highest number of severe injuries and fatalities were reported in crashes involving drivers aged between 20 and 24.
About 43% of the crashes were at intersections controlled by a traffic signal or stop sign/flasher.
Eleven pedestrians and one bicyclist were killed from 2005 to 2009 in traffic crashes. Pedestrian and bicyclist deaths account for about 40% of the total traffic crash related fatalities in Champaign-Urbana over the five year analysis period (2005-2009).
Almost all the pedestrian and bicycle crashes resulted in an injury. Also, a significant number of pedestrians were severely injured (26% of injured pedestrians had a Type A injury).
A significant number of pedestrians (51%) and bicyclists (58%) involved in
traffic crashes between 2005 and 2009 were under 25 years of age.
Twelve signalized and twenty-three unsignalized intersections were identified as criticals. Different priority levels were assigned to the critical intersections based on the crash frequency, crash rate, and crash severity values.
Seven fatal crashes occurred at intersections in Champaign-Urbana from 2005 to 2009.
REFERENCES
1. Fatality Analysis Reporting System. http://www-fars.nhtsa.dot.gov/Main/index.aspx, Retrieved May 1, 2011.
2. 2009 Illinois Crash Facts and Statistics, Illinois Department of Transportation, Springfield, IL, 2010.
3. Illinois Strategic Highway Safety Plan, Illinois Department of Transportation, Springfield, IL, 2009.
4. Federal Highway Administration- Intersection Safety http://safety.fhwa.dot.gov/intersection/, retrieved May 3, 2011.
5. Traffic Safety Facts 2009. National Highway Traffic Safety Administration Center for Statistics and Analysis, Washington, D.C.
6. Illinois Travel Statistics, Illinois Department of Transportation, Springfield, IL 2009, http://www.dot.state.il.us/adttravelstats.html.
7. Pawlovich, Michael D., Safety Improvement Candidate Locations (SICL) Method, Office of Traffic and Safety, Iowa Department of Transportation, Des Moines, IA, February 2002.
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