Paper Info
Title
Optimal Controls of Vehicle Trajectories in Fleet Management Using V2I Information
Abstract
Given the raised focus on transport energy and traffic-induced environmental issues, the ability of reducing vehicular environmental impacts is of great importance for intelligent traffic management. The recent development in vehicle-to-infrastructure (V2I) communication provides an effective means for continuous management of vehicle driving. This study presents an essential step of the work towards a dynamic fleet management system that takes advantages of real-time traffic information and communication. Based on the optimal control theory, a methodological approach is developed to control the environmental impacts of live vehicle fleets. In particular, vehicle trajectories that minimize local environmental objectives are derived by applying a discrete dynamic programming method. Numerical examples show that the method is promising for local V2I based traffic management applications and can be further extended for more complex optimal control problems in dynamic fleet management.
Year
DOI
Venue
2012
10.1109/ICCVE.2012.57
Connected Vehicles and Expo
Keywords
Field
DocType
continuous management,local environmental objectives,v2i information,optimal control,optimal control theory,optimal control problems,fleet management,transport energy,local v2i based traffic management applications,traffic-induced environmental issue,vehicle trajectories,environmental impact,optimal controls,vehicular environmental impacts,real-time traffic information,traffic-induced environmental issues,vehicle driving continuous management,vehicular ad hoc networks,traffic management application,intelligent traffic management,automated highways,complex optimal control problem,environmental factors,local environmental objective,dynamic fleet management,vehicle-to-infrastructure communication,dynamic programming,live vehicle fleets,vehicle to infrastructure communication,dynamic fleet management system,discrete dynamic programming method,vehicular environmental impact,real-time traffic communication,control engineering
Dynamic programming,Automotive engineering,Optimal control,Real-time data,Operations research,Vehicle driving,Intelligent transportation system,Engineering,Fleet management
Conference
ISSN
ISBN
Citations 
2378-1289
978-1-4673-4705-1
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Xiaoliang Ma118218.51
Jonas Martensson262.57