Model predictive control for lane change decision assist system using hybrid system representation

Masakazu Mukai; Taketoshi Kawabe

doi:10.1109/SICE.2006.315230

Model predictive control for lane change decision assist system using hybrid system representation

Masakazu Mukai, Taketoshi Kawabe

Section of Measurement and Control Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Citations (Scopus)

Abstract

This paper considers an optimal lane change path generation for intelligent automobiles using hybrid system representation. A longitudinal maneuver and a lateral maneuver of automobiles are modeled. To represent a behavior of lane changes hybrid system representations, that can combine continuous dynamics and discrete dynamics are employed. An objective function is designed to obtain a smooth lane change like a skilful drivers decision. Collision avoidance conditions are also considered. The optimal lane change path generation problem by using model predictive control is formulated as mixed integer programming. The problem is solved by using multi-parametric programming. Simulation results are shown to illustrate that this control problem generates an appropriate trajectory and input.

Original language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	5120-5125
Number of pages	6
DOIs	https://doi.org/10.1109/SICE.2006.315230
Publication status	Published - Dec 1 2006
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: Oct 18 2006 → Oct 21 2006

Other

Other	2006 SICE-ICASE International Joint Conference
Country	Korea, Republic of
City	Busan
Period	10/18/06 → 10/21/06

All Science Journal Classification (ASJC) codes

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2006.315230

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Cite this

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title = "Model predictive control for lane change decision assist system using hybrid system representation",

abstract = "This paper considers an optimal lane change path generation for intelligent automobiles using hybrid system representation. A longitudinal maneuver and a lateral maneuver of automobiles are modeled. To represent a behavior of lane changes hybrid system representations, that can combine continuous dynamics and discrete dynamics are employed. An objective function is designed to obtain a smooth lane change like a skilful drivers decision. Collision avoidance conditions are also considered. The optimal lane change path generation problem by using model predictive control is formulated as mixed integer programming. The problem is solved by using multi-parametric programming. Simulation results are shown to illustrate that this control problem generates an appropriate trajectory and input.",

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AU - Kawabe, Taketoshi

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N2 - This paper considers an optimal lane change path generation for intelligent automobiles using hybrid system representation. A longitudinal maneuver and a lateral maneuver of automobiles are modeled. To represent a behavior of lane changes hybrid system representations, that can combine continuous dynamics and discrete dynamics are employed. An objective function is designed to obtain a smooth lane change like a skilful drivers decision. Collision avoidance conditions are also considered. The optimal lane change path generation problem by using model predictive control is formulated as mixed integer programming. The problem is solved by using multi-parametric programming. Simulation results are shown to illustrate that this control problem generates an appropriate trajectory and input.

AB - This paper considers an optimal lane change path generation for intelligent automobiles using hybrid system representation. A longitudinal maneuver and a lateral maneuver of automobiles are modeled. To represent a behavior of lane changes hybrid system representations, that can combine continuous dynamics and discrete dynamics are employed. An objective function is designed to obtain a smooth lane change like a skilful drivers decision. Collision avoidance conditions are also considered. The optimal lane change path generation problem by using model predictive control is formulated as mixed integer programming. The problem is solved by using multi-parametric programming. Simulation results are shown to illustrate that this control problem generates an appropriate trajectory and input.

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