# Presentation: 908103

## Low Cost Safety ImprovementsPooled Funds Study Safety of Lane/Shoulder WidthCombinations on Two-Lane Rural Roads

- Low Cost Safety ImprovementsPooled Funds Study Safety of Lane/Shoulder WidthCombinations on Two-Lane Rural Roads

**Dr. Frank Gross, Vanasse Hangen Brustlin (VHB), Inc**
**Dr. Paul P. Jovanis, Penn State University**

**Notes:**
Cover page pictures. Picture shows series of three scenarios: a vehicle on a meandering road, safety personnel at work, and a car that is very badly damaged after it appears to have collided into a telephone pole.  

This presentation addresses the evaluation of various lane and shoulder width combinations on two-lane, rural roads.

## Overview

- Introduction
- Objective
- Study Design
- Methodology
- Data Collection
- Preliminary Results
- Conclusions
- Future Research

## Background on Strategy 

- Shoulder Paving/Widening
- Proven strategy
- Pavement Width
- What lane/shoulder width produces lowest crash odds?
- Identified at Technical Advisory Committee June 2006
- Target crashes
- Head-on
- Run-off-road
- Sideswipe
- Potential Difficulties
- Confounding Variables
- Key to Success
- Flexible modeling approach

**Notes:**
Notes: 
Based on the NCHRP 500 series, shoulder paving and widening are held as “proven” strategies.
The allocation of total pavement width is not addressed by the NCHRP 500 series, but was identified as an area of interest by the Technical Advisory Committee.
The main question was: for a fixed pavement width, what allocation of lane and shoulder width will produce the lowest crash odds?
The target crash types are similar to those for lane and shoulder widening, which include head-on, ROR, and sideswipe crashes.
Potential difficulties in evaluating this strategy include the adjustment of potential confounding variables.
Therefore, we need to apply a flexible modeling technique to make the necessary adjustments.

## Literature Review

- Crash Modification Factors in Highway Safety Manual
- Key studies: Zegeer et al. (1981); Zegeer et al. (1988); Griffin and Mak (1987)

**Recommended CMF for Shoulder Width (Harwood et al., 2000)**

**Notes:**
Graph: Recommended Crash Modification Factor for Shoulder Width. The graph shows the variation of crash modification factors and average daily traffic volume for 0’, 2’, 4’, 6’, and 8’ shoulders. The average daily traffic volume (vehicle/day) is the x-axis ranging from 0 to 2500 and crash modification factors is the y-axis ranging from 0 to 1.60. The 0’ shoulder width start at 1.10 when average daily traffic is zero(0) vehicles/day, stays constant from 0 to 400 vehicle/day, then increases linearly to 1.50 at 2000 vehicle/day. The lines are constant after 2000 vehicle/day. The 2’ shoulder width start at approximately 1.08 when average daily traffic is zero(0) vehicles/day, stays constant from 0 to 400 vehicle/day, then increases linearly to 1.30 at 2000 vehicle/day. The lines are constant after 2000 vehicle/day. The 4’ shoulder width start at approximately 1.02 when average daily traffic is zero(0) vehicles/day, stays constant from 0 to 400 vehicle/day, then increases linearly to 1.12 at 2000 vehicle/day. The lines are constant after 2000 vehicle/day. The graph shows a general increase in crash modification factors with ADT for 0’, 2’ and 4’ shoulders. Crash modification factors remains constant (1.00) for a 6’ shoulder as ADT increases from 0 to 2500 vehicle/day. The 8’ shoulder width start at approximately 0.9 when average daily traffic is zero(0) vehicles/day, stays constant from 0 to 400 vehicle/day, then decreases linearly to 0.88 at 2000 vehicle/day and remains constant after 2000 vehicle/day. 

The safety effectiveness of lane and shoulder width have been addressed in several studies individually.
These variables are included as Crash Modification Factors in the Highway Safety Manual.
The Crash Manual Factors, shown here, was developed by an expert panel based on past research.
A similar Crash Modification Factors was developed for lane width.
Key studies included Zegeer et al. in 1981 and 1988 as well as Griffin and Mak in 1987.

## Literature Review

- Few Studies Address Allocation of Total Width
- “Road diets” change total number of lanes
- Burden and Lagerwey (2001); Welch (1999)
- Reallocation of width on urban freeways
- Add lane by reducing lane and shoulder width
- McCasland (1978); Urbanik and Bonilla (1987)
- Evaluate Re-allocation Without Other Changes

**Notes:**
Notes: 
Although there has been a great deal of research on the safety effects of lane and shoulder width, there has not been much attention given to the allocation of total paved width.
Road diets are an example of re-allocation; however, the total number of lanes is changed.
Another application of re-allocation has been used to increase capacity.
Add lanes by reducing lane and shoulder width, but use same total width.
This study evaluates the re-allocation of pavement width without changing the number of lanes

## Objective

- Estimate Safety Effectiveness
- For a given pavement width, what allocation of lane/shoulder width produces the lowest crash odds?
- Secondary Questions of Interest
- Do effects vary by:
- Traffic volume?
- Speed limit?
- For a given lane width, do effects vary as shoulder width increases?
- Is the treatment economically feasible?

**Notes:**
Notes: 
Primary Research Question:
What is the best allocation of lane/shoulder width for a given fixed pavement width?
Secondary questions to be answered are as follows:
Do effects vary by traffic volumes?
Do effects vary by speed limit?
Is the treatment economically feasible?
A preliminary analysis has been completed to address the main objective.
The secondary questions are yet to be answered.

## Methodology

- Case-Control Methodology
- Cases: crash-involved segments for a given year
- Controls: non-crash-involved segments for a given year
- Matching Variables
- ADT and Segment Length
- Additional Covariates
- Speed, District, Unpaved Shoulder, Curvature, and Grade

**Notes:**
Notes: 
This study differs from those in the Low Cost evaluations 1-4, which applied an Empirical Bayes Before-After analysis to estimate safety effectiveness.
This study applies a case-control methodology, which is a cross-sectional design rather than before-after.
Cases were defined as those segments where at least one crash occurred in a given year.
Controls were defined as those segments not experiencing a crash.
The case-control design accounts for potential confounding variables through a combination of  matching and modeling.
The variables used in the matching scheme are accounted for automatically.
The remaining variables of interest are included as covariates in the model.
District and Unpaved Shoulder were available in PA. District refers to specific PennDOT districts and the variable was used to account for differences between districts such as driver populations, weather conditions, etc.
Horizontal and vertical curvature were not available in PA, but were available in WA.
The table illustrates the matching procedure and database format.

## Methodology

| Pair | ADT | Segment length | SW: 0 | SW: 1 | SW: 2 | SW: 3 | SW: 4 | SW: 5 | LW: 9 | LW: 10 | LW:11 | LW:12 | Outcome |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 2 | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 |
| 1 | 2 | 5 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 |
| 2 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 |
| 2 | 4 | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |

**SW means shoulder width and LW means lane width**

**Notes:**
Notes: 
The case-control design is flexible and allows for the examination of several questions at once.
Regression-to-the-mean is not an issue in this study because the sites were not selected for treatment based on crash rates.
The case-control design accounts for potential confounding variables through matching and modeling.
The variables used in the matching scheme are accounted for automatically.
The remaining variables of interest are included as covariates in the model.

## Methodology

- Case-Control Methodology
- Allows answer to primary and secondary questions
- Regression-to-the-mean not an issue
- Accounts for confounding variables
- Matched design
- Model covariates

**Notes:**
Notes:
The case-control design is flexible and allows for the examination of several questions at once.
Regression-to-the-mean is not an issue in this study because the sites were not selected for treatment based on crash rates.
The case-control design accounts for potential confounding variables through matching and modeling.
The variables used in the matching scheme are accounted for automatically.
The remaining variables of interest are included as covariates in the model.

## Study Design

- Required Sample Size
- Minimum: 15,094 segment-years
- Detect 10 percent reduction in total crashes with 90 percent confidence
- Desirable: 57,576 segment-years
- Detect 5 percent reduction in total crashes with 90 percent confidence
- Assumption
- 50 percent discordant pairs
- How Does Assumption Hold?
- PA discordant pairs: 70 percent (LW) and 80 percent (SW)
- WA discordant pairs: 66 percent (LW) and 84 percent (SW)

**Notes:**
Notes: 
Sample size calculations were based on the assumption of a matched case-control study design.
We determined that 15,094 segment-years are required to detect a 10 percent reduction in total crashes with 90 percent confidence
However, it was desirable to be able to detect a 5 percent reduction in total crashes with 90 percent confidence.
This would require 57,576 segment-years
Assumption
50 percent discordant pairs
How does assumption hold?
Both PA and WA had a higher than expected percentage of discordant pairs, which would reduce the required sample size.

## Data Collection-1

**Notes:**
Figure: Shows 50 States of America with Pennsylvania and Washington shaded blue to indicate data were obtained from these States.
Data were collected in PA through PennDOT and from the State of Washington through the HSIS.

## Data Collection-2

- Crash Data
- 5 years of PA data
- 6 years of WA data

- Roadway Data
- 	(PA and WA)
- Number of Lanes
- Area Type
- AADT
- Segment Length
- Speed Limit
- Surface Width
- Paved Shoulder Width

- 	(WA only)
- Horizontal Curvature
- Vertical Curvature
- 	(PA only)
- Unpaved Shoulder Width
- District

**Notes:**
Notes: 
Data were collected for all two-lane, rural, undivided roads in PA (from PennDOT) and WA (from HSIS).
Crash data were obtained to determine the total crash frequency and target crash frequency for each segment.
AADT and geometric variables were obtained to control for potential confounding effects.
Horizontal and vertical curvature were available in WA only, which provided additional information to include in the study.

## Data Collection-3

|  Variable |       PA
   Cases
    (total  crashes)                     | PA
Controls    (total crashes)                     | WA
Cases (total crashes)                      | WA
Controls (total crashes)                       | PA
Cases (target crashes) | PA
Controls (target crashes)  | WA
Cases (target crashes) | WA
Controls (target crashes) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Length (ft) | 2598 | 2578 | 1936 | 1874 | 2628 | 2609 | 2059 | 1996 |
| AADT | 3921 | 3701 | 4693 | 4398 | 3530 | 3363 | 4133 | 3970 |
| Speed
(mph) | 47.36 | 48.20 | 51.04 | 51.18 | 47.61 | 48.26 | 51.76 | 51.65 |
| Lane
Width (ft) | 11.21 | 11.19 | 11.55 | 11.61 | 11.02 | 11.10 | 11.49 | 11.61 |
| Shoulder
Width (ft) | 2.96 | 3.14 | 4.95 | 5.23 | 2.82 | 3.02 | 4.81 | 5.33 |

**Notes:**
Notes: 
Here you can see the average segment length and AADT for PA and WA case and control sites.
These numbers should be pretty close since these were the matching variables.
The other variables (Speed, Lane Width, and Shoulder Width) were not used in the matching scheme
Speeds are fairly similar for case and control sites as are lane and shoulder widths
However, shoulder widths are greater (on average) for control sites

## Data Collection -4

| Pavement
Width | Lane
Width | Shoulder
Width |         PA Sample  (Total  crashes) |     WA Sample (Total  crashes) |      PA Sample (Target  crashes) |     WA Sample (Target  crashes)  |
| --- | --- | --- | --- | --- | --- | --- |
| 26' | 10‘  | 3' | 4,838 | 352 | 3,550 | 60 |
| 26' | 11' | 2' | 4,443 | 2,001 | 3,134 | 522 |
| 26' | 12' | 1' | 196 | 173 | 148 | 53 |
| 28' | 10' | 4' | 4,024 | 225 | 2,803 | 20 |
| 28' | 11' | 3' | 6,756 | 2,581 | 4,601 | 686 |
| 28' | 12' | 2' | 1,485 | 591 | 994 | 161 |
| 30' | 10' | 5' | 567 | 84 | 393 | 17 |
| 30' | 11' | 4' | 10,156 | 2,388 | 6,622 | 526 |
| 30' | 12' | 3' | 2,156 | 1,479 | 1,420 | 429 |
| 32' | 10' | 6' | 406 | 63 | 250 | 12 |
| 32' | 11' | 5' | 2,960 | 778 | 1,932 | 206 |
| 32' | 12' | 4' | 4,859 | 2,358 | 3,107 | 640 |
| 34' | 10' | 7' | 84 | 4 | 54 | 1 |
| 34' | 11' | 6' | 2,677 | 1,190 | 1,667 | 277 |
| 34' | 12' | 5' | 1,242 | 906 | 720 | 242 |
| 36' | 10' | 8' | 75 | 61 | 42 | 14 |
| 36' | 11' | 7' | 294 | 403 | 188 | 115 |
| 36' | 12' | 6' | 1,577 | 1,691 | 954 | 454 |
| Total |   |   | 48,795 | 17,328 | 32,579 | 4,435 |

**Notes:**
There are yellow shaded cells that represent sample sizes less than 200. The highlighted cells are the following:
WA Sample (Target crashes) with 26’ pavement width and 10’ lane width 
PA Sample (Total crashes), WA Sample (Total crashes), PA Sample (Target crashes), and WA Sample (Target crashes), with 26’ pavement width and 12’ lane width 
WA Sample (Target crashes) with 28’ pavement width and 12’ lane width 
WA Sample (Total crashes) and WA Sample (Target crashes) with 30’ pavement width and 10’ lane width 
WA Sample (Total crashes) and WA Sample (Target crashes) with 32’ pavement width and 10’ lane width 
PA Sample (Total crashes), WA Sample (Total crashes), PA Sample (Target crashes) and WA Sample (Target crashes), with 34’ pavement width and 10’ lane width 
PA Sample (Total crashes), WA Sample (Total crashes), PA Sample (Target crashes) and WA Sample (Target crashes), with 36’ pavement width and 10’ lane width
PA Sample (Target crashes) and WA Sample (Target crashes), with 36’ pavement width and 11’ lane width

The sample sizes here are based on a new analysis where lane widths were collapsed to obtain larger sample sizes (include 9.5’ lanes with 10’ lanes; include 10.5’ lanes with 11’ lanes; and include 11.5’ lanes with 12’ lanes)
The highlighted cells represent relatively small sample sizes that we need to be aware of when evaluating the results.
Overall, the total sample sizes compare favorably to the minimum required sample size (~15,000) except for the WA target crash sites.

## Evaluation Results (PA Total Crashes)

**Notes:**
Graph. Graph shows a plot of Crash risk on the vertical axis versus lane width category (ft) on the horizontal axis for 36’, 34’, 32’, 30’, 28’, and 26’ pavement widths for PA total crashes. The horizontal axis ranges from 0 to 12 and crash risk ranges from 0 to 2.0
The crash risk for 34’ pavement width decreases from 1.9 to approximately 0.82 at 11’ lane width. The line then increases slightly to 0.85 from 11’ lane width to 12’ lane width. The points are cross marked. 
The crash risk for 30’ pavement width decrease from 1.1 to 1.0 as lane width increase from 10 feet to 12 feet. The points are marked with a triangle. 
The crash risk for 28’ pavement width increases from 1.0 to 1.1 as lane width increases from 10 feet lane width to 11 feet lane width and back to 1.0 as lane width increases from 11 feet to 12 feet.
The crash risk for 26’ pavement width remains relatively the same approximately 1.05 as lane width increases from 10 feet to 12 feet. 
The crash risk for 32’ pavement width increases from 0.85 to 1.1 as lane width increases from 10 feet to 11 feet and back to 1.0 as lane width increases from 11 feet to 12 feet.
The crash risk for 36’ pavement width increases steadily from 0.8 to approximately 0.9 as lane width increases from 10 feet to 11 feet and then to 1.0 as lane width increases from 11 feet to 12 feet.
Highlighted circles are used to indicate small sample sizes. Refer to the data collection-4 slide for specific lane-shoulder combinations.

The PA models account for ADT, segment length, speed, district, and additional shoulder width.
In general, there is not a significant change in total crash odds as lane and shoulder width change across a given pavement width.
The exceptions are for 32’ and 36’ pavement widths
The 34’ pavement width is an anomaly and may be due to the relatively small sample size in this category

## Evaluation Results (PA Target Crashes)

**Notes:**
Graph. Graph shows a plot of Crash risk on the vertical axis versus lane width category (ft) on the horizontal axis for 36’, 34’, 32’, 30’, 28’, and 26’ pavement widths for PA target crashes. The horizontal axis ranges from 0 to 12 and crash risk ranges from 0 to 2.0
The crash risk for 34’ pavement width decreases from 1.8 to 0.8 at 11’ lane width. The line then remains constant at crash risk of 0.85 from 11’ lane width to 12’ lane width. The points are cross marked. 
The crash risk for 30’ pavement width decrease from 1.1 to approximately 1.05 as lane width increase from 10 feet to 11 feet and further decreases to 1.0 as lane width increase from 11 feet to 12 feet. The points are marked with a triangle. 
The crash risk for 28’ pavement width remains constant at 1.1 as lane width increases from 10 feet to 11 feet and decreases to 1.0 as lane width increases from 11 feet to 12 feet.
The crash risk for 26’ pavement width remains relatively the same approximately 1.0 as lane width increases from 10 feet to 11 feet and increases to approximately 1.55 as lane width increases from 11 feet to 12 feet. 
The crash risk for 32’ pavement width increases from 0.65 to 1.0 as lane width increases from 10 feet lane width to 11 feet lane width and decreases to approximately 0.95 as lane width increases from 11 feet to 12 feet.
The crash risk for 36’ pavement width increases steadily from 0.35 to approximately 0.8 as lane width increases from 10 feet lane width to 11 feet lane width and then to 1.0 as lane width increases from 11 feet to 12 feet.
Highlighted circles are used to indicate small sample sizes. Refer to the data collection-4 slide for specific lane-shoulder combinations.

Again, the PA models account for ADT, segment length, speed, district, and additional shoulder width.
26’, 28’, and 30’ pavement widths do not show a significant change in target crash odds for different combinations.
32’ and 36’ pavement widths indicate a decrease in target crash odds for narrow lane widths with wide shoulders.
Again, the 34’ pavement width is an anomaly and the circles indicate relatively small sample sizes.
The highlighted circles indicate those small sample sizes from the data collection-2 slide.

## Evaluation Results (WA Total Crashes)

**Notes:**
Graph. Graph shows a plot of Crash risk on the vertical axis versus lane width category (ft) on the horizontal axis for 36’, 34’, 32’, 30’, 28’, and 26’ pavement widths for WA total crashes. The horizontal axis ranges from 0 to 12 and crash risk ranges from 0 to 2.0
The crash risk for 30’ pavement width decrease from 2.0 to approximately 1.1 as lane width increase from 10 feet to 11 feet and further decreases to 1.0 as lane width increase from 11 feet to 12 feet. The points are marked with a triangle. 
The crash risk for 26’ pavement width slightly increases from approximately 1.05 to 1.15 as lane width increases from 10 feet to 11 feet decreases to approximately 0.95 as lane width increases from 11 feet to 12 feet.
The crash risk for 28’ pavement width remains constant at  0.9 as lane width increases from 10 feet to 12 feet.
The crash risk for 32’ pavement width increases from 0.65 to 1.0 as lane width increases from 10 feet to 11 feet and decreases to 0.8 as lane width increases from 11 feet to 12 feet.
The crash risk for 36’ pavement width increases steadily from 0.45 to approximately 1.0 as lane width increases from 10 feet to 11 feet lane width and remains constant as lane width increases from 11 feet to 12 feet.
The crash risk for 34’ pavement width increases from 0.0 to approximately 1.05 at 11’ lane width. The line then decreases to a crash risk of 0.8 from 11’ lane width to 12’ lane width. The points are cross marked. 
Highlighted circles are used to indicate small sample sizes. Refer to the data collection-4 slide for specific lane-shoulder combinations.
The WA models account for ADT, segment length, speed, horizontal curvature, and vertical curvature.
For the total crash model, there appears to be a general decrease in crash odds for the 10’ lane widths, although there are several points where small sample sizes may be a concern.

## Evaluation Results (WA Target Crashes)

**Notes:**
Graph. Graph shows a plot of Crash risk on the vertical axis versus lane width category (ft) on the horizontal axis for 36’, 34’, 32’, 30’, 28’, and 26’ pavement widths for WA target crashes. The horizontal axis ranges from 0 to 12 and crash risk ranges from 0 to 2.0
The crash risk for 26’ pavement width decreases from approximately 1.4 to 1.1 as lane width increases from 10 feet to 11 feet and increases to approximately 1.3 as lane width increases from 11 feet to 12 feet.
The crash risk for 32’ pavement width increases from 1.1 to 1.0 as lane width increases from 10 feet lane width to 11 feet lane width and further decreases to 0.8 as lane width increases from 11 feet to 12 feet.
The crash risk for 30’ pavement width increases from 0.85 to approximately 1.1 as lane width increase from 10 feet to 11 feet and decreases to approximately 0.95 as lane width increase from 11 feet to 12 feet. The points are marked with a triangle. 
The crash risk for 28’ pavement width increases from approximately 0.55 to approximately 1.0 and decreases to 0.85 as lane width increases from 11 feet to 12 feet.
The crash risk for 36’ pavement width increases steadily from 0.25 to approximately 0.8 as lane width increases and further increases to 1.0 as lane width increases from 11 feet  to 12 feet.
The crash risk for 34’ pavement width increases from 0.0 to approximately 0.8 at 11’ lane width. The line then decreases to a crash risk of 0.7 from 11’ lane width to 12’ lane width. The points are cross marked.
Highlighted circles are used to indicate small sample sizes. Refer to the data collection-4 slide for specific lane-shoulder combinations.
Account for ADT, segment length, speed, horizontal curvature, and vertical curvature.
The WA target crash model indicates the most consistent reduction in crash odds for narrow lanes with wide shoulders.
Again, there are several cases where sample size may be a concern.

## Example Odds Ratio

|   
Total Paved
Width (ft)
 | LW
(ft) | SW
(ft) | Odds
Ratio | Standard
Error | P value |        Lower
   Confidence Level. |         Lower
Confidence Level |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 32 | 10 | 6 | 1.000 | * | * | * | * |
| 32 | 11 | 5 | 1.419 | 0.197 | 0.012 | 1.081 | 1.863 |
| 32 | 12 | 4 | 1.366 | 0.185 | 0.021 | 1.047 | 1.783 |

**Notes:**
Equation. Odds Ratio bracket ij. Odds Ratio bracket ij equals exponent open bracket beta subscript 1 superscript i minus beta subscript 1 superscript j close bracket.
Equation. Standard error open bracket beta subscript 1 superscript i minus beta subscript 1 superscript j close bracket equals the square root of the sum of variance open bracket beta subscript 1 superscript i close bracket and variance open bracket beta subscript 1 superscript j close bracket minus 2 times covariance open bracket beta subscript 1 superscript i and beta subscript 1 superscript j close bracket.
Equation. 95 percent confidence interval. 95 percent confidence interval equals the exponent of the following open bracket beta subscript 1 superscript i minus beta subscript 1 superscript j close bracket plus or minus 1.96 multiplied by the standard error open bracket beta subscript 1 superscript i minus beta subscript 1 superscript j close bracket.

The previous graphs illustrated the safety effects of various lane-shoulder combinations in comparison to one baseline (12’ lane and 6’ shoulder).
We can just as easily calculate the odds ratio and confidence intervals for any baseline within a specific pavement width.
In this example, we take the 32’ pavement width and use the 10’ lane and 6’ shoulder category as the baseline to determine the relative effects of lane and shoulder width for this pavement width.
In this example, the effects of widening the lane and narrowing the shoulder increase the odds of a crash significantly
Significance can be determined by the p-value or looking at the confidence interval
If the CI includes 1.0, the results are not significantly different

## Conclusions

- Within Pavement Width
- PA: Not many significant changes
- Particularly for total crashes
- WA: General decrease in crashes for narrow lane and wide shoulder
- Target crashes in particular
- Be aware of small samples
- Within Lane Width
- General decrease in crashes as shoulder increases
- Supports model results (consistent with prior studies)
- Preliminary Results!
- Need to explore outliers
- Answer secondary questions

**Notes:**
Notes: 
The results for PA did not show many significant changes in crash odds, given a fixed pavement width.
For WA, there was a more pronounced effect for different configurations, but sample sizes may be an issue.
To confirm the validity of the results, the crash risk was plotted for similar lane widths with various shoulder widths.
Within lane widths, there was a general reduction in crash odds as shoulder width increases.
This is consistent with previous studies and supports the results of the models.
It should be noted that these results are based on a preliminary analysis and there is still work to be done.
First, the results need to be explored in more detail to evaluate outliers.
Also, there are several secondary questions that are yet to be answered.

## Future Research

- Field-verify sites in PA
- Preliminary data verification using PA video logs
- Evaluate Anomalies
- Met with PennDOT to discuss results
- Review PennDOT and WSDOT design guides
- Secondary Questions
- Do effects vary by:
- Traffic volumes?
- Speed limit?
- Economic analysis

**Notes:**
Notes: 
Future efforts will include the following.
First, data have been spot-checked using PennDOT video logs to confirm number of lanes and relative pavement widths.
May be worth spot-checking a few sites in the field to verify actual lane and shoulder widths.
We have met with PennDOT representatives to discuss the results.
Possible explanations for outliers were discussed, but no definitive conclusions were made.
May be nice to review PennDOT and WSDOT design guides to determine potential reasons for outliers.
We still need to answer the secondary questions including potential variations in the effects of lane-shoulder combinations across AADT and speed limit.
Finally, an economic evaluation will be completed to determine the cost effectiveness of this strategy.
It is expected that the strategy will be cost effective (assuming certain combinations will significantly reduce crash odds) because the allocation of pavement width only includes proper delineation.
If re-striping can be included as part of resurfacing or reconstruction projects, thee will be virtually no cost associated with the strategy.

## QUESTIONS
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