Historically, the traditional planning process has not given much attention to the road safety evaluation of development plans. To make an informed, defensible, and proactive choice between alternative plans and their safety implications, it is necessary to have a procedure for estimating and evaluating safety performance. A procedure is required for examining the influence of the urban network development on road safety, and in particular, determining the effects of the many variables that affect safety in urban planning. Safety planning models can provide a decision-support tool that facilitates the assessment of the safety implications of alternative network plans. The first objective of this research study is to develop safety planning models that are consistent with the regional models commonly used for urban transportation planning. Geographically weighted Poisson regression (GWPR), full-Bayesian semiparametric additive (FBSA), and traditional generalized linear modelling (GLM) techniques are used to develop the models. The study evaluates how well each model is able to handle spatial variations in the relationship between collision explanatory variables and the number of collisions in a zone. The evaluation uses measures of goodness of fit (GOF) and finds that the GWPR and FBSA models perform much better than the conventional GLM approach. There is little difference between the GOF values for the FBSA and GWPR models. The second objective of this research study is to examine the temporal transferability of the safety planning models and alternative updating methods. The updating procedures examine the Bayesian approach and application of calibration factors. The results show that the models are not temporally transferable in a strict statistical sense. However, relative measures of transferability indicate that the transferred models yield useful information in the application context. The results also show that the updated safety planning models using the Bayesian approach predict the number of collisions better than the calibration factor procedure.

In multi-modal transit networks with several intersecting lines and modes, travel through the network typically requires one or more transfers among transit lines and modes, and as such transfer time is a significant component of transit travel time from the perspective of passengers. Accordingly, efficient transfers are very important to increase the attractiveness and productivity of transit service. This study presents two approaches for the provision of efficient transfers: schedule coordination and real-time CP (Connection Protection) control. The coordination of transit schedules can reduce transfer time significantly. This dissertation develops an optimization model for generating transit timetables that minimize transfer-related times. The model attempts to find an optimal timetable by shifting the existing timetable and/or adding holding time to the timetable to minimize delays associated with transfers from a feeder route to a receiving route. Analytical models are developed to estimate the waiting time of the transfer passengers, and also to determine the influence of the schedule modification on the waiting times of non-transfer passengers. The developed model is evaluated through a case study, and the results show that the model reduces effectively the total transfer and waiting times through the modification of the current schedule. However, even though timetables among intersecting lines may be properly coordinated, an operational control method is necessary to maintain coordinated transfers, which may occasionally be disrupted due to unexpected delays of transit vehicles. A promising approach is to utilize real-time CP control. It involves holding a transit unit in order to wait for another transit unit that is planned to provide a coordinated transfer but has been delayed. This study also develops a CP model to apply a holding control to a receiving run in order to protect the scheduled connection. It incorporates the probabilistic nature of transit operations in formulating a cost function, and accordingly makes more robust decisions for control. The developed model is evaluated and compared with previous models to demonstrate its ability to improve transfer efficiency and reduce the waiting times of affected passengers.

Public transit is considered a cost-effective alternative to mitigate the effects of traffic gridlock through the implementation of innovative service designs, and deploying new smart systems for operations control and traveller information. Public transport planners use transit assignment models to predict passenger loads and levels of service. Existing transit assignment approaches have limitations in evaluating the effects of information technologies, since they are neither sensitive to the types of information that may be provided to travellers nor to the traveller’s response to that information. Moreover, they are not adequate for evaluating the impacts of Intelligent Transportation Systems (ITS) deployments on service reliability, which in turn affect passengers’ behaviour. This dissertation presents an innovative transit assignment framework, namely the MIcrosimulation Learning-based Approach to TRansit ASsignment – MILATRAS. MILATRAS uses learning and adaptation to represent the dynamic feedback of passengers’ trip choices and their adaptation to service performance. Individual passengers adjust their behaviour (i.e. trip choices) according to their experience with the transit system performance. MILATRAS introduces the concept of ‘mental model’ to maintain and distinguish between the individual’s experience with service performance and the information provided about system conditions. A dynamic transit path choice model is developed using concepts of Markovian Decision Process (MDP) and Reinforcement Learning (RL). It addresses the departure time and path choices with and without information provision. A parameter-calibration procedure using a generic optimization technique (Genetic Algorithms) is also proposed. A proof-of-concept prototype has been implemented; it investigates the impact of different traveller information provision scenarios on departure time and path choices, and network performance. A large-scale application, including parameter calibration, is conducted for the Toronto Transit Commission (TTC) network. MILATRAS implements a microsimulation, stochastic (nonequilibrium-based) approach for modelling within-day and day-to-day variations in the transit assignment process, where aggregate travel patterns can be extracted from individual choices. MILATRAS addresses many limitations of existing transit assignment models by exploiting methodologies already established in the areas of traffic assignment and travel behaviour modeling. Such approaches include the microsimulation of transportation systems, learning-based algorithms for modelling travel behaviour, agent-based representation for travellers, and the adoption of Geographical Information Systems (GIS). This thesis presents a significant step towards the advancement of the modelling for the transit assignment problem by providing a detailed operational specification for an integrated dynamic modelling framework – MILATRAS.

Historically, the traditional planning process has not given much attention to the road safety evaluation of development plans. To make an informed, defensible, and proactive choice between alternative plans and their safety implications, it is necessary to have a procedure for estimating and evaluating safety performance. A procedure is required for examining the influence of the urban network development on road safety, and in particular, determining the effects of the many variables that affect safety in urban planning. Safety planning models can provide a decision-support tool that facilitates the assessment of the safety implications of alternative network plans. The first objective of this research study is to develop safety planning models that are consistent with the regional models commonly used for urban transportation planning. Geographically weighted Poisson regression (GWPR), full-Bayesian semiparametric additive (FBSA), and traditional generalized linear modelling (GLM) techniques are used to develop the models. The study evaluates how well each model is able to handle spatial variations in the relationship between collision explanatory variables and the number of collisions in a zone. The evaluation uses measures of goodness of fit (GOF) and finds that the GWPR and FBSA models perform much better than the conventional GLM approach. There is little difference between the GOF values for the FBSA and GWPR models. The second objective of this research study is to examine the temporal transferability of the safety planning models and alternative updating methods. The updating procedures examine the Bayesian approach and application of calibration factors. The results show that the models are not temporally transferable in a strict statistical sense. However, relative measures of transferability indicate that the transferred models yield useful information in the application context. The results also show that the updated safety planning models using the Bayesian approach predict the number of collisions better than the calibration factor procedure.

In multi-modal transit networks with several intersecting lines and modes, travel through the network typically requires one or more transfers among transit lines and modes, and as such transfer time is a significant component of transit travel time from the perspective of passengers. Accordingly, efficient transfers are very important to increase the attractiveness and productivity of transit service. This study presents two approaches for the provision of efficient transfers: schedule coordination and real-time CP (Connection Protection) control. The coordination of transit schedules can reduce transfer time significantly. This dissertation develops an optimization model for generating transit timetables that minimize transfer-related times. The model attempts to find an optimal timetable by shifting the existing timetable and/or adding holding time to the timetable to minimize delays associated with transfers from a feeder route to a receiving route. Analytical models are developed to estimate the waiting time of the transfer passengers, and also to determine the influence of the schedule modification on the waiting times of non-transfer passengers. The developed model is evaluated through a case study, and the results show that the model reduces effectively the total transfer and waiting times through the modification of the current schedule. However, even though timetables among intersecting lines may be properly coordinated, an operational control method is necessary to maintain coordinated transfers, which may occasionally be disrupted due to unexpected delays of transit vehicles. A promising approach is to utilize real-time CP control. It involves holding a transit unit in order to wait for another transit unit that is planned to provide a coordinated transfer but has been delayed. This study also develops a CP model to apply a holding control to a receiving run in order to protect the scheduled connection. It incorporates the probabilistic nature of transit operations in formulating a cost function, and accordingly makes more robust decisions for control. The developed model is evaluated and compared with previous models to demonstrate its ability to improve transfer efficiency and reduce the waiting times of affected passengers.

Understanding how households make decisions with regards to their vehicle fleet based on their demographics, socio-economic status and travel patterns is critical for managing the financial, economic, social and environmental health of cities. Vehicle fleets therefore form a component of the Integrated Land Use, Transportation and Environment (ILUTE) modelling system under development at the University of Toronto. ILUTE is a year-by-year agent-based microsimulation model of demographics, land use and economic patterns, vehicle fleet decisions and travel choices in the Greater Toronto and Hamilton Area. This thesis extends previous work that modelled the quantity, class and vintage of vehicles in ILUTE households. This revised model offers three key improvements: transaction decisions are made sensitive to travel patterns, fuel costs are better represented, and vehicle purchases are considered in the context of the overall household budgeting. Results are promising, but further model validation is required. Potential extensions of the research are discussed.

Because conventional seismic force resisting systems rely on yielding of key structural members to limit seismic forces, structural damage is expected after a design-level earthquake. Repairing this damage can be very expensive, if it is possible at all. Researchers have been developing a new family of self-centring systems that avoid structural damage. One such system is a controlled rocking steel frame, which is the subject of this thesis. In a controlled rocking steel frame, the columns of a frame are permitted to uplift from the foundation, and the response is controlled by using a combination of post-tensioning and energy dissipation. Although previous studies have confirmed the viability of this system, they have also shown that rocking does not fully limit the peak seismic forces because of higher mode effects. If a structure is designed to account for these effects, it may be uneconomical, but if it is not designed to account for them, it may be unsafe. The purpose of this thesis is to develop recommendations for the design of controlled rocking steel frames, particularly with regard to higher mode effects. A theoretical framework for understanding higher mode effects is developed, and large-scale shake table testing is used to study the behaviour of a controlled rocking steel frame. Two mechanisms are proposed to mitigate the increase in structural forces due to higher mode effects, and these mechanisms are validated by shake table testing. Numerical modelling of controlled rocking steel frames is shown to become more reliable when higher mode mitigation mechanisms are used to limit the seismic response. In the final chapters, the thesis proposes and validates a new methodology for the limit states design of controlled rocking steel frames.

This research aims at developing a better understanding of commuters preferences and mode switching behaviour towards local transit for work trips. The proposed methodological approach incorporates three main stages. The first introduces a conceptual framework for modal shift maximized transit route design model that extends the use of demand models beyond forecasting transit ridership to the operational extent of transit route design. The second deals with designing and implementing a socio-psychometric COmmuting Survey for MOde Shift (COSMOS). Finally, the third stage focuses on developing econometric choice models of mode switching behaviour towards public transit. Advanced mode shift models are developed using state-of-the-art methodology of combining Revealed Preference (RP) and Stated Preference (SP) information. The results enriched our understanding of mode switching behaviour and revealed some interesting findings. Some socio-psychological variables have shown to have strong influence on mode shift and improved the models in terms of fitness and statistical significance. In an indication of the superiority of the car among other travel options, strong car use habit formation was realized for car drivers, making it hard to persuade them to switch to public transit. Further, unlike conventional choice models, the developed mode shift models showed that travel cost and in-vehicle travel time are of lower importance compared to other transit Level of Service (LOS) attributes such as waiting time, service reliability, number of transfers, transit technology, and crowding level. The results also showed that passengers are more likely to shift to rail-based modes (e.g. LRT and subway) than rubber-tyred modes (e.g. BRT). On the other hand, the availability of park-and-ride facilities as well as both schedule and real-time information provision did not appear to be significant for mode switching to public transit for work trips. This research provides evidence that mode shift is a complex process which involves socio-psychological variables beside common socio-demographic and modal attributes. The developed mode switching models present a new methodologically sound tool for evaluating the impacts of alternative transit service designs on travel behaviour. Such tool is more desirable for transit service planning than the traditional ones and can aid in precisely estimating transit ridership.

The shear rupture of massive (intact non-jointed) brittle rock in underground high stress mines occurs under a variety of different boundary conditions ranging from constant stress (no resistance to deformation) to constant stiffness (resistance to deformation). While a variety of boundary conditions exist, the shear rupture of massive rock in the brittle field is typically studied under constant stress boundary conditions. According to the theory, the fracturing processes leading to shear rupture zone creation occur at or near peak strength with a shear rupture surface created in the post-peak region of the stress-strain curve. However, there is evidence suggesting that shear rupture zone creation can occur pre-peak. Limited studies of shear rupture in brittle rock indicate pre-peak shear rupture zone creation under constant stiffness boundary conditions. This suggests that the boundary condition influences the shear rupture zone creation characteristics. In this thesis, shear rupture zone creation in brittle rock is investigated in direct shear under constant normal stress and normal stiffness boundary conditions. It is hypothesized that the boundary condition under which a shear rupture zone is created influences its characteristics (i.e., shear rupture zone geometry, load-displacement response, shear rupture zone creation relative to the load-displacement curve, and peak and ultimate strengths). In other words, it is proposed that the characteristics of a shear rupture zone are not only a function of the rock or rock mass properties but the boundary conditions under which the rupture zone is created. The hypothesis is tested and proven through a series of simulations using a two dimensional particle based Distinct Element Method (DEM) and its embedded grain based method. The understanding gained from these simulations is then used in the analysis and re-interpretation of rupture zone creation in two mine pillars. This is completed to show the value and practical application of the improved understanding gained from the simulations. The re-interpretation of these case histories suggests that one pillar ruptured predominately under a constant stress boundary condition while the other ruptured under a boundary condition changing from stiffness to stress control.

This research aims at developing a better understanding of commuters preferences and mode switching behaviour towards local transit for work trips. The proposed methodological approach incorporates three main stages. The first introduces a conceptual framework for modal shift maximized transit route design model that extends the use of demand models beyond forecasting transit ridership to the operational extent of transit route design. The second deals with designing and implementing a socio-psychometric COmmuting Survey for MOde Shift (COSMOS). Finally, the third stage focuses on developing econometric choice models of mode switching behaviour towards public transit. Advanced mode shift models are developed using state-of-the-art methodology of combining Revealed Preference (RP) and Stated Preference (SP) information. The results enriched our understanding of mode switching behaviour and revealed some interesting findings. Some socio-psychological variables have shown to have strong influence on mode shift and improved the models in terms of fitness and statistical significance. In an indication of the superiority of the car among other travel options, strong car use habit formation was realized for car drivers, making it hard to persuade them to switch to public transit. Further, unlike conventional choice models, the developed mode shift models showed that travel cost and in-vehicle travel time are of lower importance compared to other transit Level of Service (LOS) attributes such as waiting time, service reliability, number of transfers, transit technology, and crowding level. The results also showed that passengers are more likely to shift to rail-based modes (e.g. LRT and subway) than rubber-tyred modes (e.g. BRT). On the other hand, the availability of park-and-ride facilities as well as both schedule and real-time information provision did not appear to be significant for mode switching to public transit for work trips. This research provides evidence that mode shift is a complex process which involves socio-psychological variables beside common socio-demographic and modal attributes. The developed mode switching models present a new methodologically sound tool for evaluating the impacts of alternative transit service designs on travel behaviour. Such tool is more desirable for transit service planning than the traditional ones and can aid in precisely estimating transit ridership.