Accurate vehicle classification data is fundamental to pavement design and road safety analysis. In addition, vehicle classification data is important for Florida Department of Transportation’s Transportation Statistics Office’s clients including consultants, researchers, designers, and planners who use the data to perform various analyses. In the mid-1980s, the Federal Highway Administration (FHWA) developed a standardized vehicle classification system which was designed to meet the needs of many traffic data users. This resulted in the FHWA 13-category classification rule set presently used for most Federal reporting requirements. Furthermore, this serves as the foundation for most State vehicle classification reporting efforts.The Florida Department of Transportation (FDOT) uses the FHWA F-Scheme to classify vehicles throughout the state highway system. This scheme relies mainly on the number of axles and the axle spacing, but on some Weigh-in-Motion (WIM) sites, vehicle weights are also used to improve classification. This thesis evaluates the performance of the Florida vehicle classification table of non-WIM sites using video data as the ground truth.This thesis has two main parts. Part I compares the performance of different data recorders that use FDOT vehicle classification table for WIM and non-WIM sites in classifying vehicles and evaluate the misclassification rates for each recorder. Part II evaluates the accuracy of the Florida vehicle classification table, determines the sources of misclassification, describes the changes recommended in the classification table to improve the classification accuracy, proposes and validates the improved vehicle classification table. This report will be of interest to Florida Department of Transportation and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures. / A Thesis submitted to the Department of Civil Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2016. / July 6, 2016. / classifier, decision tree, misclassification, vehicle classification / Includes bibliographical references. / Ren Moses, Professor Directing Thesis; Eren Erman Ozguven, Committee Member; John Sobanjo, Committee Member.

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Maritime transportation has been continuously playing an undeniable role for the global trade and economy of many countries. Based on the fast growth of the maritime trade, the marine container terminal (MCT) operators should focus on improving the operations planning at the MCTs. Seaside operations have substantial impacts on the general throughput of the MCTs. The daily berth planning as a seaside operation is the point of focus herein. The daily berth planning is modeled as a berth scheduling problem (BSP) in this dissertation. The BSP (as a decision problem) aims to assign the arriving vessels to the available berthing positions and can be reduced to the unrelated machine scheduling problem, which has NP-hard complexity. The large-size instances of decision problems with NP-hard complexity cannot be solved using exact optimization algorithms, while metaheuristic algorithms can effectively solve large-size problem instances and return good-quality solutions. Evolutionary Algorithms (EAs) are among the most popular metaheuristic algorithms deployed to solve the real-size BSPs. There are some algorithmic parameters in EAs (e.g., crossover probability, mutation probability, population size, etc.), which should be assigned the appropriate values to have the best possible performance of the algorithm for a given BSP. The process of determination of algorithmic parameters values is called the parameter selection. Several methodologies have been introduced in the EA literature for parameter selection, which can be classified as follows: (1) parameter tuning; and (2) parameter control. In parameter tuning, the algorithmic parameter values remain constant throughout the algorithmic evolution, while the parameter control strategy updates the algorithmic parameters considering different approaches. In this dissertation, an EA with a self-adaptive parameter control strategy is proposed to solve the developed BSP. Based on a self-adaptive parameter control strategy, the crossover and mutation probabilities are encoded in the solutions and evolve with the EA. The problem is formulated as a mixed-integer linear programming model, minimizing the total weighted vessel turnaround time and the total weighted vessel late departures. Comprehensive numerical experiments are conducted to assess performance of the proposed self-adaptive EA against the alternative EAs, which rely on the different parameter selection strategies. Results demonstrate that all the considered solution algorithms show a promising performance in terms of the objective function values at termination. However, application of the self-adaptive parameter control strategy substantially enhances the objective function values at convergence without a significant impact on the computational time. Furthermore, an EA with an augmented self-adaptive parameter control strategy is presented in this dissertation as another solution algorithm for the BSPs. Based on an augmented self-adaptive parameter control strategy, not only the crossover and mutation probabilities are encoded in the solutions but they are also updated based on the feedback from the search. A mixed-integer linear programming mathematical model is developed for the BSP, aiming to minimize the total costs for serving vessels at the MCT. The designed algorithm is evaluated against nine alternative state-of-the-art metaheuristic algorithms, which have been widely utilized in the BSP literature. The results show that all the developed algorithms have a high level of stability and return high-quality solutions at termination. The computational experiments also prove the superiority of the designed augmented self-adaptive EA over the alternative algorithms considering different performance indicators. Another innovative solution methodology is developed in this dissertation, which relies on the island-based concept. Specifically, a universal island-based metaheuristic algorithm is designed for the BSP, where four different population-based metaheuristics are executed simultaneously in order to effectively search for solutions. A mixed-integer linear mathematical model is developed for the BSP, minimizing the total cost to serve the arriving vessels at the MCT. Comprehensive numerical experiments are conducted to evaluate performance of the island-based algorithm against seven commonly used metaheuristics in the BSP literature. The stability and the capability of the adopted algorithms in providing high-quality solutions at convergence are proven. The results demonstrate that the island-based algorithm outperforms other adopted algorithms considering different performance indicators. To summarize, this dissertation proposes three different solution methodologies for various BSP mathematical formulations. The algorithms have been evaluated based on extensive numerical experiments against the alternative algorithms, which have been widely used in the MCT and freight terminal operations literature. Findings confirm effectiveness of the proposed solution methodologies. Therefore, the developed solution methodologies can serve as promising decision support tools and assist MCT operators with the development of berth schedules. The latter will also assist with serving the growing demand for containerized trade and ensure that the vessel service will be completed in a timely manner. / A Dissertation submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / 2019 / October 29, 2019. / Berth Scheduling Problem, Marine Container Terminal, Metaheuristic, Optimization, Supply Chain / Includes bibliographical references. / Maxim A. Dulebenets, Professor Directing Dissertation; O. Arda Vanli, University Representative; Ren Moses, Committee Member; Eren Ozguven, Committee Member; Hui Wang, Committee Member.

The exodus of residents and employment opportunities from central cities has greatly impacted the low income residents which have remained as suitable employment opportunities are locating further from their residence. This trend has negatively impacted the employment participation of these residents, worsening their economic situation. The implementation of light rail transit is considered to address this issue as it can connect this population to new labor markets and attract development along its corridor. This development has the potential to produce suitable employment opportunities for low income residents. Surprisingly, studies have found light rail investment to have negligible impacts on the employment participation of low income inner city residents. The researcher theorizes that these findings are due, in part, to the development outcomes achieved within light rail service areas. The aggressive development activity which is commonly observed within new transit areas has the potential to change the character of the surrounding environment. This change may come at the expense of low income residents as areas experience gentrification and lose suitable employment opportunities. This study explores the change in, and nature of, development which arises within light rail station areas in order to better comprehend the impact which resulting development outcomes have on opportunities suitable for low income residents. This is done by focusing on four cities which have implemented a light rail system between 2000 and 2010. The change in employment opportunities within station areas which can be attributed to the presence of light rail is estimated via a difference in difference model implemented within a negative binomial regression. Focus is placed on the change in employment opportunities suitable for low income residents. Next, the impact which light rail has on the odds of station areas gentrifying is explored via the generation of a gentrification index and application of a logistic regression. Lastly, cases which experienced diverging development outcomes were identified and further explored. Interviews and the review of relevant documents provided additional insight on the factors which contribute to the attainment of more equitable development outcomes. The results of this study indicate that development activity within light rail service areas has the potential to eliminate certain which are likely to employ low income residents. At the same time, some employment categories which employ low income residents were found to experience growth. Additionally, station areas in one case were found to face greater odds of gentrifying when compared to similar areas not serviced by rail transit. Results were not consistent across all cases as they deviated based on their respective location. The exploration of cases which experienced diverging outcomes provided insight on factors which may contribute to the attainment of specific development outcomes. / A Dissertation submitted to the Department of Urban and Regional Planning in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / June 20, 2018. / Development, Equity, Light Rail, Urban Planning / Includes bibliographical references. / Jeffrey R. Brown, Professor Directing Dissertation; Earle Klay, University Representative; Michael Duncan, Committee Member; April Jackson, Committee Member.

Resilience simply means to rebound when exposed to a disruptive event. Damage to bridges in transportation networks usually result in long detours and increased travel time hence have massive cost implications. Transportation networks composed of major bridge infrastructures frequently depend on the bridges to carry high traffic volumes. Transportation network resilience explains the ability of transportation networks to contain and recover from disruptions. Transportation network resilience entails the transportation network’s capability to continue functioning in spite of hazard-induced breakdown to network segments and how quickly those sections can be restored for the network to return to pre-disaster performance levels. Most resilience-related research in this area have primarily focused on physical bridge resilience without necessarily considering the resilience impact of bridge damage on the overall or regional network. This thesis is focused on filling this research gap by considering the resilience of transportation networks subject to bridge damage and road closures. This research further proposes the use of regional travel demand models and Geographic Information Systems (GIS) visualization techniques for network level impact visualization and accessibility analyses. The socio-technical approach associated with transportation system resilience is broad and multidisciplinary, focusing on the network’s ability to sustain functionality and recover speedily when faced with disruptions or shocks. Academic works in this area are generally viewed in terms of having qualitative or quantitative frameworks. There is also significantly less literature evaluating response and recovery phases of resilience. Developed resilience indexes have sparsely touched on many salient aspects of resilience; hence they are only applicable to very specific scenarios. Further investigative efforts are therefore necessary for post-disaster phases of resilience, evaluating the applicability of resilience indexes on multiple hazard events for transportation networks, and developing resilience indexes based on regional road network models while considering all network links and not just alternative routes. Temporary, long-term, and partial closures to bridges can result in enormous cost implications. However, bridge closures are inevitable not only due to the likelihood of hazard-induced damages, but routine maintenance, repair, and rehabilitation (MR&R) activities may also warrant closures. It is a current practice that vehicles are rerouted to the shortest alternative route (detour approach) during bridge closures. In an initial study, a scenario-based network approach for evaluating the impact of bridge closures on transportation user cost is proposed. Both the detour-based and network-based approaches were applied to the Tampa Bay regional network model while considering five bridge closure scenarios. User costs were computed in terms of delay and vehicle operating costs. Findings indicated that for closures to I-275, Gandy, Highway 580 and W.C.C Causeway bridges, there were increases of about 42%, 18%, 61%, and 45% respectively, in total user costs for the network-based approach when compared with the current detour-only approach, indicating a significant network impact captured by the network-based approach. The proposed methodology captures the effects of bridge closures on all road segments within the regional network jurisdiction, provides a more rigid framework for analysis by ensuring user costs are computed efficiently while avoiding overestimation, takes into account the fact that road users may have advance knowledge of roadway conditions prior to trips hence significantly influencing route choices, and provides sufficient information for agencies to implement preemptive measures to cater for network-level disruptions due to bridge closures. Also, regional network resilience was assessed, first through a schematic framework developed for selecting at-risk bridges during hurricane events by: (i) computing exposure probabilities for hurricane events at bridge locations; (ii) developing bridge damage state functions and damage state rating assignments using historical data from the National Bridge Inventory (NBI) database; (iii) identification of bridges at risk to hurricane-induced damage; and (iv) computing aging accessibility to hospitals from which resilience was measured. Results indicated an increase from about 1200 minutes to 2100 minutes and from about 900 to 1100 minutes, for the congested travel time (CTT) and free flow travel time (FFTT), respectively, representing about 75% and 15% for CTT and FFTT, respectively. Furthermore, an additional total travel distance of 52.85 miles was observed for CTT and FFTT. The mean travel times after bridge closures increased from 8.43 to 15.1 minutes and from 6.6 to 7.76 minutes for CTT and FFTT, respectively. The resulting resilience index scaled from 0 to 1 was computed with 1 representing a network which can recover immediately after a disruption (or a network without any performance loss) and zero for one that may never recover to its pre-disaster form. Restoration to moderately damaged bridge led to functionality improvement from 0.87 to 0.94 considering FFTT, and from 0.57 to 0.83 considering the CTT. Reinstating extensively-damaged bridges resulted in functionality increase from 0.94 to 0.96, and 0.83 to 0.85, respectively, for FFTT and CTT. The resilience index for this study was computed as 0.94 and 0.81 for FFTT and CTT respectively, implying a significant loss in senior mobility hence the need for mitigation measures A framework for assessing the regional network resilience was developed by leveraging scenario-based traffic modeling and Geographic Information System (GIS) techniques. High impact zones location identification metrics were developed and implemented in preliminarily identifying areas affected by bridge closures. Resilience index measures were developed by utilizing practical functionality metrics based on vehicle distance and hours traveled. These are illustrated for the Tampa Bay area. Findings for ten bridge closure scenarios and recovery schemas indicate substantial regional network functionality losses during closures. I-275 bridge closure yielded the highest functional loss to the regional network: the aggregated resilience index below 0.5 reflects severe network performance deficit and mobility limitations. Closure to the WCC Causeway bridge results in a network level resilience index value of 0.87, while the indexes for the other scenarios range between 0.76 and 0.97. These results reflect the high dependency of the network on the I-275 bridge. Damage to this bridge is foreseen to have a massive impact on the network in terms of travel cost. Lower resilience index values imply either significant functionality losses or lengthy closure durations or both. To demonstrate the proposed methodology, a hypothetical network illustration indicated that: (i) Single bridge closure scenarios recorded significant performance losses for bridges which directly connected to the destination zone; (ii) Resilience indexes echoed the need to compare predicted recovery times to scheduled restoration times since index measures are either compensated or penalized the speed of predicted recovery with respect to scheduled recovery durations; (iii) Sensitivity analyses reinforced the previous assertion by accounting for both performance loss and restoration or recovery times; (iv) Multiple closures had a significant impact on network performance hence rapidity is vital in improving network resilience. Like any study, there are some limitations identified in this research. While it was clearly identified that variation in response and recovery times may have a significant impact on explaining and formulating resilience measures, there is insufficient data on the road closure and bridge closure durations after hazard events. Such databases will help researchers in evaluating resilience more accurately. Furthermore, even though case studies in this thesis took into account large networks, the utilized models were based on static traffic assignment which suffices for long-term transportation planning. However, it is recommended that use of dynamic traffic assignment models should be explored since they are known to reflect more accurate travel times. This is especially important for equity-based case study applications with respect to post-disaster accessibility. The use of user equilibrium assignment which accounts for each road user minimizing his or her travel time was used for this study, it is recommended that the system optimal solution which minimizes the overall network travel time should be considered since it may be of specific interest to agencies. Solution-based resilience studies are encouraged, especially efforts which incorporate the influx of connected and autonomous vehicles and other shared mobility solutions. This study also recognized the need for collaborative efforts between management authorities and researchers to facilitate the development and implementation of necessary policies and systems for the enhancement of transportation systems’ resilience. / A Dissertation submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 19, 2018. / Bridges, Hazards, Infrastructure, Network Performance, Resilience, Transportation Networks / Includes bibliographical references. / John O. Sobanjo, Professor Directing Dissertation; Eric Chicken, University Representative; Ren Moses, Committee Member; Eren E. Ozguven, Committee Member.

Despite the rapid global motorization, especially in developing countries, the use of the bicycle as urban transportation has increased in the last 35 years (Shaheen, Guzman, & Zhang, 2012). However, the United States, Canada, and Mexico have low cycling levels with bicycle mode share of little more than one percent (Buehler & Pucher, 2012). Some of the possible alternatives to promote the use of the bicycle is that the presence of bikeshare systems can encourage cycling by providing a safer environment for all types of cyclists (Fischman & Schepers, 2014). This dissertation examines the drivers’ perception towards cyclists and the possible difference in perception towards Ecobici bikeshare users and private cyclists. This research was carried out in Mexico City, at the EcoBici bikeshare service area. Data collection was done by a self-reported survey distributed online and by intercept surveys conducted to drivers who drive within the study area and control area. The analysis of the 710 participants' responses shows that drivers from the control area have a more positive perception towards cyclists, especially on issues related to bicycle investment and bicycle infrastructure. Overall, younger generations reported a more positive perception towards cyclists, and most drivers perceive that cyclists are not predictable on the roads as most of the drivers reported feel nervous when overtaking cyclists. When comparing Ecobici users to private cyclists, the results suggest that drivers do not have a clear preference for Ecobici users over private cyclists. Nevertheless, drivers are also more in favor of encouraging family and friends to use Ecobici bicycles over private bicycles, which could indicate that, unconsciously, participants consider that traveling on an Ecobici bicycle is safer than going on a private bicycle. The results from this study could have an impact on policymakers and transportation practitioners in Mexico City who would like to improve drivers-cyclists’ interactions in the road and to promote the use of the bicycle for transportation. / A Dissertation submitted to the Department of Urban and Regional Planning in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / 2019 / October 31, 2019. / Bikeshare systems, Drivers perception / Includes bibliographical references. / Michael Duncan, Professor Directing Dissertation; Mark Horner, University Representative; Jeffrey Brown, Committee Member; John Felkner, Committee Member.

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The advent of accelerated global warming and volatile climate change has prompted the need for a better understanding of what factors and policies might contribute to mitigate these events as well as increase the resilience of communities. Transit systems’ effectiveness and efficiency in increasingly disperse, car-dependent, and poly-centric urban agglomerations is one such factor, including the search for strategies to increase transit patronage and decrease car-dependence. Improving access to rapid-transit systems is one key area as it has the potential to expand the system’s influence beyond station’s immediate pedestrian service areas into larger and less developed suburban areas, and/or serve more disperse employment. Precedent studies and most on-board surveys have focused on a variety of access modes to reach rapid-transit services, including automobile, walking, and bicycle. Bus access, despite representing on average a non-trivial 19.3% of all access trips at national level, more than 30% at some large poly-centric cities in the U.S., and close to 50% of access trips for some rapid-transit lines (out-sizing the share of pedestrian access) has not received as much attention as other access modes. Predictive models for bus access mode report notably lower explanatory power as compared to other modes and the account of bus access events is often conflated with that of walk access in many technical reports and surveys for reasons yet to be understood. Ignoring, overlooking and/or misrepresenting this mode of access may lead to misunderstanding of multi-modal transit travel behavior and its spatial extent, possibly misguiding planners and policy-makers’ decision-making and resulting in system-wide ineffectiveness and/or inefficiency. This investigation documents bus access share for one exemplary case study and clarifies built-environment and bus networks’ influence on rapid-transit patronage within descriptive and inferential quantitative methodologies. This study seeks to answer two guiding research questions: 1- How important are bus networks to rapid-transit ridership in large, dispersed, poly-centric metropolitan regions in the U.S.? and 2- Do land-use and built-environment attributes around feeder bus-stops influence rapid-transit boardings? Because of diverse geographical scales and service levels experienced by a rider on a chained bus / rapid-transit trip this study focuses on two distinct yet linked geographies for analysis: 1-rapid-transit station; and 2- bus-stop. Research design is based on a single-case study in the United States (Los Angeles metropolitan multi-modal transit system). The first study focuses on quantifying the share of bus access trips at station-level and gaging its influence on total boardings within a multivariate generalized regression framework. Several socio-economic, service-level, built-environment, and network attributes are taken into consideration as informed by travel behavior theory and literature review. A strong positive association between bus network’s service and connectivity levels with rapid-transit station boardings registers high statistical confidence levels with boardings across all specified models. The mutual dependence of rapid-transit and bus networks evinced in the case of Los Angeles argues for a full multi-modal transit planning and operations paradigm for advancing a more effective, equitable, and sustainable transit system if it is to compete with ubiquitous automobile travel and its underpinning policy, fiscal, infrastructural, and cultural support. For Los Angeles, rapid-transit bus access represents an estimated 33.5% of all access events at a system-wide level, 20% - 49% at line-level, and a notably wider range at station-level (0% - 86%). The second study in this investigation focuses in assessing bus-stop pedestrian service areas built-environment and land-use attributes’ potential influence on rapid-transit station boardings, whilst controlling for both known and hypothesized control factors at bus-stop and station-level. By simultaneously focusing on bus-stop level attributes and higher-level rapid-transit stations’ attributes this part of the investigation fills a gap in the extant land-use / travel-behavior literature that more often focuses on pedestrian service areas adjacent to rapid-transit stations and ignores those around feeder bus-stops. Results evince a highly significant statistical relationship between bus-stop service area built-environment characteristics and the number of boardings associated with access trips to rapid-transit stations. However, the absolute effect relative to bus service levels and to automobile availability is notably smaller. Taken together as a multi-scalar study of bus and rapid-transit network interactions this investigation points to the importance of bus / rapid-transit network connectivity and service integration for maintaining and increasing rapid-transit patronage and the potential of synergistic contributions of built-environment interventions at feeder bus stops that seek to improve walkability and shorter walking distances. As a general conclusion, Los Angeles County Metropolitan Transit Authority and its associated MPO policy emphasis on TOD development as a strategy to increase transit ridership is limited. A more comprehensive policy approach based on ‘integrated public transportation’ and a more extensive station access policy that incorporates improvements around feeder bus stops, not only around stations, is the recommended course. / A Dissertation submitted to the Department of Urban and Regional Planning in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / June 19, 2018. / built-environment, bus, multimodal, rapid-transit access, sustainable, transit / Includes bibliographical references. / Jeffrey Brown, Professor Directing Dissertation; Mark Horner, University Representative; Michael Duncan, Committee Member; John Felkner, Committee Member.