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Section 3: Problem Identification and Community Assessment

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What Is Problem Identification?

Problem identification and assessment is the discovery of where, when, how, and why crashes occur. Also of major importance is the identification of the causes of crashes and collisions.

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Purpose of Problem Identification

The purpose of problem identification and assessment is:

  • to understand the crash problem and causation factors
  • to develop effective countermeasures to reduce or eliminate the problem
  • to design evaluation mechanisms to measure changes in problem severity
  • to manage influences (for example, using statistical crash data to highlight a particular problem area in order to obtain the necessary support for instituting an effective countermeasure in a jurisdiction).
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General Problem Identification Procedure

Using the sources of information and the analytical processes described later in this section, TRF-TS systematically analyzes data to determine whether a proposed project is the best alternative among the available options. Conclusions must:

  • support the available data
  • be site specific, whether that site is a county, city, or roadway section.

Typically, TRF-TS proceeds as follows with problem identification and analysis:

  1. Identify evidence that a traffic safety problem exists.
  2. Collect applicable data in the target jurisdiction.
  3. Analyze the data to determine what factors or characteristics are overrepresented.
  4. Is the problem of a magnitude that warrants action? If yes, proceed to the following steps. If no, consider possibility that initial indication may have been random.
  5. Investigate all possible corrective actions.
  6. Determine the best course of action.
  7. Initiate corrective action.

Explanations of the requirements involved in these steps follow.

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Data Collection and Analysis

Once a perceived problem is identified, data must be collected and analyzed (Steps 2 and 3 of the previous procedure). This process involves the following steps.

Collecting and Analyzing Data

Step

Action

Notes:
1

Identification of data sources.

See “Data Sources” later in this section.

2

Data collection.

See “Data Sources” later in this section.

3

Determination of analysis strategy (how best to determine if a problem exists.)

See “Data Analysis and Interpretation” later in this section.

4

Data analysis.

See “Data Analysis and Interpretation” later in this section.

5

Display and reporting analysis results.

For example, a graph or chart may display the data overtime to show that the problem is either increasing or decreasing in frequency.

6

Identification of high-incidence crash locations.

Of all crash locations in a jurisdiction, are there any that appear more frequently than others?

7

Identification of overrepresented crash characteristics.

For example, youth with alcohol involvement. See “Data Elements” later in this section.

8

Analysis of support problems. (Who has the information you need? Will they share it? Is the data reliable?)

Attempt to solve data access problems by enlisting the support of agencies or offices that collect or possess the information you need. See “Data Sources” later in this section.


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Data Elements

Data elements fall into three general categories: people, vehicles, and roadway. These categories may be broken down into subgroups and assigned relevant characteristics, as shown in the following table.

Categories of Traffic Safety Data

Data Category

Subgroups

Characteristics

People

drivers, occupants, pedestrians

age, sex, blood alcohol level, driver’s education experience and training

Vehicles

passenger cars, trucks, busses, motorcycles, bicycles, etc.

sedans, convertibles, anti-lock brakes

Roadway

interstate, primary, secondary

political subdivisions, light conditions, surface conditions



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Crash Specific Data

Crash specific data might include any of the following:

  • type and severity of crash (fatal, pedestrian, etc.)
  • location
  • roadway characteristics
  • violations
  • time of day
  • day of week and month
  • type of vehicle
  • direction of travel
  • driver’s age
  • driver’s sex
  • weather conditions
  • vehicle maneuver
  • occupant protection usage
  • alcohol or drug involvement
  • emergency medical services (EMS) data
  • investigating agency.
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Data Sources

Data sources might include any of the following:

  • Department of Public Safety
  • local police department
  • Texas Department of Transportation district or headquarters office
  • State Department of Health or regional or local health agencies
  • emergency medical service providers
  • evaluations
  • surveys
  • national or statewide studies (such as Fatality Analysis Reporting System [FARS])
  • local court system
  • district traffic engineering and roadway analyses
  • web-based software for conducting community assessments — specifically, a computerized method for analyzing traffic safety problems within a community and a set of plans for implementing proven programs that address the identified traffic safety problems.) (See “Web-based Tools for Identifying Resources” later in this section.)
  • other sources (interest groups, task forces, school districts, colleges, hospitals, universities, insurance companies, etc.)
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Data Analysis and Interpretation

Analysis means to divide a whole into its parts in order to discover the nature, function, and relationship of those parts.

Data subgroups should be reviewed to determine overrepresentation. Such overrepresented subgroups indicate highway safety problems. A good example of this would be the high percentage of teenager drivers involved in crashes versus the much lower percentage among all drivers.

Further analysis should focus on subgroup characteristics — for example, increased severity or any other factors available from the data.

Overrepresented factors can be determined by comparing the rate of crashes for a subgroup or characteristic within the jurisdiction to the same rate in a comparable or larger jurisdiction. The rate may be expressed either as a percentage or a ratio.

Percentage Example: If the percentage of adult vehicle occupants that do not use safety belts within a jurisdiction is greater than the statewide percentage, then that characteristic is overrepresented.

Ratio Example: Dividing nighttime (10 P.M. to 6 A.M.) crashes by the total number of crashes for the jurisdiction within a given timeframe produces a ratio, as follows:

(click in image to see full-size image)

Where:

  • F = fatality crashes
  • A = incapacitating injury crashes
  • B = non-incapacitating injury crashes
  • Night = 10 P.M. to 6 A.M.

    • If that ratio is higher than the statewide ratio, a DWI problem may be indicated (since most nighttime crashes are DWI related).

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Some Key Questions in Problem Identification

Asking the following questions may help with data analysis and ultimately problem identification.

Questions to Help with Data Analysis and Program Identification

Question

Examples

Are high crash incidence locations identified?

specific road sections, highways, streets, and intersections

What appears to be the major crash causation?

Alcohol, other drugs, speed, other traffic violation, weather, road condition.

What characteristics are overrepresented or occur more frequently than would be expected in the crash picture?

Number of crashes involving 16- to 19-year-olds versus other age groups or number of alcohol crashes occurring on a particular roadway segment as compared with