Cooperative driving: an ant colony system for autonomous intersection management

Wu, Jia; Abbas-Turki, Abdeljalil; Moudni, Abdellah El

doi:10.1007/s10489-011-0322-z

Cited by 130 publications

(61 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While efficient for low traffic, this method gave poor performance in high traffic conditions. In [31], ACO was used in a fuzzy controller for autonomous parking application in networked vehicles by researchers who developed multi-colony parallel optimization models in MATLAB. Traffic management via Internet of Vehicles (IoV) [32] was implemented in the city of Vellore, India.…”

Section: Vehicle Routing Problem and Autonomous Vehiclesmentioning

confidence: 99%

Applications of Ant Colony Optimization in Control Systems, Robotics and Vision

Jahagirdar¹,

Dhuri²,

Bobade³

et al. 2019

IJCA

View full text Add to dashboard Cite

Swarm Intelligence is driving research in multi-agent system based robotic and mobile control applications. A swarm optimization algorithm-Ant Colony Optimization (ACO) provides a stochastic 'shortest path' approach inspired by ant colonies to obtain global solution in an optimization problem. This paper reviews the impact of ACO in robotics, computer vision, control systems and sensor networks for autonomous systems. The performance of ACO as a metaheuristic or general optimization is discussed with respect to its consequences on parameters like energy efficiency, time for convergence, route selection, etc.

show abstract

Section: Vehicle Routing Problem and Autonomous Vehiclesmentioning

confidence: 99%

Applications of Ant Colony Optimization in Control Systems, Robotics and Vision

Jahagirdar¹,

Dhuri²,

Bobade³

et al. 2019

IJCA

View full text Add to dashboard Cite

show abstract

“…Vehicle collision warning/avoidance systems are introduced to improve the intersection safety, while traffic management methods, such as Cooperative Intersection Management (CIM) [17][18][19], are introduced for a smooth and comfort intersection passing.…”

Section: Cooperative Intersectionmentioning

confidence: 99%

Future Applications of VANETs

Englund

Chen

Vinel

et al. 2015

Vehicular Ad Hoc Networks

View full text Add to dashboard Cite

Current transportation systems face great challenges due to the increasing mobility. Traffic accidents, congestion, air pollution, etc., are all calling for new methods to improve the transportation system. With the US legislation in progress over vehicle communications and EU's finalization of the basic set of standards over cooperative intelligent transportation systems (C-ITS), vehicular ad hoc network (VANET) based applications are expected to address those challenges and provide solutions for a safer, more efficient and sustainable future intelligent transportation systems (ITS). In this chapter, transportation challenges are firstly summarized in respect of safety, efficiency, environmental threat, etc. A brief introduction of the VANET is discussed along with state of the art of VANET-based applications. Based on the current progress and the development trend of VANET, a number of new features of future VANET are identified, together with a set of potential future ITS applications. The on-going research and field operational test projects, which are the major enabling efforts for the future VANET-based C-ITS, are presented. The chapter is of great interest to readers working within ITS for current development status and future trend within the C-ITS area. It is also of interest to general public for an overview of the VANET enabled future transportation system.

show abstract

“…And this has motivated our research on this topic. Some other research works on autonomous intersection management can be found in [13], [23], [24].…”

Section: Introductionmentioning

confidence: 99%

Autonomous and connected intersection crossing traffic management using discrete-time occupancies trajectory

Qiang

Kim

2018

Appl Intell

View full text Add to dashboard Cite

In this paper, we address a problem of safe and efficient intersection crossing traffic management of autonomous and connected ground traffic. Toward this objective, we propose an algorithm that is called the Discrete-time occupancies trajectory based Intersection traffic Coordination Algorithm (DICA). We first prove that the basic DICA is deadlock free and also starvation free. Then, we show that the basic DICA has a computational complexity of O(n 2 L 3 m ) where n is the number of vehicles granted to cross an intersection and L m is the maximum length of intersection crossing routes. To improve the overall computational efficiency of the algorithm, the basic DICA is enhanced by several computational approaches that are proposed in this paper. The enhanced algorithm has the computational complexity of O(n 2 L m log 2 L m ). The improved computational efficiency of the enhanced algorithm is validated through simulation using an open source traffic simulator, called the Simulation of Urban MObility (SUMO). The overall throughput as well as the computational efficiency of the enhanced algorithm are also compared with those of an optimized traffic light control.

show abstract

Cooperative driving: an ant colony system for autonomous intersection management

Cited by 130 publications

References 37 publications

Applications of Ant Colony Optimization in Control Systems, Robotics and Vision

Applications of Ant Colony Optimization in Control Systems, Robotics and Vision

Future Applications of VANETs

Autonomous and connected intersection crossing traffic management using discrete-time occupancies trajectory

Contact Info

Product

Resources

About