Matching Items (2)

Certainty, Severity, and Low Latency Deception

Description

There has been an ongoing debate between the relative deterrent power of certainty and severity on deceptive and criminal activity, certainty being the likelihood of capture and severity being the

There has been an ongoing debate between the relative deterrent power of certainty and severity on deceptive and criminal activity, certainty being the likelihood of capture and severity being the magnitude of the potential punishment. This paper is a review of the current body of research regarding risk assessment and deception in games, specifically regarding certainty and severity. The topics of game theoretical foundations, balance, and design were covered, as were heuristics and individual differences in deceptive behavior. Using this background knowledge, this study implemented a methodology through which the risk assessments of certainty and severity can be compared behaviorally in a repeated conflict context. It was found that certainty had a significant effect on a person’s likelihood to lie, while severity did not. Exploratory data was collected using the dark triad personality quiz, though it did not ultimately show a pattern.

Contributors

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Created

Date Created
  • 2019

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Determinants of bicycle and pedestrian crash severity in San Francisco, CA

Description

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road users are particularly vulnerable to

sustain serious injuries. With this in mind, it is important to identify the factors that

influence the severity of bicyclist and pedestrian injuries in automobile collisions. This

study uses traffic collision data gathered from California Highway Patrol’s Statewide

Integrated Traffic Records System (SWITRS) to predict the most important

determinants of injury severity, given that a collision has occurred. Multivariate binomial

logistic regression models were created for both pedestrian and bicyclist collisions, with

bicyclist/pedestrian/driver characteristics and built environment characteristics used as

the independent variables. Results suggest that bicycle infrastructure is not an important

predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed

played significant roles. Pedestrian injuries were influenced by pedestrian and driver age

and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.

Understanding these key determinants that lead to severe and fatal injuries can help

local communities implement appropriate safety measures for their most susceptible

road users.

Contributors

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Created

Date Created
  • 2016