Dynamic Curve Warning Systems

1
Dynamic Curve Warning Systems
2
Objective

• Reduce crashes and related costs.
• Catch attention of drivers that fail to heed
  static warning signs.

3
Data Collection

• Geometric Features at site.
• Curve radius, length, grade, and direction.
• Find suitable location for CMS and study
  equipment.
• AADT
• Proportion of trucks vs. cars.
• Existing warning signs.
• What is already at the site.

4
Data Collection

• Recent changes to highway.
• Speed limits, striping, etc.
• Effects of CMS can be isolated.

5
Measures of Effectiveness

• Crash reduction
• Separate data for trucks and cars from TASAS
  crash database.
• 6 month average from 5 years prior to deployment
• 6 months after deployment
• Crashes that occurred between CMS location and
  1/10th mile following endpoint of curve.

6
Measures of Effectiveness

• Speed reduction
• Stopwatch speed measurement over 300
• 300 prior to CMS and again 300 prior to BC.
• 50-100 vehicles per visit would be statistical
  sample size.
• Every 5th vehicle taken in order to be random and
  practical.
• One visit prior 9 months to deployment, 3
  afterwards 60 days, 5 months, 10 months.

7
Measures of Effectiveness

• Erratic Maneuvers
• Manual observations during visits.
• Brake Actuations, Lane Encroachments.
• May indicate drivers are attempting curve at an
  unsafe speed and correction for their actions.

8
Measures of Effectiveness

• Motorist Survey
• Importance.
• Placement.
• Visibility.
• From Trucks, cars, and RVs.
• Truck stop, rest area.

9
Measures of Effectiveness

• Maintenance Personnel Interviews
• Maintenance since installation.
• Who conducted the maintenance.
• Difficulty/ease of maintenance.

10
Lessons learned

• Stop watch within 1.1mph of radar.
• Erratic maneuvers are difficult to study.
• Can be triggered for a variety of reasons.
• Crash data should be taken for a longer period of
  time after deployment. 1-2 years perhaps.
• Drivers can be once again desensitized