|
Activity Number:
|
517
- Issues in Transportation Statistics
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Transportation Statistics Interest Group
|
|
Abstract #323100
|
View Presentation
|
|
Title:
|
WHY IS ROAD SAFETY BETTER UNDER DRIVING IMPAIRMENT DUE to BOTH MARIJUANA and ALCOHOL THAN EACH SEPARATELY? DATA ANALYTICS ANSWERS,Ramalingam Shanmugam1, Ram C. Tripathi2 and Karan
|
|
Author(s):
|
Ramalingam Shanmugam* and Ram Tripathi and Karan Singh
|
|
Companies:
|
Texas State University and UTSA, Texas and UT-Tyler
|
|
Keywords:
|
Confounded Poisson distribution, ;
fatal road accidents, ;
conscious self-control, ;
road safety, ;
psychologic cautionary alertness
|
|
Abstract:
|
Thoughts of encountering fatal road accidents due to impaired driver(s)are of serious concern to the public, regulating agencies, and community groups such as Mothers Against Drunk Driving (MADD). For details on impaired driving and community efforts to stop traffic deaths, the reader is referred to www.madd.org. The research for this paper is motivated by the following two facts (Arnold and Teft 2016): (1) the average number of fatal road accidents caused by drivers impaired due to alcohol alone is greater than by those impaired due to marijuana alone and (2), the average number of fatal accidents due to drivers impaired by both alcohol and marijuana is greater than the average number of fatal road accidents due to drivers impaired by either alcohol or marijuana. With an appropriate probability model for the incidences of fatal road accidents, this presentation examines and explains statistical reasons for this disparity. This probability model is named confounded Poisson distribution (CPD). Statistical properties of CPD are identi ed and applied to analyze and demystify the uncertainty patterns using the data on fatal accidents during 2013-2015 among the drivers.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2017 program
|
