Citation

Bandyopadhyaya R, Ujjwal J. Adv. Transp. Stud. 2018; 45: 33-42.

Copyright

(Copyright © 2018, Arcane Publishers)

DOI

unavailable

PMID

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Abstract

Identifying high crash locations or hotspots is essential for focusing road safety improvement efforts. Hot spot identification (HSID) techniques generally utilize some metric like equivalent cost, observed counts, expected counts, expected severe counts or Accident Reduction Potential (ARP). However, each technique has fair chances of false identifications. Also, it is difficult to demarcate a location as truly safe or truly hazardous, as each location can have a certain degree of hazard from low to high. Locations can thus be categorized based on degree of hazard and safety improvement potential into level of service of safety (LOSS) groups. Determining LOSS requires complex mathematical models and data of crash history, traffic exposure and road inventory. It will be beneficial if simple easy to assess factors can be related with LOSS of roads. Identification of such factors may help in categorizing roads into different LOSS groups in absence of systematic crash data and complex safety performance functions. The present work develops a guideline for determining LOSS of two-lane rural highway using road geometry and roadside features only. With this guideline LOSS can be assessed even when systematic crash history database, traffic exposure and or prediction models (SPFs) are not available. The guidelines are developed using data from two lane rural highways in Patna, Bihar, India. It was observed that LOSS has distinct relationship with the road geometry features including carriageway width, shoulder width, distance to off shoulder hazards and with roadside features, mainly the land use and number of accesses per km.

Keywords: Level of Service of Safety (LOSS); two lane highway safety; roadside features; apriori algorithm

Language: en