Browsing by Subject "Wireless communication"

Now showing 1 - 4 of 4
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    A Bus Signal Priority System Using Automatic Vehicle Location / Global Position Systems and Wireless Communication Systems
    (University of Minnesota Center for Transportation Studies, 2008-12) Liao, Chen-Fu; Davis, Gary A.; Iyer, Priya
    Current signal priority strategies implemented in various US cities mostly utilize sensors to detect buses at a fixed or preset distance away from an intersection. Traditional presence detection systems, ideally designed for emergency vehicles, usually send signal priority request after a preprogrammed time offset as soon as transit vehicles were detected without the consideration of bus readiness. The objective of this study is to integrate the already equipped Global Positioning System/Automated Vehicle Location (GPS/AVL) system on the buses in Minneapolis and develop an adaptive signal priority system that could consider the bus schedule adherence, its number of passengers, location and speed. Buses can communicate with intersection signal controllers using wireless technology to request for signal priority. Similar setup can also be utilized for other transit-related Intelligent Transportation Systems (ITS) applications. The City of Minneapolis recently deployed wireless technology to provide residents, businesses and visitors with wireless broadband access anywhere in the city. Communication with the roadside unit (e.g., traffic controller) for signal priority may be established using the readily available 802.11x WLAN or the Dedicated Short Range Communication (DSRC) 802.11p protocol currently under development for wireless access in vehicular environment. This report documents the development, verification and validation of the embedded signal priority prototype systems, field testing results and limitations of using the City of Minneapolis Wi-Fi network for Transit Signal Priority (TSP).
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    Distributed tracking, decoding, and demodulation using wireless sensor networks.
    (2009-12) Zhu, Hao
    Recent advances in hardware technology have led to the emergence of small, low-power, and possibly mobile sensors with limited onboard processing and wireless communication capabilities. When deployed in large numbers over space, these individually primitive sensors can cooperate to form an intelligent network, the wireless sensor network (WSN), capable of measuring aspects or identities of the operational environment with unprecedented accuracy. This is a promising technology ideal for applications as diverse as environmental and healthcare monitoring, smart-house climate control, tactical surveillance, space exploration, and intelligent transportation, to name a few. The advent of WSNs enables re-thinking the field of distributed processing, whereby distributed sensors collaborate to perform power- efficient tracking of nonstationary processes, and reduced-complexity detection of multiple hypotheses. In this thesis, WSN-based distributed tracking and detection algorithms are developed, and analyzed in terms of their optimality, robustness, as well as performance. The underlying mobility and spatial diversity offered by WSNs gives rise to the interest in distributed tracking of nonstationary signals, and motivates well the distributed counterpart of Kalman filtering developed in this thesis, that is based on judicious shar- ing of sensor observations. Different from the traditional (centralized) Kalman filter, the low-energy budget per sensor necessitates transmission of reduced-dimensionality data and awareness to imperfect sensor links as integral parts of the distributed design. Adhering to these operational conditions, optimal transmission schemes are developed to minimize the corresponding tracking error by judicious allocation of each sensor's limited power in order to facilitate the fusion of most informative observations. Through wireless broadcast communications, WSNs offer a suitable platform to realize cooperative information exchange. To comply with their low-complexity radio frequency circuit, individual sensors collaborate to eliminate the ambiguity and detect the broadcasting message, either coded or modulated. As the number of candidate messages grows exponen- tially, traditional distributed detection algorithms cannot operate with the sensors' limited computation and communication capabilities. This motivates the reduced-complexity dis- tributed decoding and demodulation algorithms of this thesis that rely on in-network one- hop communications to achieve consensus on the sufficient statistics required to decipher the broadcasted message. For both algorithms, the robustness to imperfect inter-sensor links affected by additive noise or random link failures is established, and error rate analysis is provided to evaluate their performance.
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    Intersection Decision Support Surveillance System: Design, Performance and Initial Driver Behavior Quantization
    (Minnesota Department of Transportation, 2007-08) Alexander, Lee; Cheng, Pi-Ming; Donath, Max; Gorjestani, Alec; Menon, Arvind; Shankwitz, Craig
    In rural Minnesota, approximately one-third of all crashes occur at intersections. Analysis of crash statistics and reports of crashes at rural expressway through-stop intersections shows that, for drivers who stop before entering the intersection, the majority of crashes involve an error in selecting a safe gap in traffic. The Intersection Decision Support system, developed at the University of Minnesota, is intended to reduce the number of driver errors by providing better information about oncoming traffic to drivers stopped at intersections. This report deals primarily with the surveillance technology which serves as the foundation upon which the IDS system will be built. Three components of the surveillance system are described in detail in the body of the report: 1) a Mainline Sensor subsystem; 2) a Minor Road Sensor subsystem; 3) a Median Sensor subsystem. These subsystems include radar units, laser-scanning sensors, and infrared cameras, integrated with a vehicle tracking and classification unit that estimates the states of all vehicles approaching the intersection. The design, installation, performance, and reliability of each of these three subsystems are documented in the report. The report concludes with an analysis of driver gap acceptance behavior at an instrumented intersection. Gap selection is examined as a function of time of day, traffic levels, weather conditions, maneuver, and other parameters. Log-normal distributions describe gaps acceptance behavior at rural, unsignalized expressway intersections.
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    IoT Networking via Cross-technology Communication
    (2022-06) Liu, Ruofeng
    The prevalence of Internet of Things (IoT) brings various heterogeneous wireless techniques, such as Wi-Fi, LTE, ZigBee,Bluetooth, and LoRa. Due to the scarcity of spectrum resources, these wireless technologies commonly share the unlicensed industrial, scientific and medical (ISM) radio band. The coexistence scenario motivates the studies of IoT networking among heterogeneous wireless devices, which breaks the boundary between wireless protocols and paves way for a lot of novel applications (e.g., cross-technology data dissemination, data collection, location services, etc.). This dissertation focuses on the key enabler of IoT networking among heterogeneity - cross-technology communication (CTC) which allows heterogeneous wireless devices to directly exchange data without modifying their hardware. To address the critical roadblock of CTC - incompatibility in their physical (PHY) layers, we propose two approaches, demonstrating the feasibility of CTC both from high-speed to low-speed radios and from low-speed to high-speed ones. First, we present LTE2B which enables CTC from high-speed radios (e.g., LTE) to low-speed radios (e.g., ZigBee and Bluetooth). The key technical contribution is a time-domain signal emulation (TDE) approach which allows a LTE transmitter to produce emulated ZigBee or Bluetooth signal by approximating their time-domain waveform. In addition, it addresses other practical constraints (e.g., turbo coding constraint) to achieve transparent CTC with full compatibility with LTE standards. Our experiment result shows that LTE smartphones can directly disseminate messages to ZigBee devices within a 400-meter range. Second, we introduce XFi which shows the feasibility of CTC in the reverse direction, i.e., from low-speed radios (e.g., ZigBee and LoRa) to high-speed Wi-Fi. To address the fundamental limitation of bandwidth disparity, XFi adopts signal hitchhiking - low-speed IoT packets from ZigBee and LoRa devices can hitchhike on the high-speed Wi-Fi traffic and be captured by Wi-Fi radios. The unique discovery is that Wi-Fi devices can obtain the hitchhiking IoT data from the errors in decoded Wi-Fi payloads that are available in the software. The key insight enables CTC with zero modification to Wi-Fi hardware. Our evaluation demonstrates that Wi-Fi can collect data from 8 IoT devices in parallel with an overall throughput of 1.8 Mbps. Finally, we adopt CTC technique in a commercial Bluetooth location service to study and address the challenges of applying cross-technology design in real-world scenarios. We propose WiBeacon which repurposes ubiquitously deployed WiFi access points (AP) into virtual BLE beacons via only moderate software upgrades. This offers fast deployment of BLE LBS with zero additional hardware costs and low maintenance burdens. WiBeacon is carefully integrated with native WiFi services, retaining transparency to WiFi clients. We implement WiBeacon on commodity WiFi APs (with various chipsets such as Qualcomm, Broadcom, and MediaTek) and extensively evaluate it across various scenarios, including a real commercial application for courier check-ins. During the two-week pilot study, WiBeacon provides reliable services, i.e., as robust as conventional BLE beacons, for 697 users with 150 types of smartphones.