Diamond interchange design has been commonly utilized in United States to facilitate traffic exchange between freeway and frontage roads. Another less common interchange design is X-ramp interchange, which is the reversed version of diamond. The major benefit of X-ramp interchange is that it can keep travelers on the freeway until the downstream exit ramp to avoid going through the intersection. It also has drawbacks such as travelers with cross street destinations will experience more delay. This study focuses on when the ramp reversal is desirable. To compare the diamond and X-ramp design, an experimental design is conducted using Latin Hypercube Design method. Four varying factors include interchange design type, traffic volume on the frontage road, through movement percentage and saturation rate of the intersection. 40 scenarios are generated for simulation study using Synchro and VISSIM. Based on the simulation study, optimal signal timing strategies are recommended for each type of interchange design under various traffic conditions. Also, ramp reversal is found closely related to the following factors such as interchange frequency, upstream interchange design, traffic volume on frontage road, through movement percentage and intersection saturation rate. Conclusions are made on when X-ramp is better than diamond interchange design. At last, future research directions are recommended.

Evacuation processes can be evaluated using different simulation models. However, recently, microscopic simulation models have become a more popular tool for this purpose. The objectives of this study are to model multiple evacuation scenarios and to compare the INTEGRATION microscopic traffic simulation model against the MATSim mesoscopic model. Given that the demand was the same for both models, the comparison was achieved based on three indicators: estimated evacuation time, average trip duration, and average trip distance. The results show that the estimated evacuation times in both models are close to each other since the Origin-Destination input file has a long tail distribution and so the majority of the evacuation time is associated when travelers evacuate and not the actual evacuation times. However, the evaluation also shows a considerable difference between the two models in the average trip duration. The average trip duration using INTEGRATION increases with increasing traffic demand levels and decreasing roadway capacity. On the other hand, the average trip duration using MATSim decreases with increasing traffic demand and decreasing the roadway capacity. Finally, the average trip distance values were significantly different in both models. The conclusion showed that the INTEGRATION model is more realistic than the MATSim model for evacuation purposes. The study concludes that despite the large execution times of a microscopic traffic simulation, the use of microsimulation is a worthwhile investment. / Master of Science

The analysis of grade crossing safety has long focused on vehicle-train crashes using statistical models based on crash data. The potential crashes generated by vehicle-vehicle rear-end conflicts have often been ignored. The interaction of different traffic attributes on safety performance of a grade crossing is also not well-understood. The primary objective of this thesis is to model the causal relationship of vehicle-vehicle interactions by developing the operation logic of gate-equipped grade crossing using a commercially available microscopic simulation package that models human driver behaviors. The simulation-generated vehicle trajectory data allows detail safety performance analysis on vehicle-vehicle interaction over time as they approach the track. A dual-gate equipped crossing at Kitchener, Ontario is selected as the study area. Initially, logic modifications are made to the simulation package (VISSIM) in order to accurately model the grade crossing segment. A two-step calibration is used in this thesis. Firstly, model input parameters for a signalized intersection from literature are used to model typical car-following behavior along this type of roadway. Secondly, parameters used to model drivers’ decision and reaction when approaching crossing is fine tuned through data collection and calibration. After incorporating all the modifications to the simulation package, validation is undertaken by comparing model-generated speed profiles to on-site observed speed profile. The established model is tested for its safety performance sensitivity through varying three traffic attributes in the simulation: (i) percentage of bus, (ii) total traffic volume, (iii) percentage of cars in the center lane of a 2-lane approach. Four safety performance measures were selected. The overall results indicate that the established model is functional and reliable in modeling grade crossing vehicles interactions at gated crossings. In the absence of a train, vehicles’ reduction in speed in the vicinity of a crossing results in traffic flow turbulence that increases the opportunity for high risk rear-end vehicle interactions. The sensitivity test revealed that the spillback behavior of vehicles due to the stopping behaviors of buses increases risk in the upstream section. Also, overloading of vehicles into the network indeed improves safety as the effect of differential speed diminishes. Among the four selected safety performance measures, DRAC seems to reflect problems with rear-end vehicle interactions in the vicinity of a crossing as a function of the traffic attributes considered in this research.

The analysis of grade crossing safety has long focused on vehicle-train crashes using statistical models based on crash data. The potential crashes generated by vehicle-vehicle rear-end conflicts have often been ignored. The interaction of different traffic attributes on safety performance of a grade crossing is also not well-understood. The primary objective of this thesis is to model the causal relationship of vehicle-vehicle interactions by developing the operation logic of gate-equipped grade crossing using a commercially available microscopic simulation package that models human driver behaviors. The simulation-generated vehicle trajectory data allows detail safety performance analysis on vehicle-vehicle interaction over time as they approach the track. A dual-gate equipped crossing at Kitchener, Ontario is selected as the study area. Initially, logic modifications are made to the simulation package (VISSIM) in order to accurately model the grade crossing segment. A two-step calibration is used in this thesis. Firstly, model input parameters for a signalized intersection from literature are used to model typical car-following behavior along this type of roadway. Secondly, parameters used to model drivers’ decision and reaction when approaching crossing is fine tuned through data collection and calibration. After incorporating all the modifications to the simulation package, validation is undertaken by comparing model-generated speed profiles to on-site observed speed profile. The established model is tested for its safety performance sensitivity through varying three traffic attributes in the simulation: (i) percentage of bus, (ii) total traffic volume, (iii) percentage of cars in the center lane of a 2-lane approach. Four safety performance measures were selected. The overall results indicate that the established model is functional and reliable in modeling grade crossing vehicles interactions at gated crossings. In the absence of a train, vehicles’ reduction in speed in the vicinity of a crossing results in traffic flow turbulence that increases the opportunity for high risk rear-end vehicle interactions. The sensitivity test revealed that the spillback behavior of vehicles due to the stopping behaviors of buses increases risk in the upstream section. Also, overloading of vehicles into the network indeed improves safety as the effect of differential speed diminishes. Among the four selected safety performance measures, DRAC seems to reflect problems with rear-end vehicle interactions in the vicinity of a crossing as a function of the traffic attributes considered in this research.

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

Though comparisons of simulation models have been conducted, few investigations have examined in detail the logical differences between models. If the output measures of effectiveness are to be interpreted correctly, it is important that the analyst understand some of the underlying logic and assumptions upon which the results are based. An understanding of model logic and its inherent effect on the results will aid the transportation analyst in the application and calibration of a simulation model. In this thesis, the car-following behavior of the CORSIM and INTEGRATION simulation models are examined in significant detail, and its impact on output results explained. In addition, the thesis presents a calibration procedure for the CORSIM sub-model, FRESIM. Currently, FRESIM is calibrated by ad hoc trial-and-error, or by utilizing empirically developed cross-referencing tables. The literature reveals that the relationship between the microscopic input parameters of the CORSIM model, and the macroscopic parameters of capacity is not understood. The thesis addresses this concern. Finally, the thesis compares the INTEGRATION and CORSIM models in freeway and urban environments. The comparison is unique in that the simulated networks were configured such that differences in results could be identified, isolated, and explained. Additionally, the simplified nature of the test networks allowed for the formulation of analytical solutions. The thesis begins by relating steady-state car-following behavior to macroscopic traffic stream models. This is done so that a calibration procedure for the FRESIM (Pipes) car-following model could be developed. The proposed calibration procedure offers an avenue to calibrate microscopic car-following behavior using macroscopic field measurements that can be easily obtained from loop detectors. The calibration procedure, while it does not overcome the inherent shortcomings of the Pipes model, does provide an opportunity to better calibrate the network FRESIM car-following sensitivity factor to existing roadway conditions. The thesis then reports an observed inconsistency in the link-specific car-following sensitivity factor of the FRESIM model. Because calibration of a network on a link-specific basis is key to an accurate network representation, a correction factor was developed that should be applied to the analytically calculated link-specific car-following sensitivity factor. The application of the correction factor resulted in observed saturation flow rates that were within 5% of the desired saturation flow rates. The thesis concludes with a comparison of the CORSIM and INTEGRATION models for transient conditions. As a result of the various intricacies and subtleties that are involved in transient behavior, the comparisons were conducted by running the models on simple networks where analytical solutions to the problem could be formulated. In urban environments, it was observed that the models are consistent in estimates of delay and travel time, and inconsistent in estimates of vehicle stops, stopped delay, fuel consumption, and emissions. Specifically, it was observed that the NETSIM model underestimates the number of vehicle stops in comparison with INTEGRATION and the analytical formulation. It was also observed that the NETSIM vehicles speed and acceleration profiles are characterized by abrupt accelerations and decelerations. These abrupt movements significantly impact stopped time delay and vehicle emissions estimates. Inconsistencies in emissions estimates can also be attributed to differences in the embedded rate tables of each model. In freeway environments for under-saturated conditions, INTEGRATION returned higher values of travel time and delay, and lower values of average speed than the FRESIM model. These results are consistent with the analytical solution, and can be attributed to the speed-flow relationship of each model. In saturated conditions, when the capacity of the bottleneck is equal to the demand volume, the emergent vehicle behavior of the FRESIM model was observed to be inconsistent with the analytical solution. The FRESIM vehicles were observed to dramatically decelerate upon entering a lower-capacity link. This deceleration behavior led to higher travel time and delay time estimates in FRESIM than in INTEGRATION. In over-saturated conditions, longer queue lengths were observed in FRESIM than in INTEGRATION, resulting in slightly higher travel and delay estimates in the FRESIM model. The reason for the discrepancy in queue lengths is unclear, as the network jam density in each model was equivalent. / Master of Science

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.

Transportation safety has been recognized as a public health issue worldwide, consequently, transportation researchers and practitioners have been attempting to provide adequate safety performance for the various transportation components and facilities to all road users given the usually scarce resources available. Safety engineers have been trying to make decisions affecting safety based on the knowledge extracted from different types of statistical models and/or observational before-after analysis. It is generally recognized that this type of factual knowledge is not easily obtained either statistically or empirically. Despite the intuitive link between road safety and observed crashes, a good understanding of the sequence of events prior to the crash can provide a more rational basis for the development of engineering countermeasures. The development of more comprehensive mechanistic models for safety assessment is heavily dependent on detailed vehicle tracking data that is not readily available. The potential of microscopic simulation in traffic safety and traffic conflict analysis has gained increasing interest mostly due to recent developments in human behaviour modelling and real-time vehicle data acquisition. In this thesis, we present a systematic investigation of the use of existing behavioural microscopic simulation models in short-term road safety studies. Initially, a microscopic framework is introduced to identify potentially unsafe vehicle interactions for different vehicle movements based on three types of traffic behaviour protocols: car-following, lane change and gap acceptance. This microscopic model for safety assessment applies a safety performance measure based on pairwise comparisons of spacing and speed differential between adjacent vehicles and individual braking power in real-time. A calibration/validation procedure using factorial analysis is presented to select best model input parameters for this safety performance measure by using high resolution vehicle tracking data. The ability of the proposed safety performance measure to reflect real-life observed high-risk vehicular interactions is explored in three intuitive tests using observed crash data. Finally, the usefulness of the model is illustrated through its application to investigate the safety implications of two different geometric and operational traffic strategies. The overall results indicate that, notwithstanding the fact that actual behavioural microscopic algorithms have not been developed strictly to model crashes, they are able to replicate several factors directly related to high risk situations that could lead to crashes with reasonable accuracy. With the existing upward trend in computing power, modelling techniques and increasing availability of detailed vehicle tracking data, it is likely that safety studies will be carried out using a more mechanistic and inclusive approach based on disruptive driving behaviour rather than ultimate unpredictable and heavily restrictive crash events.