Abstract
This study investigates the dynamics of traffic containing human-driven vehicles along with a fraction of self-organized artificial intelligence (AI) autonomous vehicles (AVs) on multilane freeways. We propose guidelines for the development of AI agents, such that a small fraction of AVs forms local constellations that significantly accelerate the entire traffic flow while reducing fuel consumption and increasing safety. Specifically, we report a 40% enhancement in traffic flow efficiency and up to a 28% reduction in fuel consumption even when only 5% of vehicles are autonomous. This scenario does not require changes to current infrastructure or communication between vehicles; it only requires proper regulations. The results indicate that more efficient, safer, faster, and greener traffic flow can be realized in the near future.
Original language | English |
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Article number | 414001 |
Journal | Journal of Physics A: Mathematical and Theoretical |
Volume | 53 |
Issue number | 41 |
DOIs | |
State | Published - 16 Oct 2020 |
Keywords
- artificial intelligence
- autonomous vehicles
- complex systems
- self organization
- statistical mechanics and learning
- statistical physics
All Science Journal Classification (ASJC) codes
- Statistical and Nonlinear Physics
- General Physics and Astronomy
- Statistics and Probability
- Mathematical Physics
- Modelling and Simulation