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. / Master of Science

Variable speed limits (VSL) are dynamic traffic management systems designed to increase the efficiency and safety of highways. While the macroscopic performance of VSL systems is well explored in the existing literature, there is a need to further understand the microscopic behavior of vehicles driving in VSL zones. Specifically, driver compliance to advisory VSL systems is quantified based on a driving-simulation experiment and introduced into a broader microscopic behavior model. Statistical analysis indicates that VSL compliance can be predicted based upon several VSL design parameters. The developed two-state microscopic model is calibrated to driving-simulation trajectory data. A calibrated VSL microscopic model can be utilized for new VSL control and macroscopic performance studies, adding an increased dimension of realism to simulation work. As an example, the microscopic model is implemented within VISSIM (overriding the default car-following model) and utilized for a safety-mobility performance assessment of an incident-responsive VSL control algorithm implemented in a MATLAB COM interface. Examination of the multi-objective optimization frontier reveals an inverse relationship between safety and mobility under different control algorithm parameters. Engineers are thus faced with a decision between performing multi-objective optimization and selecting a dominant VSL control objective (e.g. maximizing safety versus mobility performance). / Master of Science / Variable speed limits (VSL) are dynamic traffic management systems designed to increase the efficiency and safety of highways. While the system performance of VSL systems is well explored in previous research, there is a need to further understand the individual behavior of vehicles driving under VSL control. Specifically, driver compliance to advisory VSL systems is modelled based on a driving-simulation experiment. Low compliance equates to poor VSL performance so it is important for engineers to have the ability to predict compliance based on VSL design conditions. The compliance model is introduced into a driver behavior model that quantifies and predicts the driver decision process on VSL controlled highways. The driver behavior model parameters are set using data obtained from the driving-simulation experiment. Utilization of the developed driver behavior model will increase the accuracy of future simulation work on VSL system performance. In this study, the model is implemented within a traffic simulation software to conduct an assessment of the trade-offs between safety and mobility VSL performance for different VSL control designs. An accident is modelled in the simulation software, and VSL is utilized to respond to and alleviate the incident. Simulation results indicate an inverse relationship between safety and mobility performance – indicating that engineers must select a primary objective when selecting VSL control design parameters.

Microscopic traffic simulation software have gained significant popularity and are widely used both in industry and research mainly because of the ability of these tools to reflect the dynamic nature of the transportation system in a stochastic fashion. To better utilize these software, it is necessary to understand the underlying logic and differences between them. A Car-following model is the core of every microscopic traffic simulation software. In the context of this research, the thesis develops procedures for calibrating the steady-state car-following models in a number of well known microscopic traffic simulation software including: CORSIM, AIMSUN, VISSIM, PARAMICS and INTEGRATION and then compares the VISSIM and INTEGRATION software for the modeling of traffic signalized approaches. The thesis presents two papers. The first paper develops procedures for calibrating the steady-state component of various car-following models using macroscopic loop detector data. The calibration procedures are developed for a number of commercially available microscopic traffic simulation software, including: CORSIM, AIMSUN2, VISSIM, Paramics, and INTEGRATION. The procedures are then applied to a sample dataset for illustration purposes. The paper then compares the various steady-state car-following formulations and concludes that the Gipps and Van Aerde steady-state car-following models provide the highest level of flexibility in capturing different driver and roadway characteristics. However, the Van Aerde model, unlike the Gipps model, is a single-regime model and thus is easier to calibrate given that it does not require the segmentation of data into two regimes. The paper finally proposes that the car-following parameters within traffic simulation software be link-specific as opposed to the current practice of coding network-wide parameters. The use of link-specific parameters will offer the opportunity to capture unique roadway characteristics and reflect roadway capacity differences across different roadways. Second, the study compares the logic used in both the VISSIM and INTEGRATION software, applies the software to some simple networks to highlight some of the differences/similarities in modeling traffic, and compares the various measures of effectiveness derived from the models. The study demonstrates that both the VISSIM and INTEGRATION software incorporate a psycho-physical car-following model which accounts for vehicle acceleration constraints. The INTEGRATION software, however uses a physical vehicle dynamics model while the VISSIM software requires the user to input a vehicle-specific speed-acceleration kinematics model. The use of a vehicle dynamics model has the advantage of allowing the model to account for the impact of roadway grades, pavement surface type, pavement surface condition, and type of vehicle tires on vehicle acceleration behavior. Both models capture a driver's willingness to run a yellow light if conditions warrant it. The VISSIM software incorporates a statistical stop/go probability model while current development of the INTEGRATION software includes a behavioral model as opposed to a statistical model for modeling driver stop/go decisions. Both software capture the loss in capacity associated with queue discharge using acceleration constraints. The losses produced by the INTEGRATION model are more consistent with field data (7% reduction in capacity). Both software demonstrate that the capacity loss is recovered as vehicles move downstream of the capacity bottleneck. With regards to fuel consumption and emission estimation the INTEGRATION software, unlike the VISSIM software, incorporates a microscopic model that captures transient vehicle effects on fuel consumption and emission rates. / Master of Science

Mathematical models to predict vehicle fuel consumption and emission metrics are presented in this thesis. Vehicle fuel consumption and emissions are complex functions to be approximated in practice due to numerous variables affecting their outcome. Vehicle energy and emissions are particularly sensitive to changes in vehicle state variables such as speed and acceleration, ambient conditions such as temperature, and driver control inputs such as acceleration pedal position and gear shift speeds, among others. Recent empirical studies have produced large amounts of data concerning vehicle fuel consumption and emissions rates and offer a wealth of information to transportation planners. Unfortunately, unless simple relationships are found between fuel consumption and vehicle emission metrics, their application in microscopic traffic and macroscopic planning models becomes prohibitive computationally. This thesis describes the development of microscopic energy and emission models using nonlinear multiple regression and neural network techniques to approximate vehicle fuel consumption and emissions field data. The energy and emission models described in this thesis utilized data collected by the Oak Ridge National Laboratory. The data include microscopic fuel consumption and emission measurements (CO, HC, and NOx) for eight light duty vehicles as a function of vehicle speed and acceleration. The thesis describes modeling processes and the tradeoffs between model accuracy and computational efficiency. Model verification results are included for two vehicle driving cycles. The models presented estimate vehicle fuel consumption within 2.5% of their actual measured values. Vehicle emissions errors fall in the range of 3-33% with correlation coefficients ranging between 0.94 and 0.99. Future transportation planning studies could also make use of the modeling approaches presented in the thesis. The models developed in this study have been incorporated into a microscopic traffic simulation tool called INTEGRATION to further demonstrate their application and relevance to traffic engineering studies. Two sample Intelligent Transportation Systems (ITS) application results are included. In the case studies, it was found that vehicle fuel consumption and emissions are more sensitive to the level of vehicle acceleration than to the vehicle speed. Also, the study shows signalization techniques can reduce fuel consumption and emissions significantly, while incident management techniques do not affect the energy and emissions rates notably. / Master of Science

Ground transportation systems are essential for the mobility of people, goods and services. Thus, making sure these systems are resilient to the impact of natural and man-made disasters has become a top priority for engineers and policy makers. One of the major obstacles for increasing the resilience of ground transportation systems is the lack of a measuring framework. Such measuring framework is critical for identifying needs, monitoring changes, assessing improvements, and performing cost-benefit analysis. This research addresses this problem by developing a traffic-based framework for measuring the resilience of ground transportation systems under normal and extreme conditions. The research methodology consisted of: (1) creating a microscopic traffic model of the road under study, (2) simulating different intrusions and interventions, and (3) measuring the resilience of the system under the different scenarios using the framework developed. This research expanded the current definition of infrastructure resilience, which includes the assessment of system performance versus time, to add a third dimension of resilience for ground transportation system's applications, namely: location. This third dimension considers how the system changes along the different locations in the network, which reflects more accurately the continuous behavior of a ground transportation network. The framework was tested in a 24 km segment of Interstate 95 in Virginia, near Washington, D.C. Four hazard conditions were simulated: inadequate base capacity, traffic incidents, work zones, and weather events. Intervention strategies tested include ramp meters and the use of the shoulder lane during extreme events. Public policy was also considered as a powerful intervention strategy. The findings of this research shed light over the current and future resilience of ground transportation systems when subject to multiple hazards, and the effects of implementing potential interventions. / Ph. D. / Ground transportation systems are essential for the mobility of people, goods and services. Thus, making sure these systems are <i>resilient</i> to the impact of natural and manmade disasters has become a top priority for engineers and policy makers. Disaster resilience is defined as the ability of a system to withstand the impact of a disaster and recover as quickly as possible. One of the major obstacles for increasing the resilience of ground transportation systems is the lack of a measuring framework. Such measuring framework is critical for identifying needs, monitoring changes, assessing improvements, and performing cost-benefit analysis. This research addresses this problem by developing a traffic-based framework for measuring the resilience of ground transportation systems under normal and extreme conditions. The research methodology consisted of: (1) creating a microscopic traffic model of the road under study, (2) simulating multiple hazards and mitigation strategies, and (3) measuring the resilience of the system under the different scenarios using the framework developed. This research expanded the current definition of infrastructure resilience, which includes the assessment of system performance versus time, to add a third dimension of resilience for ground transportation system’s applications, namely: location. This third dimension considers how the system changes along the different locations in the network, which reflects the continuous behavior of a ground transportation network. The framework was tested in a 24 km segment of Interstate 95 in Virginia, near Washington, D.C. Four hazard conditions were simulated: inadequate base capacity, traffic incidents, work zones, and weather events. Intervention strategies tested include ramp meters and the use of shoulder lanes. Public policy was also considered as a powerful intervention strategy. The findings of this research shed light over the current and future resilience of ground transportation systems when subject to multiple hazards, and the effects of implementing potential interventions.

Aerosol Jet® Printing (AJP) is a direct-write based additive manufacturing process that is capable of printing electronics with fine features and various materials. It eliminates the complex masking process in traditional semiconductor manufacturing, thus enables flexible electronics design and reduces manufacturing cost. However, the quality control of AJP processes is still a challenging problem, primarily due to the lack of understanding of the potential root causes of the quality issues. There is a complex interaction among process setting variables, in situ feature variables, and quality variables in AJP processes. In this research, an ensemble model strategy is proposed to quantify the effect of the process setting variables on the in situ feature variables, and the effect of the in situ feature variables on quality variables in a two-level hierarchical way. By identifying significant in situ feature variables as responses for the process setting variables, as well as predictors for product quality in a joint estimation problem, the proposed models have a hierarchical variable relationship to enable in situ process control for variation reduction and defect mitigation. A real case study is investigated to demonstrate the advantages of the proposed method. / Master of Science / Printed electronics is a promising technique for the future of the electronics manufacturing industry due to its potential for producing thin, flexible and low cost electronic devices. For the printing of any electronic device, a fundamental step is to print the conductive wires. Aerosol Jet® Printing (AJP) is one of the emerging additive manufacturing technologies for printing the conductive wires on a variety of substrates. It is a maskless additive manufacturing technique capable of printing high resolution wires. However, the quality control of AJP processes is still a challenging problem, primarily due to the lack of understanding of the potential root cause factors of the quality issues. There is a complex interaction among process setting variables, <i>in situ</i> feature variables, and quality variables. More importantly, the selection of the <i>in situ</i> feature variables is typically based on engineering domain knowledge and sensor instrumentation capability, rather than based on statistical significance of variables. In this research, an ensemble model strategy is proposed to quantify the effect of the process setting variables on the <i>in situ</i> feature variables, and the effect of the <i>in situ</i> feature variables on quality variables in a two-level hierarchical way. By identifying significant <i>in situ</i> feature variables as responses for the process setting variables, as well as predictors for product quality in a joint estimation problem, the proposed models have a hierarchical variable relationship to enable <i>in situ</i> process control for variation reduction and defect mitigation. A real case study is investigated to demonstrate the advantages of the proposed method.

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about driving environment. Studies have proved that automated vehicles have a potential to decrease traffic congestion on road networks by reducing the time headway, enhancing the traffic capacity and improving the safety margins in car following. Furthermore, vehicle movement and driver’s behavior of conventional vehicles will be affected by the presence of automated vehicles in traffic networks. Despite different encouraging factors, automated driving raises some concerns such as possible loss of situation awareness, overreliance on automation and degrading driving skills in absence of practice. Moreover, coping with complex scenarios, such as merging at ramps and overtaking, in terms of interaction between automated vehicles and conventional vehicles need more research. This thesis work aims to investigate the effects of automated vehicles on driver’s behavior and traffic performance. A broad literature review in the area of driving simulators and psychological studies was performed to examine the automated vehicle effects on driver’s behavior. Findings from the literature survey, which has been served as setup values in the simulation study of the current work, reveal that the conventional vehicles, which are driving close to the platoon of automated vehicles with short time headway, tend to reduce their time headway and spend more time under their critical time headway. Additionally, driving highly automated vehicles is tedious in a long run, reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of automated vehicles on traffic performance, a microscopic simulation case study consisting of different penetration rates of automated vehicles (0, 50 and 100 percentages) was conducted in VISSIM software. The scenario network is a three-lane autobahn segment of 2.9 kilometers including an off-ramp, on-ramp and a roundabout with some surrounding urban roads. Outputs of the microscopic simulation in this study reveal that the positive effects of automated vehicles on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably decreased by 8.09% during p.m. peak hours in scenario with automated vehicles. Besides, Smoother traffic flow with less queue in the weaving segment was observed. Result of the scenario with 50% share of automated vehicles moreover shows a feasible interaction between conventional vehicles and automated vehicles. Meaningful outputs of this case study, based on the input data from literature review, demonstrate the capability of VISSIM software to simulate the presence of automated vehicles in great extent, not only as an automated vehicle scenario but also a share of them, in traffic network. The validity of the output values nonetheless needs future research work on urban and rural roads with different traffic conditions.

Traffic safety has traditionally been measured by analyzing historical accident data, which is a reactive method where a certain number of accidents must occur in order to identify the safety problem. An alternative safety assessment method is to use proximal safety indicators that are defined as measures of accident proximity, which is considered a proactive method. With this method it is possible to detect the safety problem before the accidents have happened. To be able to detect problems in traffic situations in general, microscopic simulation is commonly used. In these models it may be possible to generate representative near-accidents, measured by proximal safety indicator techniques. A benefit of this would be the possibility to experiment with different road designs and evaluate the traffic safety level before reconstructions of the road infrastructure. Therefore has an investigation been performed to test the possibility to identify near-accidents (conflicts) in a microscopic simulation model mimicking the Traffic Conflict Technique developed by Hydén (1987). In order to perform the investigation a case study has been used where an intersection in the city center of Stockholm was studied. The intersection has been rebuilt, which made it possible to perform a before and after study. For the previous design there was a traffic safety assessment available which was carried out using the Traffic Conflict Technique. Microscopic simulation models representing the different designs of the intersection were built in PTV Vissim. In order to evaluate and measure the traffic safety in reality as well as in the microscopic simulation models, a traffic safety assessment was performed in each case. The traffic safety assessment in field for the present design was carried out as a part of this thesis. The main focus of this thesis was the road safety for vulnerable road users. The method to identify conflicts in the simulation model has been to extract raw data output from the simulation model and thereafter process this data in a Matlab program, aiming to mimic the Traffic Conflict Technique. The same program and procedure was used for both the previous and the present design of the intersection. The results from the traffic safety assessment in the simulation model have been compared to the results from the field study in order to evaluate how well microscopic simulation works as an evaluation tool for traffic safety in new designs. The comparison shows that the two methods of conflict identification cannot replace each other straight off. But with awareness of the differences between the methods, the simulation model could be used as an indication when evaluating the level of traffic safety in a road design.

Radiation chemistry is concerned with understanding the chemical kinetics following the application of ionising radiation. There are two main methods for modelling recom- bination and spin dynamics in radiation chemical systems: The Monte Carlo random flights algorithm, in which the trajectories of the diffusing species are followed ex- plicitly and the Independent Reaction Times (IRT) algorithm, where reaction times are sampled from appropriate marginal distribution functions. This thesis reports develop- ments to both methods, and applies them to better understand experimental findings, particularly spin relaxation effects. Chapter 4 introduces current simulation techniques and presents newly developed algorithms and simulation programs (namely Hybrid and Slice) for modelling spatially dependent spin effects. A new analytical approximation for accurately treating ion-pair recombination in low-permittivity solvents in also presented in this chapter. Chapter 5 explores the photodissociation of H₂O₂, where there is some controversy in the literature on the spin state of the precursor. This chapter explores the possibility of reproducing the observed spin polarisation phase using the Radical Pair Mechanism. Chapter 6 presents two new algorithms for treating reactive products in the IRT framework. These have been tested for two chemical systems: (i) photodissociation of H₂O₂ where the ·OH are scavengeable; (ii) water photolysis which produces H⁺, ·OH and e⁻__aq. In the latter case a careful handling of three body correlations is required. Chapter 7 presents simulation results which suggest a strong correlation between scavenging and ion recombination in low permittivity solvents. A path decomposition method has been devised that allows IRT simulations to be corrected for this effect. Chapter 8 presents evidence for spin-entanglement and cross-recombination to act as an extra source of relaxation for ion-recombination in low permittivity solvents. It is hypothesised this effect contributes to the anomalous relaxation times observed for certain cyclic hydrocarbons. Chapter 9 presents an extension of the IRT simulation method to micelles. The kinetics are shown to be accurately described using the mean reaction time and the exponential approximation.

Side friction factors are defined as all those actions related to the activities taking place by the sides of the road and sometimes within the road, which interfere with the traffic flow on the travelled way. They include but not limited to pedestrians, bicycles, non-motorised vehicles, parked and stopping vehicles. These factors are normally very frequent in densely populated areas in developing countries, while they are random and sparse in developed countries making it of less interest for research and consequently there is comparatively little literature about them. The objective of this thesis is to analyze the effect of these factors on traffic performance measures on urban roads. To carry out this work, a research design was formulated including specific methods and prescribed limitations. An empirical case study methodology was adopted where Dar-es-salaam city in Tanzania was chosen as a representative case. The scope was limited to include only road-link facilities. A sample of these facilities including two-lane two-way and four-lane two-way roads were selected and studied. The study was conducted in two parts, of which each involved a distinctive approach. Part one involved a macroscopic approach where traffic and friction data were collected and analyzed at an aggregated level, whereas part two involved a microscopic approach where data of individual frictional elements were collected and analysed individually. Data collection was mainly performed by application of video method, which proved to be effective for simultaneous collection of traffic and side friction data. Data reduction was conducted chiefly by computer, using standard spreadsheet and statistical software packages, mainly SPSS and some computer macros. The analysis part was based on statistical methods, chiefly regression analysis. In the macroscopic approach, traffic and friction data from all sites were adjusted through a process called ‘normalization’, which enabled the data from the different sites to be merged, and consequently to obtain speed-flow curves for each road type. The individual friction factors through regression analysis were weighted and combined into one unit of measure of friction called "FRIC". The effect of "FRIC" on speed-flow curves was analyzed. The results showed significant impact on speed for both road types. Impact on capacity was identified on two-lane two-way roads while field data on four-lane two-way roads did not allow this. In the microanalysis approach, effect of individual side friction factors on speed was analyzed. The results showed that on two-lane two-way roads, all studied factors exhibited statistically significant impact on speed, while on four-lane two-way roads, only one factor showed the same. The results also identified impact values characteristic to the individual friction factors on some roads. Recommendations were made based on these results that highway capacity studies particularly in developing countries, should include the friction variable, though in the form suitable to their own particular circumstances. Further recommendations were made that these results should be applied to formulate management programs seeking to limit levels of side friction on high mobility urban arterial streets in order to improve traffic safety and operation efficiency. / <p>QC 20100701</p>