Developing inexpensive crash countermeasures for Louisiana local roads.

Details

• Creators:
  Schneider, Helmut ; Sun, Xiaoduan ; Kelle, Peter
• Corporate Creators:
  Louisiana State University (Baton Rouge, La.)
• Corporate Contributors:
  United States. Federal Highway Administration
• Subject/TRT Terms:
  • Traffic crashes
  • Countermeasures
  • Safety programs
  • Risk assessment
  • Benefit cost analysis
  • Highway safety
  • Annual average daily traffic
  • Bayes' theorem
  • Methodology
• Publication/ Report Number:
  FHWA/LA.13/503
• Resource Type:
  Tech Report
• Geographical Coverage:
  Louisiana
• Corporate Publisher:
  Louisiana. Dept. of Transportation and Development
• Abstract:
  Although 40% of all crashes in Louisiana are on local roads, local road safety improvement programs have not received ; the attention needed to reduce crashes. Local road crash countermeasures are an important part of the overall efforts to ; reduce crashes and their severity in Louisiana. The efforts to develop a local road safety program are hampered by the lack ; of appropriate risk assessment that enables local agencies to reduce crashes using low cost countermeasures. This paper ; provides a methodology that can be used by local agencies to deploy countermeasures based on a risk assessment and ; optimization to meet a fixed budget. First, a statistical model is presented to assess the risk of local road segments taking ; into account AADT and geometric features of the road segment or intersection. Secondly, low cost countermeasures are ; recommended for individual road segments and costs for improvements are assessed. Thirdly, a score which allows the ; ranking of road projects is developed for each road segment. This score incorporates the risk associated with the observed ; number of crashes, the benefits of improvements, and the total cost of a project. Finally, guidelines for a local road safety ; improvement program are presented to allow local agencies to institute procedures for a systematic system-wide road ; improvement methodology. The deliverables include an Excel application that uses OLAP to obtain a ranking of ; candidates for road improvements. This application makes use of crash data, engineering features, and AADT to compute ; empirical Bayes (EB) estimates and tail probabilities for each road segment and intersection. Road segments and ; intersections with a tail probability below 5% are selected as candidates for countermeasures. These candidates are ; evaluated using Google Earth, countermeasures are suggested, and costs and benefits of the countermeasures are obtained ; using published information. The resulting road improvement projects are then ranked using multi criteria DEA including ; costs, benefits and crash risks.
  More +
• Format:
  PDF
• Funding:
  10-5SS;30000240
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/27172/dot_27172_DS1.pdf
• File Type:
  [PDF - 2.88 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:fccdbc061958a87ad647ad4c38c6805fc1b7b5d1da6f579efab1aa449562e41b7608769d1d476e5b3c4aa8b715ac23d6aeaa09f73e1ccc90bee9119b68e056e7