DocumentCode :
2891248
Title :
Model predictive control for intelligent speed adaptation in Intelligent Vehicle Highway Systems
Author :
Baskar, L.D. ; Schutter, Bart De ; Hellendoorn, Hans
Author_Institution :
Delft Center for Syst. & Control, Delft Univ. of Technol., Delft
fYear :
2008
fDate :
3-5 Sept. 2008
Firstpage :
468
Lastpage :
473
Abstract :
Intelligent vehicle highway systems (IVHS) consist of automated highway systems in combination with intelligent vehicles and roadside controllers. The intelligent vehicles can communicate with each other and with the roadside infrastructure. The vehicles are organized in platoons with short intraplatoon distances, and larger distances between platoons. Moreover, all vehicles are assumed to be automated, i.e., throttle, braking, and steering commands are determined by an automated on-board controller. In this paper we first propose a model predictive control (MPC) approach to determine appropriate speeds for the platoons. Next, we discuss which prediction models are suited to be used as an on-line traffic prediction model in MPC for IVHS. The proposed approach is then applied to a simple simulation example in which the aim is to minimize the total time all vehicles spend in the network by optimally assigning speeds to the platoons.
Keywords :
automated highways; predictive control; velocity control; intelligent speed adaptation; intelligent vehicle highway systems; intraplatoon distances; model predictive control; onboard controller; roadside controllers; steering commands; throttle, braking; Automated highways; Automatic control; Communication system traffic control; Control systems; Intelligent control; Intelligent vehicles; Predictive control; Predictive models; Road transportation; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2008. CCA 2008. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2222-7
Electronic_ISBN :
978-1-4244-2223-4
Type :
conf
DOI :
10.1109/CCA.2008.4629646
Filename :
4629646
Link To Document :
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