Title

Developing A Module For Estimating Climate Warming Effects On Hydropower Pricing In California

Keywords

Data mining; Macro-level safety analysis; Random forest; Safety planning; Severe crash; Total crash

Abstract

Exploring the significant variables related to specific types of crashes is vitally important in the planning stage of a transportation network. This paper aims to identify and examine important variables associated with total crashes and severe crashes per traffic analysis zone (TAZ) in four counties of the state of Florida by applying nonparametric statistical techniques such as data mining and random forest. The intention of investigating these factors in such aggregate level analysis is to incorporate proactive safety measures in transportation planning. Total and severe crashes per TAZ were modeled to provide predictive decision trees. The variables which carried higher weight of importance for total crashes per TAZ were - total number of intersections per TAZ, airport trip productions, light truck productions, and total roadway segment length with 35 mph posted speed limit. The other significant variables identified for total crashes were total roadway length with 15 mph posted speed limit, total roadway length with 65 mph posted speed limit, and non-home based work productions. For severe crashes, total number of intersections per TAZ, light truck productions, total roadway length with 35 mph posted speed limit, and total roadway length with 65 mph posted speed limit were among the significant variables. These variables were further verified and supported by the random forest results. © 2011 Elsevier Ltd. All rights reserved.

Publication Date

3-1-2012

Publication Title

Energy Policy

Volume

42

Number of Pages

261-271

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.enpol.2011.11.083

Socpus ID

84856276335 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84856276335

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