Adaptive traffic light cycle time controller using microcontrollers and crowdsource data of Google APIs for developing countries

Mishra, S., Bhattacharya, D., Gupta, A., & Singh, V. R. (2018). Adaptive traffic light cycle time controller using microcontrollers and crwodsource data of Google APIs for developing countries. In 3rd International Conference on Smart Data and Smart Cities (4/W7 ed., Vol. 4, pp. 83-90). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). DOI: 10.5194/isprs-annals-IV-4-W7-83-2018Controlling of traffic signals optimally helps in avoiding traffic jams as vehicle volume density changes on temporally short and spatially small scales. Nowadays, due to embedded system development with the rising standards of computational technology, condense electronics boards as well as software packages, system can be developed for controlling cycle time in real time. At present, the traffic control systems in India lack intelligence and act as an open-loop control system, with no feedback or sensing network, due to the high costs involved. This paper aims to improve the traffic control system by integrating different technologies to provide intelligent feedback to the existing network with congestion status adapting to the changing traffic density patterns. The system presented in this paper aims to sense real-time traffic congestion around the traffic light using Google API crowdsource data and hence avoids infrastructure cost of sensors. Subsequently, it manipulates the signal timing by triggering and conveying information to the timer control system. Generic information processing and communication hardware system designed in this paper has been tested and found to be functional for a pilot run in real time. Both simulation and hardware trials show the transmission of required information with an average time delay of 1.2 seconds that is comparatively very small considering cycle time.publishersversionpublishe

Instrumentation for safe vehicular flow in intelligent traffic control systems using wireless networks

This paper describes a ZigBee based wireless system to assists traffic flow on arterial urban roads. Real-time simulation in laboratory environment is conducted to determine the traffic throughput to avoid possible congestions or ease existing congestions. Random numbers are generated to mimic approaching traffic, and this information is shared by a ZigBeebased real-time wirelessly network. Wireless nodes are connected to different PLCs representing different traffic lights in a cluster. Once the information is shared the timing and sequencing decisions are taken collectively in a synchronized manner. In this paper, the information is displayed on SCADA connected to each PLC for viewing the characteristics of continuous vehicular flow. It is found that the topology of the network can play an important role in the throughput of data, which may be critical in safety critical operations such as the control of traffic lights. This paper aims to highlight some of the possible effects of dataflow flow and time-delays faced by modern intelligent control of traffic lights

ADAPTIVE TRAFFIC LIGHT CYCLE TIME CONTROLLER USING MICROCONTROLLERS AND CROWDSOURCE DATA OF GOOGLE APIs FOR DEVELOPING COUNTRIES

Mishra, S., Bhattacharya, D., Gupta, A., & Singh, V. R. (2018). Adaptive traffic light cycle time controller using microcontrollers and crwodsource data of Google APIs for developing countries. In 3rd International Conference on Smart Data and Smart Cities (4/W7 ed., Vol. 4, pp. 83-90). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). DOI: 10.5194/isprs-annals-IV-4-W7-83-2018 Controlling of traffic signals optimally helps in avoiding traffic jams as vehicle volume density changes on temporally short and spatially small scales. Nowadays, due to embedded system development with the rising standards of computational technology, condense electronics boards as well as software packages, system can be developed for controlling cycle time in real time. At present, the traffic control systems in India lack intelligence and act as an open-loop control system, with no feedback or sensing network, due to the high costs involved. This paper aims to improve the traffic control system by integrating different technologies to provide intelligent feedback to the existing network with congestion status adapting to the changing traffic density patterns. The system presented in this paper aims to sense real-time traffic congestion around the traffic light using Google API crowdsource data and hence avoids infrastructure cost of sensors. Subsequently, it manipulates the signal timing by triggering and conveying information to the timer control system. Generic information processing and communication hardware system designed in this paper has been tested and found to be functional for a pilot run in real time. Both simulation and hardware trials show the transmission of required information with an average time delay of 1.2 seconds that is comparatively very small considering cycle time. publishersversion published Document type: Articl

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities

It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed decisions about their travel plans, thereby preventing congestion altogether or mitigating its nefarious effects

Building Decentralized Fog Computing-Based Smart Parking Systems: From Deterministic Propagation Modeling to Practical Deployment

[Abstract] The traditional process of finding a vacant parking slot is often inefficient: it increases driving time, traffic congestion, fuel consumption and exhaust emissions. To address such problems, smart parking systems have been proposed to help drivers to find available parking slots faster using latest sensing and communications technologies. However, the deployment of the communications infrastructure of a smart parking is not straightforward due to multiple factors that may affect wireless propagation. Moreover, a smart parking system needs to provide not only accurate information on available spots, but also fast responses while guaranteeing the system availability even in the case of lacking connectivity. This article describes the development of a decentralized low-latency smart parking system: from its conception, design and theoretical simulation, to its empirical validation. Thus, this work first characterizes a real-world scenario and proposes a fog computing and Internet of Things (IoT) based communications architecture to provide smart parking services. Next, a thorough analysis on the wireless channel properties is carried out by means of an in-house developed deterministic 3D-Ray Launching (3D-RL) tool. The obtained results are validated through a real-world measurement campaign and then the communications architecture is implemented by using ZigBee sensor nodes. The implemented architecture also makes use of Bluetooth Low Energy beacons, an Android app, a decentralized database and fog computing gateways, whose performance is evaluated in terms of response latency and processing rate. Results show that the proposed system is able to deliver information to the drivers fast, with no need for relying on remote servers. As a consequence, the presented development methodology and communications evaluation tool can be useful for future smart parking developers, which can determine the optimal locations of the wireless transceivers during the simulation stage and then deploy a system that can provide fast responses and decentralized services.Xunta de Galicia; ED431G2019/01Agencia Estatal de Investigación of Spain; TEC2016-75067-C4-1-RAgencia Estatal de Investigación of Spain; RED2018-102668-TAgencia Estatal de Investigación of Spain; PID2019-104958RB-C42Ministerio de Ciencia, Innovación y Universidades; RTI2018-095499-B-C3