Vehicle Platoon Control with Multi-configuration Ability

El-Zaher, Madeleine; Dafflon, Baudouin; Gechter, Franck; Contet, Jean-Michel

doi:10.1016/j.procs.2012.04.165

Cited by 26 publications

(10 citation statements)

References 12 publications

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“…This requires very high reliability and ultra-low delay data transmission, namely, vehicles should control the delay caused by the process of information processing and exchanging within 100 ms. On the other side, platooning is able to reduce fuel consumption and gas emission, as well as safe and efficient transportation in the context of intelligent transportation system (ITS) [3]. Generally, the platoon consists of two kinds of members: one is the leader (controller) and others are the members of the platoon (including the tail vehicle, the relay vehicle) [4], as shown in Figure 1. The longitudinal and lateral positions of each vehicle in the platoon are controlled by the collected data and vehicle status information (such as speed, acceleration, deceleration and location and so on).…”

Section: Introductionmentioning

confidence: 99%

Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning

Fan

Cui

Cao

et al. 2019

Sensors

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In this paper, we study the offloading decision of collaborative task execution between platoon and Mobile Edge Computing (MEC) server. The mobile application is represented by a series of fine-grained tasks that form a linear topology, each of which is either executed on a local vehicle, offloaded to other members of the platoon, or offloaded to a MEC server. The objective of the design is to minimize the cost of tasks offloading and meets the deadline of tasks execution. The cost minimized task decision problem is transformed into the shortest path problem, which is limited by the deadline of the tasks on a directed acyclic graph. The classical Lagrangian Relaxation-based Aggregated Cost (LARAC) algorithm is adopted to solve the problem approximately. Numerical analysis shows that the scheduling method of the tasks decision can be well applied to the platoon scenario and execute the tasks in cooperation with the MEC server. In addition, compared with task local execution, platoon execution and MEC server execution, the optimal offloading decision for collaborative task execution can significantly reduce the cost of task execution and meet deadlines.

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Section: Introductionmentioning

confidence: 99%

Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning

Fan

Cui

Cao

et al. 2019

Sensors

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“…The most widely studied platoon configuration in transportation is the column, also known as road trains, although other types of formations can also be considered [1]. Platooning enables vehicles to drive closer (maintain a smaller headway) than normal vehicles with the same speed, which improves traffic throughput as well as homogeneity.…”

Section: Introductionmentioning

confidence: 99%

Platoon management with cooperative adaptive cruise control enabled by VANET

Amoozadeh

Deng

Chuah

et al. 2015

Vehicular Communications

276

147

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TitlePlatoon management with cooperative adaptive cruise control enabled by VANET AbstractPrevious studies have shown the ability of vehicle platooning to improve highway safety and throughput. With Vehicular Ad-hoc Network (VANET) and Cooperative Adaptive Cruise Control (CACC) system, vehicle platooning with small headway becomes feasible. In this paper, we developed a platoon management protocol for CACC vehicles based on wireless communication through VANET. This protocol includes three basic platooning maneuvers and a set of micro-commands to accomplish these maneuvers. Various platooning operations such as vehicle entry and vehicle (including platoon leader) leaving can be captured by these basic platoon maneuvers. The protocol operation is described in detail using various Finite State Machines (FSM), and can be applied in collaborative driving and intelligent highway systems. This protocol is implemented in an integrated simulation platform, VENTOS, which is developed based on SUMO and OMNET++. The validity and effectiveness of our approach is shown by means of simulations, and different platooning setting are calibrated.

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“…The coordination between vehicles in the platoon is based on the frequent exchange of communication messages containing information about vehicle's position, speed, acceleration and other attributes. A set of vehicles in the platoon have a predefined geometrical configuration, while the most widely studied platoon configuration is the column or train configuration, often called Road Train (RT) [7]. The behaviour of vehicles in the Platoon is expressed through the control system and it is based on distance relations between these vehicles [8].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Automaton Based Vehicle Platoon Modelling and Cooperation Behaviour Profile Prediction

Banjanović-Mehmedović

Butigan²,

Mehmedović³

et al. 2018

Teh. vjesn.

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Autonomous cooperative driving systems require the integration of research activities in the field of embedded systems, robotics, communication, control and artificial intelligence in order to create a secure and intelligent autonomous drivers behaviour patterns in the traffic. Beside autonomous vehicle management, an important research focus is on the cooperation behaviour management. In this paper, we propose hybrid automaton modelling to emulate flexible vehicle Platoon and vehicles cooperation interactions. We introduce novel coding function for Platoon cooperation behaviour profile generation in time, which depends of vehicles number in Platoon and behaviour types. As the behaviour prediction of transportation systems, one of the primarily used methods of artificial intelligence in Intelligent Transport Systems, we propose an approach towards NARX neural network prediction of Platoon cooperation behaviour profile. With incorporation of Platoon manoeuvres dynamic prediction, which is capable of analysing traffic behaviour, this approach would be useful for secure implementation of real autonomous vehicles cooperation.

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Vehicle Platoon Control with Multi-configuration Ability

Cited by 26 publications

References 12 publications

Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning

Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning

Platoon management with cooperative adaptive cruise control enabled by VANET

Hybrid Automaton Based Vehicle Platoon Modelling and Cooperation Behaviour Profile Prediction

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