Analysis of reservation algorithms for cooperative planning at intersections

Fortelle, Arnaud de La

doi:10.1109/itsc.2010.5624978

Cited by 92 publications

(48 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, we augment the double integrator model representing a CAV with an additional state corresponding to the distance from its preceding CAV, thus we are able to address the lateral colision constraint in the low-level optimization. Second, in several efforts reported in the literature to date, the upper-level optimization either (a) was implemented with centralized approaches [14], [15], [17]- [19]; or (b) was considered given [35], [38]; or (c) was implemented using a strict first-in-first-out queueing structure [27], [29], [32], [36]. In our proposed framework, the upper-level optimization yields, in a decentralized fashion, the optimal time for each CAV to pass a given traffic scenario along with the appropriate lane that needs to occupy.…”

Section: Comparison With Related Workmentioning

confidence: 99%

Optimal Path Planning for Connected and Automated Vehicles at Urban Intersections

Malikopoulos

Zhao

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

In this paper, we provide a decentralized theoretical framework for coordination of connected and automated vehicles (CAVs) in different traffic scenarios. The framework includes: (1) an upper-level optimization that yields for each CAV its optimal path, including the time, to pass through a given traffic scenario while alleviating congestion; and (2) a low-level optimization that yields for each CAV its optimal control input (acceleration/deceleration) to achieve the optimal path and time derived in the upper-level. We provide a complete, analytical solution of the low-level optimization problem that includes the rear-end safety constraint, where the safe distance is a function of speed, in addition to the state and control constraints. Furthermore, we provide a geometric duality framework using hyperplanes to prove strong duality of the upper-level optimization problem. The latter implies that the optimal path and time for each CAV does not activate any of the state, control, and safety constraints of the low-level optimization, thus allowing for online implementation. We validate the effectiveness of the proposed theoretical framework through simulation.

show abstract

Section: Comparison With Related Workmentioning

confidence: 99%

Optimal Path Planning for Connected and Automated Vehicles at Urban Intersections

Malikopoulos

Zhao

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

show abstract

“…In this literature, an extensive range of different prediction models has been studied and used for the transportation network to generate the prediction for traffic flow. There are some nonlinear model used for the forecasting short-term models like neural network [12], [13]and Auto-Regressive Integrated Moving Average Models (ARIMA) [18], [19]. Kalman et al [14], [15], [20]for linear models, and simulation-based methods.…”

Section: Related Workmentioning

confidence: 99%

An IoTbased Smart Architecture for Traffic Management System

Kaur¹,

Malhotra²

2017

IOSR JCE

View full text Add to dashboard Cite

“…We call autonomous intersection [8,[10][11][12], an intersection that is managed without any visible signalization. Autonomous intersection decides the sequence of robots that cross the intersection instead of computing the green time given to a particular movement.…”

Section: Autonomous Intersectionmentioning

confidence: 99%

On the conflict with dioid algebra: Autonomous Intersection Management

Abbas-Turki

Ahmane

Gao

et al. 2012

2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)

View full text Add to dashboard Cite

Abstract-Autonomous Intersection Management (AIM) is an intersection through which vehicles are independently directed according to a given policy. This is an innovative approach based on a positioning system and on the wireless negotiation of the "right of way". However, AIM raises the issue of the feasibility that is strongly related to whether the vehicles are able to cross the intersection without collisions. In this paper, instead of vehicles we used robots in order to prototype an elementary AIM. For that, we present a Petri net model of an elementary AIM. The Petri net model is used to define a centralized protocol that allows the robots to cross the intersection without collisions. This protocol uses an event observer that controls the distribution of "rights of way" to the robots. The event observer is based on a linear system of inequalities under constraints. An elementary AIM of robots is developed. Tests show that the protocol allows a safe intersection with two different scheduling algorithms. Although delayed and several losses of messages, collisions and deadlocks are avoided by means of the event observer.

show abstract

Analysis of reservation algorithms for cooperative planning at intersections

Cited by 92 publications

References 8 publications

Optimal Path Planning for Connected and Automated Vehicles at Urban Intersections

Optimal Path Planning for Connected and Automated Vehicles at Urban Intersections

An IoTbased Smart Architecture for Traffic Management System

On the conflict with dioid algebra: Autonomous Intersection Management

Contact Info

Product

Resources

About