Feasibility of Bluetooth Data as a Surrogate Analysis Measure of Traffic

Background The proliferation of portable electronic devices among consumers has created in recent times new opportunities for traffic data collection. Many of these devices contain short range Bluetooth radios in addition to other electronic equipment. The included Bluetooth radio on each device was intended to provide a low-power communications protocol to connect devices such as cell phones, headphones, music players, and more to each other. The presence of a unique identification number as part of the Bluetooth protocol on each device, that when activated can be discovered electronically, unintentionally creates anonymous probes in the traffic stream. This research explored possibilities of using Bluetooth technologies for various traffic data collection studies to expand the tools available to traffic engineers. Data Collection This study began with testing Bluetooth roadside data logger hardware configurations. Controllable variables included Bluetooth antenna selection and roadside placement options. Through the use of controlled conditions, detection areas for five antenna options were mapped, and their detection reliabilities were assessed. Other tests were conducted to assess the impacts of roadside antenna placement, vehicular speeds and in-vehicle source placement. This research then builds on the data collected about Bluetooth hardware performance metrics by investigating the feasibility of using Bluetooth data as a surrogate for traditional traffic engineering data for several traffic study applications. These studies included: urban corridor travel time monitoring, freeway travel time monitoring, origin-destination studies, and estimating turning movements at roundabouts. Each of these studies was parallel in nature to each other and showed how the same technology could be applied to different study objectives. Analysis The data collected during each of the studies provided valuable insight into Bluetooth technology. The hardware evaluations showed that a dipole antenna placed 6-12 feet from the edge of the roadway with at least 3 feet of elevation performed the best. The antenna power of the dipole could be changed to increase or reduce the coverage area as needed. The urban corridor study found that the Bluetooth data collection method provided similar results in a before-after analysis as GPS probe vehicles. The urban freeway corridor study found statistically significant differences in travel time data compared with permanent travel time sensor data provided by the regional traffic management center for seven of the eight freeway corridor segments tested. However, these differences were small and appeared not to be practically significantly different. The origin-destination study found no significant differences for either travel times or percentage or through trips between Bluetooth data collection and video re-identification of vehicles. Finally, the roundabout study showed that estimates of turning movement counts could be successfully accomplished, but in one case was significantly different than manual count data; additional research is needed to better understand the differences in roundabout turning movement counts. Conclusions The use of Bluetooth technology showed new possibilities for data collection. The data collected allowed for an automated process for identifying and re-identifying vehicles along a corridor. Traditional traffic study methodologies, such pairing of vehicular data or simply observing (counting) traffic flows, required many hours of labor intensive data collection that could be replicated with Bluetooth technology in a matter of minutes. Additionally, Bluetooth data sets opened up new potential analyses of the data. Such additional analyses included being able to separate frequent (repeat) travelers from occasional travelers along a corridor. While this technology was found to have enormous potential, it was not found to be completely stand-alone. The chief weakness of the technology was that it was found to sample around 5 percent of the available traffic. The implication of this was that Bluetooth data were not always available or sufficient in size for analysis. This could be a particular issue when one needs to delineate a day into small time frames. Furthermore, because of this unintentional use of Bluetooth technology, there was not any way to guarantee data to be available at the time periods needed. Also, in order to extrapolate volumetric data from the Bluetooth data, a secondary source was needed to assess a Bluetooth penetration rate. Thus the abandonment of current technologies and methodologies would undermine this data collection technique. A key assumption was that each Bluetooth source detected represented a separate independent vehicle. While this assumption could be violated with multiple discoverable Bluetooth devices in a single vehicle (e.g. a transit bus), this was not found to be an issue. Through this research it has been shown that the use of Bluetooth technology has earned its place in an engineer's toolbox

Exploration Of New Methods In Long Distance Transportation Data Collection And Tourism Travel In Vermont

ABSTRACT Human transportation patterns have continued to shift and increase in rate as technology has made travel between spatially disparate locations more feasible. These movements are responsible for approximately one third of global carbon emissions, and account for one half of Vermont’s greenhouse gas output. Modeling transportation behaviors is difficult due to changing travel patterns and issues of surveying human participants. Long distance travel patterns are especially difficult and have not received the attention that urban mobility has within the literature. In this Masters thesis, I describe current methods of transportation data collection and propose new methods, as well as attempt to quantify the impact on Vermont’s roadways of the transportation-based tourism sector. In the first chapter of this thesis, I describe a GPS-based travel survey conducted over the course of one year, coupled with interview data of long distance trips undertaken by 10 participants. Long distance travel has historically been underrepresented in travel surveying due to its infrequency, resulting in decreased likelihood of capturing a long distance trip in a short travel study. By extracting points at intervals from the GPS dataset, it becomes possible to determine accuracy of trip matching between the two datasets with adjusted data collection methods. The second chapter examines transportation related to tourism in Vermont. As one of Vermont’s largest industry sectors, economic impact has been of particular interest to state planners. However, limited analyses of the transportation impacts of this sector are currently available. My research models route choice of drive through tourists, whom constitute 40% of visitors, attempting to begin quantifying tourist mileage and CO2 emissions within the state. Together, these studies expand knowledge on long distance transport data collection and the role of tourism in Vermont’s transportation mileage

Matching Vehicle License Plate Numbers Using License Plate Recognition and Text Mining Techniques

License plate recognition (LPR) technology has been widely applied in many different transportation applications such as enforcement, vehicle monitoring and access control. In most applications involving enforcement (e.g. cashless toll collection, congestion charging) and access control (e.g. car parking) a plate is recognized at one location (or checkpoint) and compared against a list of authorized vehicles. In this research I dealt with applications where a vehicle is detected at two locations and there is no list of reference for vehicle identification. There seems to be very little effort in the past to exploit all information generated by LPR systems. In nowadays, LPR machines have the ability to recognize most characters on the vehicle plates even under the harshest practical conditions. Therefore, even though the equipment are not perfect in terms of plate reading, it is still possible to judge with certain confidence if a pair of imperfect readings, in the form of sequenced characters (strings), most likely belong to the same vehicle. The challenge here is to design a matching procedure in order to decide whether or not they belong to same vehicle. In view of the aforementioned problem, this research intended to design and assess a matching procedure that takes advantage of a similarity measure called edit distance (ED) between two strings. The ED measure the minimum editing cost to convert a string to another. The study first attempted to assess a simple case of a dual LPR setup using the traditional ED formulation with 0 or 1 cost assignments (i.e. 0 if a pair-wise character is the same, and 1 otherwise). For this dual setup, this research has further proposed a symbol-based weight function using a probabilistic approach having as input parameters the conditional probability matrix of character association. As a result, this new formulation outperformed the original ED formulation. Lastly, the research sought to incorporate the passage time information into the procedure. With this, the performance of the matching procedure improved considerably resulting in a high positive matching rate and much lower (about 2%) false matching rate

Secure Large Scale Penetration of Electric Vehicles in the Power Grid

As part of the approaches used to meet climate goals set by international environmental agreements, policies are being applied worldwide for promoting the uptake of Electric Vehicles (EV)s. The resulting increase in EV sales and the accompanying expansion in the EV charging infrastructure carry along many challenges, mostly infrastructure-related. A pressing need arises to strengthen the power grid to handle and better manage the electricity demand by this mobile and geo-distributed load. Because the levels of penetration of EVs in the power grid have recently started increasing with the increase in EV sales, the real-time management of en-route EVs, before they connect to the grid, is quite recent and not many research works can be found in the literature covering this topic comprehensively. In this dissertation, advances and novel ideas are developed and presented, seizing the opportunities lying in this mobile load and addressing various challenges that arise in the application of public charging for EVs. A Bilateral Decision Support System (BDSS) is developed here for the management of en-route EVs. The BDSS is a middleware-based MAS that achieves a win-win situation for the EVs and the power grid. In this framework, the two are complementary in a way that the desired benefit of one cannot be achieved without attaining that of the other. A Fuzzy Logic based on-board module is developed for supporting the decision of the EV as to which charging station to charge at. GPU computing is used in the higher-end agents to handle the big amount of data resulting in such a large scale system with mobile and geo-distributed nodes. Cyber security risks that threaten the BDSS are assessed and measures are applied to revoke possible attacks. Furthermore, the Collective Distribution of Mobile Loads (CDML), a service with ancillary potential to the power system, is developed. It comprises a system-level optimization. In this service, the EVs requesting a public charging session are collectively redistributed onto charging stations with the objective of achieving the optimal and secure operation of the power system by reducing active power losses in normal conditions and mitigating line congestions in contingency conditions. The CDML uses the BDSS as an industrially viable tool to achieve the outcomes of the optimization in real time. By participating in this service, the EV is considered as an interacting node in the system-wide communication platform, providing both enhanced self-convenience in terms of access to public chargers, and contribution to the collective effort of providing benefit to the power system under the large scale uptake of EVs. On the EV charger level, several advantages have been reported favoring wireless charging of EVs over wired charging. Given that, new techniques are presented that facilitate the optimization of the magnetic link of wireless EV chargers while considering international EMC standards. The original techniques and developments presented in this dissertation were experimentally verified at the Energy Systems Research Laboratory at FIU

The Critical Role of Public Charging Infrastructure

Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

Short and Long-Term Structural Health Monitoring of Highway Bridges

Structural Health Monitoring (SHM) is a promising tool for condition assessment of bridge structures. SHM of bridges can be performed for different purposes in long or short-term. A few aspects of short- and long-term monitoring of highway bridges are addressed in this research. Without quantifying environmental effects, applying vibration-based damage detection techniques may result in false damage identification. As part of a long-term monitoring project, the effect of temperature on vibrational characteristics of two continuously monitored bridges are studied. Natural frequencies of the structures are identified from ambient vibration data using the Natural Excitation Technique (NExT) along with the Eigen System Realization (ERA) algorithm. Variability of identified natural frequencies is investigated based on statistical properties of identified frequencies. Different statistical models are tested and the most accurate model is selected to remove the effect of temperature from the identified frequencies. After removing temperature effects, different damage cases are simulated on calibrated finite-element models. Comparing the effect of simulated damages on natural frequencies showed what levels of damage could be detected with this method. Evaluating traffic loads can be helpful to different areas including bridge design and assessment, pavement design and maintenance, fatigue analysis, economic studies and enforcement of legal weight limits. In this study, feasibility of using a single-span bridge as a weigh-in-motion tool to quantify the gross vehicle weights (GVW) of trucks is studied. As part of a short-term monitoring project, this bridge was subjected to four sets of high speed, live-load tests. Measured strain data are used to implement bridge weigh-in-motion (B-WIM) algorithms and calculate the corresponding velocities and GVWs. A comparison is made between calculated and static weights, and furthermore, between supposed speeds and estimated speeds of the trucks. Vibration-based techniques that use finite-element (FE) model updating for SHM of bridges are common for infrastructure applications. This study presents the application of both static and dynamic-based FE model updating of a full scale bridge. Both dynamic and live-load testing were conducted on this bridge and vibration, strain, and deflections were measured at different locations. A FE model is calibrated using different error functions. This model could capture both global and local response of the structure and the performance of the updated model is validated with part of the collected measurements that were not included in the calibration process

Wireless Monitoring Systems for Long-Term Reliability Assessment of Bridge Structures based on Compressed Sensing and Data-Driven Interrogation Methods.

The state of the nation’s highway bridges has garnered significant public attention due to large inventories of aging assets and insufficient funds for repair. Current management methods are based on visual inspections that have many known limitations including reliance on surface evidence of deterioration and subjectivity introduced by trained inspectors. To address the limitations of current inspection practice, structural health monitoring (SHM) systems can be used to provide quantitative measures of structural behavior and an objective basis for condition assessment. SHM systems are intended to be a cost effective monitoring technology that also automates the processing of data to characterize damage and provide decision information to asset managers. Unfortunately, this realization of SHM systems does not currently exist. In order for SHM to be realized as a decision support tool for bridge owners engaged in performance- and risk-based asset management, technological hurdles must still be overcome. This thesis focuses on advancing wireless SHM systems. An innovative wireless monitoring system was designed for permanent deployment on bridges in cold northern climates which pose an added challenge as the potential for solar harvesting is reduced and battery charging is slowed. First, efforts advancing energy efficient usage strategies for WSNs were made. With WSN energy consumption proportional to the amount of data transmitted, data reduction strategies are prioritized. A novel data compression paradigm termed compressed sensing is advanced for embedment in a wireless sensor microcontroller. In addition, fatigue monitoring algorithms are embedded for local data processing leading to dramatic data reductions. In the second part of the thesis, a radical top-down design strategy (in contrast to global vibration strategies) for a monitoring system is explored to target specific damage concerns of bridge owners. Data-driven algorithmic approaches are created for statistical performance characterization of long-term bridge response. Statistical process control and reliability index monitoring are advanced as a scalable and autonomous means of transforming data into information relevant to bridge risk management. Validation of the wireless monitoring system architecture is made using the Telegraph Road Bridge (Monroe, Michigan), a multi-girder short-span highway bridge that represents a major fraction of the U.S. national inventory.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116749/1/ocosean_1.pd

Transport systems analysis : models and data

Funding: This research project has been funded by Spanish R+D Programs, specifcally under Grant PID2020-112967GB-C31.Rapid advancements in new technologies, especially information and communication technologies (ICT), have significantly increased the number of sensors that capture data, namely those embedded in mobile devices. This wealth of data has garnered particular interest in analyzing transport systems, with some researchers arguing that the data alone are sufficient enough to render transport models unnecessary. However, this paper takes a contrary position and holds that models and data are not mutually exclusive but rather depend upon each other. Transport models are built upon established families of optimization and simulation approaches, and their development aligns with the scientific principles of operations research, which involves acquiring knowledge to derive modeling hypotheses. We provide an overview of these modeling principles and their application to transport systems, presenting numerous models that vary according to study objectives and corresponding modeling hypotheses. The data required for building, calibrating, and validating selected models are discussed, along with examples of using data analytics techniques to collect and handle the data supplied by ICT applications. The paper concludes with some comments on current and future trends

MnPASS Modeling and Pricing Algorithm Enhancement

While High Occupancy Vehicle (HOV) lanes have been used for decades as a strategy for mitigating congestion, research has shown that they are not always effective. A 2001 study of the I-394 and I-35W HOV lanes in Minnesota found that the HOV lanes were on average underutilized, moving fewer people than the General-Purpose Lanes (GPL) even with the increased number of passengers per vehicle. To address the issue of underuse, in 2003 the Minnesota Legislature authorized the conversion of the I-394 HOV lanes into High-Occupancy Toll (HOT) lanes, named the MnPASS Express Lanes. The MnPASS lanes operate using a fully dynamic pricing schedule, where pricing is dictated by the level of congestion in the HOT lane. To better understand the nature of HOT lanes and the decisions of their users, this study explored the possibilities for a microscopic traffic simulation-based model of HOT lanes. Based on a series of field studies where the price of the toll was changed while observing changes in demand in the HOT lane, models describing the lane choice behavior of MnPASS users were developed and calibrated. These models interfaced with the traffic simulation software Aimsun through a number of extension modules and tested on the two MnPASS corridors of I-394 and I35W corridors in the west and south suburbs of Minneapolis, Minnesota. The integrated HOT simulation tool was also used to develop and test a number of alternative pricing strategies including a more efficient version of the current strategy