CONVINCE: A cross-layer modeling, exploration and validation framework for next-generation connected vehicles

Next-generation autonomous and semi-autonomous vehicles will not only precept the environment with their own sensors, but also communicate with other vehicles and surrounding infrastructures for vehicle safety and transportation efficiency. The design, analysis and validation of various vehicle-to-v...

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Vydané v:Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design s. 1 - 8
Hlavní autori: Bowen Zheng, Chung-Wei Lin, Huafeng Yu, Hengyi Liang, Qi Zhu
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: ACM 01.11.2016
Predmet:
Analytical models
Computational modeling
Mathematical model
Security
Software
Timing
Vehicles
ISSN:1558-2434
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Popis
Shrnutí:Next-generation autonomous and semi-autonomous vehicles will not only precept the environment with their own sensors, but also communicate with other vehicles and surrounding infrastructures for vehicle safety and transportation efficiency. The design, analysis and validation of various vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) applications involve multiple layers, from V2V/V2I communication networks down to software and hardware of individual vehicles, and concern with stringent requirements on multiple metrics such as timing, security, reliability and fault tolerance. To cope with these challenges, we have been developing CONVINCE, a cross-layer modeling, exploration and validation framework for connected vehicles. The framework includes mathematical models, synthesis and validation algorithms, and a heterogeneous simulator for inter-vehicle communications and intra-vehicle software and hardware in a holistic environment. It explores various design options with respect to constraints and objectives on system safety, security, reliability, cost, etc. A V2V application is used in the case study to demonstrate the effectiveness of the proposed framework.
ISSN:1558-2434
DOI:10.1145/2966986.2980078