Special Issue "Positioning and Tracking Sensors and Technologies in Road Transport"
A special issue of Sensors (ISSN 1424-8220).
Deadline for manuscript submissions: closed (15 September 2014)
Dr. Felipe Jimenez
University Institute for Automobile Research (INSIA), Technical University of Madrid, INSIA, Campus Sur UPM, Carretera de Valencia km 7 28031, Madrid, Spain
Phone: +34 913365317
Fax: +34 913365302
Interests: intelligent transport systems, advanced driver assistance systems, vehicle positioning, GNSS, inertial sensors, digital maps, vehicle dynamics, driver monitoring, vehicle automation, V2X communications
Dr. Jose Naranjo
University Institute for Automobile Research (INSIA), Technical University of Madrid, INSIA, Campus Sur UPM, Carretera de Valencia km 7 28031, Madrid
Interests: intelligent transport systems, advanced driver assistance systems, vehicle positioning, GNSS, vehicle automation V2V communications
Vehicle positioning is becoming more and more relevant in many applications in road transport. The accuracy requirements are not the same for all of them and, in general, safety applications are more restrictive. Global Navigation Satellite Systems (GNSS) positioning does not guarantee a specific and constant level of accuracy. A widespread solution for dealing with GNSS positioning limitations is to combine GNSS positioning with inertial sensors or computer vision technologies. The algorithms developed for data fusion should be based on determining the confidence level of each measure. On the other hand, apart from specifically oriented instrumentation, accuracy of smartphones that offer geopositioning should be assessed.
Another problem is the interrelationship between the positioning system and location in the digital map. This problem is not trivial when dealing with imprecise information. In such cases, providing a specific location of a vehicle on a roadway presents difficulties in complex scenarios, and involves implementing complex and reliable algorithms. Map-matching algorithms try to overcome the inaccuracies of digital maps and positioning systems
Finally, over the years and the evolution of in-vehicle technologies and communications with the vehicle surroundings, there has been an important group of applications that may rely more or less on vehicle positioning and tracking.
Contributions related to vehicle tracking and positioning, using satellite systems, inertial sensors or other means will be considered. Also, submissions focused on the uncertainty of these kinds of positioning systems and the solutions that overcome such inaccuracy will also be considered. Contributions focused on specific applications in road transport should clearly indicate which challenges in positioning the work is addressing. Authors are invited to contact the guest editors, prior to submission, if they are uncertain whether their work falls within the general scope of this Special Issue.
Dr. Felipe Jimenez
Dr. Jose Eugenio Naranjo
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. Sensors is an international peer-reviewed Open Access monthly journal published by MDPI.
- vehicle tracking
- satellite positioning
- inertial sensors
- sensor fusion
- digital maps
- map-matching algorithm
- visual odometry
- smartphones geolocation