Special Issue "Intelligent and Cooperative Vehicles"

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A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: closed (30 April 2015)

Special Issue Editor

Guest Editor
Dr. Vicente Milanés (Website)

RITS Team (INRIA), France
Interests: cooperative vehicles; driverless cars; intelligent traffic and transport infrastructure and vehicle-infrastructure cooperation

Special Issue Information

Dear Colleagues,

Driverless cars are receiving more and more attention because of their potential to both significantly reduce the number of road fatalities and improve drivers’ daily lives.  In spite of the relevant results achieved up until now, it is clear that there is still a long way to go before finding completely autonomous vehicles driving on public roads. Additionally, cooperation between all road agents will be crucial in the road transportation system’s near-future. Communications with vulnerable road users (i.e., pedestrians or cyclists) will play a key role in improving road safety while inter-vehicle and vehicle-infrastructure cooperation will dramatically improve traffic flow.

This Special Issue aims to cover the most recent advances in autonomous and automated vehicles, including their interaction with other vehicles, road users or infrastructure. Novel theoretical approaches or practical applications of either driverless cars or cooperative V2X systems are welcomed. Reviews and surveys of the state-of-the-art are also welcomed. Topics of interest to this Special Issue include, but are not limited to, the following topics:

  • Intelligent navigation systems
  • Vehicle location
  • Cooperative maneuvers in urban environments
  • Obstacle avoidance
  • Pedestrian detection and tracking
  • Road traffic sign detection and classification
  • Autonomous parking systems
  • Unmanned vehicle interaction
  • Multi-sensor integration
  • Driver assistance and safety systems
  • Collision prediction and mitigation
  • Sensor fusion
  • Vehicle-to-Vehicle communication systems
  • Vehicle-pedestrian-infrastructure integration

Dr. Vicente Milanés
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Published Papers (6 papers)

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Editorial

Jump to: Research

Open AccessEditorial Introduction to the Special Issue on Intelligent and Cooperative Vehicles
Electronics 2015, 4(4), 979-981; doi:10.3390/electronics4040979
Received: 18 November 2015 / Accepted: 19 November 2015 / Published: 24 November 2015
PDF Full-text (142 KB) | HTML Full-text | XML Full-text
Abstract
Intelligent vehicles constitute one of the hot research topics on the Intelligent Transportation Systems (ITS) field. The development of Advanced Driver Assistance Systems (ADAS) based on multi-fusion information coming from on-board cameras, lidar or radar sensors is leading to more sophisticated passive [...] Read more.
Intelligent vehicles constitute one of the hot research topics on the Intelligent Transportation Systems (ITS) field. The development of Advanced Driver Assistance Systems (ADAS) based on multi-fusion information coming from on-board cameras, lidar or radar sensors is leading to more sophisticated passive and active safety systems. Additionally, the growing interest in using wireless communications to connect the vehicle either with other vehicles or the infrastructure is moving the intelligent vehicle research field toward smart interaction, moving to the Cooperative ITS (C-ITS) research field. [...] Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)

Research

Jump to: Editorial

Open AccessArticle Reactive Planning of Autonomous Vehicles for Traffic Scenarios
Electronics 2015, 4(4), 739-762; doi:10.3390/electronics4040739
Received: 16 July 2015 / Revised: 30 September 2015 / Accepted: 6 October 2015 / Published: 9 October 2015
Cited by 1 | PDF Full-text (1160 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. [...] Read more.
Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. Conversely professional human drivers usually drive using instinctive means, which enables them to reach their goal almost optimally whilst still obeying all traffic laws. In this paper we propose the use of fuzzy logic for novel motion planning. The planner is generated using an evolutionary algorithm which resembles the learning stage of professional drivers. Whether to overtake or not, is a decision which affects one’s driving and the decision is made using some deliberation. We further extend the approach to perform decision making regarding overtaking for all vehicles. Further we coordinate the motion of the vehicles at a traffic crossing to avoid any potential jam or collision. Experimental results prove that by using this approach we have been able to make the vehicles move in an optimal manner in a variety of scenarios. Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)
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Open AccessArticle Roll and Bank Estimation Using GPS/INS and Suspension Deflections
Electronics 2015, 4(1), 118-149; doi:10.3390/electronics4010118
Received: 25 September 2014 / Accepted: 16 January 2015 / Published: 29 January 2015
Cited by 1 | PDF Full-text (19409 KB) | HTML Full-text | XML Full-text
Abstract
This article presents a method that provides an estimate of road bank by decoupling the vehicle roll due to the dynamics and the roll due to the road bank. Suspension deflection measurements were used to provide a measurement of the relative roll [...] Read more.
This article presents a method that provides an estimate of road bank by decoupling the vehicle roll due to the dynamics and the roll due to the road bank. Suspension deflection measurements were used to provide a measurement of the relative roll between the vehicle body frame and the axle frame or between the sprung mass and the unsprung mass, respectively. A deflection scaling parameter was found via suspension geometry and dynamic analysis. The relative roll measurement was then incorporated into two different kinematic navigation models based on extended Kalman filter (EKF) architectures. Each algorithm was tested and then verified on the Prowler ATV experimental platform at the National Center for Asphalt Technology (NCAT). Experimental data showed that both the cascaded and coupled approach performed well in providing estimates of the current vehicle roll and instantaneous road bank. Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)
Open AccessArticle Motion Detection from Mobile Robots with Fuzzy Threshold Selection in Consecutive 2D Laser Scans
Electronics 2015, 4(1), 82-93; doi:10.3390/electronics4010082
Received: 15 September 2014 / Accepted: 9 January 2015 / Published: 22 January 2015
Cited by 2 | PDF Full-text (1288 KB) | HTML Full-text | XML Full-text
Abstract
Motion detection and tracking is a relevant problem for mobile robots during navigation to avoid collisions in dynamic environments or in applications where service robots interact with humans. This paper presents a simple method to distinguish mobile obstacles from the environment that [...] Read more.
Motion detection and tracking is a relevant problem for mobile robots during navigation to avoid collisions in dynamic environments or in applications where service robots interact with humans. This paper presents a simple method to distinguish mobile obstacles from the environment that is based on applying fuzzy threshold selection to consecutive two-dimensional (2D) laser scans previously matched with robot odometry. The proposed method has been tested with the Auriga-α mobile robot in indoors to estimate the motion of nearby pedestrians. Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)
Open AccessArticle Motion Planning of Autonomous Vehicles on a Dual Carriageway without Speed Lanes
Electronics 2015, 4(1), 59-81; doi:10.3390/electronics4010059
Received: 20 October 2014 / Accepted: 29 December 2014 / Published: 13 January 2015
Cited by 1 | PDF Full-text (790 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The problem of motion planning of an autonomous vehicle amidst other vehicles on a straight road is considered. Traffic in a number of countries is unorganized, where the vehicles do not move within predefined speed lanes. In this paper, we formulate a [...] Read more.
The problem of motion planning of an autonomous vehicle amidst other vehicles on a straight road is considered. Traffic in a number of countries is unorganized, where the vehicles do not move within predefined speed lanes. In this paper, we formulate a mechanism wherein an autonomous vehicle may travel on the “wrong” side in order to overtake a vehicle. Challenges include assessing a possible overtaking opportunity, cooperating with other vehicles, partial driving on the “wrong” side of the road and safely going to and returning from the “wrong” side. The experimental results presented show vehicles cooperating to accomplish overtaking manoeuvres. Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)
Figures

Open AccessArticle Cooperative Path-Planning for Multi-Vehicle Systems
Electronics 2014, 3(4), 636-660; doi:10.3390/electronics3040636
Received: 12 September 2014 / Revised: 27 October 2014 / Accepted: 28 October 2014 / Published: 17 November 2014
Cited by 1 | PDF Full-text (2372 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density [...] Read more.
In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently. Full article
(This article belongs to the Special Issue Intelligent and Cooperative Vehicles)

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