Proceedings of the Canadian Society for Civil Engineering Annual Conference 2024, Volume 16

This study investigates the impact of the driving behavior of connected, automated vehicles (CAVs) on greenhouse gas (GHG) emissions on different road classifications compared to driver-operated vehicles (DOVs). Four road networks were selected for traffic microsimulation and modelling of GHG emissions. The four road networks cover different general road classifications and characteristics, namely freeway, major arterials, major arterial in rural setting, and major arterial with short-spaced intersections. Employing simulations encompassing three driving behaviors (cautious, normal, and aggressive) and varying CAV penetrations from 0 to 100%, the research replicates the forecasted morning peak hour traffic demand in the City of Ottawa in 2031 while introducing fluctuations of ±20% from the predicted demand volume. Combining the variations in traffic demand, CAV behavior, and CAV penetration rate, 39 simulation scenarios were analyzed on each road network. The vehicle trajectories produced by VISSIM microsimulation were used as input file in MOVES software to estimate the GHG emissions while accounting for the micro-level differences in vehicle behavior. The results indicate that cautious CAVs would generally cause a deterioration in traffic performance and increased GHG emissions, while the general trends for normal and aggressive CAVs indicate improved traffic performance and reduced GHG emissions. However, some trend-breaking areas were observed. Regression analysis was performed to model the expected emissions (measured in terms of equivalent CO2 emissions per vehicle-kilometers travelled) as a function of the road, vehicle, and traffic parameters. Models were developed for the four road classifications and had high coefficients of determination (\({R}^{2}\)) and low root mean square error (RMSE) values. The scatter plots on a testing subset, which was not used in the model development, confirmed the goodness of fit of all developed models. Machine learning was also explored as a modelling alternative and showed a great potential for modelling GHG emissions based on the same model parameters.

Transit systems with flexible operation can help improve mobility by adapting to the changing demand with more personalized services, especially in areas where traditional fixed transit operations may be insufficient. Different operation policies vary in suitability depending on the system settings such as demand density, passenger time value, operation time value, passenger walking speed, and other factors. Operation policies should be compared in the same system setting to determine the one yielding the best system performance. This paper modelled the four most commonly adopted operational strategies in community transit systems analytically using the continuous approximation method: fixed transit service with fixed route, stops, and headway; on-demand dispatch transit service with fixed route, stops and demand-driven flexible headway; stop-on-call transit service with fixed route, demand-driven flexible stops and headway; demand responsive transit service with demand-driven flexible route, stops and headway. Both random and planned arrival of passengers at their destination are considered to estimate the waiting time. Analytical models are formulated to minimize the average cost per passenger subject to vehicle capacity and fleet size constraints. Passengers will be rejected when the system capacity is reached, and penalties will be applied accordingly. The operation policy with a minimum average cost per passenger is preferred. Closed-form solutions are obtained for the models. Numerical analysis demonstrates how the range of demand density in the service area influences the selection of the best operating policy. The impact of system configurations on the overall performance of the four policies is also illustrated. This work marks the initial step toward developing a decision-making tool for evaluating the performance of fixed and flexible public transit schemes.

Buses are pivotal modes of transportation to Montreal’s public transit system. Nevertheless, their widespread use results in increased noise and vibration in the environment and adverse effects on human health. Several studies have quantified bus vibroacoustic generation and recommended the adoption of electric buses as a measure for reducing noise and vibration. However, these studies are confined to specific geographic regions, and mostly lack a relational link to rider perception, reducing their generalization and applicability. As a result, this study assesses and quantifies noise and vibration generated and perceived by riders in Montreal’s conventional and electric buses. The study ultimately provides empirical evidence for Montreal’s pacesetting rapid transition to electric buses in light of Canada’s 2030 Transportation Strategic Plan. Data was sourced from 31 conventional and 12 electric buses from the Société de Transport de Montreal (STM). Sound Meter Pro and iDynamics mobile apps alongside rider interviews were used for data collection. The findings of the study indicated low vibroacoustic generation and annoyance perception in electric buses compared to conventional buses. Furthermore, the rider perception regression models resulted in significant and high goodness-of-fits of 73.1 and 83.2% for noise and vibration respectively. In conclusion, the study provides fundamental insights into the dynamics of bus transit in Montreal and advocates for the use of electric buses over conventional buses. Additionally, the developed models provide predictive capabilities for assessing vibroacoustic perception in buses.

Exploring the interaction between service quality and transit network design is crucial for enhancing passenger-oriented public transit. While previous research has explored incorporating crowding into network design as the intersection of comfort and security, the disutility associated with security issues at transit vehicles with lower crowding levels has been overlooked. This study, by introducing a novel parameter that accounts for the loading factor with the lowest crowding disutility, incorporates this concept into the optimal design of transit networks. Decision variables such as headway and stop spacing are optimized in a feeder-trunk network. The optimization is conducted both considering and neglecting these dimensions to assess how their inclusion modifies the network's optimality. The findings indicate that in low-demand scenarios, addressing security concerns necessitates more optimal headway and greater stop spacings compared to when such issues are overlooked. Shifting to schedule-based services with fewer stops is among the managerial actions recommended to achieve passenger-oriented transit systems during periods of lower demands.

Connected and Autonomous Vehicles (CAVs) have emerged as a significant technological advancement in recent decades, introducing various automated features that contribute to enhanced safety and improved mobility within the transportation sector. However, managing the increasingly complex network of these vehicles requires innovative solutions that consider mobility and communications perspectives. One such solution is Vehicle Cloudification, which establishes virtual clouds with vehicle clusters leveraging infrastructure-aided communication to harness the computational capabilities of intelligent vehicles on roads. This paper offers a comparative analysis between two communication models for CAVs: vehicular ad-hoc network (VANET) and vehicular cloud. Two distinct cloud models were developed: stationary and dynamic platoon-based cloudification systems. To evaluate the efficacy of the developed vehicular cloud-based network management system, simulations are conducted using the AIMSUN microscopic traffic simulator, incorporating four communication modes: DSRC, C-V2X, 4G LTE, and 5G. The results reveal significant network operational improvement with vehicular cloudification, demonstrating reduced latency and packet loss ratios by 5.1% and 8.3% respectively, compared to VANET-based systems, while maintaining freeway mobility and safety levels. Furthermore, an incident management strategy is deployed, showcasing an 8% reduction in travel time delay (TTD) compared VANET. This study underscores the potential of connected vehicular cloudification in optimizing transportation networks, by mitigating risks associated with message interference and system overload, providing valuable evidence for policymakers to consider in decisions associated with policies and infrastructure investments.

There are many facts that contribute to occurrence of aeronautical accidents by runway excursion; among them, the Runway End Safety Area (RESA) smaller than specified by RBAC. However, in some airports, the expansion of this area is impractical, mainly, due the obstacles close to the runway, such as civil constructions and water. In 1990, the Engineered Material Arresting System (EMAS) was putforth to stop the aircraft completely, in case of runway excursion, mitigating the damage generated to passengers and to the aircraft itself. The EMAS is a system that increases the security level of an airport, without the need of expansion of runway or RESA and, therefore, is highly indicated to airports where the expansion of RESA is limited, for example, Santos Dumont Airport (SBRJ). Therefore, the general objective of this work is to study the EMAS efficiency, doing risk analysis in different scenarios, through the ACRP Report 50, with support of the software RSARA2, as methodology to implementation of the system at SBRJ. The results obtained, in this present work, were satisfying, since, considering the system implementation for runway exit speeds 50, 60 and 70 knots, there was a decrease of 61.56, 64.86 and 67.06%, respectively, in the probability of occurrence, when compared to the current situation of airport. Analyzing the results obtained, it is possible to note that technically and economically, the EMAS 50 implementation is the most viable option to the SBRJ, whereas the present increase in the security level, requires a shorter length of EMAS.

Numerical modelling of visibility through smoke, during a fire incident inside a building, is required by most standards regarding fire protection, including the NFPA in North America and EN-45545 in Europe, to determine how well emergency signs can be seen. The smoke visibility data must then be communicated effectively to allow for proper planning of smoke management and evacuation paths. Interpretation of this data is difficult because smoke visibility only indicates how much sight is impaired at local points in space and does not give a clear sense of the cumulative effect of smoke along a sightline. Therefore, how is it possible to effectively communicate how far an occupant can see through smoke by presenting smoke visibility data alone, as it is often done in practice? The solution resides in overlaying sightlines directly on the smoke visibility data. The limit of any given sightline passing through smoke can be obtained by numerical integration along the corresponding streamline of a carefully crafted vector field. The resulting method is applied to the case of a fire incident in a train station to evaluate tenability along an evacuation path. This makes the communication of the smoke visibility data more effective by decreasing the time needed for a clear, repeatable, and consistent interpretation of the results. An automated procedure can then be created to produce the desired amount of additional data with little extra effort making it an indispensable tool for multidisciplinary teams in fire engineering.

The current mobility revolution in cities is reshaping our travel patterns due to digital technology advancements. This revolution has increased the interest in emerging mobility services (EMS), including ridesharing, shared micromobility, and autonomous vehicles. The EMS are not merely supplementary; they are disrupting the established public transit (PT) systems, offering enhanced flexibility, and altering the urban mobility landscape. For instance, the interaction between ride-sourcing and PT ranges from collaboration to competition. Ride-sourcing serves as a feeder to major PT lines, improving accessibility, yet it also competes by attracting riders away from PT for the primary leg of their journey. On the other hand, introducing EMS in certain urban areas while scaling back PT could disadvantage individuals who are unable to use these new services, underlining the challenge of maintaining equitable access in an evolving mobility ecosystem. Thus, there is a knowledge gap on how to integrate the two services from methodological perspectives. This study aims to fill this gap by conducting a bibliometric analysis and developing a conceptual framework to facilitate the strategic-level integration of EMS with PT, as well as exploring the consequences and uncertainties of such integration. The developed comprehensive conceptual framework emphasizes equity in urban mobility, with critical dimensions of spatial planning, stakeholder engagement, information systems, and vehicle technologies. Our investigation reveals that equitable integrated urban mobility hinges on ensuring each component synergistically contributes to the mobility ecosystem. The study also provides strategies for adaptive methodological solutions that cater to the diverse needs of mobility users, including the most vulnerable population groups.

With continuous urban growth and increased population mobility, urban transportation systems and mobility services have emerged as critical topics. Currently, public transportation facilities are being developed with a focus on cost-effectiveness and efficiency rather than reducing service disparities in urban areas. This approach has deepened the spatial disparities in service levels. Previous studies on mobility have presented various methods to quantitatively evaluate individual movements within the transportation environment. However, research on mobility concerning public transportation, especially those involving multiple modes, remains limited. In this study, we aim to develop evaluation metrics for public transportation networks considering multiple modes of transport to assess the mobility and accessibility of users. This study encompasses traditional public transportation such as buses and subways, extending to Personal Mobility (PM), Demand-Responsive Transport (DRT), and pedestrian mobility. The primary objective of this study is to differentiate between areas with excellent and vulnerable mobility services using the developed evaluation metrics. Additionally, we aim to analyze the influencing factors on vulnerable and excellent mobility areas to provide insights for establishing a sustainable transportation system in the future.

Truck freight transportation, a crucial driver of Canada's national economy, is responsible for 35% of the country's greenhouse gas (GHG) emissions related to transportation. The emergence of ‘Connected and Autonomous Vehicles’ (CAV) technologies is poised to bring about a revolutionary transformation in the trucking industry, leading to changes in fuel consumption and emissions. However, it is essential to acknowledge that achieving full mitigation may prove challenging due to the potential increase in emissions from road maintenance activities necessitated by truck platooning. With this vision, the present research aims to compare the prevalent flexible pavement distresses under normal traffic and truck platooning mode, because of the altered loading patterns of truck platooning. The alterations considered in this study include a reduction in load intervals. This study focuses on cracking-related distresses and permanent vertical deformation, which have emerged as the predominant forms of pavement deterioration. A fatigue life prediction model and an accumulated vertical deformation (rutting) model are incorporated into estimating and comparing the pavement distresses under normal traffic and platooning operations. With a case study in Ontario, this study culminates in the development of heat maps for the region. These maps visually demonstrate the impact of regional traffic variations, temperature fluctuations, and axle load ranges on the degree of pavement fatigue cracking and rutting.

Railways are essential to socio-economic development, serving as a critical piece of infrastructure that requires continuous monitoring and upkeep to maintain safety and reliability. Traditional approaches have largely depended on manual inspections and maintenance, necessitating direct physical interaction with railway infrastructure for its installation, maintenance, and repair. Yet, recent advancements in technology have opened the door to more sophisticated, data-driven methods that enhance the safety and precision of railway maintenance. This paper presents a comprehensive approach for monitoring railway tracks and identifying and classifying anomalies in track gauge. By applying a sequence of nonlinear transformations to LiDAR scan data, we align it within a cohesive coordinate system for precise track gauge measurement. We propose an algorithm for detecting abnormal gauges, leveraging both global and local detection techniques. The findings from our case study affirm that the methodology outlined in this study is capable of accurately identifying both global and local gauge irregularities, offering automated classification and in-depth analysis of these discrepancies. This significantly supports the maintenance and operational management of railway systems.

Transportation is one of the most contributing economic sectors to carbon emissions. Increasing the knowledge of individuals to understand the negative effects of climate change can encourage them to make more eco-friendly decisions. Goal framing theory enhances the impact of climate change information on vehicle choice and different framings to present the CO₂ emissions have different levels of effects on the willingness to pay (WTP) for the emission reduction. However, there might be some underlying psychological factors that induce these variations. This study introduces the Moral Foundations Values as moderating factors to explain such differences. The study demonstrates that individual moral values affect how people respond to these framings by analyzing data from discrete choice experiments with Canadian drivers. Specifically, the authority shows the strongest effects with the highest WTP under the Newspaper-fire framing. While it has the biggest negative effects on the WTP under Emojis framing. This suggests that using appropriate framing can considerably change the WTP for CO₂ emissions considering the moral foundation values of different populations.

The proliferation of autonomous driving technology and services worldwide has rapidly advanced, driving innovation in the established road transportation landscape. In particular, with the rapid increase in the number of autonomous vehicles, various research and pilot projects are underway. However, studying the interaction between autonomous and self-driving vehicles on road networks and evaluating them is constrained by the low Market Penetration Rate (MPR) of autonomous vehicles. It aims to evaluate autonomous cooperative driving services in a simulated environment where autonomous and conventional vehicles coexist on road networks. The study comprises the following procedures: (1) Surveying the current state of research on global autonomous cooperative driving services, (2) Reviewing various micro-traffic simulation tools, selecting an appropriate tool, and implementing autonomous cooperative driving services on a simulated network based on the actual network, (3) Conducting a comprehensive evaluation of mobility and safety aspects based on autonomous cooperative driving service scenarios. This study explores time travel and speed/acceleration-based Surrogate Safety Measures (SSM) indicators to assess detour degrees induced by service applications. Through grouping vehicles based on the same Origin–Destination (OD), the research aims to provide insights into the effectiveness of these measures in quantifying detours and understanding the implications of service applications on traffic flow. The network is updated based on Daejeon city in South Korea to achieve a realistic simulation, and a scenario involving route-change and lane-change services among various autonomous cooperative driving services is selected. As the development and widespread adoption of future autonomous driving technology become more certain, it is expected that this research will facilitate operational and regulatory decision-making in the future.

The increase in freight movements significantly contributes to congestion on urban arterial roads. The limited left-turn lane length and available green phase for left-turning vehicles highlight the need for closer attention to these movements. This study aims to evaluate the operational impact of using the traffic signal priority technique to enhance left-turn movements for freight vehicles, thus aiming for more efficient left turn traffic flow. This study used PTV VISSIM and developed a micro-simulation model encompassing 32 signalized intersections along a 19.2 km study corridor, Brampton, in Region of Peel. The study compares two scenarios: a baseline “do-nothing” condition and one implementing freight signal priority (FSP) for left-turning freight vehicles. The performance measures include the travel time of different vehicle types, such as passenger cars and trucks. Results show an overall travel time reduction by 1.3% with FSP application limited to left-turn movements. Specifically, the average travel times for passenger cars improved by about 2.97 min (1.2%) per vehicle, while freight travel times improved by 1.3% per vehicle, saving 3.02 min per truck. The study demonstrates that the FSP implementation for left turns effectively reduced overall freight vehicles travel times and positively impacts passenger vehicle travel times. It suggests that strategical integration of FSP for left turns can significantly enhance overall road network performance.

The COVID-19 pandemic posed a global challenge, prompting different countries to adopt distinct control strategies. This study focuses on Montreal, Quebec, and Hong Kong, China, both with similar topologies and populations but divergent approaches to tackling the pandemic. Montreal enforced strict internal control measures with lenient border policies, while Hong Kong opted for rigorous external control and relaxed internal measures. This study builds two comprehensive mobility-based epidemic simulation models for both cities. These models are then utilized to test three aspects concerning the external and internal control policies used to mitigate the outbreak of the Omicron variant: sensitivity of internal and external control measures and lag time in implementing on-demand internal control measures. Numerical experiments on the Montreal model suggest the existence of a critical value for internal restrictions and implementation lag, leading to sudden geometric increases in infections. Regardless of internal strictness, some form of external control was found necessary. Further experiments can shed light on the complex interaction between control measures in restricting the Omicron outbreak.

This paper presents a comprehensive life cycle assessment (LCA) of three electric transport technologies: Battery Electric Buses (BEBs), Hydrogenated Buses, and Trolley Bus systems. BEBs are renowned for their zero-tailpipe emissions and growing market share, while hydrogenated buses, powered by hydrogen cells, are known for their low-polluting and energy-efficient capabilities. Trolley bus frames, also known as Electric Wired Buses, provide constant operation through overhead wires. The study aims to provide insights for decision-makers in estimating future electric vehicle frameworks. The methodology considers specific mixed integer non-linear optimization models for each type of electric transportation, considering factors like fleet size, energy consumption, charging infrastructure, and battery life expectancy. The study emphasizes the importance of maximizing the life cycles of these buses to ensure sustainability, minimize costs, and reduce greenhouse gas emissions. The study provides a numerical case study to compare alternatives in terms of total life cycle. The comprehensive comparison of costs for the three types of electric buses results in similar and equal bus conditions, considering electricity sources and sensitivity analysis. This holistic perspective is crucial for developing successful techniques that balance natural sustainability with financial feasibility for a greener and more profitable future for public transportation.

Municipalities and Transportation Agencies in Canada are building more roundabout intersections to promote efficient and safe traffic movement. Roundabouts are known for their low carbon footprint, low lifetime maintenance cost, and better safety performance in reducing collision frequency and severity, among other benefits. The main disadvantage is that Persons with Vision Loss (PWVL) feel unsafe when crossing the street on roundabouts. Therefore, the objectives of this project were to conduct a comprehensive literature review regarding roundabout accessibility as it pertains to PWVL, to identify the concerns and challenges experienced by PWVL on roundabouts in Canada through participation and discussions at a workshop and an opinion survey involving participants across the country as well as to conduct a field study assessing the effectiveness of the installation of sound strips on the road to help PWVL when deciding to cross the streets on the roundabout in Thunder Bay. For the national workshop and the opinion survey, members of staff from the Canadian National Institute for the Blind (CNIB) helped plan and facilitate events by contacting their clients across the country and sharing the necessary information required for the survey. For the field study, seven clients from CNIB in Thunder Bay volunteered to participate in the project. The City of Thunder Bay collaborated and assisted with the field study. The data collection session lasted about three hours before and after the strips were installed. Data collected included details about vehicle speed and the number of times that vehicles yielded or didn’t yield to pedestrians. Also, comments made by the volunteers about their experiences onsite during the field study were noted. Additionally, a 3D model of a roundabout was used to illustrate points relevant to roundabout accessibility when discussing with PWVL and other stakeholders. Included in this conference paper are results from the literature review that are related to roundabout accessibility for PWVL, and those from the national opinion survey as well as comments from the volunteers regarding their concerns arising on-site during the study. Their comments provided insightful information about the issues that PWVL face at roundabouts, forming the basis for future investigation into ways of making roundabouts more accessible for the PWVL. Furthermore, the result obtained showed that the placement of the strips reduced the delay the pedestrians felt at the crosswalk.

Connections or transfers are an important part of public transport journeys, enabling an efficient network catering for anywhere-to-anywhere journeys at higher service levels than otherwise possible. However, transfers can be an inconvenient part of a passenger’s journey compared to direct trips, especially when connecting between low-frequency routes like commuter rail and suburban bus services. With long headways, a missed or badly timed connections can significantly lengthen one’s commute by up to a service’s headway. Transfer optimization has been considered and applied to varying degrees, but with most emphasis on station design and intra-agency timetable coordination. In contrast, inter-agency timetable coordination is rather rare. Most reliability metrics do not consider how connections are affected by delays on intersecting routes. There is a dearth of academic literature on missed transfers in urban public transport, with most research and statistics on punctuality focusing on single-line reliability rather than on missed connections from delays or where transfers involve long waits or walks. A metric of connection convenience, inspired by the limited academic literature and international best practice in Europe, was developed to evaluate the walking and schedule impedance for transfers between GO Transit rail services and connecting bus services based on the actual walking time between stops. This research is important for informing service integration policies seeking to improve multimodal and inter-agency connections. Agencies can use this metric and its analysis results along with transfer demand data to prioritize services for improved scheduling such as application of timed transfer system (TTS) pulsing and better interchange facilities.