dc.contributor.author |
Nellore, Kapileswar
|
|
dc.contributor.author |
Hancke, Gerhard P.
|
|
dc.date.accessioned |
2017-06-10T07:18:41Z |
|
dc.date.available |
2017-06-10T07:18:41Z |
|
dc.date.issued |
2016 |
|
dc.description.abstract |
Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible
traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence,
therefore the green light sequence is determined without taking the presence of the emergency
vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines,
etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property
and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic.
The approach combines the measurement of the distance between the emergency vehicle and an
intersection using visual sensing methods, vehicle counting and time sensitive alert transmission
within the sensor network. The distance between the emergency vehicle and the intersection is
calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance
techniques. The experimental results have shown that the Euclidean distance outperforms other
distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle
information, it is very important to have a Medium Access Control (MAC) protocol to deliver the
emergency vehicle information to the Traffic Management Center (TMC) with less delay. Then only
the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have
also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the
transmission delay for emergency messages.We have modified the medium access procedure used
in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention
window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model
for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p |
en_ZA |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en_ZA |
dc.description.librarian |
am2017 |
en_ZA |
dc.description.uri |
http://www.mdpi.com/journal/sensors |
en_ZA |
dc.identifier.citation |
Nellore, K & Hancke, GP 2016, 'Traffic management for emergency vehicle priority based on visual sensing', Sensors, vol. 16, pp. 1-22. |
en_ZA |
dc.identifier.issn |
1424-8220 |
|
dc.identifier.other |
10.3390/s16111892 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/61009 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
MDPI Publishing |
en_ZA |
dc.rights |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC-BY) license. |
en_ZA |
dc.subject |
Audio visual sensing |
en_ZA |
dc.subject |
Emergency vehicle |
en_ZA |
dc.subject |
Traffic lights |
en_ZA |
dc.subject |
Traffic monitoring |
en_ZA |
dc.subject |
Priority |
en_ZA |
dc.subject |
Distance measurement techniques |
en_ZA |
dc.subject |
Medium access control (MAC) |
en_ZA |
dc.subject |
Traffic management center (TMC) |
en_ZA |
dc.subject |
Vehicular Ad-Hoc Networks (VANETs) |
en_ZA |
dc.title |
Traffic management for emergency vehicle priority based on visual sensing |
en_ZA |
dc.type |
Article |
en_ZA |