Increase in daily travel activities coupled with reliance on conventional vehicles, places a significant pressure on the environment through tailpipe emissions. Fortunately, current advancements in battery technology along with the introduction of electric vehicles (EVs) is often considered as one of the more viable solutions to combating climate change and promoting sustainable energy. Due to the scarcity of EVs in the current market, many studies have utilized stated preference (SP) analysis along with estimating different forms of econometric model to identify and to understand factors affecting consumers’ choice decisions regarding new vehicle technologies (for example: Hackbarth & Madlener, 2016; Hoen & Koetse, 2014; Qian & Soopramanien, 2011). In addition, Potoglou and Kanaroglou (2008) provided a comprehensive literature review on various research methods regarding alternative fueled vehicle demand, focusing on SP analysis and different discrete choice models. Moreover, Rezvani, Jansson, & Bodin (2015) focused primarily on empirical studies evaluating various consumer behaviors towards plug-in electric vehicle adoption. While most the existing studies have been concerned with household EV ownership, little has been done to explore the potential of adopting these emerging vehicle technologies by commercial fleets. Public and private organizations typically have high vehicle purchase rates (Dijk, Orsato, & Kemp, 2013) and high average annual mileage (Gnann, Plötz, Funke, & Wietschel, 2015), making them ideal EV adopters; thus, it is important to understand the motivations behind their EV acquisition decisions. Some of these motivations are firm-specific; government agency’s EV adoption is partly driven by restrictive legislations, while the potential profit increase through technological leadership encourages corporations’ EV purchasing decisions (Sierzchula, 2014). The analysis on this study is built on the extensive works regarding new vehicle technology ownership and extends their analyses on consumer rental context. As of 2015, the rental industry accounts for about 69% of all car registrations and approximately 47% of all light truck registrations, which are the highest in both categories (Canadian Automotive Fleet, 2016). The focus of this study is to determine and evaluate the preferences and motivations of Canadian consumers towards renting certain vehicle types using a SP survey.
Transit service reliability is one of the highly valued attributes for users and operators. This paper examines the impact on headway regularity and passenger loads in a simulated bus operation due to the bus capacity limits and the variability of departure headways. For the simulation purpose, four operational scenarios are set up. Same timetable and route characteristics are considered for all scenarios. In the first scenario, it is assumed that buses have infinite capacity and can accommodate all passengers waiting at bus stops. In other scenarios, bus capacity is constrained with different carrying capacities in order to analyze the impact of passengers being left behind when buses are full. The degree of dispatch headway also is varied to examine effects of headway regularity along the downstream of the route. Passengers arrival and dispatch headway of bus are assumed to follow Poisson and Gamma distribution respectively. Travel time between stops is assumed as constant in order to isolate the effect of dispatch headway variability. The simulation studies demonstrate the propagation of headway irregularity along the downstream of routes, a correlation between bus headways and passenger loading that caused bus bunching.
Meeting the needs of passengers will increasingly become a competitive factor for each stakeholder of the air transportation system. To achieve this goal, a passenger-centric view needs to be employed. Since passengers may encounter many modes of transportation during travel, adopting the passenger-centric view leads in a natural way to intermodality. Timely provision of relevant information is one of the most demanded services. Exact knowledge of information and respective interfaces required may lower the inhibition threshold of stakeholders to share information. In this paper, we describe the data model and the interface model necessary to implement a Passenger Information System on a mobile device. The features of our system comprise real-time and personalized information about departure times of urban transport and air transport, estimated time to complete the next step, such as check-in or security check, and estimated spare time for visiting the retail area. Data model and interface model are described by using standard methods in computer science, so that the description is independent of the implementation itself. Furthermore, it is transferable to other situations where a Passenger Information System is to be installed. In future work, we will implement a Passenger Information System on the basis of the data interface model described. We will evaluate the performance of the data interface model described with respect to reliability and throughput. We will answer the question of whether the model is appropriate for real-world applications. A further step would be the dissemination of the — hopefully positive — results of the evaluation among stakeholders in order to propose an information system which is independent of the data’s owner.
Our literature review reveals that most applications of Computable General Equilibrium (CGE) models in transportation fall into comparative analysis, where scenarios before and after transportation projects or policies are compared. However, the potentials of these models go beyond just comparative analysis. In this paper, a framework is proposed that introduces the concept of optimization into the CGE context. This framework is particularly aimed at optimizing transportation infrastructure investment over space and time. The proposed framework offers an empirically-based conversion of infrastructure investment (i.e., in $) into transportation network attributes (e.g., capacity). The proposed methodology is described in the next section, followed by a formulation of a simple non-trivial model. Then, concluding remarks and current and future research directions are presented.
Productivity is a measure of how a firm, such as a railway company, uses inputs like labour, material, capital, etc., to produce outputs such as transportation movements and services. An increase in productivity occurs if the company produces a greater quantity of its outputs with the same quantity of inputs, or uses less quantity of inputs to produce the same volume of outputs. Productivity can be compared between firms, industry sectors, regions, countries, or even groups of countries in economic or political blocks. The aim of this paper is to present a new method to calculate an index related to the Canadian Railways Total Factor Productivity.
This paper presented cluster-based analysis for the home-based tours. The cluster-based approach can be utilized to capture differences between homogenous clusters of travelers in terms of mode choices and their influential factors. The immediate future work includes predicting modal shares for comparing the accuracy of the model. Since this study used public-use micro data, one limitation of this study is that it cannot incorporate the effects of built-environment variables into the models. The next step will include incorporating the built-environment variables into the tour-mode choice modeling using the Halifax Space-Time Activity Research (STAR) dataset. From the cluster analysis, it has been found that there exist significant differences among the four travelers’ clusters in terms of tour attributes. This explains the need for incorporating the heterogeneity of travelers’ grouping in the travel demand forecasting model. An improvement of this work can be achieved by modeling the household interactions for joint tours, with special attention to chauffeuring trips. This study offers a clustering approach to model the travelers in separate internally homogenous clusters, so that mode-choice modeling can reflect the latent heterogeneity among the travelers.
The physical movement of goods plays a key role in many market transactions, making the transportation system an essential foundation for a national economy. As a trade-reliant nation with its population spread over a vast landscape, Canada is particularly dependent on an effective transportation system. And, in order to assess the national transport system and its ability to move freight, quality statistical information is required. In several OECD countries, a Freight Analysis Framework is used as a planning tool for assessing the transport network and its capacity to meet projected demand. This study investigates the potential of capturing import shipments by examining American outbound shipments to Canada. It begins by reviewing a plausible Canadian framework and data considerations. To further our understanding of this shipper-based approach, it examines the number, value and weight of American export shipments to Canada from the 2012 CFS. Next, it focusses on other characteristics such as the region of origin, type of industry, commodity classification, and mode of transport. The study concludes by discussing the technical and organization considerations in moving forward.
Canada signed the Canada-European Union (EU) Comprehensive Economic and Trade Agreement (CETA) in October of 2016, which was later ratified by the European Parliament in February, 2017. This agreement eliminates tariff barriers and enhances accessibility to the EU market (Government of Canada, 2016). The Canadian government investigates the future impacts of CETA on the nation’s economy, regulation, society, and employment size, but evaluation of Canada’s transportation system under the CETA is almost forgotten (Bachmann, 2017). The objective of this paper is to assess the potential impact of CETA on the Canadian transportation network by estimating the origin-destination trade flows, mode share, and transportation flows before and after the CETA.
Regional Logistics Performance (RLP) has been lacking in the literature. There are three fundamental reasons for this: First, even Logistics Performance Index (LPI) at the country level is relatively recent. Second, competitiveness at the regional level, compared to the national one, has not yet been well recognized. Third, it is hard to create a consensus on globally-accepted metrics to be used. Yet, RLP may be a vital tool for promoting regional prosperity and its benchmarking with its domestic counterparts. RLP is challenging, especially boiling it down to an index score, for two reasons: First, who will do it, systematically? Second, is the region industry-dense enough to collect data from? With these in mind, Table 1 proposes a framework for RLP that is relatively-easy to measure and use. The metrics are inspired by LPI measures and consider possible regional specificities.
The Complete Streets Design and Construction Standards (CSDCS) document provides a single point of reference that supports the planning, design, and construction of Complete Streets in Edmonton. It integrates the best practices in Complete Streets design philosophy and guidance introduced in the City’s 2013 Complete Streets Guidelines with the City of Edmonton’s former Roadway Design Standards and Construction Specifications. The intent of these Complete Streets Design & Construction Standards is to encourage a holistic approach to street design that will develop a network of streets that is safe, attractive, comfortable, and welcoming to all users in all seasons, while considering operational and maintenance challenges. The document introduces the ‘Design Domain’ approach which allows flexibility in design through variance in street element design values based on the modal priorities and context of a specific corridor. From a technical perspective, the document is intended primarily for engineers, planners, and the development industry. Though the document can be utilized by communities and the public, a less technical primer companion document will better serve those users. The Complete Streets Design and Construction Standards are intended to be a living document, with regular updates to incorporate changes in best practice and their application in the Edmonton context.
During the last decade or so in North America, activity-based travel demand modeling has become more popular than four-step and tour/trip travel demand models among urban and transport modelers. The disaggregation feature of activity-based models can help to capture different aspect of travel behavior complexity, such as flexibility in individual’s activity schedules, and associations between trips and activity participation. To date, researchers and practitioners have employed different approaches for development of activity-based models. A number of important specifications which affect the average level and variability of such models are prediction accuracy, reproducibility, computational time, large scale operation capability, and performance at the household level. The current paper presents cutting-edge methods and progress in developing a new comprehensive pattern recognition modeling framework for use in activity-based travel demand modeling. The framework leverages activity data to derive clusters of homogeneous daily activity patterns, in order to infer the scheduling behavior of individuals. In this paper, numerous new machine learning techniques are employed in the pattern recognition modeling framework. The pattern recognition model is applied to data from the large Halifax STAR household travel diary survey. The proposed modeling framework has much higher reproducibility and shorter computational time compared to other alternative modeling frameworks. Furthermore, the proposed modeling framework can be applied to any applications that contain a group of linked sequences, such as day-to-day variations in transit usage.
Parking space near shops, restaurants, and other destinations is often scarce or expensive in dense urban areas. Urban shopping malls may provide little or no parking space, or charge high hourly rates. Shoppers end up searching for cheaper parking on the street, or walking to and from residential neighborhoods. Spillover parking can also be a problem near train and metro stations, sports stadiums, concert halls, public parks, and other places that attract lots of people. Cities and towns often tackle spillover parking by enacting residential parking permit programs that ban nonresidents from parking in residential areas. Permit systems can be effective at eliminating parking problems for residents. However, like other non-price rationing tools, permit systems are generally inefficient because they allow residents to park free or for a nominal fee, and thus do not assure that parking space is allocated to those who value it the most highly.2 Residential parking permits are also hard to enforce (Rye and Llewellyn, 2016). Yet, despite these weaknesses, local politicians prefer residential parking permits to priced-based policies because residents benefit from permits, and can express their preferences at the voting booth. Another common policy to curb spillover parking is to impose minimum parking requirements, differentiated according to type of land use. Yet minimum parking requirements have well-studied drawbacks. Parking space is often underutilized outside regular business hours, and more generally at times of low demand. Expanding parking capacity is also unsightly, and it encourages people to travel by car (Guo, 2013ab). As Shoup (2013) argues at length, spillover parking can be addressed by better parking pricing. Priced-based policies enhance efficiency because they are demand (and thus value) driven. Their goal is not necessarily to eliminate spillover parking, but rather to maximize the combined welfare of residents, nonresidents and businesses. In this paper, we analyze three policies to deal with spillover parking generated by a shopping mall located in a residential area: (1) a curbside parking fee, (2) regulation of the mall parking lot fee, and (3) regulation of mall parking lot capacity. If the regulated lot capacity exceeds the mall’s profit-maximizing capacity, the third policy amounts to a minimum parking requirement, but since demand is static in the model this does not result in underutilization of capacity.
Researchers from regional and transportation planning have focused a large body of research towards Integrated Urban Models (IUMs) and agent-based microsimulation of urban systems (Miller et al., 2004; Waddell, 2002; Hunt et al., 2005; Wegener, 1995). IUMs provide a simulation environment that can be used to support strategic planning by forecasting the effects of policies on demographics, land use changes, and transportation patterns within regions. Within urban systems, firms are recognized as one of the interacting agents whose behaviour influence transportation systems. Firm events of entry, exit, and growth affect economic growth, labour dynamics, and transportation demands. New firms are sources of new jobs that induce urban changes by attracting skilled workers to the location of new jobs. This causes changes to transportation demand and ultimately affects commuter time. Firm start-up size is an important determinant of new firms. Modelling firm start-up size at the micro level is essential to understand job creation dynamics and potentially measure the impact on transportation demand. Also, some studies suggest that firm start-up size influences the firm’s subsequent performance and survival (Dunne et al., 1989; Audretsch and Mahmood, 1994; Mata and Portugal, 1994). Determinants of firm start-up size have been addressed largely for European countries (Arauzo-Carod and Segarra-Blasco, 2005; Audretsch et al., 1999; Barkham, 1994; Görg et al., 2000; Mata and Machado, 1996). To the best of the author’s knowledge, research studies in a Canadian context that address determinants of firm start-up size are absent, both in terms of employment size or tangible assets. In this paper, ordered logit models of start-up size of Canadian firms are presented. Two aspects of size are considered: the number of employees and the firm’s physical form represented as the tangible asset dollar values. The presented models are the components of a larger firm microsimulation platform introduced earlier by Mostafa and Roorda, (2015). This paper starts by exploring determinants of firm start-up size surveyed from the literature. The data and modelling approach are then explained. Model results and interpretation followed by model goodness-of-fit and model validation are presented next. Concluding remarks and future directions are then discussed
Modern transportation planning dawned in New Brunswick in 1946 with the release of the “Master Plan of the Municipality of the City and County of Saint John, NB, Canada” at the time the 12th largest metropolitan area in Canada. This plan, authored by J. Campbell Merrett, was developed in anticipation of population growth, growth in automobile ownership and desire for modern housing in Saint John, trends which were all experienced in cities across North America over the coming decades. This plan, and others, ushered in an era of large scale highway investments that changed the complexion of New Brunswick’s largest cities throughout the 1960s through the 1980s. These projects were initially informed through transportation planning practice that focused on projecting vehicular traffic on a road network, typically within a municipal environment, with transit relegated to a social service role. More recent transportation planning efforts in New Brunswick’s largest cities have expanded the focus to include transit and active transportation, though the legacy of the highway megaprojects continues to shape urban mobility in New Brunswick. This paper briefly explores the progression of transportation planning in New Brunswick’s three largest urban areas (Saint John, Greater Moncton (Moncton, Riverview and Dieppe) and Fredericton) through a review of historic plans retained at the Harriet Irving Library at the University of New Brunswick. More recent plans were sourced online from municipal websites. The plans were reviewed chronologically in terms of their overall vision, technical approach, and contributing legacy to urban mobility in New Brunswick. Plans are compared and contrasted and a final commentary provided based on the perceived ability of New Brunswick cities to leverage transportation planning tools to address present and future challenges for continued reliance on car-centric mobility, such as an aging population and climate change.
The well-known triple bottom line breaks sustainability down into economic, environmental and social dimensions. According to Vantuono (2016), the triple bottom line “in railroading terms translates to a safety culture and highly competitive wages and benefits (people); fuel efficiency and far less pollution compared to other modes (planet); and shareholder value (profit).” On a ton-mile basis, rail is known to compare favorably vis-à-vis trucking in terms of fuel consumption and GHG emissions. In highly competitive markets, motor and rail carriers have been developing sustainability initiatives focused on reducing fuel consumption and GHG emissions, along with increasing operational efficiency (Shacklett 2012). Though fuel consumption and GHG emissions are prominent among the GRI (2013) sustainability reporting guidelines, surprisingly these items did not make a more recent top 10 list of GRI “sustainability aspects for the railroad sector” (Coppola 2014). This list includes: local communities, remediation, freedom of association and collective bargaining, diversity and equal opportunity, equal remuneration for women and men, non-discrimination, indirect economic impacts, labor/management relations, corruption and product and service labeling. This paper analyzes and critiques the sustainability reports published by Canada’s Class I railroads. There are four more sections. The first one briefly profiles the Canadian railroading industry. This is followed by a definition of sustainability, which expands the typical triple bottom line (of economic, environmental and social dimensions) by adding a cultural dimension. The third section introduces sustainability reporting, based on the Global Reporting Initiative guidelines, then uses the guidelines to study the Class I railroad sustainability reports. The fourth and final section offers conclusions and suggestions for future research.
Organized volunteer driver programs are emerging as solutions to fill the transportation service gap for those unable to meet their personal transportation needs independently with the private automobile and where taxi, transit or active transportation are unrealistic or unavailable options. Volunteer driver programs (VDP) are typically able to serve areas of low population density at a lower overall cost than paratransit services by using volunteer labour and vehicles. They replicate the on-demand travel and social aspects associated with relying on friends and family for transportation, which is attractive to those who do not have access to a personal network. VDP can be stand-alone programs, extensions of non-profit or charitable activities, or in some instances in the United States, are integrated as part of rural transit. Many of these programs are targeted to supporting the transportation needs of older adults, the population of which is expected to double in Canada by the year 2036 (FCM, 2011). The challenge is that little is understood about how VDPs collectively work to satisfy Canadian transportation needs and how they will respond to meet growth in ridership anticipated with an aging population. Individual programs may record trip information for their own planning purposes, but unlike personal vehicle use, transit, or taxis, there is not a broad understanding of the number of Canadians that rely on these programs, the degree of their reliance, the types of trips they take, and distances they travel. Without a clear understanding of how VDP work, there are risks that programs may not be able to meet demand, programs may have challenges with replication and sustainability, and there may be missed opportunities to employ these programs in underserved markets. This paper summarizes recent efforts to quantify the broader usage of these programs in New Brunswick. While confounded by differing data collection and reporting approaches among groups, this paper offers a preliminary estimate of usage, as well as the results of an exercise to develop a common reporting tool.
In transit planning, accessibility “to” (i.e. access to transit) and “through” transit (i.e. geographical coverage of transit) are considered as important service quality indicators (Beimborn et al., 2003; Handy and Clifton, 2001; Murray and Wu, 2003). Typically, travel time (or distance) is used as a measure for accessibility “through” transit. In recent studies, researchers pointed out that transit fare could be an obstacle to accessibility. For example, El-Geneidy (2016) suggested that travel cost (i.e. the transit fare one pays) would also influence accessibility through transit. In addition, a more recent study suggested that an increase in transit flat fare would result in a loss in accessibility. Such loss was found to be inversely proportional to the length of the trips (i.e. substantial for short trips and unworthy for long trips), which can be considered “unfair” for short-trip users (Ma et al., 2017). This study expands on Ma et al. (2017) and constructs a fair-fare structure for improved passengers’ accessibility. It is assumed that a transit agency needs to introduce a new fare policy that will cover its increasing capital and operating costs. A pre-determined loss of accessibility is set for all short, medium, and long trips; and a new fare structure is established accordingly. The City of Kelowna, BC, is selected as a case study.
Sustainability reporting is an effectual way for airlines to communicate their sustainability strategies and achievements. In spite of the existence of sustainability reporting guidelines such as GRI, airlines have shown a wide range of performances in reporting quality. To figure out the driving forces behind airlines’ sustainability reporting performance, this paper first builds a scoring system for airlines’ sustainability reports, with which the top 100 airlines worldwide are evaluated and scored. Then we run regression analysis to gauge the impacts of factors that may have influence on this score, including the size, the nationality, the business model (full-service vs. low-cost), the alliance membership, etc.
Transportation infrastructure is a major component of municipal budgets. A sample of financial statements from four Ontario municipalities of varying jurisdiction shows that transportation costs can account for 15-40% of a municipality’s operating budget (Baker, Jackson, KPMG, 2016; Deloitte LLP, 2016; KPMG, 2016; St Amant, Rossini, Wallace, PricewaterhouseCoopers LLP, 2016). Municipalities employ key performance indicators to track the fiscal sustainability of their spending, but many of these indicators come with caveats that prevent direct comparisons. Infrastructure, population and the physical supply of infrastructure are often not included together in a single indicator, making it difficult to track trends where only one of these factors changes, and make insights into the fiscal sustainability of municipalities. This research studies two facets of fiscal sustainability. First, an indicator is proposed that combines infrastructure supply, population, and expenditures, with the goal of enabling sustainability analyses that make use of one or more of these factors. Second, a sustainability analysis is performed for the road and transit networks in the City of Waterloo, Ontario, at the local and regional level. The proposed indicator is evaluated against a series of existing indicators covering 25 years of transit funding, and 11 years of road funding, ending in 2015. By covering over a decade of spending history, insights may be made into the long-term sustainability of transportation infrastructure in Waterloo.
Modelling the Feasibility of Transitioning Diesel-Based Heavy-Duty Trucks to CNG-Powered Engines in the GTHA Heavy-duty trucks are commonly used in freight transportation due to their ability to transfer high volumes of goods. Population growth and globalization increases traffic volume of all types of vehicles, which can lead to congestion. The increase in heavy-duty trucks is of greater environmental concern as most of these vehicles are powered by diesel and on average travel longer distances. The latter is associated with higher quantities of harmful emissions. Exposure to diesel exhaust fumes increases hospital admissions and worsens chronic lung diseases. Additionally, diesel exhaust fumes are likely to be carcinogenic (11). Alternative Fuel Vehicles (AFVs) have the potential to minimize health effects and reduce emissions associated with diesel-powered vehicles. Natural gas, an alternative fuel source is “85 to 99 percent methane…clean-burning, cheap, and abundant in many parts of the world,” (4) and can be fueled in the form of Compressed Natural Gas (CNG) and Liquefied Natural Gas (LNG). Natural Gas Vehicles (NGV) “have the potential to emit lower levels of particulate matter, non-methane organic gases, nitrogen oxides, carbon monoxide and air toxins” (14) than their diesel counterparts. The reduction of these emissions has the potential to improve air quality and in-turn public health. To facilitate the adoption of NGVs while maintaining the efficiency of goods movement, the overall objective of this research is to address the existing gap by examining the feasibility of alternative fuel infrastructure and the associated supply chain. To this end, the specific objectives of this study are to estimate the potential CNG demand, to advance the current knowledge on CNG refueling and optimal allocation of facilities that can store CNG and CNG-carrying fleets; identify hotspots and potential sites in the Greater Toronto and Hamilton Area (GTHA) where the allocation of the CNG Fueling Facilities will minimize transportation cost.