Autonomous Intersection Management systems: criteria, implementation and evaluation

Xiangjun Qian; Florent Altché; Jean Grégoire; Arnaud de La Fortelle

Autonomous Intersection Management systems: criteria, implementation and evaluation

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Author(s): Xiangjun Qian ¹ ; Florent Altché ^{1, 2} ; Jean Grégoire ³ ; Arnaud de La Fortelle ¹
- Affiliations: 1: MINES ParisTech, PSL Research University, Centre for robotics, 60 Bd St. Michel, 75006 Paris, France ;
  2: École des Ponts ParisTech, Cité Descartes, 6-8 Av Blaise Pascal, 77455 Champs-sur-Marne, France ;
  3: Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
Source: Volume 11, Issue 3, April 2017, p. 182 – 189
DOI: 10.1049/iet-its.2016.0043 , Print ISSN 1751-956X, Online ISSN 1751-9578

Received 12/02/2016, Accepted 26/02/2017, Revised 01/02/2017, Published 28/02/2017

The foreseeable large-scale deployment of autonomous vehicles in the near future raises the question of autonomous intersection management (AIM). Numerous AIM designs have been proposed, but they lack a common vision of what defines a good system. In this study, the authors discuss a set of conflicting evaluation criteria that need to be balanced in the design of an AIM system, but are often considered individually in the literature. They then introduce their own priority-based design, where an intersection controller assigns priorities to incoming vehicles. On being assigned a priority, vehicles then cross the intersection while maintaining a so-called brake-safe state with respect to higher priority vehicles, rendering the system robust. They have performed extensive simulations to showcase the properties of the proposed system, and notably that it satisfactorily balances their criteria while remaining efficient.

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