We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
An improved car-following model considering the impact of safety messages.
- Authors
Li, Tenglong; Hui, Fei; Zhao, Xiangmo
- Abstract
The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.
- Subjects
TRAFFIC congestion; COMPUTER simulation of traffic flow; AUTOMOBILE driving; STATISTICAL correlation; DATA mining
- Publication
Modern Physics Letters B, 2018, Vol 32, Issue 32, pN.PAG
- ISSN
0217-9849
- Publication type
Article
- DOI
10.1142/S0217984918503980