The asphalt binder is a viscoelastic substance that exhibits both viscous and elastic behaviour. Asphalt binder is an effective adhesive material for use in the pavement, however it is a difficult material to understand and describe due to the wide variety of its behaviour. This research aimed to investigate the impact of polymer modification on nonrecoverable creep compliance (Jnr). Three modifiers (fly ash (FA), Styrene-Butadiene- Styrene (SBS), and fly ash-based on geopolymer (GF)) were used. Asphalt binders were tested at various temperatures, ranging from 40 to 70 °C with a 3 °C gap, and regression models were developed. The results revealed that 2% SBS modified asphalt binder exhibited elastomeric behaviour at low temperatures, whereas 4% SBS modified asphalt binder exhibited noteworthy elastomeric behaviour at various temperatures. The power-law models most effectively illustrated the correlation between temperature and nonrecoverable creep compliance (Jnr) at different stresses, 0.1 kPa and 3.2 kPa. The developed models proved to be effective for appropriately selecting the polymer type and amount suitable to minimize the Jnr. The hybrid and 4%SBS binders performed best in terms of strain recovery at high temperatures, with Jnr values of less than 0.5 being achieved at 58 °C and 3.2 kPa.
Calgary’s road network constitutes a major investment over many generations and plays a crucial role in the City’s well-being by guaranteeing its citizens with full accessibility, ensuring safe travel, and providing a strong business competitiveness through an efficient movement of goods and services. This study identifies key limitations in current pavement network life cycle cost analysis processes by comparing the results of traditional prioritization approaches to a true multi-year multi-constraint optimization analysis. The results shows that the optimization solutions outperformed prioritization at all years showing an average 5.3% improvement over the planning horizon and 9.3% by the end of the plan. Monetization methods also arrived at significant cost savings via added performance over a 10-year planning horizon by switching to a mathematically optimized solution. To further improve modeling accuracy and reliability of results, this study investigates the quality of performance models used within the pavement management system and discusses the development of machine learning-based deterioration models using decision tree regression. The effects of more modern performance modeling methods on investment planning is examined by comparing various optimization scenarios using both the ML-based and the traditional age-based deterioration models. The paper shows the importance of condition-based predictive modeling and integrating accurate performance models into the current asset management system to provide more accurate information on monitoring the network's life expectations, capital investment plans, and vulnerable communities with accelerated pavement deterioration patterns.
COVID-19 imposed travel restrictions have induced significant changes to our travel behaviour and daily life, such as work-from-home and online learning. The long-lasting nature of this pandemic might trigger a longer-term change in our behaviour after the pandemic, such as continued preference for work-from-home and e-learning. Such changes in work and learning arrangements do not only indicate a reduction in travel during the peak hour, it might also indicate a shift in travel to other times of day as well as changes in trip purposes and travel distances. For example, a worker telecommuting might spend the whole/part of the day at home and then go out to meet friends/family for dinner and do groceries from a store near the home while returning. Traditional four-stage travel demand models typically take the origin-destination (O\D) matrix for the peak hours as input at an aggregate-level of temporal, spatial, and population resolution and do not necessarily accommodate the trip chaining behaviour of an individual. As a result, the behavioural changes associated with time-sensitive policies such as work-from-home and e-learning are not accommodated and/or reflected by these models. This demands the development agent-based transport simulation models adopting activity-based modelling technique. This study adopts an agent-based transport network simulation technique to generate 24-hour traffic for alternative work-from-home and online learning strategies. The model is calibrated and validated for the Central Okanagan region of British Columbia, Canada. Specifically, the open source Multi-Agent Transport Simulation (MATSim) model has been adopted, which was written using the Java programming language. The 24-hour travel schedule is developed adopting an activity-based modelling technique. The findings of this study will assist the governments and transit agencies in understanding the dynamics of travel behaviour and the consequent change in traffic patterns over the 24-hour for alternative work arrangement scenarios.
The advancement of new laser technologies in recent years has changed the resolution of pavement data captured during collection, creating the opportunity for a fully automated approach to condition evaluation. Inspired by the Universal Cracking Indicator proposed by William Paterson in 1994, and developed by the ASTM E17 working group, this paper will present the application of the Pavement Surface Cracking Metric (PSCM). By using quantitative definitions in order to ensure consistency of the results, this method removes the subjectivity that happens with human rating of pavement distresses. The repeatability and reproducibility of the method were assessed by collecting multiple runs of pavement data on three separate asphalt sections. The application of the Pavement Surface Cracking Index (PSCI) to convert the PSCM value, which is a physical property of the pavement, into a 100-0 score of the pavement section is also presented. Finally, the use of the PSCM to classify the pavement distress and the inclusion of potholes and patching in the metrics are also discussed.
The City of Calgary (The City) initiated one of the first Warm Mix Asphalt (WMA) technology projects in Canada in 2005 with Tetra Tech Canada Inc. A follow-up assessment of that project was completed in 2021. This paper discusses the evaluation of the 2005 project data and the outcomes of the follow-up investigation. The Demonstration Project to evaluate WMA was constructed in Calgary in 2005. The project compared three surfacing mix types: a control mix and two WMA alternatives. The project successfully implemented the new technology. The 2021 assessment had the objective of reviewing details from the original project, completing a field assessment of the current conditions, and implementing a suitable laboratory program to assist The City in determining the feasibility of future use of WMA technology. The 2021 assessment studied the relative strength of the WMA layers and binder properties to determine the difference between Hot Mix Asphalt (HMA) and WMA. An industry assumption is that WMA is prone to reduced stiffness given the reduced mixing temperatures; however, the outcome of this trial project opposed this assumption and the results indicate that these WMA technologies could be considered equivalent to HMA in terms of design and performance.
Tetra Tech Canada Inc. was retained by Alberta Transportation (AT) to assist in the development of a risk-based Geotechnical Asset Management (GAM) framework and pilot study, with the vision of transforming AT’s current Geohazard Risk Management Program (GRMP) into a GAM program. The main objectives of the study were to develop a GAM framework for managing selected geotechnical assets located along the Provincial highway system, and to develop a spreadsheet tool for implementing this framework to a pilot-scale inventory of 27 geotechnical assets. The intent of the GAM framework development was to enhance AT’s ability to effectively prioritize, measure, and manage life-cycle investments in assets such as slopes, embankments, retaining walls and subgrades, based on performance expectations and risk tolerance. The GAM Framework Development and Pilot Study was undertaken in a manner consistent with the methodology and recommendations of NCHRP Report 903: Geotechnical Asset Management for Transportation Agencies (2019), which includes a supporting computational tool implemented in Microsoft Excel, that was customized as part of the project. The tool includes economic analyses based on annual monetized risk and life-cycle costs over a 50-year time period, through monetizing the asset-specific costs and benefits associated with the recommended treatment, applied in the optimal year. A collaborative and highly-interactive approach was essential to the project delivery, with AT’s Geotechnical Asset Management Specialist involved as one of the key team members during all stages of the project. The customized “GAM Planner” application provides an integrated solution for collecting, storing, and managing information on Alberta’s geotechnical highways assets, in one Excel-based application which can be used for capital planning and the prioritization of rehabilitation projects on an annual basis. The GAM Planner was modified from the original NCHRP tool, to reflect AT's agency-specific requirements regarding inventory, treatments, inspection requirements, site-specific user cost model, risk-based life cycle plan, incorporation of monetized risk, site-specific traffic, site-specific detour length, provincial highway classification, field inspection report, and other additional enhancements.
This paper describes the methodology used to conduct the Study on the Infrastructure Vulnerability and Risk due to a Changing Climate and Extreme Weather Events along the Alaska Highway. The Study was carried out using the methodology documented under the Vulnerability Assessment and Adaptation Framework (FHWA, 2017). The Framework provides a structured process for conducting a vulnerability assessment for the infrastructure assets. The Study assessed the impacts of climate change on drainage and geotechnical assets. It provided a specific analysis of projected changes in temperature and precipitation-related parameters as predicted by climate change models to establish a probable range of future climate conditions to which these assets may be subjected. A Life-Cycle Cost Analysis (LCCA) was carried out to identify and select the most cost-effective adaptation alternatives. This economic analysis monetized the costs and benefits associated with multiple adaptation strategies over a 60-year analysis period. The costs considered in the LCCA include both "direct costs," the cost directly incurred by the asset owners, and "user costs," costs that users of the road would incur through delays and detours. A total of 410 culverts, 74 geotechnical assets and 24 bridges along the highway were identified for consideration in this Study. The methodology is intrinsically compatible for integration into Transportation Asset Management Plans and cross-asset optimization.
Anthropogenic climate change is among the greatest challenges we face, given the threat it poses to the natural and built environments. This paper addresses resilience of pavements in the context of climate change by reviewing the major vulnerabilities and adaptation measures. First, the basic concepts relevant to this topic, such as sources of climate information and downscaling climate data, climate scenarios, and uncertainty in climate projection, are introduced. The climate-induced pavement stressors of particular interest in this regard are increases in temperature and precipitation intensity. As such, the proposed engineering-informed adaptation measures relevant to these stressors are evidence-based, and they relate to monitoring pavement key performance parameters and pavement adaptations in structural design, materials, and mix design, along with adaptation in maintenance, regulations, and construction. The measures proposed in various research studies include increasing pavement layer thickness, using stiffer binders, use of geotextiles, performing more frequent maintenance, and enforcing more stringent acceptance tolerances for mixes and materials. This study concludes that climate adaptation measures in pavement should be incorporated in the decision-making process at the planning and design stages. In turn, this underscores the importance of integrating practical adaptation strategies in design and construction standards and supporting awareness of, and education on, climate change adaptation among engineers and practitioners.
The maritime industry has always been one of great change over time. From the Age of Sail transitioning to steamships and eventually modern cargo carriers, the type and manner of vessel has continually evolved with advances in technology. Once again the industry finds itself on the cusp of a significant shift in how we view the ship with the development of the unmanned vessel. Whether it be an autonomous or remotely controlled vessel, the removal of master and crew presents a significant potential for change in how the ship may be configured and operated. One area that deserves consideration in the legal context is how this technology may affect the concept of seaworthiness. This is a legal concept that can be described as underlying “almost all aspects of private maritime law” (Chircop, Moreira, Kindred and Gold, 2016, p. 72). The autonomous and remote technology currently being developed raises many questions as to where the technology itself may fit within this definition and the requirements under maritime law and conventions. This paper will attempt to survey the technology of autonomous shipping as it currently stands, the legal concepts of seaworthiness most important to autonomous and remote technology, and assess how a potential shift in technology will affect this legal concept.
Active transportation’s place within transportation engineering has continued to grow. Pedestrian infrastructure has always been a consideration, but bicycle infrastructure was generally an afterthought. Where it was once not considered whatsoever in road design or for planning purposes, it is now normal to see its inclusion, often prominently, in transportation master plans as an effective method of transportation demand management, in the promotion of healthy lifestyles and the mitigation of greenhouse gas emissions from motor vehicles. There are some important implications related to attempts to increase the cycling mode share for commuters and increasing cycling in general. It would seem obvious that different types of cycling infrastructure would have different effects on the number and frequency of collisions involving cyclists. That relationship was explored though an examination of applicable research. The establishment of different types of cycling infrastructure also are likely to have an effect on the amount of commuters who would be willing to switch to that mode. Their willingness to switch, even if it is not full-time, is likely based upon their own perceived safety and comfort levels with the different types of infrastructure options. This was the second focus of examination. Finally, there is a discussion of the methods in which jurisdictions within New Brunswick can incorporate active transportation infrastructure and the potential effect on vehicular traffic. New Brunswick is in a cold weather climate; Fredericton sees average daily temperatures below freezing for 4 months per year (Environment Canada, 2017). These conditions will also affect cycling commuting numbers and this will be considered in the discussion.
Autonomous Vehicles (AVs) will bring advantages such as enhanced mobility, increased safety, and eliminated hassles of finding a parking spot. AV users can exit from their vehicles at their final destinations, and send the vehicles to find a parking spot themselves. This self-parking capability of AVs is considered as their most beneficial advantage in the World Economic Forum survey by approximately 50% of respondents (Mitchell, 2019). The self-parking capability not only provides the opportunity to park AVs farther from the final destination (Nourinejad &Amirgholy, 2018) but also can decrease the area needed for parking and revitalize valuable lands allocated to parking. Since passengers do not present in the AVs when they enter a parking lot, the required room for opening an AV's doors becomes redundant. This along with the elimination of elevators and staircases can decrease the average space per vehicle by 2 square meters (Techworld, 2016). Another essential strategy to decrease land utilization is stacking AVs behind each other in car-parks as shown in Figure 1. Although this kind of design reduces land utilization and increases parking capacity, it causes a blockage if the barricaded AV wants to leave earlier, and the parking operator must relocate blocking vehicles. Nourinejad et al. (2018) investigate the design of such parking facility layouts. They divide a car-park into a number of islands and gaps. The islands are used to store vehicles and the gaps are used for vehicles to maneuver in and out of parking spots. Each island is made of some stacks as shown in Figure 1. The inter-island gaps are used as waiting area for blocking AVs. In this way, the blocking AVs move to the inter-island gap and wait there to make a clear path for the summoned AV to exit the facility.
In this study, we propose a new estimation approach which uses aggregate market-level operational data to estimate air passengers’ ground transport mode choice. Unlike the abovementioned traditional survey approach, this method does not need any individual-level attributes and preferences. The estimation simply replies on those easily observed market-level data, namely the ridership, fare, schedule, in-vehicle travel time of each airport ground transport mode, and airport passenger traffic. This significantly lowers the data requirement. In addition, this empirical approach utilizes the information on the continuous airport passenger-flow and discretely scheduled airport ground transport modes, which substantially improves estimation efficiency. Specifically, the indirect utility of a choice alternative to access or egress the airport is developed to account for the effects of fare, in-vehicle travel time, schedule delay and other service quality characteristics. We estimate the choice probability of each individual passenger, and aggregate these individual probabilities into a total predicted ridership for each scheduled airport ground transport service. We estimate the utility function using nonlinear least squares, which minimizes the empirical differences between the estimated and true ridership for each scheduled airport ground transport service.
Forecasting airport and ferry passenger traffic can be problematic when one of the exogenous variables is politically determined, rather than determined by the market. In particular, fuel costs, which typically make up the largest non-labour cost for airlines, are influenced by geopolitical and policy developments rather than fundamental market dynamics. Because of their impact on airline and ferry operating expenses, fuel costs are an important supply-side consideration for projections of future passenger traffic. The unpredictability, volatility and uncertainty surrounding the future price of a politically-dependent and policy-motivated variable such as fuel prices makes it difficult to provide medium and long-term projections of passenger traffic. This paper will examine the use of stochastic forecasting techniques using Monte Carlo simulation methods to develop traffic forecasts where oil and fuel prices can vary widely and unpredictably. The Monte Carlo modelling process also allows for the inclusion of risk factors to quantify and model that uncertainty. An illustrative forecasting example is developed to demonstrate the stochastic forecasting process and quantify an illustrative selection of risk factors pertaining to oil price volatility. The results show that the stochastic forecasting approach provides meaningful information regarding the range of impacts uncertain and volatile factors to traffic development may have and provides additional insight into the risk associated with future shock events and uncertainty.
At present, the priority signal control strategy of transit is aimed to improve the efficiency of bus transit as a target, and they take little account of the effect on social vehicles. YM Bie (2011), in order to reduce the influence of bus signal priority on the social vehicles, a finite signal priority strategy considered saturation constraint is proposed and simulated by VISSIM simulation. D Qiu (2014), the method of calculating the congestion rate based on the critical queuing length is proposed. Based on this, a priority traffic control strategy for single intersection is designed based on the value of congestion rate. The experimental results show that the method can effectively alleviate the congestion of non-priority vehicles while improving the traffic efficiency of buses. However, existing research is implemented by adjusting the critical green light time in real time. Historical analysis data are used as the method for judging the green light time in the subsequent period. The real-time performance is poor, and the response of the bus signal priority strategy has a certain lag. Therefore, this paper calculates the green light time based on the shortest cycle duration and the best cycle duration, so as to determine the range of compressible green light time. Based on the critical saturation constraints, we formulated conditional response to bus signal priority control strategy, green light extension strategy, red light early break strategy, and combined strategy.
New forms of mobility are transforming the transportation landscape globally. As the landscape evolves, it will become increasingly viable for travellers to meet most of their mobility needs through purchasing rides or seats, instead of the traditional purchasing of vehicles. The concept of selling mobility rather than vehicles is experiencing renewed interest, thanks to recent developments in digital technology that allow for greater levels of personalization and integration across multiple transport services. With this early trend in traveller attitudes and behaviour, there is an opportunity for government agencies to analyse opportunities for participation before this transition matures (Smith et al., 2019). The objective of this paper is to help governments define their roles as it pertains to Mobility as a Service (MaaS), the term used to describe an integrated platform for payment, multi-modal trip planning, and incentives. The levels of MaaS integration will be an effective measuring stick as platforms and services are expanded. There are several multi-modal trip planners that exist (or are being developed) that indicate that Level 1 integration is already maturing. The companies Moovit, TomTom, and Microsoft recently announced a partnership to introduce a comprehensive multi-modal trip planner that will incorporate driving, parking and transit options in a single package (Moovit, 2019). Level 2 Payment Integration and Level 3 Contractual Integration are also both being explored and in some regions are being deployed at a small scale (Masabi, 2018). An example of this is the company Whim, who have developed subscription plans in Helsinki, Finland to provide discounted use of taxi, car-share, and ride-source services along with unlimited transit access, as a method of steering travellers away from vehicle ownership (MaaS Global, 2016). Level 4 Policy Integration will be the final frontier for governments and private entities working together to achieve regional goals through incentives and discounts, resulting in more shared and sustainable travel and fewer private vehicles on the road (Sarasini, Sochor, & Arby, 2017). This paper will focus on how government agencies can participate in transitioning MaaS beyond Level 0 and 1, to a more integrated state that maximizes traveller experience and meets public objectives.
In the long history of economic regulation of the transport of Western Canadian grain, the current regulatory environment, created by the Maximum Revenue Entitlement (MRE), has been in effect since August 1, 2000. The MRE, as a regulatory framework, is statutorily enabled through the Canada Transportation Act [CTA], namely Sections 150-152 and the list of ‘eligible grains’ and products to which the regulation applies as listed in Schedule II of the Act. Although the administrative application of the regulation has evolved over time, specifically through the successive determinations of the Canadian Transportation Agency, the statutory foundation has remained static and untouched; even in the face of two major independent statutory reviews of the legislation which both recommended a gradual elimination of the regulation. This paper does not present a specific argument regarding the MRE as a policy, its effects, its administration, etc. Rather, this paper surveys the way in which the MRE was treated under two comprehensive reviews of the Canada Transportation Act (in 2001 and 2015), summarizes how stakeholders viewed the regulation at those two specific junctures in time and what the two Review Panels recommended in their respective final reports. No major reform of the MRE was undertaken by government following the 2001 CTA Review, while a legislative package, in the form of Bill C-49, the Transportation Modernization Act was the government’s response to the 2015 CTA Review (and subsequent Transportation 2030 vision consultation). Introduced on May 16, 2017, the Bill took over one year to move through the legislative process, finally passing on May 23, 2018. The provisions within Bill C-49 represent the first legislative changes to the MRE in its 17-year existence.
This paper reviews the noteworthy developments in Canadian transportation in 2018. It briefly examines the state of the industry in various transportation subsectors (air, rail, water and road) by examining the statistics for 2018. It then examines regulatory and policy developments that have occurred in each of the subsectors such as the passage of new laws, other transportation bills, and proposed policy, etc. It then briefly touches on developments on other transportation fronts.
Of central interest to this paper, because of uncertainty about the speed of climate change and the irreversibility of infrastructure investment, it can be advantageous to wait for better information before making large investments. With this as background, we investigate the optimal timing and scale of adaptation and capacity investments in the face of uncertainty about the likelihood of disasters. We adopt a two-period model and Bayesian learning whereby a port and shippers update their prior probability of a disaster in period 2 based on what happens in period 1. We analyze how optimal capacity and adaptation investment interact with each other, how the two types of investments affect port fees, and how different governance structures and corresponding objective functions affect a port’s investment decisions. The study offers managerial insights for ports and their stakeholders to develop appropriate capacity and adaptation management strategies to climate change. Although the focus is on seaports, the general lessons also apply to protective investments for other types of vulnerable infrastructure.
The primary objective of this paper is to assess the role of port efficiency as a determinant of maritime transport costs in Canada. Linear and log-log regression models of container freight rates as a function of port utilization indicators (PUIs) are developed to determine which, if any, of the ports’ activities are related to container freight rates. Unlike previous studies that relied on proxy measures, this study tests several empirical measures of port efficiency, which have been collected by Canadian port authorities over several years.