Titre :

Trajectory planning for autonomous intersection management of connected vehicles

Auteur(s) :

Liu, Bing [Auteur]
Centrale Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Shi, Qing [Auteur]
Centrale Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Song, Zhuoyue [Auteur]
Beijing Institute of Technology [BIT]
El Kamel, Abdelkader [Auteur]
Centrale Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la revue :

Simulation Modelling Practice and Theory

Pagination :

16-30

Éditeur :

Elsevier

Date de publication :

2019-01

ISSN :

1569-190X

Mot(s)-clé(s) en anglais :

Autonomous intersection management
Intelligent transportation systemsTrajectory planning
V2X communications
Dynamic programming

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Automatique / Robotique
Informatique [cs]/Automatique

Résumé en anglais : [en]

This paper proposes a cooperative scheduling mechanism for autonomous vehicles passing through an intersection, called TP-AIM. The main objective of this research is to ensure safe driving while minimizing delay in an ...
Lire la suite >This paper proposes a cooperative scheduling mechanism for autonomous vehicles passing through an intersection, called TP-AIM. The main objective of this research is to ensure safe driving while minimizing delay in an intersection without traffic lights. Firstly, an intersection management system, used as an info-collecting-organizing center, assigns reasonable priorities for all present vehicles and hence plans their trajectories. Secondly, a window searching algorithm is performed to find an entering window, which can produce a collision-free trajectory with minimal delay, besides backup windows. Finally, vehicles can arrange their trajectory individually, by applying dynamic programming to compute velocity profile, in order to pass through intersection. MATLAB/Simulink and SUMO based simulations are established among three types of traffic mechanisms with different traffic flows. The results show that the proposed TP-AIM mechanism significantly reduces the average evacuation time and increases throughput by over 20%. Moreover, the paper investigates intersection delay, which can be reduced to less than 10% compared to classical light management systems. Both safety and efficiency can be guaranteed in our proposed mechanism.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL