ORCID Profile
0000-0002-4604-7256
Current Organisation
University of Technology Sydney
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Publisher: American Society of Civil Engineers (ASCE)
Date: 05-2022
Publisher: Springer Science and Business Media LLC
Date: 21-06-2021
DOI: 10.1007/S13280-021-01574-2
Abstract: As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by in iduals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants ( N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2015
Publisher: IEEE
Date: 09-2015
Publisher: American Society of Civil Engineers (ASCE)
Date: 03-2023
Publisher: Public Library of Science (PLoS)
Date: 02-2021
DOI: 10.1371/JOURNAL.PONE.0245886
Abstract: The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the in idual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents’ perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.
Publisher: American Society of Civil Engineers (ASCE)
Date: 07-2023
Publisher: Elsevier BV
Date: 11-2016
Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.AAP.2019.04.017
Abstract: A current issue within the driver distraction community centres around different findings regarding the impact of mobile phone conversation on driving found in driving simulators versus instrumented vehicles employed in real-world naturalistic driving studies (NDSs). This paper compares and contrasts the two types of studies and aims to provide reasons for the differences in findings that have been documented. A comprehensive review of literature and consultations with human factors experts highlighted that simulator studies tend to show degradation in driving performance, suggestive of increased crash risk as a result of mobile phone conversation. Whilst NDSs, at times, present data suggesting that mobile phone conversation distraction actually reduces crash risk. This study identifies that these differences may be attributed to behavioural hypotheses associated with driver self-regulation, arousal from cognitive loading, task displacement and gaze concentration - all of which need to be explicitly tested in future driving studies. Metric estimation and application was also revealed to be polarising results and the subsequent assessment of the crash risk. A common metric applied in this domain is the 'Odds Ratio', particularly prevalent in NDSs. This study presents a detailed investigation into the assumptions and application of the Odds Ratio which revealed the potential for over- and under-estimation of the metric depending on the core data and s ling assumptions. Furthermore, this research presents a comparative analysis of select driving simulator studies and an NDS considering only driving behaviour data as a means to consistently compare the findings of both methodologies. The findings from this investigation implores the need for greater consistency in the application of analysis methods and metrics across both simulator and NDSs. Improvements can yield a more robust platform to systematically compare and interpret data across both approaches, ultimately leading to enhanced planning and safety regarding mobile phone use while driving.
Publisher: Elsevier BV
Date: 07-2020
Publisher: Public Library of Science (PLoS)
Date: 13-09-2017
Publisher: Elsevier BV
Date: 09-2016
Publisher: MDPI AG
Date: 16-07-2021
DOI: 10.3390/SU13147938
Abstract: Autonomous vehicles (AVs) are being extensively tested on public roads in several states in the USA, such as California, Florida, Nevada, and Texas. AV utilization is expected to increase into the future, given rapid advancement and development in sensing and navigation technologies. This will eventually lead to a decline in human driving. AVs are generally believed to mitigate crash frequency, although the repercussion of AVs on crash severity is ambiguous. For the data-driven and transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. This study performed a comprehensive assessment of CA DMV data from 2014 to 2019 from a safety standpoint, and some trends were discerned. The results show that decrement in automated disengagements does not necessarily imply an improvement in AV technology. Contributing factors to the crash severity of an AV are not clearly defined. To further understand crash severity in AVs, the features and issues with data are identified and discussed using different machine learning techniques. The CA DMV accident report data were utilized to develop a variety of crash AV severity models focusing on the injury for all crash typologies. Performance metrics were discussed, and the bagging classifier model exhibited the best performance among different candidate models. Additionally, the study identified potential issues with the CA DMV data reporting protocol, which is imperative to share with the research community. Recommendations are provided to enhance the existing reports and append new domains.
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 10-2018
Publisher: International Group for Lean Construction
Date: 27-07-2022
DOI: 10.24928/2022/0130
No related grants have been discovered for Kasun Wijayaratna.