31st & Harvard. Pedestrian Crosswalk Intersections: Where Did Your Money Go?

This is the follow-up to the initial “Gearing Up for A Hawk Intersection: 31st & Harvard, Ranch Acres, Midtown Tulsa.”  By Terence Morris, author, PACE TULSA AGS. Apr. 21, 2017 10:28 AM. feed-icon-28x28


During a public outreach process spanning 3 years, residents identified and prioritized roadway recommendations for the Destination 2030 Long Range Transportation Plan (LRTP). The results, in order of priority, were:

  1. Make the maintenance of existing roadways and bridges an increasing priority
  2. Focus on improving safety at arterial street intersections, including signalization at intersections and signal coordination in corridors
  3. Effectively finance the development and maintenance of the transportation system and optimize the use of transportation funds
  4. Include alternative transportation features in the design of traffic improvements
  5. Increase the coordination of transportation planning and land-use planning or development
  6. Continue needed expansion of highways and major roadways
  7. Enhance safety by increasing or improving enforcement of existing laws and regulations, improving the education of new drivers, and increasing education for existing drivers
  8. Give priority to roadways serving significant regional economic centers
  9. Consideration should be given to minimizing the mix of vehicles (separating tractor-trailers from smaller vehicles) on highways and major roadways
  10. Improve access across the Arkansas River

31st & Harvard, Ranch Acres, Midtown Tulsa is Zoned as a Commercial Limits area. In regards to continuing access, the ATS project on 31st and Harvard, Ranch Acres, in Midtown Tulsa, OK, has made substantial improvements because of technology modernization funding available from Tulsa City-County Street & Road Tax initiatives.

District law requires motorists to legally stop and give the right of way to pedestrians within crosswalks. However, DDOT research has shown that on busy, high traffic roadways, only about one in four drivers are willing to stop for pedestrians in the crosswalk. If appropriate warrants are met, a HAWK signal can be installed on those roadways that do not meet engineering standards for installing a conventional traffic signal.

Let’s Look at SAFETY EFFECTIVENESS! There was a brief study period before implementation of the High-Intensity Crosswalk Treatment at 31st & Harvard.


Study Periods

For the before-after study, the goal was to have 3 months of before data and 3 months of after data. The before period reflected month 1 to month 3 prior to the installation date of the HAWK. The calculations assumed 2 weeks prior to the installation date as construction. The 2 weeks following installation of the HAWK were assumed to be a learning period for drivers to become familiar with the treatment. The after period occurred 1 to 3 months following the installation of the HAWK or until April 5, 2017, which was the limit of crash data available.

The number of months in the after period for the 31st & Harvard HAWK site varied depending on when the HAWK was installed. The site had a 3-month or greater after period.  The 31st & Harvard HAWK group site had the same time period in their before and after periods as their corresponding HAWK site.

Crash Data

Crash data were supplied by the city of Tulsa, OK, and street names were used to match crashes with the geometric database. Identifying all crashes with matching street names should capture the crashes that could be influenced by the intersection’s traffic control; however, it may also capture crashes that would not have been influenced. The intersection-related (IR) variable may provide insight into whether the crash is related to the intersection’s traffic control. The permitted responses for IR crashes were “yes,” “no,” or blank, and about 1/3 of the crashes had this field blank. A comparison of the number of IR crashes for a sample of intersections to material available in a previous study indicated that the IR variable may be too restrictive. Therefore, the following two crash datasets were used in the evaluations:

  • Intersecting street name (ISN) crashes were identified by matching the street names for the intersection.
  • IR crashes were identified as the crashes in the ISN crash dataset with “yes” for the IR code.

The following types of crashes from each of the crash datasets were considered:

  • Total crashes included all crashes identified.
  • Severe crashes included all crashes with an injury severity code of possible injury, nonincapacitating injury, incapacitating injury, or fatal injury.
  • Pedestrian crashes included all crashes with the type of collision coded as pedestrian.

Aggregating Crash Data

In developing the SPFs, the crash counts at reference sites can be treated as aggregated data over the entire study period (including both the before and after periods) or as disaggregated data with two crash counts from each intersection–one for the before period and one for the after period. Aggregating the data is one way to account for the correlations that might be present in the crash counts when the intersections are included twice (once for the before period and once for the after period) in estimating the SPFs. Disaggregating the data provides the opportunity to account for a general time trend (if any exists) within the two periods. For the disaggregated data, it is desirable to use the generalized estimating equation approach in estimating the SPF coefficients to incorporate the potential correlation in the before and after crash counts from the same intersection. Both approaches were explored in this study.

  • Employed in the areas of 31st & Harvard Over 3,816.2 (highest 20%)
  • Population in the areas of 31st & Harvard 2,192.5 – 3,816.1


Table 1 summarizes the number of crashes by control type. HAWKs are installed to assist pedestrians in crossing the roadway; therefore, installing the device should have a notable impact on pedestrian crashes. The impact on total or severe crashes is not as intuitive. Using IR crashes, the HAWK sites experienced a decrease in the total crash rate of about 35 percent after installation. The 102 unsignalized intersections in reference group 2 experienced a 9 percent decrease, and signalized intersections in reference group 1 had a 17 percent decrease. These observations indicate that citywide conditions may have contributed to the reduction in crashes since all types of intersection control showed reductions in total IR crashes.

The HAWK sites experienced a large decrease of 86 percent in the pedestrian IR crash rate after installation. The 102 unsignalized intersections experienced an increase in pedestrian crashes of 143 percent. Therefore, if citywide conditions were contributing to reductions in total crashes, these conditions were not having the same impact on pedestrian crashes, or other factors were contributing to a rise in pedestrian crashes at unsignalized intersections but not at signalized and HAWK intersections.

From table 1, it is observed that HAWK locations have crash rates higher than unsignalized intersections. For this dataset, the HAWK locations were associated with a slightly greater number of crashes per million entering vehicles and pedestrians, as compared to the nearby unsignalized intersections. This observation does not imply that if the HAWK was removed, the crash rate for a given intersection would be similar to the crash rate identified for the neighboring unsignalized intersections. When the sites were unsignalized intersections (i.e., before the HAWK was installed), the crash rate at the sites exceeded the crash rate for nearby unsignalized intersections. Therefore, conditions at the HAWK locations before the treatment was installed were generating crashes in greater numbers than the unsignalized intersections. This indicates that those intersections were associated with conditions that resulted in a higher number of crashes. Addressing those conditions with a HAWK resulted in a decrease in total crashes and a large decrease in pedestrian crashes. The following section provides the findings from the statistical evaluation.

Table 1. Crash data for before-after study by groups in 21 other HAWK SITES FOR A PERIOD OF 38 Months.

Measure ISN Crashes IR Crashes
Before After Percent Change (%) Before After Percent Change (%)
CompareHAWK sites (21) Frequency 11.0 9.2 -17 5.0 3.3 -34
Total crashes/MEV&P 0.748 0.618 -17 0.341 0.223 -35
Severe crashes/MEV&P 0.265 0.210 -21 0.138 0.094 -32
Pedestrian crashes/MEV&P 0.029 0.005 -83 0.017 0.002 -86
Pedestrian crashes/MEP 3.081 0.511 -83 1.826 0.255 -86
Reference group 1: Signalized intersections (36) Frequency 44.9 41.9 -7 19.6 16.8 -14
Total crashes/MEV&P 1.953 1.788 -8 0.854 0.716 -16
Severe crashes/MEV&P 0.549 0.503 -8 0.294 0.241 -18
Pedestrian crashes/MEV&P 0.020 0.016 -23 0.010 0.008 -16
Pedestrian crashes/MEP 2.051 1.546 -25 1.025 0.839 -18
Reference group 1: Unsignalized intersections (35) Frequency 4.2 4.3 3 1.6 1.3 -17
Total crashes/MEV&P 0.285 0.292 2 0.108 0.090 -17
Severe crashes/MEV&P 0.098 0.088 -10 0.043 0.038 -10
Pedestrian crashes/MEV&P 0.006 0.009 52 0.003 0.004 42
Pedestrian crashes/MEP 1.383 2.078 50 0.615 0.866 41
Reference group 2: Unsignalized intersections (102) Frequency 5.9 6.1 3 2.4 2.1 -9
Total crashes/MEV&P 0.418 0.430 3 0.166 0.150 -9
Severe crashes/MEV&P 0.140 0.141 0 0.060 0.056 -6
Pedestrian crashes/MEV&P 0.006 0.011 93 0.001 0.003 143
Pedestrian crashes/MEP 1.233 2.297 86 0.257 0.602 134

What is a “HAWK” Pedestrian Crosswalk Signal?

High-intensity Activated Crosswalk is a combination of a beacon flasher and traffic control signaling technique. Pedestrians can face traffic conditions that are risky to extremely hazardous. The pedestrian activated HAWK traffic control signal offers increased safety and at an affordable price.

  • As required by the MUTCD standards (Chapter 4F 2009 Edition), a typical pole/mast arm includes:
    • Two 3-signal beacon assemblies for each approach (minimum requirement)
    • One pedestrian signal head (WALK/DON’T WALK) at each end of crosswalk (countdown timer optional)
    • Pedestrian Activated (push button or passive activation)
  • Sequence of Operation of “HAWK” Pedestrian Crosswalk Signal
    • Traffic signal dark/Dont Walk signal active to pedestrian
    • Pedestrian pushes button to activate
    • Flashing yellow beacon begins (7 seconds)
    • Solid yellow beacon begins (4 seconds)
    • Beacon turns to all Red for 3 seconds prior to walk indication to pedestrian
    • Pedestrian view walk indication to walk (10 seconds)
    • This is followed by a flashing don’t walk symbol with a count down to pedestrians/the beacon starts flashing red
    • Ending in signal going dark and pedestrian don’t walk signal is solid

In 38 Months we will be filling in the Table Below with the before and after statistics from our Study An Examination: Intersection Awareness 31st & Harvard to 41st & Yale.  


To account for the effects of variables in crash reduction as well as the potential regression-to-the-mean bias, the EB approach was employed to identify the safety effectiveness of the HAWK treatment. The corresponding main report includes the reasonable SPFs identified in this study. [1]  Although the magnitude of the safety effectiveness estimate varied to some extent as different predictors were included in the SPFs, the results did not seem to change materially. Table 2 summarizes the percent reduction and whether the finding was significant at the 95 percent confidence level from the different approaches used in evaluating the HAWK beacon.

Table 2. Summary of results.

Reference Group (Aggregation) Percent Reduction
(Significant at the 95 Percent Confidence Level)
Total Crashes Severe Crashes Pedestrian Crashes
ISN Crashes
1 (aggregated)      
2 (aggregated)      
2 (disaggregated)      
IR Crashes
1 (aggregated)    
2 (aggregated)      
2 (disaggregated)      

After we get the numbers tabled, we will be attempting to explain the results for total crashes. The percent for ISN crashes  and percent for IR crashes, and calculate the percentage of confidence level.  The results for pedestrian crashes, with the disaggregate approach resulting in the aggregate approaches variance. As seen in several evaluations, severe crash results affect the desired confidence levels. The sample size probably will influence the results.  The safety effectiveness estimate will factor into each reference group  used. Either reference group 1 or reference group 2 will be chosen as the more appropriate reference group, since in most cases, the HAWK is installed at a previously unsignalized or undersignalized pedestrian crosswalk intersection.


The objective of this study is to evaluate the safety effectiveness of the HAWK device. This study used a before-after EB method which accounted for possible regression-to-the-mean bias as well as traffic, weather, citywide public relations campaigns, and other factors that changed over time. SPFs were developed using reference site data consisting of nearby intersections that did not have HAWK treatments. The study included 21 intersections where a HAWK had been installed and two reference groups. Evaluation approaches explored the following:

  • Three types of crashes (total, severe, and pedestrian).
  • Two methods for identifying crashes (ISN and IR).
  • Two reference groups (reference group 1 with 36 signalized and 35 unsignalized intersection and reference group 2 with 102 unsignalized intersections).
  • Two ways to combine the reference group before and after data (aggregated and disaggregated).

The crash prediction during the before period was calculated from SPFs and combined with the observed crash count for the before period by using a weighted average to control for regression-to-the-mean bias. This weighted average was adjusted for differences in duration and traffic volumes (and general time trends if any existed) between the before and after periods. This lead to a crash prediction for the after period had the treatment not been applied. EB then compared this predicted value to the observed crash frequency for the after period.

Two crash datasets were used in the before-after evaluation. In theory, the IR crash dataset should have better represented those crashes that would be affected by the traffic control at the intersection. A closer review revealed that the IR code was not used in over a 1/3 of the crashes; therefore, too many crashes may have been eliminated. The ISN crash dataset, however, may include crashes that are not related to the traffic control. Therefore, both datasets were considered. The IR crashes were considered as the more appropriate dataset for total and severe crashes. The ISN crash dataset, however, may be more representative of the change in pedestrian crashes since the HAWK device could induce pedestrians to walk an additional distance to benefit from an activated traffic control device.

The before-after evaluation results were as follows:

  • There is a percent +/- of total crashes, which is/ is not statistically significant in percentage confidence level.
  • There is a percent +/- in pedestrian crashes, which is/ is not statistically significant in percentage confidence level.
  • There is a percent +/- severe crashes, which is/ is not statistically significant in percentage confidence level.

The prime objective of a HAWK is to provide pedestrians with safe crossing opportunities. As such, a reduction in pedestrian crashes would be expected to be associated with the HAWK, and a statistically significant reduction in pedestrian crashes was found. The installation of the HAWK was also found to be associated with a statistically significant reduction in total crashes. It should be noted that the HAWK treatment, just like any other warning traffic control device, may not work as effectively if it is overused. In addition, such high crash reductions identified in this study may not be achieved at future locations if the site has different characteristics, such as less pedestrian activity.

This is a list of sponsors

[1] Fitzpatrick, K. and Park, E.S. (2010). Safety Effectiveness of the HAWK Pedestrian Crossing Treatment, FHWA-HRT-10-042, Federal Highway Administration, Washington, DC.

© 2017 | PACE TULSA AGS FOUNDATION.  “Pedestrian Awareness Crosswalk Education is an online think-tank intersecting awareness of public transportation policy in the United States.”


Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s