A method for detecting drivers’ intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and norm...

M odel-based test automation has helped reduce cost, provide early identification of requirements defects, and improve test coverage [1, 2, 3, 4, 5, 6]. Industry use of model-based test automation has provided insight into practical methods that use interface driven analysis with requirements mod-eling to support automated test generation. However, the term interface is used loosely in this art...

In the area of optimization of public transportation there are several methods for modeling and solving vehicle and driver scheduling problems. We designed a sequential heuristic method for solving the combined (vehicle and driver scheduling) problem. Our model is based on a modification of the vehicle schedules to satisfy driver requirements. We introduced a driver friendly approach of the opt...

Intelligent Driver Model (IDM) is a well-known microscopic model of traffic flow within the traffic engineering societies. While it is a powerful technique for modeling traffic flows, the Intelligent Driver Model lacks the potential of accommodating the notion of drivers’ heterogeneous behavior whenever they are on roads. Concerning the above mentioned, this paper takes the lane to recognize th...

.......................................................................................................................................... i Executive Summary ...................................................................................................................... 1 PART I: Introduction ...................................................................................................

Abstract – Modeling of the cascode switching structure used in Flyback converter for achieving fast startup in the deeply dimmed phase-cut LED driver is presented in this paper. The cascode structure’s inherent instability and oscillation issue is modeled and analyzed quantitatively. Three solutions are proposed to stabilize the structure and suppress the unstable voltage oscillation. Solutions...

Advanced driver assistance systems (ADAS) can be significantly improved with effective driver action prediction (DAP). Predicting driver actions early and accurately can help mitigate the effects of potentially unsafe driving behaviors and avoid possible accidents. In this paper, we formulate driver action prediction as a timeseries anomaly prediction problem. While the anomaly (driver actions ...

Our work on modeling driver behavior in a cognitive architecture has benefited greatly from two types of integration: composition of independently developed theories and models into the framework of a cognitive architecture, and generalization of common elements of theories and models into higher-level constructs within the architecture. This chapter highlights three ways in which integration b...

OBJECTIVE This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. BACKGROUND Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to ...

Driver distraction has become a critical area of study both for research in investigating human multitasking abilities and for practical purposes in developing and constraining new in-vehicle devices. This work utilizes an integratedmodel approach to predict driver distraction from a primarily cognitive secondary task. It integrates existing models for a sentence-span task and driving task and ...