dc.contributor.author |
Lytrivis, P |
en |
dc.contributor.author |
Thomaidis, G |
en |
dc.contributor.author |
Tsogas, M |
en |
dc.contributor.author |
Amditis, A |
en |
dc.date.accessioned |
2014-03-01T01:35:05Z |
|
dc.date.available |
2014-03-01T01:35:05Z |
|
dc.date.issued |
2011 |
en |
dc.identifier.issn |
1524-9050 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/20966 |
|
dc.subject |
Cooperative systems |
en |
dc.subject |
data fusion |
en |
dc.subject |
path prediction |
en |
dc.subject |
road safety |
en |
dc.subject |
vehicular ad hoc networks (VANETs) |
en |
dc.subject.classification |
Engineering, Civil |
en |
dc.subject.classification |
Engineering, Electrical & Electronic |
en |
dc.subject.classification |
Transportation Science & Technology |
en |
dc.subject.other |
Cooperative systems |
en |
dc.subject.other |
Map data |
en |
dc.subject.other |
Path prediction |
en |
dc.subject.other |
Road curvature |
en |
dc.subject.other |
Road environment |
en |
dc.subject.other |
Road geometry |
en |
dc.subject.other |
Road safety |
en |
dc.subject.other |
Road users |
en |
dc.subject.other |
Safety applications |
en |
dc.subject.other |
Vehicular ad hoc networks |
en |
dc.subject.other |
Vehicular networks |
en |
dc.subject.other |
Vehicular safety |
en |
dc.subject.other |
Wireless communications |
en |
dc.subject.other |
Yaw rate |
en |
dc.subject.other |
Accident prevention |
en |
dc.subject.other |
Ad hoc networks |
en |
dc.subject.other |
Algorithms |
en |
dc.subject.other |
Data fusion |
en |
dc.subject.other |
Forecasting |
en |
dc.subject.other |
Motor transportation |
en |
dc.subject.other |
Roads and streets |
en |
dc.subject.other |
Vehicles |
en |
dc.subject.other |
Wireless telecommunication systems |
en |
dc.subject.other |
Mobile ad hoc networks |
en |
dc.title |
An advanced cooperative path prediction algorithm for safety applications in vehicular networks |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1109/TITS.2011.2123096 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/TITS.2011.2123096 |
en |
heal.identifier.secondary |
5740605 |
en |
heal.language |
English |
en |
heal.publicationDate |
2011 |
en |
heal.abstract |
Vehicular ad hoc networks (VANETs) are in the heart of current and future automotive research. Most of the current vehicular safety applications are based on sensors installed on the vehicle, e.g., radars and laserscanners. Due to the evolution of wireless networks, there is a tendency to exploit the cooperation among vehicles to enhance road safety through the related applications. Path prediction of a driver's own vehicle and other vehicles is crucial for road safety. Path prediction can assist the driver in having an enhanced perception of the road environment and of the intention of other neighboring drivers. In this paper, an advanced cooperative path prediction algorithm is presented. This algorithm gathers position, velocity, acceleration, heading, and yaw rate measurements from all connected vehicles to calculate their future paths. In addition, map data with regard to the road geometry and, in particularly, the road curvature are used to enhance the path prediction algorithm. Comparative results of the path prediction, with and without wireless communications, are discussed. In addition, the algorithm is adapted for use in the emergency-electronic-brake-lights application. The results of this adaptation are also presented. This paper is another contribution in highlighting the advantages and, at the same time, the challenges of using communications among road users. © 2006 IEEE. |
en |
heal.publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
en |
heal.journalName |
IEEE Transactions on Intelligent Transportation Systems |
en |
dc.identifier.doi |
10.1109/TITS.2011.2123096 |
en |
dc.identifier.isi |
ISI:000294550900005 |
en |
dc.identifier.volume |
12 |
en |
dc.identifier.issue |
3 |
en |
dc.identifier.spage |
669 |
en |
dc.identifier.epage |
679 |
en |