Wireless Sensor Networks for Intelligent Transportation Systems

Franceschinis, Mirko; Gioanola, Luca; Messere, Massimiliano; Tomasi, Riccardo; Spirito, Maurizio A.; Civera, Pierluigi

doi:10.1109/vetecs.2009.5073915

Cited by 37 publications

(17 citation statements)

References 2 publications

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“…In literature several works show WSNs architectures for safety warnings signalling and for traffic lights management. In fact, in the approach proposed in [18], a WSN is used to automatically generate safety warnings at black spots along the road network. Instead, an architecture in which sensor nodes detect road information and send them to the nearest Intersection Control Agent, which determines the flow model of the intersection depending on data gathered by sensor nodes, is proposed in [19].…”

Section: Traffic Lights Management Techniques Using Wireless Sensor Nmentioning

confidence: 99%

A dynamic traffic light management system based on wireless sensor networks for the reduction of the red-light running phenomenon

Collotta

Pau

Scatà

et al. 2014

Transport and Telecommunication Journal

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The real-time knowledge of information concerning traffic light junctions represents a valid solution to congestion problems with the main aim to reduce, as much as possible, accidents. The Red Light Running (RLR) is a behavioural phenomenon that occurs when the driver must to choose to cross (or not) the road when the traffic light changes from green to yellow. Most of the time the drivers cross even during transitions from yellow to red and, as a consequence, the possibility of accidents increases. This often occurs because the drivers wait too much in the traffic light queue as a consequence of the fact that the traffic light is not well balanced. In this paper we propose a technique that, based on information gathered through a wireless sensor network, dynamically processes green times in a traffic light of an isolated intersection. The main aim is to optimise the waiting time in the queue and, as a consequence, reduce the RLR phenomenon occurrence.

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Section: Traffic Lights Management Techniques Using Wireless Sensor Nmentioning

confidence: 99%

A dynamic traffic light management system based on wireless sensor networks for the reduction of the red-light running phenomenon

Collotta

Pau

Scatà

et al. 2014

Transport and Telecommunication Journal

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“…These systems either rely on multi-hop routing to transmit information from origin to destination or they make assumptions about the potential range of each node. In [32] an implementation that assumes the average transmission range of each node to be between 500 m and 1 km is described. The focus of most studies has been on the system architecture [31] and little attention has been paid to wireless signal propagation issues.…”

Section: Introductionmentioning

confidence: 99%

Signal Propagation Analysis for Low Data Rate Wireless Sensor Network Applications in Sport Grounds and on Roads

Ndzi¹,

Arif²,

Shakaff³

et al. 2012

PIER

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Abstract-This paper presents results of a study to characterise wireless point-to-point channel for wireless sensor networks applications in sport hard court arenas, grass fields and on roads. Antenna height and orientation effects on coverage are also studied and results show that for omni-directional patch antenna, node range is reduced by a factor of 2 when the antenna orientation is changed from vertical to horizontal. The maximum range for a wireless node on a hard court sport arena has been determined to be 70 m for 0 dBm transmission but this reduces to 60 m on a road surface and to 50 m on a grass field. For horizontal antenna orientation the range on the road is longer than on the sport court which shows that scattered signal components from the rougher road surface combine to extend the communication range. The channels investigated showed that packet error ratio (PER) is dominated by large-scale, rather than small-scale, channel fading with an abrupt transition from low PER to 100% PER. Results also show that large-scale received signal power can be modeled with a 2nd order log-distance polynomial equation on the sport court and road, but a 1st order model is sufficient for the grass field. Small-scale signal variations have been found to have a Rice distribution for signal to noise ratio levels greater than 10 dB but the Rice K-factor exhibits

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“…The paper [4] presents a project aimed to "provide a wireless solution for obtaining traffic-related data that can be used for automatically generating safety warnings at black spots along the road network". The WSN consists of numerous sensors deployed along the road.…”

Section: A Wireless Sensor Networkmentioning

confidence: 99%

The Tool for Modeling of Wireless Sensor Networks with Nested Petri Nets

Nina¹,

Leonid

2013

Proceedings of the Spring/Summer Young Researchers' Colloquium on Software Engineering

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The work describes a specific approach to modeling and simulating Wireless Sensor Networks (WSN), using nested Petri Nets formalism. The tool for modeling/simulating WSN must take into consideration resources, time and sensors cost. Even though Petri Nets are good for modeling dynamic systems, they do not have enough means to express these aspects. Hence some extension were introduced to handle them.

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Wireless Sensor Networks for Intelligent Transportation Systems

Cited by 37 publications

References 2 publications

A dynamic traffic light management system based on wireless sensor networks for the reduction of the red-light running phenomenon

A dynamic traffic light management system based on wireless sensor networks for the reduction of the red-light running phenomenon

Signal Propagation Analysis for Low Data Rate Wireless Sensor Network Applications in Sport Grounds and on Roads

The Tool for Modeling of Wireless Sensor Networks with Nested Petri Nets

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