VTechWorks Repository :: Browsing by Author "Katz, Bryan J."

Browsing by Author "Katz, Bryan J."

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An Analysis of Traffic Behavior at Freeway Diverge Sections using Traffic Microsimulation Software
Kehoe, Nicholas Paul (Virginia Tech, 2011-06-22)
Microscopic simulation traffic models are widely used by transportation researchers and practitioners to evaluate and plan for transportation facilities. The intent of these models is to estimate the second-by-second vehicle movements and interactions on such facilities. Due to constraints related to time, budget, and availability of data, these models are typically designed in such a way where the microscopic output is viewed on the macroscopic level. Inherently, this can leave uncertainty to how the model estimates the individual interactions between vehicles on the microscopic level. This thesis utilizes three microsimulation models, INTEGRATION, VISSIM, and CORSIM, to investigate the lane changing behavior as vehicles approach a freeway diverge area. The count of lane changes, lane use distribution, and visual inspection of the simulated lane changing behavior was compared to video data collected at two freeway diverge areas on U.S. 460 in the vicinity of Blacksburg, Virginia during both off-peak and peak periods. It was observed that all three models generally overestimated the number of lane changes near the diverge areas compared to field observations. By modifying the models' lane changing logic, the models were able to closely match field observations in one of the four scenarios. It was found that microsimulation models accurately estimated the lane use distribution. In addition, the INTEGRATION lane use distribution results were found to be more consistent when compared to observed lane use distribution than either VISSIM or CORSIM.
Applications of Connected Vehicle Technology to Address Issues of School Bus and School Bus Stop Safety
Donoughe, Kelly (Virginia Tech, 2016-03-01)
An analysis of crash data shows that the number of fatal school bus related crashes has remained nearly constant over the past ten years, despite an increase in available safety-improving technology. One of the main concerns related to school bus safety is the issue of illegally passing a stopped school bus. To improve safety around stopped school buses, this dissertation presents a Concept of Operations for a connected vehicle application to improve safety around stopped school buses using Dedicated Short Range Communication. The focus of this application is to increase awareness of stopped school buses or bus stops that are obscured from the driver's view. An on-road naturalistic driving experiment evaluated driver response to an in-vehicle message to warn drivers that they were approaching a school bus that was stopped around a curve. The dissertation concludes by using microsimulation to evaluate the impact of implementing specialized speed control algorithms to reduce vehicle speeds near bus stops along high speed roads. The simulation evaluated the effect of the reduce speed zone on travel time and emissions when the system was considered as a pre-timed speed limit and also when the system was modeled as a connected vehicle system.
Decision Support for Civil Engineering Students: Analysis of Alumni Career Paths
Hotle, Susan; Katz, Bryan J. (Sage, 2018-11-02)
Undergraduate students in engineering face many important decisions in the final 2 years of their degree program. These decisions can have an impact on long-term career choices, such as specialization area, career role of interest, and whether to apply to graduate school. Unfortunately, uninformed decisions can lead to missed opportunities, as well as the student potentially leaving science, technology, engineering, and mathematics education due to choosing a specialization that is not well aligned with their interests. This survey-based study assists students by analyzing the personality types, demographics, and career paths of 567 alumni that have earned an undergraduate degree in civil and environmental engineering (CEE) and are no longer enrolled in a university. Study findings include the fact that certain demographics, personality types, and job preferences are significant predictors of the final outcome of an alumni’s career when choosing between the different technical areas within CEE and professional roles. Family history of having an engineer in the immediate family did not prove to be a significant factor in these decisions. In addition, little significance was found between the data captured in the survey of whether or not someone would go on to earn a graduate degree in CEE. Given where significant relationships were found, it is recommended that future studies focus on testing additional personality types (e.g., is enthusiastic) and job traits (e.g., likes a desk job) to provide even greater distinctions between the technical areas and roles.
Development and Testing Of The iCACC Intersection Controller For Automated Vehicles
Zohdy, Ismail Hisham (Virginia Tech, 2013-10-28)
Assuming that vehicle connectivity technology matures and connected vehicles hit the market, many of the running vehicles will be equipped with highly sophisticated sensors and communication hardware. Along with the goal of eliminating human distracted driving and increasing vehicle automation, it is necessary to develop novel intersection control strategies. Accordingly, the research presented in this dissertation develops an innovative system that controls the movement of vehicles using cooperative cruise control system (CACC) capabilities entitled: iCACC (intersection management using CACC). In the iCACC system, the main assumption is that the intersection controller receives vehicle requests from vehicles and advises each vehicle on the optimum course of action by ensuring no crashes occur while at the same time minimizing the intersection delay. In addition, an innovative framework has been developed (APP framework) using the iCACC platform to prioritize the movements of vehicles based on the number of passengers in the vehicle. Using CACC and vehicle-to-infrastructure connectivity, the system was also applied to a single-lane roundabout. In general terms, this application is considered quite similar to the concept of metering single-lane entrance ramps. The proposed iCACC system was tested and compared to three other intersection control strategies, namely: traffic signal control, an all-way stop control (AWSC), and a roundabout, considering different traffic demand levels ranging from low to high levels of congestion (volume-to-capacity ration from 0.2 to 0.9). The simulated results showed savings in delay and fuel consumption in the order of 90 to 45 %, respectively compared to AWSC and traffic signal control. Delays for the roundabout and the iCACC controller were comparable. The simulation results showed that fuel consumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuel consumption for the traffic signal, AWSC and roundabout control strategies, respectively. In summary, the developed iCACC system is an innovative system because of its ability to optimize/model different levels of vehicle automation market penetrations, weather conditions, vehicle classes/models, shared movements, roundabouts, and passenger priority. In addition, the iCACC is capable of capturing the heterogeneity of roadway users (cyclists, pedestrians, etc.) using a video detection technique developed in this dissertation effort. It is anticipated that the research findings will contribute to the application of automated systems, connected vehicle technology, and the future of driverless vehicle management. Finally, the public acceptability of the new advanced in-vehicle technologies is a challenging task and this research will provide valuable feedback for researchers, automobile manufacturers, and decision makers in making the case to introduce such systems.
Development of a Tool to Calculate Appropriate Advisory Speeds on Horizontal Curves
Trumpoldt, Julie Marie (Virginia Tech, 2015-01-17)
Horizontal curves are a contributing factor for numerous deaths on roadways. The curve characteristics dictate the severity of the curve and require the driver to be more attentive while driving. To address this issue, advisory speeds are posted on horizontal curves to warn drivers to slow down for their safety. There are six main procedures to assign advisory speeds. This paper focuses on two of these methods, finds a connection between the two, and develops an Android Application that can be used to determine an advisory speed for a curve. In this work, a brief summary of the six existing methods for advisory speed assignment are discussed. Pros and cons are included for each for comparison purposes. Next, two of these methods are highlighted by applying them in the field. Data is collected and a relationship between them is determined. Using this relationship, an Android Application is created and the various details of the design process are described. This Application, called CurveAdvisor, allows the user to assign the appropriate advisory speed on a desired horizontal curve. An analysis is then conducted to test the effectiveness of CurveAdvisor. Results indicate that CurveAdvisor is successful in many cases. Finally, contributions and suggestions for future work are included.
Do Roundabouts Work? An Evaluation for Uniform Approach Demands
Jackson, Meredith A. (Virginia Tech, 2011-08-01)
With the increased prevalence of roundabouts in the United States, there is a need to evaluate the performance of roundabouts relative to other intersection control strategies. Few studies have compared roundabouts with other intersection control strategies in a systematic fashion. Consequently, this Thesis compares four types of intersection control strategies considering a single lane approach with a 58 km/hr speed limit and equal demand on all approaches. The study demonstrates that vehicle delay is minimized with the use of a roundabout intersection control for all demand levels below 500 veh/hr/approach. Above this point if the left turn percentage exceeds 70% traffic signal control is more efficient. The roundabout alternative also produces the fewest vehicle stops for low demand levels, low left turn demand and high right turn demand, however a TWSC alternative produces the least number of vehicle stops when the through and total demand is high. This study illustrates that fuel consumption and carbon dioxide, carbon monoxide, hydrocarbon and nitrogen oxide emissions can be improved with roundabout control over other intersection control strategies. The research presented here demonstrates that for low traffic demand levels roundabouts should be part of design alternatives considered for isolated intersection control.
Driver Response to Dynamic Message Sign Safety Campaign Messages
Kryschtal, Pamela Jean (Virginia Tech, 2020-02-03)
Unsafe driving habits increase the severity of roadway accidents. The behaviors that are generally associated with unsafe driving are influenced by drivers and their decision to engage in dangerous habits. In order to solve this problem, Departments of Transportation use roadside safety campaigns. To gain a comprehensive understanding of the effectiveness of these campaigns, this research study captured five different metrics of effectiveness to understand what messages are effective and how to target messages to different groups of people. Since reading and interpreting the messages produces cognitive activation among participants, a neuroimaging technology called functional near-infrared spectroscopy (fNIRS) was used to measure neurocognitive activation as a proxy for response. The fNIRS system captures this cognitive activation by measuring change in oxygenated blood (oxy-Hb). An increase in oxy-Hb is a proxy for increased task engagement. The first journal paper provides an understanding of what types of messages are perceived as effective, are misunderstood, are memorable, are considered inappropriate, and cause the greatest increase in cognitive engagement. Overall, drivers perceive messages to be effective at changing behavior, but particular messages are perceived as more effective than others. Messages about distracted driving and driving without a seat belt, messages that are intended to produce a negative emotional response, and messages with statistics are the behaviors, emotions, and themes that are most likely to be perceived to change driver behavior. Messages about distracted driving and messages about statistics are most likely to be remembered by drivers. In general, drivers do not find messages used in safety campaigns to be inappropriate. Drivers elicit more cognitive attention to signs about distracted driving and signs with a humorous emotion. The second journal considers the effectiveness of these messages with different target demographics by further investigating the first journal's results by different dependent variables, including age, gender, and risky driving habits of the participants. In the second study, the results from the first study are further examined to determine if some campaigns are more effective among different demographics of drivers. The behavioral results indicated that females, drivers over 65, low-risk and high-risk drivers, and urban and rural drivers perceive the safety campaigns as more effective. The neurological data revealed that younger drivers had more activation in the ventrolateral prefrontal cortex, an area known for semantics and word processing, which might indicate more cognitive attention to these types of messages. This study provides a unique application of using neuroimaging techniques to understand driver response to safety messages. The recommendations for an effective safety campaign are to use messages about distracted driving, messages with an emotional stimulus, and messages about statistics. Messages about word play and rhyme are recommended for appealing to younger demographics.
Eco-Driving in the Vicinity of Roadway Intersections - Algorithmic Development, Modeling and Testing
Kamalanathsharma, Raj Kishore (Virginia Tech, 2014-05-06)
Vehicle stops and speed variations account for a large percentage of vehicle fuel losses especially at signalized intersections. Recently, researchers have attempted to develop tools that reduce these losses by capitalizing on traffic signal information received via vehicle connectivity with traffic signal controllers. Existing state-of-the-art approaches, however, only consider surrogate measures (e.g. number of vehicle stops, time spent accelerating and decelerating, and/or acceleration or deceleration levels) in the objective function and fail to explicitly optimize vehicle fuel consumption levels. Furthermore, the majority of these models do not capture vehicle acceleration and deceleration limitations in addition to vehicle-to-vehicle interactions as constraints within the mathematical program. The connectivity between vehicles and infrastructure, as achieved through Connected Vehicles technology, can provide a vehicle with information that was not possible before. For example, information on traffic signal changes, traffic slow-downs and even headway and speed of lead vehicles can be shared. The research proposed in this dissertation uses this information and advanced computational models to develop fuel-efficient vehicle trajectories, which can either be used as guidance for drivers or can be attached to an electronic throttle controlled cruise control system. This fuel-efficient cruise control system is known as an Eco-Cooperative Adaptive Cruise Control (ECACC) system. In addition to the ECACC presented here, the research also expands on some of the key eco-driving concepts such as fuel-optimizing acceleration models, which could be used in conjunction with conventional vehicles and even autonomous vehicles, or assistive systems that are being implemented in vehicles. The dissertation first presents the results from an on-line survey soliciting driver input on public perceptions of in-vehicle assistive devices. The results of the survey indicate that user-acceptance to systems that enhance safety and efficiency is ranked high. Driver–willingness to use advanced in-vehicle technology and cellphone applications is also found to be subjective on what benefits it has to offer and safety and efficiency are found to be in the top list. The dissertation then presents the algorithmic development of an Eco-Cooperative Adaptive Cruise Control system. The modeling of the system constitutes a modified state-of-the-art path-finding algorithm within a dynamic programming framework to find near-optimal and near-real-time solutions to a complex non-linear programming problem that involves minimizing vehicle fuel consumption in the vicinity of signalized intersections. The results demonstrated savings of up to 30 percent in fuel consumption within the traffic signalized intersection vicinity. The proposed system was tested in an agent-based environment developed in MATLAB using the RPA car-following model as well as the Society of Automobile Engineers (SAE) J2735 message set standards for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. The results showed how multi-vehicle interaction enhances usability of the system. Simulation of a calibrated real intersection showed average fuel savings of nearly 30 percent for peak volumes. The fuel reduction was high for low volumes and decreased as the traffic volumes increased. The final testing of the algorithm was done in an enhanced Traffic Experimental Simulation tool (eTEXAS) that incorporates the conventional TEXAS model with a new web-service interface as well as connected vehicle message set dictionary. This testing was able to demonstrate model corrections required to negate the effect of system latencies as well as a demonstration of using SAE message set parsing in a connected vehicle application. Finally, the dissertation develops an integrated framework for the control of autonomous vehicle movements through intersections using a multi-objective optimization algorithm. The algorithm integrated within an existing framework that minimizes vehicle delay while ensuring vehicles do not collide. A lower-level of control is introduced that minimizes vehicle fuel consumption subject to the arrival times assigned by the upper-level controller. Results show that the eco-speed control algorithm was able to reduce the overall fuel-consumption of autonomous vehicles passing through an intersection by 15 percent while maintaining the 80 percent saving in delay when compared to a traditional signalized intersection control.
Effects of Font Design on Highway Sign Legibility
Perez Vidal-Ribas, Marta (Virginia Tech, 2023-08-31)
The Manual on Uniform Traffic Control Devices (MUTCD) set Standard Highway Alphabet, or Highway Gothic, as the standard font for all American roadway signs in 1966. Since then, that standard has not changed, with all signs following the norm. In the 1980s, new retro-reflective sheeting introduced on American roadways caused Highway Gothic to be more difficult to read, due to the light "halo" effect caused around the letters, or halation. Recently, more studies have been conducted to improve the overall legibility of Highway Gothic. One study found that its legibility could greatly improve if it's size was increased by 20%. This, however, is extremely unlikely, since increasing the font size would also entail an increase in the physical signs lining roadways. In the 1990s, a new font was created, Clearview, to help combat the negative effects of Standard Highway Alphabet. This font received interim approval in 2004, which was removed in 2016 due to ambiguous results from studies as to whether it was more beneficial than Highway Gothic. It was reinstated two years later, in 2018. Legibility has five different components: retro-reflectivity, irradiation, luminance, contrast, and font design. Understanding these five components, and the benefits of each, can lead to the betterment of the font design on highway signs. This study consisted of two web-based tests. In the first test, the "Letters Test", participants would see a character slowly increasing in size on the screen. Once they could decipher the character, they would click the screen and input the character shown. On the second test, the "Words Test", participants would follow the same instructions, albeit with words in place of characters. There were four fonts tested, on both a positive and negative contrasts. The positive contrast consisted of a green background with a white font, and the negative contrast was a white background with a black font. The four tested fonts were E Modified Base, Alpha Two FHWA E Narrow, Alpha Two FHWA D, and Alpha Two FHWA C, named Base, Narrow, D-Altered, and C-Altered respectively. Forty-two participants participated in both tests. For the "Letters Test", the smallest average font size was the narrow font, followed by the base and D-altered. For the "Words Test", the smallest average font size was the base font, followed by the narrow, D-altered, and C-altered fonts. Overall, the base and narrow fonts took up more space than the D-altered and C-altered fonts. It is recommended that field tests are conducted with these fonts, taking into account the space that they take up, not the font size. This analysis could help to determine whether or not the altered fonts are as legible, or even more legible, than the base and narrow fonts when occupying the same space.
Enhancing Delivery of Operations by Optimizing the Omni-Channel Supply Chain through Delivery as a Service
Kaplan, Marcella Mina (Virginia Tech, 2021-05-24)
The need for delivery grew significantly during the COVID-19 pandemic because people avoided activities in public to limit the spread of the virus. The purpose of this research was to evaluate how the pandemic influenced many individual's delivery preferences through the administration of a stated preference survey targeted at residents in the New River Valley, Virginia. Conclusions revealed from the survey show that people want more efficient and accessible delivery services. A new delivery ecosystem called Delivery as a Service (DaaS) was developed using the input from the survey, existing service-based models being widely implemented in many industries, and emerging technologies. This thesis details a framework for DaaS derived by defining major actors, characteristics, and a method to measure the effectiveness of a DaaS system. This comprehensive definition of integrated delivery services illustrates areas for future research to further optimize the DaaS system. DaaS has the potential to significantly change the current delivery ecosystem through increased delivery accessibility and efficiency. Goods can be brought to users at a faster rate and on a larger scale. Autonomous vehicle and drone delivery technologies can significantly reduce the cost while correspondingly reducing the time of delivery. DaaS is a concept that is needed for people to thrive in modern times and brings the opportunity to provide added benefits to even rural areas.
Factors Affecting Severity Level in Speed-Related Crashes and in Identification of Crashes Involving Exceeding Maximum Safe Travel Speed
Tanim, Md Fardeen (Virginia Tech, 2024-08-30)
This research investigates factors that influence severity of speed-related crashes on mainline roadway segments, with a particular emphasis on comparing single-vehicle and multiple-vehicle incidents and distinguishing between crashes involving legal speed limit violations and those exceeding the maximum safe travel speed as determined by law enforcement. Additionally, it examines significant factors related to classifying a crash as exceeding the maximum safe travel speed. Using crash data from the Traffic Records Electronic Data System (TREDS) for Virginia for 2023, the research employs both Ordinal and Nominal Logistic Regression models for analysis. The findings reveal that higher vehicle speeds before a crash significantly increase crash severity level across all scenarios. Rain and snow/sleet weather conditions exhibit significant impacts on crash outcomes, with adverse conditions often leading to increased severity levels. Roadway characteristics in terms of presence of medians and road surface conditions, are also found to be significant, as are. the driver-related factors of age, safety equipment used, EMS transport after the crash, and vehicle type. The study's comparative analysis between single and multiple vehicles speeding crashes, as well as speeding beyond legal limits and exceeding maximum safe travel speed highlights the contextual differences in crash severity determinants. The findings on classifying crashes as exceeding maximum safe travel speed highlight conditions that influence this designation as well as factors that can lead to inconsistencies in that classification. For example, environmental conditions like rain or snow, certain crash types, and work zone crashes may result in subjective assessments rather than objective determinations. The research offers valuable insights for informing targeted road safety strategies within the Safe System framework – targeted at reducing the severity of speed-related crashes for mainline road segments. The findings support implementing comprehensive strategies that address the complex interplay of speed, road conditions, vehicle characteristics, and driver factors in mitigating crash severity.
Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion: SHRP 2
Rakha, Hesham A.; Du, Jianhe; Park, Sangjun; Guo, Feng; Doerzaph, Zachary R.; Viita, Derek; Golembiewski, Gary A.; Katz, Bryan J.; Kehoe, Nicholas; Rigdon, H. (National Research Council (U.S.). Transportation Research Board, 2011)
Nonrecurring congestion is traffic congestion due to nonrecurring causes, such as crashes, disabled vehicles, work zones, adverse weather events, and planned special events. According to data from the Federal Highway Administration (FHWA), approximately half of all congestion is caused by temporary disruptions that remove part of the roadway from use, or "nonrecurring" congestion. These nonrecurring events dramatically reduce the available capacity and reliability of the entire transportation system. The objective of this project is to determine the feasibility of using in-vehicle video data to make inferences about driver behavior that would allow investigation of the relationship between observable driver behavior and nonrecurring congestion to improve travel time reliability. The data processing flow proposed in this report can be summarized as (1) collect data, (2) identify driver behavior, (3) identify correctable driver behavior, and (4) model travel time reliability, as shown in Figure ES.1.
Field and Modeling Framework and Case Study of Truck Weigh Station Operations: Final report
Katz, Bryan J.; Rakha, Hesham A. (Virginia Tech. Virginia Tech Transportation Institute, 2002-01)
Weigh-in-Motion (WIM) systems improve the capacity of weigh station operations significantly by screening trucks while traveling at high speeds and only requiring trucks within a threshold of a maximum permissible gross of axle weight to be weighed on more accurate static scales. Consequently, the operation of a weigh station is highly dependent on the accuracy of the screening WIM system. This thesis develops a procedure for relating axle accuracy to gross vehicle accuracy and develops a field and modeling framework for evaluating weigh station operations. The WIM scale operation at the Stephens City weigh station in Virginia is examined to demonstrate how the field and modeling framework can be applied to evaluate the operation of a weigh station. Specifically, the field evaluation evaluated the accuracy of the WIM technology in addition to the operations of the weigh station in terms of service time, system time, and delay incurred at the static scales. During the field evaluation of the Stephens City WIM load cell system, the WIM technology was found to estimate truck weights to within 6 and 7 percent of the static weights 95 percent of the time. The modeling framework provides a methodology that can be used to determine the effects of the truck demand, the WIM accuracy, the system threshold, and the WIM calibration on system performance. The number of vehicles sent to the static scale and bypass lanes as well as the amount of delay experienced were analyzed for various system characteristics. The proposed framework can be utilized to estimate vehicle delay at a weigh station.
The Impact of Airport Size on Service Continuity and Operational Performance
Atallah, Stephanie (Virginia Tech, 2020-04-14)
This dissertation looks at the relationship between airport size (e.g. small, medium, large) and air service continuity and operational performance. It consists of three studies, each written in journal format. The first study analyzes the markets served pre- and post-recession while focusing on the operational strategies adopted by the top Major Carriers and Low-Cost Carriers (LCCs) in the United States. Findings show that LCCs have outpaced major carriers in terms of expanding their network and the number of markets served. During the same time, major carriers have gained a greater flight share in the markets they already serve. Post-recession, LCCs have shown preference to competing with major carriers over other LCCs. The second study investigates the declining service levels at small airports compared to large-hub airports, which continue to benefit from higher levels of service and increased airline presence. Using a fixed-effects conditional logistic regression, this study looked at factors contributing to service loss in region-to-region markets serving small communities between 2007 and 2013. Results show that 1) markets affected by a merger are indeed at a higher risk of losing service; 2) markets that are operated by a fuel-intensive, small-aircraft fleet have a higher chance to be discontinued and 3) an increased number of competitors greatly reduces potential market service loss. The third and final study proposes a new methodology to calculate original delay and propagated delays using combined aviation operational datasets that provide detailed flight information and causal factors behind delays. In addition to calculating original and propagated delay for the month of July of 2018, this study differentiated between original delays that occur during the turnaround phase, taxiing phase and en-route and incorporates causal factor information to identify the true source behind propagated delay. Two fixed-effects linear regression models were introduced that predict Total Propagated Delay and the share of propagated delay given an airport's ability to absorb upstream delay during the turnaround phase. Results show that most delay propagation chains originate at large-hub airports and are mostly concentrated at airports within the same geographical area. However, delays originating at large-hub airports were found to be the quickest to recover (i.e. least number of downstream flight legs affected) and large-hub airports have a higher ability to absorb delay at the turnaround phase compared to smaller airports given the significantly higher schedule buffer time airlines plan at large-hub airports.
Impact of COVID-19 on Public Transit and Micromobility Ridership
Dietrich, Cara A. (Virginia Tech, 2021-01-15)
The Coronavirus pandemic changed the normal lives across the country as strategies for mitigating the spread of the virus were put in place. Daily life was moved to a virtual setting as much as possible and typical mobility purposes changed or were eliminated. Shared transportation ridership declined dramatically in response to the pandemic, with reported drops of up to 90% across the United States. Mobility providers were tasked with determining strategies to encourage ridership during the risky time. The main research question that was explored in this study was, "What is the impact of the Coronavirus pandemic on public transit and micromobility ridership?" The study aimed to determine important factors that potential riders considered and emphasized in their decision making. The research approach was to use a custom-developed stated preference survey. The survey collected opinions about public transit and micromobility ridership during and emerging from the Coronavirus pandemic. The study focused on Blacksburg, VA as it has both public transit and micromobility services. Personal characteristics and stated important factors that influenced potential rider decisions were determined to understand what is most important to potential riders. Mobility providers can use these findings to better address rider concerns and make informed decisions on provided service. Therefore, encouraging an increase in shared transportation ridership.
The Impact of Cyberattacks on Safe and Efficient Operations of Connected and Autonomous Vehicles
McManus, Ian Patrick (Virginia Tech, 2021-09-01)
The landscape of vehicular transportation is quickly shifting as emerging technologies continue to increase in intelligence and complexity. From the introduction of Intelligent Transportation Systems (ITS) to the quickly developing field of Connected and Autonomous Vehicles (CAVs), the transportation industry is experiencing a shift in focus. A move to more autonomous and intelligent transportation systems brings with it a promise of increased equity, efficiency, and safety. However, one aspect that is overlooked in this shift is cybersecurity. As intelligent systems and vehicles have been introduced, a large amount of research has been conducted showing vulnerabilities in them. With a new connected transportation system emerging, a multidisciplinary approach will be required to develop a cyber-resilient network. Ensuring protection against cyberattacks and developing a system that can handle their consequences is a key objective moving forward. The first step to developing this system is understanding how different cyberattacks can negatively impact the operations of the transportation system. This research aimed to quantify the safety and efficiency impacts of an attack on the transportation network. To do so, a simulation was developed using Veins software to model a network of intelligent intersections in an urban environment. Vehicles communicated with Road-Side Units (RSUs) to make intersection reservations – effectively simulating CAV vehicle network. Denial of Service (DoS) and Man in the Middle (MITM) attacks were simulated by dropping and delaying vehicle's intersection reservation requests, respectively. Attacks were modeled with varying degrees of severity by changing the number of infected RSUs in the system and their attack success rates. Data analysis showed that severe attacks, either from a DoS or MITM attack, can have significant impact on the transportation network's operations. The worst-case scenario for each introduced an over 20% increase in delay per vehicle. The simulation showed also that increasing the number of compromised RSUs directly related to decreased safety and operational efficiency. Successful attacks also produced a high level of variance in their impact. One other key finding was that a single compromised RSU had very limited impact on the transportation network. These findings highlight the importance of developing security and resilience in a connected vehicle environment. Building a network that can respond to an initial attack and prevent an attack's dissemination through the network is crucial in limiting the negative effects of the attack. If proper resilience planning is not implemented for the next generation of transportation, adversaries could cause great harm to safety and efficiency with relative ease. The next generation of vehicular transportation must be able to withstand cyberattacks to function. Understanding their impact is a key first step for engineers and planners on the long road to ensuring a secure transportation network.
Implications of Advanced Technologies on Rural Delivery
Kaplan, Marcella Mina (Virginia Tech, 2024-05-24)
This dissertation integrates the strengths of individual emergent delivery technologies with package characteristics, and rural community needs to meet the demand for equitable, accessible, and inclusive rural delivery that is also cost-effective. To find ways to meet the package delivery service needs in rural areas and to fill research gaps in rural package delivery modeling, this study introduced a novel model known as the Parallel Scheduling Vehicle Routing Problem (PSVRP) in an endeavor to revolutionize package delivery by enhancing its efficiency, accessibility, and cost-effectiveness. The PSVRP represents a state-of-the-art approach to vehicle routing problems, incorporating a diversified fleet of innovative delivery modes. The multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems works in unison to minimize operational costs in various settings. A solution methodology that implemented the Adaptive Large Neighborhood Search (ALNS) algorithm was designed to solve the PSVRP in this research to produce optimal or near-optimal solutions. A variety of scenarios in a rural setting that include different quantities of customers to deliver to and different package weights are tested to evaluate if a multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems can provide cost-effective, low emissions, and efficient rural delivery services from local stores. Different fleet combinations are compared to demonstrate the best combined fleet for rural package delivery. It was found that implementation of electric vans, ADVs, drones, and truck-drone systems does decrease rural package delivery cost, but it does not yet decrease cost enough for the return on investment to be high enough for industry to implement the technology. Additionally, it was found that electric technologies do significantly decrease emissions of package delivery in rural areas. However, without a carbon tax or regulation mandating reduced carbon emissions, it is unlikely that the delivery industry will quickly embrace these new delivery modes. This dissertation not only advances academic understanding and practical applications in vehicle routing problems but also contributes to social equity by researching methods to improve delivery services in underserved rural communities. The PSVRP model could benefit transportation professionals considering technology-enabled rural delivery, developing rural delivery plans, looking for cost-effective rural delivery solutions, implementing a heterogeneous fleet to optimize rural delivery, or planning to reduce rural delivery emissions. It is anticipated that these innovations will spur further research and investment into rural delivery optimization, fostering a more inclusive and accessible package delivery service landscape.
An Interdisciplinary and Probabilistic Treatment of Contemporary Highway Design Standards
Kim, Troy Jaisohn (Virginia Tech, 2024-05-14)
Although Autonomous Vehicles (AVs) are quickly becoming a reality, there is much that needs to be understood before mainstream commercialization can occur. One critical issue is the interplay between multiple fields of engineering. Whereas the first part of this work is a granular treatment of a specific issue, the second part simultaneously examines numerous fields within the transportation industry. In the surge to understand and develop AVs, researchers tend to study specific subdivisions within the "vehicle engineering umbrella". In particular, mechanical and civil engineers study vehicle dynamics in two different levels of specificity. Mechanical engineers typically investigate small-scale dynamic behavior which applies to a single vehicle, such as vehicle-terrain interactions or the behavior of mechanical components. On the other hand, civil engineers tend to study kinematic behavior: the behavior of platoons as it pertains to large-scale traffic flow. Regardless of the scale of study, each subdivision has a set of performance metrics. Due to the differences among subdivisions, some performance metrics may (unintentionally) compete. Compromises must be made in the design stage to produce a vehicle which caters to an appropriate audience. The first part of this work features two major contributions to bridge the gap between the dynamic and kinematic perspectives. One is the application of Design Envelopes that establishes a framework to balance constraints and assess design tradeoffs arising from each viewpoints. Three Design Envelopes are introduced to reach compromises on a vehicle's velocity, acceleration, and jerk. Another contribution is a methodology to tune the parameters of a car-following model analytically. Current tuning practices require empirically collected traffic count data, which is cumbersome to obtain. Analytically parameterizing car-following models facilitates more robust planning and encompasses both the dynamic and kinematic perspectives. The second contribution utilizes these Design Envelopes to improve a currently-existing speed profile generator. Integrating the Design Envelopes reformulates the existing algorithm as a constrained LQR problem, which enhances ride comfort and maintains dynamic stability for not just one vehicle, but a platoon. Simulations demonstrate that the refined algorithm can reduce the travel time on a specific route by 3-4.4%. More importantly, the simulations demonstrate it is possible to synthesize multiple engineering fields to enhance AV design. The second part of this work features two contributions aimed at revisions to modern-day highway design policies based on the concept of combining microscopic and macroscopic principles. One common belief is that AVs should drive better than the best human drivers, which suggests operating at or close to the vehicle's theoretical handling limits. Operating in this manner requires a thorough understanding of the associated risks, particularly the risks stemming from uncertainty. This is especially pertinent as there are many inherently probabilistic quantities that are conveniently treated as deterministic in vehicle performance simulations, such as the coefficient of friction. This is a questionable practice when operating on the precipice of compromised safety. Thus, the second part of this work probabilistically examines the chance of handling loss given the amount of tire-road friction and driver acceleration. The result is a mathematically rigorous quantification of a safety margin for various road conditions and driver ability levels. Changes to the official US highway design handbook are recommended based on the findings.
Isolated Traffic Signal Optimization Considering Delay, Energy, and Environmental Impacts
Calle Laguna, Alvaro Jesus (Virginia Tech, 2017-01-10)
Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This thesis includes two studies that develop new formulations to compute the optimum cycle length of isolated intersections, considering measures of effectiveness such as vehicle delay, fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model against simulated data. The microscopic simulation software, INTEGRATION, was used to simulate two-phase and four-phase isolated intersections over a range of cycle lengths, traffic demand levels, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) were derived from the simulation software. The cycle lengths that minimized the various measures of effectiveness were then used to develop the proposed formulations. The first research effort entailed recalibrating the Webster model to the simulated data to develop a new delay, fuel consumption, and emissions formulation. However, an additional intercept was incorporated to the new formulations to enhance the Webster model. The second research effort entailed updating the proposed model against four study intersections. To account for the stochastic and random nature of traffic, the simulations were then run with twenty random seeds per scenario. Both efforts noted its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths optimized for vehicle delay only. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle demands.
On Demand Mobility Commuter Aircraft Demand Estimation
Syed, Nida Umme-Saleem (Virginia Tech, 2017-09-12)
On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1.

Browsing by Author "Katz, Bryan J."

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