A5102760637- Traffic and Road Safety
- Human-Automation Interaction and Safety
- Advanced Statistical Process Monitoring
- Sleep and Work-Related Fatigue
- Autonomous Vehicle Technology and Safety
- Distributed Sensor Networks and Detection Algorithms
- Target Tracking and Data Fusion in Sensor Networks
- Advanced MIMO Systems Optimization
- Safety Warnings and Signage
- Millimeter-Wave Propagation and Modeling
- Older Adults Driving Studies
- Color perception and design
- Ergonomics and Musculoskeletal Disorders
- Energy Harvesting in Wireless Networks
Purdue University West Lafayette
2024
San Francisco State University
2024
University of California, Los Angeles
2024
San Jose State University
2022-2024
Korea Advanced Institute of Science and Technology
2012-2014
In this paper, the pilot signal design for massive MIMO systems to maximize training-based received signal-to-noise ratio (SNR) is considered under two channel models: block Gauss-Markov and independent identically distributed (i.i.d.) models. First, it shown that model, optimal problem reduces a semi-definite programming (SDP) problem, which can be solved numerically by standard convex optimization tool. Second, i.i.d. an solution obtained in closed form. Numerical results show proposed...
This study aimed to investigate the impact of automated vehicle (AV) interaction mode on drivers' trust and preferred driving styles in response pedestrian- traffic-related road events.
In this letter, the performance of mismatched likelihood ratio detectors for binary Bayesian hypothesis testing problems is considered. Based on large deviation theory, a method achieving maximum error exponent detector presented. It shown that given by generalized Chernoff information, which an extension information to case two distributions and has similar properties those original information. As application example, energy detection under Gauss-Markov signal model, detection, achieved...
A key factor to optimal acceptance and comfort of automated vehicle features is the driving style. Mismatches between driver preferred styles can make users take over more frequently or even disable automation features. This work proposes identification user style preference with multimodal signals, so could match in a continuous automatic way. We conducted simulator study 36 participants collected extensive data including behavioral, physiological, situational data. includes eye gaze,...
In this paper, the performance and optimization of energy detection stationary Gaussian signals are considered. Based on Bahadur asymptotic relative efficiency, to optimal is compared, threshold for derived. It shown that not detection, an integral equation determining provided. A numerical example equi-correlated provided, result validates our analysis in finite sample regime.