Toward Optimal MEC Resource Dimensioning for a Vehicle Collision Avoidance System: A Deep Learning Approach

IEEE Network ◽  
2021 ◽  
Vol 35 (3) ◽  
pp. 74-80
Author(s):  
Bouziane Brik ◽  
Adlen Ksentini
Keyword(s):  
Deep Learning ◽  
Collision Avoidance ◽  
Learning Approach ◽  
System A ◽  
Vehicle Collision ◽  
Collision Avoidance System ◽  
Resource Dimensioning

scholarly journals A Safety Collision Avoidance Algorithm Based on Comprehensive Characteristics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Y. J. Zhang ◽  
F. Du ◽  
J. Wang ◽  
L. S. Ke ◽  
M. Wang ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Vehicle Safety ◽  
Model Parameters ◽  
Collision Risk ◽  
Environmental Characteristics ◽  
Time Model ◽  
System A ◽  
Vehicle Collision ◽  
Collision Avoidance System ◽  
The Relationship

Aiming at the requirements of vehicle safety collision avoidance system, a safety collision avoidance algorithm based on environmental characteristics and driver characteristics is proposed. By analyzing the relationship between collision avoidance time and the environment, a safety time model is established. In the established safety time model, parameters based on driver characteristics are added, which increases the flexibility of the algorithm. The algorithm can adapt to more different driving conditions and give appropriate warning thresholds. After simulation and comparison with other algorithms, the algorithm proposed in this paper can satisfied the requirements of reducing vehicle collision risk. The effectiveness and feasibility of the algorithm are verified, and the safety of vehicle driving can be improved.

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