scholarly journals Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

Sensors ◽  
2015 ◽  
Vol 15 (9) ◽  
pp. 23262-23285 ◽  
Author(s):  
Kazi Alam ◽  
Mukesh Saini ◽  
Abdulmotaleb Saddik
Keyword(s):  
Dynamic Adaptation ◽  
Internet Of Vehicles ◽  
Model Based

Robust dynamic adaptation of the Smagorinsky model based on a sub-grid activity sensor

2021 ◽  
Vol 33 (1) ◽  
pp. 015117
Author(s):  
J. Hasslberger ◽  
L. Engelmann ◽  
A. Kempf ◽  
M. Klein
Keyword(s):  
Dynamic Adaptation ◽  
Smagorinsky Model ◽  
Model Based

Collaboration optimization model of dynamic traffic control and guidance based on Internet of Vehicles

2018 ◽  
Vol 32 (22) ◽  
pp. 1850253
Author(s):  
Zhi-Yuan Sun ◽  
Yue Li ◽  
Wen-Cong Qu ◽  
Yan-Yan Chen
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Optimization Model ◽  
Programming Model ◽  
Urban Traffic ◽  
Middle Level ◽  
Internet Of Vehicles ◽  
Model Based ◽  
Level Model ◽  
Upper Level

In order to improve the comprehensive effect of Urban Traffic Control System (UTCS) and Urban Traffic Flow Guidance System (UTFGS), this paper puts forward a collaboration optimization model of dynamic traffic control and guidance based on Internet of Vehicles (IOV). With consideration of dynamic constraints of UTCS and UTFGS, UTCS is taken as the fast variable, and UTFGS is taken as the slow variable in the collaboration optimization modeling. The conception of Variable Cycle Management (VCM) is presented to solve the mathematical modeling problem under the background of the two variables. A unified framework for VCM is proposed based on IOV. The delay and travel time are calculated based on lane-group-based cell transmission model (LGCTM). The collaboration optimization problem is abstracted into a tri-level programming model. The upper level model is a cycle length optimization model based on multi-objective programming. The middle level model is a dynamic signal control decision model based on fairness analysis. The lower level model is a user equilibrium model based on average travel time. A Heuristic Iterative Optimization Algorithm (HIOA) is set up to solve the tri-level programming model. The upper level model is solved by Non-dominated Sorting Genetic Algorithm II (NSGA II), the middle level model and the lower level model are solved by Method of Successive Averages (MSA). A case study shows the efficiency and applicability of the proposed model and algorithm.

scholarly journals Location Prediction Model Based on the Internet of Vehicles for Assistance to Medical Vehicles

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 10754-10767
Author(s):  
Jiujun Cheng ◽  
Huaichen Yan ◽  
Aiguo Zhou ◽  
Chunmei Liu ◽  
Ding Cheng ◽  
...  
Keyword(s):  
Prediction Model ◽  
The Internet ◽  
Location Prediction ◽  
Internet Of Vehicles ◽  
Model Based
Sign in / Sign up

Export Citation Format

Share Document