REFLECTION ON TEACHING A POSTGRADUATE, PROJECT-BASED LEARNING COURSE WITH DIVERSE DISCIPLINES

This paper is a teaching reflection on the delivery of the postgraduate, project-based learning (PBL) engineering course (subject) that is common to five Masters of Engineering program at School of Engineering, RMIT. The data was sourced from end-of-semester surveys of the perceptions of students who completed the course between 2017, when we taught the course for the first time, and 2019. The analysis showed substantial improvements in overall satisfaction, percentage of agreement on the project-based learning helping students to work well with peers, and percentage of agreement that students became more able to apply the theories to practice. The mastery in teaching such a course, especially when the students from various disciplines are involved, demands an adaptive teaching approach wherein the instructors or teachers experiment to continuously improve on the shortcomings in subsequent offerings to enhance the students’ learning experience. A PBL course that is well-designed, well-supported, well-implemented, and well-taught can engage students by improving their comprehension, helping them to work well with peers, improving their communication, and assisting them to apply theories to real application or practice

Piloting ecological sanitation toilets in peri-urban community of Nepal

Concept of Ecological Sanitation; referred as ECOSAN, integrates sanitation and agriculture by using human waste as fertilizer and soil conditioner. The ECOSAN concept has been applied in Siddhipur village of Lalitpur District, which is nearby urban settlement of the Kathmandu Valley, Nepal. The project, initiated on a small scale as a pilot project, is first of its kind in the country. The ECOSAN toilets in this village have been implemented after the demand from the community for proper management of their wastes. Main thrust of constructing ECOSAN toilets is due to their potential of preventing groundwater pollution, reuse in agriculture and management of sanitary waste. The acceptance, active participation, sharing of cost for building ECOSAN units and use of urine in agriculture are few of the indicators of sustainability of the project. The significant impact on the whole community has given impetus for replication to other areas as well

Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model

The economic and health impacts resulting from the greenhouse effect is a major concern in many countries. The transportation sector is one of the major contributors to greenhouse gas (GHG) emissions worldwide. Almost 15 percent of the global GHG and over 20 percent of energy-related CO"sub"2"/sub" emissions are produced by the transportation sector. Quantifying GHG emissions from the road transport sector assists in assessing the existing vehicles’ energy consumptions and in proposing technological interventions for enhancing vehicle efficiency and reducing energy-supply greenhouse gas intensity. This paper aims to develop a model for the projection of GHG emissions from the road transport sector. We consider the Vehicle-Kilometre by Mode (VKM) to Number of Transportation Vehicles (NTV) ratio for the six different modes of transportation. These modes include motorcycles, passenger cars, tractors, single-unit trucks, buses and light trucks data from the North American Transportation Statistics (NATS) online database over a period of 22 years. We use multivariate regression and double exponential approaches to model the projection of GHG emissions. The results indicate that the VKM to NTV ratio for the different transportation modes has a significant effect on GHG emissions, with the coefficient of determination adjusted R"sup"2"/sup" and R"sup"2"/sup" values of 89.46% and 91.8%, respectively. This shows that VKM and NTV are the main factors influencing GHG emission growth. The developed model is used to examine various scenarios for introducing plug-in hybrid electric vehicles and battery electric vehicles in the future. If there will be a switch to battery electric vehicles, a 62.2 % reduction in CO"sub"2"/sub" emissions would occur. The results of this paper will be useful in developing appropriate planning, policies, and strategies to reduce GHG emissions from the road transport sector. Document type: Articl

Crowd dynamics under emergency conditions: using non-human organisms in the development of a pedestrian crowd model

The rapid movement of large numbers of people is critical in emergency and/or panic situations, such as during the evacuation of buildings, stadiums, theatres, and public transport stations; outdoor events such as public assemblies, open concerts, and religious gatherings; and community evacuations following natural disasters or terrorist attacks. Perhaps the most critical reason for studying collective pedestrian dynamics under emergency/panic conditions is the lack of complementary data to develop and validate an explanatory model. That lack of data is likely to explain why very few models focus on panic situations. The bulk of the literature is restricted to the study of normal evacuation processes. Even the researchers responsible for developing the few existing models of crowd panic have identified the need for more rigorous modelling frameworks and the development of approaches to assess the reliability of model predictions. The broad aim of this dissertation is to use empirical data from non-human organisms in the development of a pedestrian traffic model under emergency conditions. Experiments undertaken with non-human organisms under panic conditions are a crucial component of the research reported here. Those experiments are found to be a promising and feasible means of circumventing the limitations posed by the scarcity of complementary human data under panic conditions. Argentine ants (Linepithema humile) were used as test organisms in the experiments reported here because they are abundant and simple to maintain in the laboratory. The experiments reported in this thesis reflect an original attempt to study the effects of structural features, that is, the layout of the escape area, on the collective movement patterns of non-human entities during rapid egress and to translate those results to the study of human panic. Large potential effects from the adjustments of small structural features of the escape area have been demonstrated via experiments with panicking Argentine ants. Insights from the experiments with panicking Argentine ants, along with previous studies on animal dynamics and pedestrian dynamics, have been used in the development of a simulation model called EmSim (short for Emergency Simulation). The formulation for the model recognises the role of both attractive and repulsive forces in maintaining the coherence of collective dynamics under panic conditions. To date, consideration of both repulsive and attractive forces has received limited attention in studies of crowd panic reported in the literature. Also the granular forces for pushing behaviour were modified to consider the case of discontinuity when the relative velocity is zero or near to zero. A first attempt has also been made to scale the model parameters for collective pedestrian traffic via ant traffic, based on a scaling concept commonly used in biology. With this innovative framework combining insights from biology and traffic engineering, there is scope to compare the collective movement patterns of non-human biological entities and pedestrians in order to devise sound strategies to aid evacuation. The proposed model also provides insight into the minimal interactions or physical mechanisms required for the emergence of collective dynamics. The nature of those underlying mechanisms was investigated through experiments with panicking ants. The proposed model is first calibrated and validated (with independent data) through simulation of panicking ant traffic as observed from the experiment and then scaled up for the human panic situation. Since data does not exist for direct measurement of model parameter values appropriate for panicking humans, the parameter values in the model were allometrically scaled up from the ant values to human values. The model predictions for collective pedestrian traffic were consistent with observations of collective traffic for ants. This consistency suggests that there are fundamental features of crowd behavior that transcend the biological idiosyncrasies of the organisms involved. The effectiveness of the proposed modelling framework is also validated through the comparison of the simulation results for the pedestrian traffic with the observed data from the experiment (under non-panic conditions). For normal (non-panic) conditions, the model was validated with experimental data on pedestrian traffic; specifically through comparisons of: •headway distributions in uni-directional traffic, •speed distributions and lane formation in bi-directional traffic, and, •outflow from bottlenecks of various widths. The results provide reassurance of the robustness of the model in explaining the collective dynamics of the panicking individuals despite the differences in speed, size and other biological details between ants and humans. The results also demonstrate the capability of the EmSim model to represent both non-panic and panic conditions within the same modelling framework. The model organism approach is commonplace in medical research but not in engineering, yet it is shown in this dissertation that it has enormous potential to provide insight and theoretical understanding of crowd panic. It will enhance understanding about what properties of panic are inherent to the physical nature of crowds, and what properties depend on idiosyncratic details. Also in biology, little attention has been given to the study of the effect of nest design elements on collective movements of social insects. The experiments that are reported here address those gaps in the study of alarm traffic in social insects by focussing attention to the relationship between nest architecture and internal traffic under alarm conditions. It is expected that the experimental studies and modelling framework presented in this dissertation will appeal to a broad audience, including researchers interested in social insects and nest architecture, self-organization, evacuation and traffic dynamics and engineering

Crowd dynamics under emergency conditions: using non-human organisms in the development of a pedestrian crowd model

The rapid movement of large numbers of people is critical in emergency and/or panic situations, such as during the evacuation of buildings, stadiums, theatres, and public transport stations; outdoor events such as public assemblies, open concerts, and religious gatherings; and community evacuations following natural disasters or terrorist attacks. Perhaps the most critical reason for studying collective pedestrian dynamics under emergency/panic conditions is the lack of complementary data to develop and validate an explanatory model. That lack of data is likely to explain why very few models focus on panic situations. The bulk of the literature is restricted to the study of normal evacuation processes. Even the researchers responsible for developing the few existing models of crowd panic have identified the need for more rigorous modelling frameworks and the development of approaches to assess the reliability of model predictions. The broad aim of this dissertation is to use empirical data from non-human organisms in the development of a pedestrian traffic model under emergency conditions. Experiments undertaken with non-human organisms under panic conditions are a crucial component of the research reported here. Those experiments are found to be a promising and feasible means of circumventing the limitations posed by the scarcity of complementary human data under panic conditions. Argentine ants (Linepithema humile) were used as test organisms in the experiments reported here because they are abundant and simple to maintain in the laboratory. The experiments reported in this thesis reflect an original attempt to study the effects of structural features, that is, the layout of the escape area, on the collective movement patterns of non-human entities during rapid egress and to translate those results to the study of human panic. Large potential effects from the adjustments of small structural features of the escape area have been demonstrated via experiments with panicking Argentine ants. Insights from the experiments with panicking Argentine ants, along with previous studies on animal dynamics and pedestrian dynamics, have been used in the development of a simulation model called EmSim (short for Emergency Simulation). The formulation for the model recognises the role of both attractive and repulsive forces in maintaining the coherence of collective dynamics under panic conditions. To date, consideration of both repulsive and attractive forces has received limited attention in studies of crowd panic reported in the literature. Also the granular forces for pushing behaviour were modified to consider the case of discontinuity when the relative velocity is zero or near to zero. A first attempt has also been made to scale the model parameters for collective pedestrian traffic via ant traffic, based on a scaling concept commonly used in biology. With this innovative framework combining insights from biology and traffic engineering, there is scope to compare the collective movement patterns of non-human biological entities and pedestrians in order to devise sound strategies to aid evacuation. The proposed model also provides insight into the minimal interactions or physical mechanisms required for the emergence of collective dynamics. The nature of those underlying mechanisms was investigated through experiments with panicking ants. The proposed model is first calibrated and validated (with independent data) through simulation of panicking ant traffic as observed from the experiment and then scaled up for the human panic situation. Since data does not exist for direct measurement of model parameter values appropriate for panicking humans, the parameter values in the model were allometrically scaled up from the ant values to human values. The model predictions for collective pedestrian traffic were consistent with observations of collective traffic for ants. This consistency suggests that there are fundamental features of crowd behavior that transcend the biological idiosyncrasies of the organisms involved. The effectiveness of the proposed modelling framework is also validated through the comparison of the simulation results for the pedestrian traffic with the observed data from the experiment (under non-panic conditions). For normal (non-panic) conditions, the model was validated with experimental data on pedestrian traffic; specifically through comparisons of: •headway distributions in uni-directional traffic, •speed distributions and lane formation in bi-directional traffic, and, •outflow from bottlenecks of various widths. The results provide reassurance of the robustness of the model in explaining the collective dynamics of the panicking individuals despite the differences in speed, size and other biological details between ants and humans. The results also demonstrate the capability of the EmSim model to represent both non-panic and panic conditions within the same modelling framework. The model organism approach is commonplace in medical research but not in engineering, yet it is shown in this dissertation that it has enormous potential to provide insight and theoretical understanding of crowd panic. It will enhance understanding about what properties of panic are inherent to the physical nature of crowds, and what properties depend on idiosyncratic details. Also in biology, little attention has been given to the study of the effect of nest design elements on collective movements of social insects. The experiments that are reported here address those gaps in the study of alarm traffic in social insects by focussing attention to the relationship between nest architecture and internal traffic under alarm conditions. It is expected that the experimental studies and modelling framework presented in this dissertation will appeal to a broad audience, including researchers interested in social insects and nest architecture, self-organization, evacuation and traffic dynamics and engineering

Passengers’ Perception of Satisfaction and Its Relationship with Travel Experience Attributes: Results from an Australian Survey

Rail, one of the most sustainable modes of transport, is vital in carrying mass passengers in many urban cities. Passengers’ satisfaction with railway services is mostly discussed in the context of service quality in the literature. However, limited studies have considered other attributes that may influence passengers’ satisfaction, such as their travel experience and issues encountered. This study aims to systematically model passengers’ satisfaction and its relationship with travel experience attributes. This paper makes a theoretical contribution by proposing a conceptual model that evaluates the overall satisfaction of passengers through four attribute groups, including traveller attributes, trip attributes, service attributes, and other attributes. The model is tested with the 429 valid responses collected from a passenger survey targeting Metro train users in Melbourne, Australia. Result shows that the best-fitted model is produced only when all attribute groups are considered together, for which 60% of the variation in overall satisfaction is accountable. It is found that all attribute groups have at least one variable included in the final model, and the service attribute group has the greatest influence. The best model has nine significant variables, with eight having positive associations to the overall satisfaction and one variable (GroupTravel) having a negative association. This finding suggests that consideration of other attributes is also important besides the service attributes, and hence advances our scientific understanding of train passengers’ satisfaction with train services. The public transport sector and the operators can use this knowledge to improve service and increase passenger satisfaction

The Role of Big Five Personality Traits in Explaining Pedestrian Anger Expression

Although the relationship between anger and personality characteristics in the literature is well-acknowledged for drivers, there is a lack of systematic investigation of pedestrians. The current study aimed to evaluate pedestrian anger expression (PAX) and its contributing factors, including demographics, travel habits, and the big five personality traits. To test the effects of different variables on PAX scales, data from 742 respondents were collected. The data were analyzed through a two-stage approach of clustering and a logistic regression model. Participants were clustered into two groups of low expression and high expression based on their responses to PAX items. An exploratory factor analysis identified significant constructs of PAX, including “Adaptive/Constructive Expression”, “Anger Expression-In”, and “Anger Expression-out”. It was found that males were more likely to show high anger expressions. Public transport usage and previous crash involvement could significantly increase the probability of high anger expression. On the other hand, life satisfaction and intention to avoid traffic were negatively associated with high anger expression. The results revealed that neuroticism, extraversion, and openness to experience could positively contribute to higher anger expression; however, agreeableness and conscientiousness were negatively associated with high anger expression for pedestrians

Interpolation-Based Framework for Generation of Ground Truth Data for Testing Lane Detection Algorithm for Automated Vehicle

Automated vehicles, predicted to be fully electric in future, are expected to reduce road fatalities and road traffic emissions. The lane departure warning system, an important feature of automated vehicles, utilize lane detection and tracking algorithms. Researchers are constrained to test their lane detection algorithms because of the small publicly available datasets. Additionally, those datasets may not represent differences in road geometries, lane marking and other details unique to a particular geographic location. Existing methods to develop the ground truth datasets are time intensive. To address this gap, this study proposed a framework for an interpolation approach for quickly generating reliable ground truth data. The proposed method leverages the advantage of the existing manual and time-slice approaches. A detailed framework for the interpolation approach is presented and the performance of the approach is compared with the existing methods. Video datasets for performance evaluation were collected in Melbourne, Australia. The results show that the proposed approach outperformed four existing approaches with a reduction in time for generating ground truth data in the range from 4.8% to 87.4%. A reliable and quick method for generating ground truth data, as proposed in this study, will be valuable to researchers as they can use it to test and evaluate their lane detection and tracking algorithms

The Role of Big Five Personality Traits in Explaining Pedestrian Anger Expression

Although the relationship between anger and personality characteristics in the literature is well-acknowledged for drivers, there is a lack of systematic investigation of pedestrians. The current study aimed to evaluate pedestrian anger expression (PAX) and its contributing factors, including demographics, travel habits, and the big five personality traits. To test the effects of different variables on PAX scales, data from 742 respondents were collected. The data were analyzed through a two-stage approach of clustering and a logistic regression model. Participants were clustered into two groups of low expression and high expression based on their responses to PAX items. An exploratory factor analysis identified significant constructs of PAX, including “Adaptive/Constructive Expression”, “Anger Expression-In”, and “Anger Expression-out”. It was found that males were more likely to show high anger expressions. Public transport usage and previous crash involvement could significantly increase the probability of high anger expression. On the other hand, life satisfaction and intention to avoid traffic were negatively associated with high anger expression. The results revealed that neuroticism, extraversion, and openness to experience could positively contribute to higher anger expression; however, agreeableness and conscientiousness were negatively associated with high anger expression for pedestrians