Technology and Enhancements to Improve Pre-Crash Safety
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2018-09-30
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TRIS Online Accession Number:01691819
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Edition:Final Report
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Abstract:This project was a combination of multiple smaller, short-term sub-projects under the general theme of “Technology and Enhancements to Improve Pre-Crash Safety”. It focuses on technology improvements that can be implemented in intelligent and autonomous vehicles toward the goal of improving pre-crash safety. Projects include: (1) Electroencephalogram (EEG) and Lane Change Intent Evaluation on a Driving Simulator. The authors explore technologies for sensing driver attention and their impact in pre-crash scenarios. (2) Cognitive Radio Based Communication. The authors study the value of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications for improving pre-crash safety. (3) Secure, Privacy-preserving, and Efficient Communication Framework to Support Crash-Imminent Safety Situations. The authors study the impact of both intra-vehicle and inter-vehicle communication cybersecurity on pre-crash scenarios. (4) Analyzing and Mining Big Data of Driving Videos for Crash Avoidance. The purpose of this project is to construct an online video database to host big data of naturalistic driving video including crash and near miss cases from recent populated vehicle borne cameras for accident verification and the crash avoidance technology development. (5) CAAIS: Context-Aware Authentication Interchange Scheme in Vehicular Networks. This sub-project introduces an authentication interchange protocol that mixes three cryptographic frameworks to address security in vehicular network communications. (6) Safety Implications of Traffic Dynamics in Congested Freeway Traffic. This research focuses on driver behavior in the presence of large speed differentials between lanes. (7) Smart Cities: A Simple Framework for On-Demand Mobility Services. This project provides an opportunity to investigate crash imminent scenarios for slow-moving platforms in dense pedestrian environments and related human factor issues.
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