The Internet-of-Things (IoT) is a vision for an internetwork of intelligent, communicating objects such as home appliances, vehicles, factory machines, wearable devices and various types of sensors. The convergence of technologies like ubiquitous wireless communications, machine learning, real-time analytics and embedded systems has made novel IoT applications possible in a multitude of domains. A combination of commercial interests and government initiatives have made smart homes, smart healthcare, smart cities, and smart transport primary areas of focus for IoT application development.
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This paper analyzes urban taxi mobility traces obtained from San Francisco Yellow cabs. The paper presents a rigorous analysis of taxi mobility pattern with the instantaneous velocity profile, spatio-temporal distribution, connectivity of vehicle communications, clustering, hotspots and other characteristics like trip duration and empty cruise interval. The empirical data analyses presented here can be a helpful resource for wireless researchers, government organizations, taxi companies and even for the drivers or passengers. While wireless researchers can estimate the capabilities and constraints of vehicular communication from connectivity and mobility patterns, government can plan and work on issues related to implementing proper DSRC infrastructure. Finally, taxi companies and drivers can benefit from maximizing the trip revenue and minimize empty cruise time though balanced loaddistribution and awareness of the hotspots. (Abstract)
The augmented scale and complexity of urban transportation networks have significantly increased the execution time and resource requirements of vehicular network simulations, exceeding the capabilities of sequential simulators. The need for a parallel and distributed simulation environment is inevitable from a smart city perspective, especially when the entire city-wide information system is expected to be integrated with numerous services and ITS applications. In this paper, we present a conceptual model of an Integrated Distributed Connected Vehicle Simulator (IDCVS) that can emulate real-time traffic in a large metro area by incorporating hardware-in-the-loop simulation together with the closed-loop coupling of SUMO and OMNET++. We also discuss the challenges, issues, and solution approaches for implementing such a parallel closed-loop transportation network simulator by addressing transportation network partitioning problems, synchronization, and scalability issues. One unique feature of the envisioned integrated simulation tool is that it utilizes the vehicle traces collected through multiple roadway sensors-DSRC onboard unit, magnetometer, loop detector, and video detector. Another major feature of the proposed model is the incorporation of hybrid parallelism in both transportation and communication simulation platforms. We identify the challenges and issues involved in IDCVS to incorporate this multi-level parallelism. We also discuss the approaches for integrating hardware-in-the-loop simulation, addressing the steps involved in preprocessing sensor data, filtering, and extrapolating missing data, managing large real-time traffic data, and handling different data formats. W Pre-print (Authors' Version) Communication (DSRC) technology. Automakers and technology developers like Google, Ford, and General Motors etc. are working to improve the controllability features of autonomous or semi-autonomous vehicles. While self-driving cars can potentially reduce the stress of navigating through congested traffic, CVs can optimize the traffic flow across an entire transportation network through the exchange of information among vehicles and infrastructure. CV applications use information obtained through V2X communications to assist drivers in avoiding congestion, reducing vehicle stops, choosing the best route, and optimizing fuel efficiency. Hence, CV-based emerging Intelligent Transportation Systems (ITS) applications can result in transformative changes to the overall surface transportation system.To accurately simulate ITS applications on a scenario involving connected vehicles, it is necessary to integrate a full-fledged transportation simulator with a wireless network simulator, resulting in the need for a closed-loop simulator. This kind of closed-loop simulator requires a tight synchronization between two stand-alone simulation modules: a transportation module and a communication module. The transportation module is responsible for the modeling of vehicle mobility applications including traffic routing, ca...
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