ORCID Profile
0000-0003-1082-1200
Current Organisation
RMIT University
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Civil Engineering | Transport Engineering | Transport Planning | Architectural Design |
Urban Planning | Commercial Building Management and Services | Ground Transport not elsewhere classified | Health Protection and/or Disaster Response
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 2021
Publisher: American Society of Civil Engineers
Date: 24-06-2014
Publisher: Elsevier BV
Date: 07-2022
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2312-12
Abstract: Interactions between humans and physical features of the escape area can considerably impede collective movement of panicked crowds. The turning angle is one of the physical features that must be designed carefully as angled or circuitous egress routes such as corridors are unavoidable features of mass gathering places. Previous studies on crowd disasters have highlighted the importance of considering turning movements, particularly under panic situations. However, few qualitative and quantitative studies have addressed this phenomenon. One reason for the limited study might be the lack of empirical data to validate the predictions from mathematical models. In this work, empirical data collected from panicking ants and data from a crowd dynamic simulation model are used to describe how right-angled egress paths work ineffectively compared with straight egress paths during the collective panic egress. Empirical data with panicking ants and simulation results show that right-angled egress paths are more than 20% ineffective compared with straight paths of the same dimensions. That is, right-angled egress paths decrease the flow rate and increase the escape times significantly compared with those of straight egress paths. Results suggest that it is possible to study evacuation strategies and design solutions that can prevent crowd disasters by using empirical data collected from biological entities.
Publisher: Hindawi Limited
Date: 25-05-2023
DOI: 10.1155/2023/2250590
Abstract: Due to a lack of physical protection and balance, motorcycle riders are one of the most vulnerable road users and are more likely to suffer severe injuries than motorists. Between 2009 and 2020, about 60% of motorcycle crashes occurred on nonintersection urban roadways in Victoria, Australia. While considerable research on intersections and their influence on the severity of motorcycle crashes has been conducted, there are limited studies on motorcycle crashes on nonintersection roadways. Since gathering all information from every motorcycle crash may not be possible, heterogeneity can arise from unobserved factors and cause problems in developing reliable crash severity models. Therefore, this study aims to investigate the factors contributing to motorcycle crash severity on Victorian nonintersection urban roadways while considering the heterogeneity of factors. A total of 10,897 nonintersection motorcycles crash data from the beginning of 2009 to November 2020 in the State of Victoria, Australia, were analyzed. A random parameters (mixed) logit model (RPL) was used for evaluating motorcycle crashes. The severity of motorcycle crashes was ided into three categories: fatal injury, serious injury, and minor injury. Also, marginal effects were calculated to see how each parameter estimate affects crash severity outcomes. The RPL model results showed that some factors increased the likelihood of fatal injuries. These factors included not wearing a helmet, being in the older rider age group, riding during the early morning or midnight hours, weekend motorcycle use, riding in the early morning or midnight hours (00:00–6:29 A.M), and insufficient lighting (dark and dusk/dawn). Also, the following factors enhanced the probability of serious injuries: having a pillion passenger, having a motorcycle age of more than 7 years, riding at higher speed limits (more than 50 km/h) or during peak hours in the morning (6:30−8:59 A.M), and being in the younger age group (less than 26 years old). The findings from this study are valuable resources for road safety policy managers to develop effective strategies for improving motorcyclists’ safety at nonintersections. This may include improving the light conditions at nonintersection, encouraging the motorcyclist to maintain motorcycles regularly, and educating the motorcyclist to wear a helmet, avoid distractions, and ride responsibly on the weekends.
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2353-03
Abstract: This research paper explores the manner in which passenger rail transit organizations plan for and manage unplanned service disruptions through an international survey of practices. The research reported here included semistructured interviews of those staff responsible for service disruption management within 71 international transit agencies. Results suggested that 20% of agencies had parallel transit systems that could be used by commuters whose service was disrupted. Most of these systems existed in inner-city contexts. Track intrusions, medical emergencies, weather extremes, and track and rolling stock failures were common causes of unplanned disruptions. Bus bridging was the most common response to line blockages, while transfer of passengers to the next train was the most common approach to in idual rolling stock failures. Track crossovers were widely seen as critical to manage responses to disruptions. A small minority, mostly in cold climates, also saw crossovers as a cause of unplanned failures. Most agencies used spare buses as bus-bridging vehicles. Only 45% actively retracted buses from existing scheduled bus services. Some of these agencies did acknowledge that retraction often was done in extenuating circumstances, however. Rarely did agencies have a strategic reserve of buses for bus-bridging purposes. This paper discusses the implications of the study findings for further research and practice. This paper also documents that all responses to unplanned disruptions can be categorized according to the key disruption characteristics of duration, cause, time, and location, and it provides a typology of response mechanisms on the basis of such characteristics.
Publisher: Elsevier BV
Date: 12-2022
Publisher: Elsevier BV
Date: 09-2020
Publisher: MDPI AG
Date: 30-11-2022
DOI: 10.3390/SU142315948
Abstract: Hydropower has been one of the mature renewable energy systems encompassing a major fraction of renewable energy. Archimedean screw turbines are gaining new interest in hydropower generation that are suitable for low head applications. This paper empirically and experimentally studies the flow inside Archimedean screw turbines along with the influence of blade numbers on their performance. The major objective of this work is to investigate performance and conduct design optimization of a screw turbine operating under ultra-low head ( .2 m) conditions. Experimentally verified empirical results show its reliability in estimating the performance of turbines at low operational speeds. Further, the results show that with the increasing number of blades, the efficiency and power generation capacity can be increased, but the overall performance improvement relative to one blade turbine peaks at around 7 blades. Increasing the power generation capacity can in turn make the turbine compact and could be fabricated at a low-cost.
Publisher: MDPI AG
Date: 03-11-2020
DOI: 10.3390/SU12219152
Abstract: 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 CO2 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 R2 and R2 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 CO2 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.
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 02-2022
DOI: 10.1016/J.AAP.2021.106515
Abstract: Emerging Connected and Autonomous Vehicles (CAVs) technology have a ubiquitous communication framework. It poses security challenges in the form of cyber-attacks, prompting rigorous cybersecurity measures. There is a lack of knowledge on the anticipated cause-effect relationships and mechanisms of CAVs cybersecurity and the possible system behaviour, especially the unintended consequences. Therefore, this study aims to develop a conceptual System Dynamics (SD) model to analyse cybersecurity in the complex, uncertain deployment of CAVs. Specifically, the SD model integrates six critical avenues and maps their respective parameters that either trigger or mitigate cyber-attacks in the operation of CAVs using a systematic theoretical approach. These six avenues are: i) CAVs communication framework, ii) secured physical access, iii) human factors, iv) CAVs penetration, v) regulatory laws and policy framework, and iv) trust-across the CAVs-industry and among the public. Based on the conceptual model, various system archetypes are analysed. "Fixes that Fail", in which the upsurge in hacker capability is the unintended natural result of technology maturity, requires continuous efforts to combat it. The primary mitigation steps are human behaviour analysis, knowledge of motivations and characteristics of CAVs cyber-attackers, CAVs users and Original Equipment Manufacturers education. "Shifting the burden", where policymakers counter the perceived cyber threats of hackers by updating legislation that also reduces CAVs adaptation by imitations, indicated the need for calculated regulatory and policy intervention. The "limits to success" triggered by CAVs penetration increase the defended hacks to establish regulatory laws, improve trust, and develop more human analysis. However, it may also open up caveats for cyber-crimes and alert that CAVs deployment to be alignment with the intended goals for enhancing cybersecurity. The proposed model can support decision-making and training and stimulate the roadmap towards an optimized, self-regulating, and resilient cyber-safe CAV system.
Publisher: American Society of Civil Engineers
Date: 13-07-2015
Publisher: American Society of Civil Engineers
Date: 29-06-2016
Publisher: IEEE
Date: 12-2016
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 03-2021
Publisher: Informa UK Limited
Date: 02-01-2019
Publisher: MDPI AG
Date: 30-05-2022
DOI: 10.3390/SU14116697
Abstract: Around 90% of accidents stem from human error. Disruptive technology, especially automated vehicles (AVs), can respond to the problems by, for instance, eradicating human error when driving, thus increasing energy efficiency due to the platoon effect, and potentially giving more space to human activities by decreasing parking space hence, with the introduction of the autonomous vehicle, the public attitude towards its adoption needs to be understood to develop appropriate strategies and policies to leverage the potential benefits. There is a lack of a systematic and comprehensive literature review on adoption attitudes toward AVs that considers various interlinked factors such as road traffic environment changes, AV transition, and policy impacts. This study aims to synthesize past research regarding public acceptance attitude toward AVs. More specifically, the study investigates driverless technology and uncertainty, road traffic environment changes, policy impact, and findings from AV adoption modelling approaches, to understand public attitudes towards AVs. The study points out critical problems and future directions for analysis of AV impacts, such as the uncertainty on AVs adoption experiment, policy implementation and action plans, the uncertainty of AV-related infrastructure, and demand modelling.
Publisher: MDPI AG
Date: 14-04-2023
DOI: 10.3390/SU15086645
Abstract: 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.
Publisher: Elsevier BV
Date: 2020
Publisher: Hindawi Limited
Date: 16-04-2022
DOI: 10.1155/2022/6511225
Abstract: This study aimed to evaluate the driving behavior of taxi drivers in Isfahan, Iran, and assess the probability of a driver being among the high-risk taxi drivers. To identify risky driving behaviors among taxi drivers, the Driver Behavior Questionnaire (DBQ) was used. By collecting data from 548 taxi drivers, exploratory factor analysis identified the significant components of DBQ including “Inattention errors,” “Inexperience errors,” “Lapses,” “Ordinary violations,” and “Aggressive violations.” K-means clustering was conducted to cluster taxi drivers into three risk groups of low-risk, medium-risk, and high-risk taxi drivers based on their self-reported annual traffic crashes and fines. In addition, logistic regressions identified the extent to which drivers’ crashes and traffic fines are related to their driving behavior, and therefore, what aberrant driving behaviors are more important in explaining the presence of taxi drivers in the high-risk cluster. The results revealed that the majority of participants (66.78%) were low-risk taxi drivers. Aggressive violations and ordinary violations were significant predictors of taxi drivers being in the high-risk group, while inattention errors and aggressive violations were significant predictors of being in the medium/high-risk cluster. The findings from this study are valuable resources for developing safety measures and training for new drivers in the taxi industry.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 06-2015
Publisher: IEEE
Date: 12-2018
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 2013
Publisher: Elsevier BV
Date: 11-2021
Publisher: Hindawi Limited
Date: 02-09-2018
DOI: 10.1155/2018/1063043
Abstract: Complex movement patterns of pedestrian traffic, ranging from unidirectional to multidirectional flows, are frequently observed in major public infrastructure such as transport hubs. These multidirectional movements can result in increased number of conflicts, thereby influencing the mobility and safety of pedestrian facilities. Therefore, empirical data collection on pedestrians’ complex movement has been on the rise in the past two decades. Although there are several reviews of mathematical simulation models for pedestrian traffic in the existing literature, a detailed review examining the challenges and opportunities on empirical studies on the pedestrians complex movements is limited in the literature. The overall aim of this study is to present a systematic review on the empirical data collection for uni- and multidirectional crowd complex movements. We first categorized the complex movements of pedestrian crowd into two general categories, namely, external governed movements and internal driven movements based on the interactions with the infrastructure and among pedestrians, respectively. Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, erging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, erging, and random flows. We put emphasis on the need for the future global collaborative efforts on data sharing for the complex crowd movements.
Publisher: Elsevier BV
Date: 12-2021
Publisher: MDPI AG
Date: 05-12-2022
DOI: 10.3390/FUTURETRANSP2040055
Abstract: Airlines’ major adoption of digital technology during the COVID-19 crisis may have changed how customers experience the services and may affect passengers’ perceptions compared to the past. However, there is a lack of studies systematically examining the adoption of new technology in the airline industry from a passenger satisfaction-centric perspective. This study investigates passengers’ perceptions and satisfaction with digital technology adoption by airlines during the COVID-19 pandemic. An online questionnaire survey was conducted to examine Chinese passengers’ perceptions and satisfaction with 11 digital technology-based services offered by airlines. A total of 365 valid responses were analyzed using ANOVA tests and stepwise multiple linear regression analysis. The analysis indicates that most passengers have a positive attitude towards airlines’ new technology adoption. In the final selected regression model, six technologies offered by the airlines are statistically significant and have impacted passenger satisfaction. They are artificial intelligence (AI) customer service, e-luggage tag, cleaning robot, ultraviolet light and antimicrobial cabin cleaning, an app-controlled in-flight entertainment system, and e-library. The facial recognition service, digital documentation and AI Customer service are the least favorable among the 11 technologies offered by the airlines. There is an opportunity for airlines to improve these services further to gain the trust of the passengers.
Publisher: MDPI AG
Date: 24-09-2022
DOI: 10.3390/SU141912099
Abstract: 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.
Publisher: Hindawi Limited
Date: 26-02-2021
DOI: 10.1155/2021/6638640
Abstract: Taxi drivers face many problems every day including safety issues. The tendency to quickly transport passengers to their destinations for more income has resulted in dangerous driving behaviors leading to traffic violations. So, taxi drivers need appropriate support and training programs to improve safety and reduce the risk of crashes. Implementing different support and safety training programs requires an effective management system. There is a dearth of research on the safety issues of taxis from the perspective of taxi organization managers. This study aims to evaluate the safety issues of taxi transport management through a case study of the Tehran Taxi Organization. A questionnaire survey was conducted with 22 regional managers and 20 transportation specialists of the Tehran Taxi Organization. Issues related to taxi drivers, roads and road users, vehicles, and management systems were evaluated in the questionnaire. Participants determined the relevance level and priority ranking of each question. The level of agreement was then tested using the Kendall concordance test. According to the results, the use of GPS was selected as the best in-vehicle monitoring system that can be used to evaluate drivers in the fleet. Participants believed that passengers’ loading and unloading had the most risk for taxi users. The start-inhibit technology to detect open doors was unanimously evaluated as an efficient technology for taxi safety. With respect to educating taxi users, starting education in schools had the most relevance and priority. Recommendations for increasing the safety of taxis include the use of GPS in taxis to monitor and evaluate drivers, receiving crash reports from police and submitting monthly safety assessment reports, flexibility in drivers’ working hours’ schedule, providing training on drivers fatigue management, and evaluating drivers’ health.
Publisher: IOP Publishing
Date: 02-2023
Abstract: The single-file movement experiment offered a convenient way to investigate the one-dimensional leader–follower behavior of pedestrians. This study investigated the time delays of children pedestrians in the leader–follower behavior by introducing a time-dependent delayed speed correlation. A total of 118 German students from the fifth grade (aged 11–12 years old) and the 11th grade (aged 17–18 years old) participated the single-file experiment. The characteristic delay time for each pedestrian was identified by optimising the time-dependent delayed speed correlation. The influences of the curvature of the experimental scenario, density, age, and gender on the delay time were statistically examined. The results suggested that to a large extent, the revealed characteristic delay time was a density-dependent variable, and none of the curvatures, the age and gender of the in idual, and the age and gender of the leader had a significant influence on it. The findings from this study are variable resources to understand the leader–follower behavior among children pedestrians and to build related simulation models.
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2234-11
Abstract: Collective egress comes into play during emergencies such as natural disasters or terrorist attacks, when rapid egress is essential for escape. An important aspect of collective egress under emergency conditions is the turning movement when a sudden change in the direction or the layout of the escape area occurs. Previous case studies of crowd disasters have highlighted the importance of such turning movements however, both qualitative and quantitative studies seldom address this phenomenon specifically for emergency and panic situations. The paucity of complementary data on human panic presents a considerable challenge to undertaking quantitative analysis. The study described in this paper uses empirical data from real-life video footage of a crowd st ede and from panicking ants, paired with a simulation model, to demonstrate how potential problems and consequences of turning movements during collective dynamics can be studied. With this modeling tool, it may be possible to develop evacuation strategies and design solutions that can prevent st edes and tr ling, which occur when large groups of people try to escape from confined spaces where escape path directions abruptly change.
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 12-2016
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 12-2023
Publisher: Elsevier BV
Date: 06-2020
Publisher: Informa UK Limited
Date: 30-01-2014
Publisher: Elsevier BV
Date: 08-2022
Publisher: Springer Science and Business Media LLC
Date: 02-2023
DOI: 10.1038/S41598-023-29018-9
Abstract: The digital transformation of Automated Vehicles (AVs) has raised concerns in the cyber realm among prospective AV consumers. However, there is a dearth of empirical research on how cyber obstacles may impact the operation of AVs. To address this knowledge gap, this study examines the six critical cyber impediments (data privacy, AV connectivity, ITS infrastructure, lack of cybersecurity regulations, AV cybersecurity understanding, and AV cyber-insurance) that influence the deployment of AVs. The impact of gender, age, income level, and in idual AV and cybersecurity knowledge on these obstacles are statistically assessed using a s le of 2061 adults from the United States, the United Kingdom, New Zealand, and Australia. The research revealed intriguing empirical findings on all cyber barriers in the form of a trichotomy: participants' education level, understanding of AVs, and cybersecurity knowledge. As education levels increase, the significance of a cyber barrier to AV deployment decreases however, as AV comprehension and cybersecurity knowledge increase, the perception of a cyber barrier becomes significantly more important. In addition, the study demonstrates differences in perceptions of cyber barriers and AV deployments based on gender, age, income, and geographic location. This study's findings on cyber barriers and AV deployment have implications for academia and industry.
Publisher: MDPI AG
Date: 09-02-2023
DOI: 10.3390/WEVJ14020048
Abstract: 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.
Publisher: Elsevier BV
Date: 2021
Publisher: Informa UK Limited
Date: 12-05-2014
Publisher: Elsevier BV
Date: 11-2023
Publisher: Hindawi Limited
Date: 14-03-2021
DOI: 10.1155/2021/1576315
Publisher: MDPI AG
Date: 15-10-2021
DOI: 10.3390/SU132011417
Abstract: Autonomous vehicles and advanced driver assistance systems are predicted to provide higher safety and reduce fuel and energy consumption and road traffic emissions. Lane detection and tracking are the advanced key features of the advanced driver assistance system. Lane detection is the process of detecting white lines on the roads. Lane tracking is the process of assisting the vehicle to remain in the desired path, and it controls the motion model by using previously detected lane markers. There are limited studies in the literature that provide state-of-art findings in this area. This study reviews previous studies on lane detection and tracking algorithms by performing a comparative qualitative analysis of algorithms to identify gaps in knowledge. It also summarizes some of the key data sets used for testing algorithms and metrics used to evaluate the algorithms. It is found that complex road geometries such as clothoid roads are less investigated, with many studies focused on straight roads. The complexity of lane detection and tracking is compounded by the challenging weather conditions, vision (camera) quality, unclear line-markings and unpaved roads. Further, occlusion due to overtaking vehicles, high-speed and high illumination effects also pose a challenge. The majority of the studies have used custom based data sets for model testing. As this field continues to grow, especially with the development of fully autonomous vehicles in the near future, it is expected that in future, more reliable and robust lane detection and tracking algorithms will be developed and tested with real-time data sets.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Inderscience Publishers
Date: 2021
Publisher: Elsevier BV
Date: 09-2016
Publisher: Elsevier BV
Date: 06-2022
DOI: 10.1016/J.JSR.2022.01.008
Abstract: The safety of pedestrians is a major concern in Victoria, Australia. Despite the considerable number of pedestrian fatalities and injuries in traffic crashes, a limited number of studies focused on pedestrian crash severity in Victoria. This study investigates and identifies the influential factors determining the severity of pedestrian injuries in traffic crashes in Victoria by using crash data from 2010 to 2019. An unordered multinomial logit model and an ordered logit model are developed for this purpose. The results indicate that pedestrian crashes on weekends, in the period of 10 a.m. to 10 p.m., on dark streets, at intersections, in areas with a speed limit above 50 km/h, and on medians or footpaths are associated with a higher probability of severe and fatal injuries. Male pedestrians, children, and older adults (>59) were more likely to sustain a higher level of injury in crashes. Concerning the driver characteristics, no significant relationship was found between pedestrian injury severity and driver gender and license status, but older drivers were more likely to cause severe and fatal injuries. Pedestrian collisions with motorcycles, heavy vehicles, light commercial vehicles, bus/minibus/coach, and trams increase the probability of more severe injuries compared to cars. Moreover, older vehicles are associated with a higher probability of severe pedestrian injuries. Comparison of the model results illustrated that the MNL model was slightly better fitted on the data than the ordered logit model, but the conclusions inferred from these two models were generally similar. To reduce the injuries of pedestrian crashes, we recommend improving lighting conditions and sidewalk design, implementing speed reduction strategies at high pedestrian activity areas, introducing more pedestrian crossings at midblock, installing warning signs to drivers, and discouraging the use of vehicles that are more than 20 years old.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 12-2021
DOI: 10.1016/J.JSR.2021.09.005
Abstract: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.
Publisher: Wiley
Date: 06-07-2010
Publisher: Elsevier BV
Date: 10-2016
DOI: 10.1016/J.AAP.2015.10.009
Abstract: A recent crowd st ede during a New Year's Eve celebration in Shanghai, China resulted in 36 fatalities and over 49 serious injuries. Many of such tragic crowd accidents around the world resulted from complex multi-direction crowd movement such as merging behavior. Although there are a few studies on merging crowd behavior, none of them have conducted a systematic analysis considering the impact of both merging angle and flow direction towards the safety of pedestrian crowd movement. In this study, a series of controlled laboratory experiments were conducted to examine the safety constraints of merging pedestrian crowd movements considering merging angle (60°, 90° and 180°) and flow direction under slow running and blocked vision condition. Then, macroscopic and microscopic properties of crowd dynamics are obtained and visualized through the analysis of pedestrian crowd trajectory data derived from video footage. It was found that merging angle had a significant influence on the fluctuations of pedestrian flows, which is important in a critical situation such as emergency evacuation. As the merging angle increased, mean velocity and mean flow at the measuring region in the exit corridors decreased, while mean density increased. A similar trend was observed for the number of weaving and overtaking conflicts, which resulted in the increase of mean headway. Further, flow direction had a significant impact on the outflow of the in iduals while blocked vision had an influence on pedestrian crowd interactions and merging process. Finally, this paper discusses safety assessments on crowd merging behaviors along with some recommendations for future research. Findings from this study can assist in the development and validation of pedestrian crowd simulation models as well as organization and control of crowd events.
Publisher: Elsevier BV
Date: 11-2023
Publisher: Springer Science and Business Media LLC
Date: 15-06-2019
Publisher: Springer Science and Business Media LLC
Date: 20-03-2020
Publisher: Vilnius Gediminas Technical University
Date: 05-12-2018
DOI: 10.3846/16484142.2016.1155170
Abstract: The practical implementations of congestion-pricing are largely restricted, due to the low public acceptance level. Based on a field survey, this study reveals the public acceptance level in Melbourne, Australia. It was found that the level of acceptance for a new congestion-pricing scheme is 42%, which still needs to be improved if a congestion-pricing scheme is to be implemented. Some strategies are proposed and discussed to increase the acceptance level towards congestion charge in urban cities, including an information c aign, public transport improvements and a trial.
Publisher: SAGE Publications
Date: 2015
DOI: 10.3141/2537-02
Abstract: A new approach explores the economic viability of dedicated bus reserves purely for bus bridging purposes. The approach estimates feet costs and user benefits of reduced delay by improving the response to unplanned rail disruption. The feasibility of dedicated bus reserves has not been considered in previous research. Sourcing buses for bus bridging purposes is problematic during weekday peak periods, which coincide with the highest demand for rail travel. At all other times spare buses are available. Consequently, a dedicated bus reserve would exist mainly to provide bus bridging in the peak. Results suggest that a dedicated bus bridging reserve can be economically viable. Of 18 corridors studied, a dedicated reserve was feasible for 78%. Economically viable corridors have a benefit–cost ratio ranging between 1.5 and 9.7 (average, 4.5). Reserves were not feasible where existing rail demand, disruption likelihood, or both were low. Sensitivity tests explored viability with more conservative assumptions. In each test, the dedicated bus reserve in most corridors remained economically viable. The research suggests that a dedicated bus reserve should be considered by rail operators worldwide because of strong net economic benefits. However, reserves are a net cost (with no income), so investment must be based on economic, not financial, benefits. This aspect suggests that government authorities, rather than commercial operators, may find a dedicated reserve more feasible. This approach illustrates where reserves might best be allocated to maximize investment returns.
Publisher: Elsevier BV
Date: 10-2019
Publisher: Elsevier BV
Date: 08-2016
Publisher: MDPI AG
Date: 23-05-2019
DOI: 10.3390/SU11102930
Abstract: A safer and securer public transport provides a wide range of sustainability benefits to a community. This paper explores passengers’ perception of security checks (SCs) in metro stations, with a focus on the safety and mobility of passenger flows. We used 27 scaling items categorized into five variables: efficiency, comfort, safety, privacy and willingness-to-pay. A questionnaire survey of 880 metro passengers in China showed that respondents are generally homogenous in their perceptions of metro SCs in terms of their agreement on mandatory SC policy and the priority of safety. Most passengers are willing to trade-off their trip efficiency and privacy in exchange for safety improvement, while a small proportion of people are inclined to trade-off their trip efficiency for a more comfortable waiting and riding experiences. Demographic differences such as gender and age group effects are observed. For ex le, females tend to be more concerned with trip comfort while older passengers are more likely to compromise their privacy with enhancement in safety features. Findings from this study can be a valuable resource to railway authorities in designing and developing a SC system at major railway hubs.
Publisher: MDPI AG
Date: 24-08-2023
DOI: 10.3390/S23177388
Abstract: With the increasing use of automated vehicles (AVs) in the coming decades, government authorities and private companies must leverage their potential disruption to benefit society. Few studies have considered the impact of AVs towards mode shift by considering a range of factors at the city level, especially in Australia. To address this knowledge gap, we developed a system dynamic (SD)-based model to explore the mode shift between conventional vehicles (CVs), AVs, and public transport (PT) by systematically considering a range of factors, such as road network, vehicle cost, public transport supply, and congestion level. By using Melbourne’s Transport Network as a case study, the model simulates the mode shift among AVs, CVs, and PT modes in the transportation system over 50 years, starting from 2018, with the adoption of AVs beginning in 2025. Inputs such as current traffic, road capacity, public perception, and technological advancement of AVs are used to assess the effects of different policy options on the transport systems. The data source used is from the Victorian Integrated Transport Model (VITM), provided by the Department of Transport and Planning, Melbourne, Australia, data from the existing literature, and authors’ assumptions. To our best knowledge, this is the first time using an SD model to investigate the impacts of AVs on mode shift in the Australian context. The findings suggest that AVs will gradually replace CVs as another primary mode of transportation. However, PT will still play a significant role in the transportation system, accounting for 50% of total trips by person after 2058. Cost is the most critical factor affecting AV adoption rates, followed by road network capacity and awareness programs. This study also identifies the need for future research to investigate the induced demand for travel due to the adoption of AVs and the application of equilibrium constraints to the traffic assignment model to increase model accuracy. These findings can be helpful for policymakers and stakeholders to make informed decisions regarding AV adoption policies and strategies.
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 2021
Publisher: MDPI AG
Date: 12-11-2019
DOI: 10.3390/SU11226346
Abstract: In the past, different forecasting models have been proposed to predict greenhouse gas (GHG) emissions. However, most of these models are unable to handle non-linear data. One of the most widely known techniques, the Adaptive Neuro-fuzzy inference system (ANFIS), can deal with nonlinear data. Its ability to predict GHG emissions from road transportation is still unexplored. This study aims to fulfil that gap by adapting the ANFIS model to predict GHG emissions from road transportation by using the ratio between vehicle-kilometers and number of transportation vehicles for six transportation modes (passenger cars, motorcycle, light trucks, single-unit trucks, tractors, and buses) from the North American Transportation Statistics (NATS) online database over a period of 22 years. The results show that ANFIS is a suitable method to forecast GHG emissions from the road transportation sector.
Publisher: Elsevier BV
Date: 11-2011
Publisher: Informa UK Limited
Date: 03-04-2021
Publisher: IEEE
Date: 06-2022
Publisher: Springer Science and Business Media LLC
Date: 21-02-2018
Publisher: IEEE
Date: 19-02-2021
Publisher: Springer Science and Business Media LLC
Date: 27-04-2020
Publisher: Elsevier BV
Date: 2020
Publisher: IEEE
Date: 11-2021
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2196-19
Abstract: An interesting aspect of collective dynamics of various biological entities is that they are emergent systems. A literature review examines how the fundamental principles of emergent systems can be applied to model collective pedestrian dynamics. A simulation model is then proposed on the basis of modifications of collective animal dynamics. Recent findings from experiments with panicking Argentine ants are presented to illustrate how such experiments can be used to study collective pedestrian traffic. Despite the difference in speed, size, and other biological details of the panicking in iduals, the model proved capable of explaining the collective dynamics. The model's robustness is demonstrated by comparing its ability to simulate the collective traffic of panicking ants as well as collective human traffic. The lack of complementary data during emergency and panic situations is a challenge for model development. Empirical data from biological organisms can play a valuable role in the development of pedestrian traffic models from a theoretical perspective and in instances in which model validation is based on empirical data collected by video. Such a novel framework, which is based on complementary expertise, can be used as a basis for the design of solutions for the safe egress of pedestrians.
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 05-2019
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2137-04
Abstract: It may be possible to use nonhuman biological entities for empirical study of pedestrian crowds under emergency conditions. A literature review is used to examine how the study of mass movement of organisms might enhance the safety of pedestrians during emergency egress. Recent findings from experiments with panicking ants are presented as ex les, with two scenarios, of how such experiments can be used as a basis for the design of solutions to ensure safe egress of pedestrians in emergencies. Although the experiments are still in progress and it is too early to draw definitive conclusions with statistical significance, some preliminary results show promise in using ants to test models for pedestrian traffic in emergency conditions. Because of the lack of complementary data during emergency or panic-inducing situations, experiments such as these with ants provide alternate empirical ways to test whether designs developed by means of mathematical models may actually be efficacious and improve the safety of pedestrians.
Publisher: Elsevier BV
Date: 2020
Publisher: AIP Publishing
Date: 2022
DOI: 10.1063/5.0115912
Publisher: MDPI AG
Date: 21-09-2022
DOI: 10.3390/SU141911875
Abstract: Limited studies have investigated pedestrians’ exit choices in an emergency in multi-level commercial buildings. In particular, the comparison between exit choices before and after awareness of an incident location is non-existent in the literature. Likewise, the influence of in idual attributes, such as the presence of a child or a companion, on the in idual’s exit choice in complex architectural layouts has rarely been studied in the literature. This paper aims to address these knowledge gaps by investigating pedestrians’ exit choice behavior in an emergency at a multi-level shopping complex considering exit choice behavior before and after awareness of incident location and the influence of personal attributes (e.g., presence of a child or companion). A survey of 1271 pedestrians for two hypothetical emergency scenarios in a multi-level shopping center in Tehran, Iran was conducted. A tablet-based simulator of a multi-story commercial complex was designed, and on-site interviews were conducted. In the first scenario, participants were asked to select their preferred exit door at the start of the emergency alarm without being informed about the incident location. In the next scenario, the scene of an incident (fire) was displayed without altering the conditions, and pedestrians were asked to choose their desired exit. The utility models investigated the differences in pedestrians’ behavior before and after awareness of the fire location. The models show differences in pedestrian decisions to evacuate and select the exit when the fire location information was available compared to when only emergency alarm information was available. Further, differences in evacuation strategy between the people who preferred to delay the exit and those who preferred to exit immediately were observed. Participants with children were more concerned about the ease of moving on the route and preferred a less congested route and exit area. Differences in evacuation behavior on the ground floor and other floors were also observed.
Publisher: AIP Publishing
Date: 2022
DOI: 10.1063/5.0115914
Publisher: Elsevier BV
Date: 11-2019
Publisher: MDPI AG
Date: 22-12-2022
DOI: 10.3390/SU15010185
Abstract: Traffic crashes involving pedestrians have a high frequency in developing countries. Among road users, pedestrians are the most vulnerable, as their involvement in traffic crashes is usually followed by severe and fatal injuries. This study aims to identify pedestrian crash patterns and reveal the random parameters in the dataset. A three-year (2015–2017) pedestrian crash dataset in Mashhad, Iran, was employed to investigate the influence of a rich set of factors on pedestrian injury severity, some of which have been less accounted for in previous studies (e.g., the vicinity to overpasses, the existence of vegetated buffers, and park lanes). A two-step method integrating latent class cluster analysis (LCA) and the mixed logit model was utilized to consider unobserved heterogeneity. The results demonstrated that various factors related to the pedestrian, vehicle, temporal, environmental, roadway, and built-environment characteristics are associated with pedestrian injuries. Furthermore, it was found that integrated use of LCA and mixed logit models can considerably reduce the unobserved heterogeneity and uncover the hidden effects influencing severity outcomes, leading to a more profound perception of pedestrian crash causation. The findings of this research can act as a helpful resource for implementing effective strategies by policymakers to reduce pedestrian casualties.
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 07-2014
Publisher: MDPI AG
Date: 26-07-2023
DOI: 10.3390/SU151511564
Abstract: The focus on sustainable transportation has increased interest in promoting sustainable modes of transport, such as rail. Understanding train passengers’ behaviors and perceptions is essential to enhance their travel experience and increase train ridership. Pre-boarding behaviors and perceptions are crucial in shaping the overall train travel experience. However, there are limited studies that have developed a systematic framework for investigating train passengers’ pre-boarding behaviors and perceptions. This paper examines the train passenger’s pre-boarding behaviors and perceptions about the station and platform. The study adopts a mixed-methods approach by developing a pre-boarding decision framework and combining it with questionnaire surveys to explore passengers’ behaviors and perceptions on the platform before boarding. A total of 429 valid responses from Melbourne metro train users were used for analysis. Descriptive statistics and correlation techniques were applied to identify patterns and relationships. The findings reveal common pre-boarding behaviors and perceptions. Furthermore, the study uncovers factors influencing these behaviors and perceptions, such as passenger demographics, travel patterns, and specific trip characteristics. For ex le, carrying large items and travel frequency significantly impact passengers’ travel experience in the pre-boarding phase. Waiting time, group travel, carrying small items, gender, and age group also significantly impact some pre-boarding behavior variables. Travel time, on the other hand, makes no significant impact on any of the pre-boarding variables that we examined. This research provides valuable insights for rail service operators and policymakers to enhance the pre-boarding experience, optimize station design, and improve passenger satisfaction.
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 2011
Publisher: MDPI AG
Date: 24-09-2022
DOI: 10.3390/SU141912100
Abstract: Disruptive technology, especially autonomous vehicles, is predicted to provide higher safety and reduce road traffic emissions. Lane detection and tracking are critical building blocks for developing autonomous or intelligent vehicles. This study presents a lane detecting algorithm for autonomous vehicles on different road pavements (structured and unstructured roads) to overcome challenges such as the low detection accuracy of lane detection and tracking. First, datasets for performance evaluation were created using an interpolation method. Second, a learning-based approach was used to create an algorithm using the steering angle, yaw angle, and sideslip angle as inputs for the adaptive controller. Finally, simulation tests for the lane recognition method were carried out by utilising a road driving video in Melbourne, Australia, and the BDD100K dataset created by the Berkeley DeepDrive Industrial Consortium. The mean detection accuracy ranges from 97% to 99%, and the detection time ranges from 20 to 22 ms under various road conditions with our proposed algorithm. This lane detection algorithm outperformed conventional techniques in terms of accuracy and processing time, as well as efficiency in lane detection and overcoming road interferences. The proposed algorithm will contribute to advancing the lane detection and tracking of intelligent-vehicle driving assistance and help further improve intelligent vehicle driving safety.
Publisher: Elsevier BV
Date: 12-2013
Publisher: MDPI AG
Date: 18-04-2023
DOI: 10.3390/S23084085
Abstract: Lane detection in driving situations is a critical module for advanced driver assistance systems (ADASs) and automated cars. Many advanced lane detection algorithms have been presented in recent years. However, most approaches rely on recognising the lane from a single or several images, which often results in poor performance when dealing with extreme scenarios such as intense shadow, severe mark degradation, severe vehicle occlusion, and so on. This paper proposes an integration of steady-state dynamic equations and Model Predictive Control-Preview Capability (MPC-PC) strategy to find key parameters of the lane detection algorithm for automated cars while driving on clothoid-form roads (structured and unstructured roads) to tackle issues such as the poor detection accuracy of lane identification and tracking in occlusion (e.g., rain) and different light conditions (e.g., night vs. daytime). First, the MPC preview capability plan is designed and applied in order to maintain the vehicle on the target lane. Second, as an input to the lane detection method, the key parameters such as yaw angle, sideslip, and steering angle are calculated using a steady-state dynamic and motion equations. The developed algorithm is tested with a primary (own dataset) and a secondary dataset (publicly available dataset) in a simulation environment. With our proposed approach, the mean detection accuracy varies from 98.7% to 99%, and the detection time ranges from 20 to 22 ms under various driving circumstances. Comparison of our proposed algorithm’s performance with other existing approaches shows that the proposed algorithm has good comprehensive recognition performance in the different dataset, thus indicating desirable accuracy and adaptability. The suggested approach will help advance intelligent-vehicle lane identification and tracking and help to increase intelligent-vehicle driving safety.
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Springer Science and Business Media LLC
Date: 14-11-2013
Publisher: Elsevier BV
Date: 2014
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 12-2014
Publisher: MDPI AG
Date: 11-02-2020
DOI: 10.3390/SU12041301
Abstract: Complex pedestrian or passenger crowd movements, such as intersecting movements, can create a bottleneck resulting in delays during emergency escape from public infrastructure such as major public transport hubs. Limited studies have examined the effect of different intersecting angles and walking speeds on pedestrian outflow. This study aims to systematically investigate the effect of different intersecting angles (30°, 90°, and 150°) and walking speeds (normal walking, faster walking) on pedestrian outflow at an intersecting path or junction through controlled laboratory experiments. Further, we consider both blocked vision and un-blocked vision in our experiments. The results from our experiments show that the acute angle of 30° has a higher flow rate and less evacuation time as compared to the other angles. The obtuse intersecting angle of 150° was the most undesirable intersecting angle in terms of outflow, evacuation time, and delays at the junction. Faster walking generally led to reduced evacuation time as compared to normal walking. It is also interesting to note that the results from both blocked vision and un-blocked vision were not statistically significant, suggesting that line of sight was not an important factor in regulating the flow at the junction. The results from our findings are a valuable resource to verify the mathematical model intended to simulate pedestrian or passenger crowd movements and behavior within major public infrastructure under both normal and evacuation conditions.
Start Date: 2012
End Date: 2015
Funder: Australian Research Council
View Funded ActivityStart Date: 2016
End Date: 2017
Funder: Transport Accident Commission
View Funded ActivityStart Date: 2017
End Date: 2017
Funder: Cass Foundation
View Funded ActivityStart Date: 2017
End Date: 2017
Funder: Defence Science Institute
View Funded ActivityStart Date: 02-2013
End Date: 12-2018
Amount: $210,000.00
Funder: Australian Research Council
View Funded Activity