Paper Info
Title
A validated fuzzy logic inspired driver distraction evaluation system for road safety using artificial human driver emotion.
Abstract
This research paper presents a validated emotion enabled cognitive driver assistance model (EECDAM) as an accident prevention scheme while keeping in mind different types of driver distractions. It is observed that distracted drivers know that distraction can lead them to a crash but they are not aware of distractions when they take over and they continue to drive. With advancements in autonomous vehicles technologies, it is possible to have an onboard driver assistance systems. However, research is yet to be reported on this issue whether onboard driver assistance program will be effective or not. The Emotion Enabled Cognitive Driver Assistance Model is a system based on an encapsulated Emotion Enabled Cognitive Driver Assistant (EECDA), which computes the effects of external factors at the distraction level of the subject and generates algorithmically generated fear emotion. During experiments, the EECDA intervenes when the fear intensity of the driver crosses a threshold by sending two sound alerts to the driver to take appropriate action. To demonstrate the effectiveness of the proposed approach as a road safety system, a Cognitive Agent-Based Computing (CABC) framework has been utilized to validate the results of the EECDAM. Algorithms are utilized using fuzzy sets to compute distraction of the drivers. We also present an Agent-Based Model (ABM) to validate the implementation of the proposed scheme. Extensive experiments demonstrate the proficiency of the proposed model for robust collision avoidance.
Year
DOI
Venue
2018
10.1016/j.comnet.2018.06.007
Computer Networks
Keywords
Field
DocType
Fuzzy logic,Driver distraction learning,Artificial emotions,Safe road traffic system,Driver assistant model
Distraction,Crash,Evaluation system,Computer science,Fuzzy logic,Advanced driver assistance systems,Fuzzy set,Collision,Human–computer interaction,Cognition,Distributed computing
Journal
Volume
ISSN
Citations 
143
1389-1286
1
PageRank 
References 
Authors
0.36
11
6
Name
Order
Citations
PageRank
Faisal Riaz111.38
Sania Khadim210.36
Rabia Rauf310.36
Mudassar Ahmad432.10
Sohail Jabbar531434.55
Junaid Ahsenali Chaudhry65914.78