Hayleyesus Alemayehu’s scientific contributions

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (1)


Figure 1. Most commonly used sensors and communication devices in CAVs.
Figure 2. V2X communication at a four-way intersection.
Figure 3. An integrated sequence of steps in the testing and verification framework (some graphics in this figure are AI-generated).
SAE level of automation and CDA classes.
Abbreviations and their descriptions.

+3

Testing and Verification of Connected and Autonomous Vehicles: A Review
  • Article
  • Full-text available

February 2025

·

69 Reads

·

1 Citation

Hayleyesus Alemayehu

·

Arman Sargolzaei

Connected and Autonomous Vehicles (CAVs) have the potential to revolutionize transportation by addressing critical challenges such as safety, energy efficiency, traffic congestion, and environmental impact. Realizing these benefits, however, requires the development of a rigorous testing and verification framework to enable the safe, efficient, and reliable deployment of CAVs across diverse operational scenarios. Despite the growing body of research, there remains a significant gap in review papers that comprehensively summarize recent studies related to the testing and verification of CAVs while identifying current challenges and highlighting future research directions. This paper seeks to address this gap by presenting a comprehensive review of the existing testing and verification frameworks for CAVs and identifying their associated challenges. Key topics covered include scenario generation, verification cost functions, assertion values, and security considerations. Furthermore, the paper highlights limitations within current frameworks, emphasizing the gaps that hinder systematic and comprehensive evaluations.

Download

Citations (1)


... Forensic data is processed by large amounts of AI with great speed, shortening the backlogs and enhancing decision making. Furthermore, AI is also useful in cyberforensics in threat detection, digital evidence analysis and predictive modeling for cybercrimes thereby leading to a proactive measure of digital investigations [3]. Though the AI has advanced significantly, the integration of AI into forensic science faces many issues due to data privacy, ethical concerns, and the need for explainable AI models to guarantee transparency in legal cases. ...

Reference:

Artificial Intelligence in Forensic Sciences: Bridging Systematic Challenges with Next-Generation Applications
Testing and Verification of Connected and Autonomous Vehicles: A Review