Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC)
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IIHCC focuses its attention on the ways that people interact with one another and with their environment. Interest areas in this DA include smart, healthy, and sustainable cities and communities; transportation systems; human safety, health, and wellness; integrated energy systems; network science and engineering; public policy; and cyber-physical systems. The initial focus for IIHCC will be on four themes:
Ubiquitous Mobility: The location-agnostic promise of new communication and information technologies
Automated Vehicle Systems: vehicles that can transit safely and efficiently through our communities independent of a human operator
Smart Design and Construction: an intelligent, integrated, adaptable, responsive, and sustainable human-centric built environment
Energy: the underlying innovations that will be required in the production, distribution, and consumption of energy to realize such a system
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Browsing Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC) by Department "Mechanical Engineering"
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- 3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehiclesMaurya, Deepam; Khaleghian, Seyedmeysam; Sriramdas, Rammohan; Kumar, Prashant; Kishore, Ravi Anant; Kang, Min-Gyu; Kumar, Vireshwar; Song, Hyun-Cheol; Lee, Seul-Yi; Yan, Yongke; Park, Jung-Min (Jerry); Taheri, Saied; Priya, Shashank (2020-10-26)The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability. Designing efficient sensors for smart tires for autonomous vehicles remains a challenge. Here, the authors present a tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis.
- Bioinspired Tracking Control of High Speed Nonholonomic Ground VehiclesShoemaker, Adam; Leonessa, Alexander (Hindawi, 2015-10-04)The behavior of nature’s predators is considered for designing a high speed tracking controller for nonholonomic vehicles, whose dynamicsare represented using a unicycle model. To ensure that the vehicle behaves intuitively and mimics the biologically inspiredpredator-prey interaction, saturation constraints based on Ackermann steering kinematics are added. A new strategy for mapping commandsback into a viable envelope is introduced, and the restrictions are accounted for using Lyapunov stability criteria. Followingverification of the saturation constraints, the proposed algorithm was implemented on a testing platform. Stable trajectories of up to 9 m/swere achieved. The results presented show that the algorithm demonstrates significant promise in high speed trajectory tracking withobstacle avoidance.
- Effectiveness and Acceptance of Adaptive Intelligent Speed Adaptation SystemsArhin, Stephen; Eskandarian, Azim; Blum, Jeremy; Delaigue, Pierre; Soudbakhsh, Damoon (The National Academies of Sciences, Engineering, and Medicine, 2008)Intelligent speed adaptation (ISA) systems face significant consumer acceptance hurdles that limit the likelihood of widespread adoption, particularly in the United States. However, if these systems are designed as speed management systems rather than speed limiting systems, with adaptability to individual driving behavior, they may be more likely to meet with consumer acceptance. The results of a fixed-based driving simulator experiment that tested the acceptance and effectiveness of a new type of ISA, called an Advanced Vehicular Speed Adaptation System (AVSAS), are reported. The results of the experiment showed that AVSAS resulted in reductions in driver speeds across a range of roadway types. AVSAS is a speed management system that adapts to an individual driver’s speed behavior and the current driving situation. AVSAS resulted in an average reduction of 5% of the maximum speeds and 3% of the average speeds of the drivers on four road segments. As expected, AVSAS did not reduce driver speeds as much as the mandatory control ISA system, and the experiment confirmed the results of tests conducted on ISA systems largely in Europe. Conversely, the results revealed that more participants were willing to purchase AVSAS compared with the information or mandatory ISAs. Although these results show the promise of a trade-off between system effectiveness and acceptability that has been missing in mandatory and information ISA research, AVSAS suggests that a range of ISA system design requirements could encourage the adoption of ISA systems in the United States.
- Radiation Mapping in Post-Disaster Environments Using an Autonomous HelicopterTowler, Jerry; Krawiec, Bryan; Kochersberger, Kevin B. (MDPI, 2012-07-05)Recent events have highlighted the need for unmanned remote sensing in dangerous areas, particularly where structures have collapsed or explosions have occurred, to limit hazards to first responders and increase their efficiency in planning response operations. In the case of the Fukushima nuclear reactor explosion, an unmanned helicopter capable of obtaining overhead images, gathering radiation measurements, and mapping both the structural and radiation content of the environment would have given the response team invaluable data early in the disaster, thereby allowing them to understand the extent of the damage and areas where dangers to personnel existed. With this motivation, the Unmanned Systems Lab at Virginia Tech has developed a remote sensing system for radiation detection and aerial imaging using a 90 kg autonomous helicopter and sensing payloads for the radiation detection and imaging operations. The radiation payload, which is the sensor of focus in this paper, consists of a scintillating type detector with associated software and novel search algorithms to rapidly and effectively map and locate sources of high radiation intensity. By incorporating this sensing technology into an unmanned aerial vehicle system, crucial situational awareness can be gathered about a post-disaster environment and response efforts can be expedited. This paper details the radiation mapping and localization capabilities of this system as well as the testing of the various search algorithms using simulated radiation data. The various components of the system have been flight tested over a several-year period and a new production flight platform has been built to enhance reliability and maintainability. The new system is based on the Aeroscout B1-100 helicopter platform, which has a one-hour flight endurance and uses a COFDM radio system that gives the helicopter an effective range of 7 km.
- Radiation Search Operations using Scene Understanding with Autonomous UAV and UGVChristie, Gordon A.; Shoemaker, Adam; Kochersberger, Kevin B.; Tokekar, Pratap; McLean, Lance; Leonessa, Alexander (Virginia Tech, 2016-08-31)Autonomously searching for hazardous radiation sources requires the ability of the aerial and ground systems to understand the scene they are scouting. In this paper, we present systems, algorithms, and experiments to perform radiation search using unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) by employing semantic scene segmentation. The aerial data is used to identify radiological points of interest, generate an orthophoto along with a digital elevation model (DEM) of the scene, and perform semantic segmentation to assign a category (e.g. road, grass) to each pixel in the orthophoto. We perform semantic segmentation by training a model on a dataset of images we collected and annotated, using the model to perform inference on images of the test area unseen to the model, and then re fining the results with the DEM to better reason about category predictions at each pixel. We then use all of these outputs to plan a path for a UGV carrying a LiDAR to map the environment and avoid obstacles not present during the flight, and a radiation detector to collect more precise radiation measurements from the ground. Results of the analysis for each scenario tested favorably. We also note that our approach is general and has the potential to work for a variety of diff erent sensing tasks.
- Synchronization challenges in media access coordination for vehicular ad hoc networksBlum, Jeremy; Natarajan, Rajesh; Eskandarian, Azim (Wiley, 2010-01-18)Vehicular ad hoc networks (VANETs) can support a wide range of future cooperative safety and efficiency applications. However, the node density and high demand for wireless media in these networks can lead to the Timeslot Boundary Synchronization Problem, in which increased transmission collisions occur due to back-off timer synchronization. This paper proposes an enhancement to the wireless access in vehicular environments (WAVE) communications architecture to address this problem, called RAndom Propagation Initiation Delay for the Distributed Coordination Function (RAPID DCF). The effectiveness of RAPID DCF is evaluated through simulations of both single-hop and multi-hop emergency messages. In these simulations, RAPID DCF was able to improve message delivery rates by as much as 35% and reduce multi-hop message latency by as much as 18%.
- Validation of Underwater Sensor Package Using Feature Based SLAMCain, Christopher; Leonessa, Alexander (MDPI, 2016-03-17)Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.
- Wind Induced Vibration Control and Energy Harvesting of Electromagnetic Resonant Shunt Tuned Mass-Damper-Inerter for Building StructuresLuo, Yifan; Sun, Hongxin; Wang, Xiuyong; Zuo, Lei; Chen, Ning (Hindawi, 2017-07-13)This paper proposes a novel inerter-based dynamic vibration absorber, namely, electromagnetic resonant shunt tuned mass-damper-inerter (ERS-TMDI). To obtain the performances of the ERS-TMDI, the combined ERS-TMDI and a single degree of freedom system are introduced. criteria performances of the ERS-TMDI are introduced in comparison with the classical tuned mass-damper (TMD), the electromagnetic resonant shunt series TMDs (ERS-TMDs), and series-type double-mass TMDs with the aim to minimize structure damage and simultaneously harvest energy under random wind excitation. The closed form solutions, including the mechanical tuning ratio, the electrical damping ratio, the electrical tuning ratio, and the electromagnetic mechanical coupling coefficient, are obtained. It is shown that the ERS-TMDI is superior to the classical TMD, ERS-TMDs, and series-type double-mass TMDs systems for protection from structure damage. Meanwhile, in the time domain, a case study of Taipei 101 tower is presented to demonstrate the dual functions of vibration suppression and energy harvesting based on the simulation fluctuating wind series, which is generated by the inverse fast Fourier transform method. The effectiveness and robustness of ERS-TMDI in the frequency and time domain are illustrated.