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.

https://sciendo.com/pdf/10.2478/ttj-2014-0001

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

The paper summarizes the results of the RealFusion project. One of the main objectives of this project was to study the Wireless Sensor Networks (WSN) in real-life industrial environment. The results for the evaluation of different radios utilizing 433 MHz, 868 MHz and 2.4 GHz license-free industrial, scientific and medical (ISM) bands in real-life industrial environment are presented in the paper. Also, the paper discusses the results of development and evaluation of two real-life industrial WSN use cases: the WSN for remote monitoring the amount of bulk substances in the silos of a refractory materials factory and the WSN for remote warehouse monitoring.

http://cc.oulu.fi/~kmikhayl/site-assets/pdfs/2012_BCFIC.pdf

Wireless Sensor Networks in industrial environment: Real-life evaluation results

The main challenge of intelligent transportation systems ITS is to deal with 'real-time' information to improve vehicular traffic management. Road data can be processed and used for dynamic traffic light management in order to reduce waiting times in queues. This paper proposes an innovative distributed architecture based on a wireless sensor network WSN with a network coordinator providing remote and ubiquitous authentication module for managing unexpected events. The architecture is completed by a dynamic module for street priority management depending on traffic rate. Many experimental trials have been carried out considering three different levels of traffic intensity to prove the effectiveness of the proposed approach. In a street with high traffic intensity 120 vehicles in queue, the average vehicles/second rate decrease from 6.135, using a fixed cycle traffic light, to 0.365 using the proposed traffic light measurement system. Moreover, to improve the system security, a fingerprints-based embedded authentication system has been implemented as a self-contained sensor to increase the security of distributed personal data storage. The best achieved FAR and FRR indexes are respectively 0.73% and 9.21%, with a mean elaboration time of 192.46 ms and a working frequency of 22.5 MHz.

Smart wireless sensor networks and biometric authentication for real time traffic light junctions management

Wireless sensor networks have grown significant attentions among researchers for providing a flexible and low-cost framework to design an architecture for Intelligent Transport Systems. The inherent challenges in distribution and management of sensor networks along the road require an application-specific protocol support for the network connectivity, the sensing coverage, the reliable data forwarding, and the network lifetime improvement. This paper introduces the concept of k-strip length coverage along the road, which ensures a better sensing coverage for the detection of moving vehicles compared with the conventional barrier coverage and full area coverage, in terms of the availability of sufficient information for statistical processing and the number of sensors required to be active. To extend the network lifetime, every sensor follows a sleep–wakeup schedule maintaining the network connectivity and the k-strip length coverage. This scheduling problem is modeled as a graph optimization, the NP-hardness of which motivates to design a centralized heuristic, providing an approximate solution. As a sensor network is inherently distributed in nature, properties of the centralized heuristic are explored to design a per-node solution based on local information. Performance of the proposed scheme is analyzed through simulation results.

ADCROSS: Adaptive Data Collection from Road Surveilling Sensors

Vehicular traffic monitoring and control using through road sensor network is challenging due to a continuous data streaming over the resource constrained sensor devices. The delay sensitivity and reliability of the large volume of application data as well as the scarcity of sensor resources demand efficient designing of data collection protocol. In this Chapter, a novel tree-based data gathering scheme has been proposed, exploiting the strip-like structure of the road network. An efficient scheduling mechanism is implemented to assure both the coverage and the critical power savings of the sensor nodes. The network connectivity is guaranteed throughout by the proposed tree maintenance module that handles the dynamics of the network as a result of sensor node joining and leaving events. An application message controller has been designed that works cooperatively with the tree management module, and handles continuous streaming of the application data to ensure no loss or redundancy in data delivery. The performance of the proposed scheme is evaluated using the simulation results and compared with other approaches for large data collection in sensor network.

Sensory Data Gathering for Road Traffic Monitoring: Energy Efficiency, Reliability, and Fault Tolerance

The monitoring application of wireless sensor network in road traffic is becoming wider. The traditional way always places the wireless sensor nodes randomly on roads to form the topology. By doing so, the energy of nodes is wasted and the throughput of the network is decreased. This paper proposes a new wireless sensor network topology for road traffic. The topology uses new data frame format and linear placement strategy to decrease the load of network and the transmission of redundant information. Simulation results show that the proposed topology can save the node energy, extend the network lifetime, increase the network throughput and enhance the sink node's processing ability effectively.

Xuefan Zhang

Papers

Wireless sensor network topology used for road traffic