Effects of Information Filtering on Driving

Abstract

As Connected Vehicle (CV) communicates information to the driver using safety and non-safety applications, problems can occur when these individual CV applications fail to communicate effectively, or when several CV technologies attempt to communicate with the driver simultaneously. Too much information would increase the driver's workload and levels of distraction resulting in growing threat to driving safety. Connected Vehicle Systems (CVS) afford opportunities to collect and share information about the driving environment, including vehicle state, traffic dynamics, and roadway conditions to infer real time workload demands on the driver and then CVS applications filter the complexity of information presented to that driver.This filter strategy strives to maintain driving performance under high workload traffic conditions by protecting the driver's cognitive resources. The primary objective of the study is to analyze critically how interaction with CVS within different levels of traffic condition influences proxy measures for crash risk in the following variables: i) lane position variability; ii) steering wheel input variability. Analysis results showed that information filtering did have positive safety effect on driving, especially under volatile traffic condition.