Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 11 de 11
Filtrar
1.
Atmos Pollut Res ; 13(6): 101438, 2022 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-35506000

RESUMEN

In response to the COVID-19 pandemic, most countries implemented public health ordinances that resulted in restricted mobility and a resultant change in air quality. This has provided an opportunity to quantify the extent to which carbon-based transport and industrial activity affect air quality. However, quantification of these complex effects has proven to be difficult, depending on the stringency of restrictions, country-specific emission source profiles, long-term trends and meteorological effects on atmospheric chemistry, emission levels and in-flow from nearby countries. In this study, confounding factors were disentangled for a direct comparison of pandemic-related reductions in absolute pollutions levels, globally. The non-linear relationships between atmospheric processes and daily ground-level NO 2 , PM10, PM2.5 and O 3 measurements were captured in city- and pollutant-specific XGBoost models for over 700 cities, adjusting for weather, seasonality and trends. City-level modelling allowed adaptation to the distinct topography, urban morphology, climate and atmospheric conditions for each city, individually, as the weather variables that were most predictive varied across cities. Pollution forecasts for 2020 in absence of a pandemic were generated based on weather and formed an ensemble for country-level pollution reductions. Findings were robust to modelling assumptions and consistent with various published case studies. NO 2 reduced most in China, Europe and India, following severe government restrictions as part of the initial lockdowns. Reductions were highly correlated with changes in mobility levels, especially trips to transit stations, workplaces, retail and recreation venues. Further, NO 2 did not fully revert to pre-pandemic levels in 2020. Ambient PM2.5 pollution, which has severe adverse health consequences, reduced most in China and India. Since positive health effects could be offset to some extent by prolonged exposure to indoor pollution, alternative transport initiatives could prove to be an important pathway towards better health outcomes in these countries. Increased O 3 levels during initial lockdowns have been documented widely. However, our analyses also found a subsequent reduction in O 3 for many countries below what was expected based on meteorological conditions during summer months (e.g., China, United Kingdom, France, Germany, Poland, Turkey). The effects in periods with high O 3 levels are especially important for the development of effective mitigation strategies to improve health outcomes.

2.
Accid Anal Prev ; 171: 106661, 2022 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-35462211

RESUMEN

Reliable knowledge of driving states is of great importance to ensure road safety. Anomaly detection in driving behavior means recognizing anomalous driving states as a direct result of either environmental or psychological factors. This paper provides an efficient anomaly recognition approach to identify anomalous lane-changing events in a personalized manner. The proposed framework includes three unsupervised algorithms. First, a Recurrent-Convolutional Autoencoder extracts the spatio-temporal characteristics from a high-dimensional naturalistic driving dataset. Second, in order to recognize anomalous lane-changing events of individual drivers, the extracted latent feature space is analyzed using Pauta criterion-based reconstruction loss analysis, as well as one-class Support Vector Machine. Last, t-Distributed Stochastic Neighbor Embedding is employed to visualize the latent space for better understanding and interpretability. Temporal anomalies of lane-changing events were analyzed by a personalized grey relational coefficient analysis, to represent robust similarities for individual drivers. Validation and calibration were performed with a natural driving study dataset collected from 50 drivers with 59,372 lane change events. The results showed heterogeneity in the pattern of abnormal lane changing behavior across the sample. At the same time, each driver exhibited heterogeneous anomalous behaviors in both temporal and spatial sequences. Without prior labels, the proposed model effectively captures personalized driving patterns and abnormal lane-changing events from high-dimensional time-series data. This unsupervised hybrid approach is a novel attempt to complete personalized anomalous lane-changing behaviors identification based on naturalistic driving data involving various traffic environments. Our approach enables the extraction of natural individual lane-changing behavior patterns and provides insights for the improvement of personalized driving behavior monitoring systems.


Asunto(s)
Conducción de Automóvil , Aprendizaje Profundo , Accidentes de Tránsito/prevención & control , Algoritmos , Conducción de Automóvil/psicología , Humanos
3.
Aust N Z J Public Health ; 46(3): 292-303, 2022 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-35238437

RESUMEN

OBJECTIVE: In 2020, we developed a public health decision-support model for mitigating the spread of SARS-CoV-2 infections in Australia and New Zealand. Having demonstrated its capacity to describe disease progression patterns during both countries' first waves of infections, we describe its utilisation in Victoria in underpinning the State Government's then 'RoadMap to Reopening'. METHODS: Key aspects of population demographics, disease, spatial and behavioural dynamics, as well as the mechanism, timing, and effect of non-pharmaceutical public health policies responses on the transmission of SARS-CoV-2 in both countries were represented in an agent-based model. We considered scenarios related to the imposition and removal of non-pharmaceutical interventions on the estimated progression of SARS-CoV-2 infections. RESULTS: Wave 1 results suggested elimination of community transmission of SARS-CoV-2 was possible in both countries given sustained public adherence to social restrictions beyond 60 days' duration. However, under scenarios of decaying adherence to restrictions, a second wave of infections (Wave 2) was predicted in Australia. In Victoria's second wave, we estimated in early September 2020 that a rolling 14-day average of <5 new cases per day was achievable on or around 26 October. Victoria recorded a 14-day rolling average of 4.6 cases per day on 25 October. CONCLUSIONS: Elimination of SARS-CoV-2 transmission represented in faithfully constructed agent-based models can be replicated in the real world. IMPLICATIONS FOR PUBLIC HEALTH: Agent-based public health policy models can be helpful to support decision-making in novel and complex unfolding public health crises.


Asunto(s)
COVID-19 , COVID-19/epidemiología , Progresión de la Enfermedad , Humanos , Nueva Zelanda/epidemiología , Salud Pública , SARS-CoV-2 , Victoria/epidemiología
4.
Accid Anal Prev ; 159: 106278, 2021 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-34218195

RESUMEN

AIM: In-vehicle telematics monitoring systems that provide driver feedback have been identified as a promising intervention to influence driver behaviours and reduce the growing burden of road injury. The current study was undertaken to assess the effect of driver feedback alone and feedback plus financial incentives on driving behaviours (speeding, hard acceleration and hard braking). METHOD: A pragmatic randomised trial was undertaken over a 28-week observational period. Drivers were recruited and randomly allocated to one of three groups namely, driver feedback, driver feedback plus incentives and a control group. The feedback group received a weekly summary of their driving performance via SMS text message and access to more detailed feedback via an online dashboard or smartphone application. The feedback plus financial incentive group received the feedback but lost financial incentives for risky driving behaviour above a threshold. RESULTS: A total of 174 drivers completed at least one driving trip during the study period; 18,082 trip days completed by these 174 drivers during the study period provided the sample for analysis. For the primary outcomes of probability of speeding, hard acceleration and hard braking on any given trip, neither feedback alone nor feedback plus incentives delivered statistically significant improvements in driving behaviour relative to the controls. Treatment effects for feedback plus incentives were, however, consistently in the expected direction and large enough to warrant further investigation. For the secondary composite measure of risky driving, namely the DriveScore™, a statistically significant improvement was observed for the feedback and incentive group compared to the control group (TE = 2.6 points on a 0-100 scale, p < 0.05). DISCUSSION: This study adds to our understanding of the potential effects of feedback and financial incentives. Findings suggest that, while feedback alone may be insufficient to motivate behaviour change, combining feedback with financial incentives can deliver potentially important and statistically significant reductions in risky driving behaviours.


Asunto(s)
Conducción de Automóvil , Motivación , Accidentes de Tránsito/prevención & control , Retroalimentación , Humanos , Asunción de Riesgos
5.
Health Place ; 70: 102601, 2021 07.
Artículo en Inglés | MEDLINE | ID: mdl-34157507

RESUMEN

Linking geospatial neighbourhood design characteristics to health and behavioural data from population-representative cohorts is limited by data availability and difficulty collecting information on environmental characteristics (e.g. greenery, building setbacks, dwelling structure). As an alternative, this study examined the feasibility of Generative Adversarial Networks (GANs) - machine learning - to measure neighbourhood design using 'street view' and aerial imagery to explore the relationship between the built environment and physical function. This study included 3102 adults aged 45 years and older clustered in 200 neighbourhoods in 2016 from the How Areas in Brisbane Influence Health and Activity (HABITAT) project in Brisbane, Australia. Exposure data were Google Street View and Google Maps images from within the 200 neighbourhoods, and outcome data were self-reported physical function using the PF-10 (a subset of the SF-36). Physical function scores were aggregated to the neighbourhood level, and the highest and lowest 20 neighbourhoods respectively were used in analysis. We found that the aerial imagery retrieved was unable to be used to adequately train the model, meaning that aerial imagery failed to produce meaningful results. Of the street view images, n = 56,330 images were downloaded and used to train the GAN model. Model outputs included augmented street view images between neighbourhoods classed as having high function and low function residents. The GAN model detected differences in neighbourhood design characteristics between neighbourhoods classed as high and low physical function at the aggregate level. Specifically, differences were identified in urban greenery (including tree heights) and dwelling structure (e.g. building height). This study provides important lessons for future work in this field, especially related to the uniqueness, diversity and amount of imagery required for successful applications of deep learning methods.


Asunto(s)
Entorno Construido , Planificación Ambiental , Adulto , Estudios de Factibilidad , Humanos , Aprendizaje Automático , Características de la Residencia , Caminata
6.
Ergonomics ; 63(8): 981-996, 2020 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-32138601

RESUMEN

How humans will adapt and respond to the introduction of autonomous vehicles (AVs) is uncertain. This study used an agent-based model to explore how AVs, human-operated vehicles, and cyclists might interact based on the introduction of flawlessly performing AVs. Under two separate experimental conditions, results of experiment 1 showed that, despite no conflicts occurring between cyclists and AVs, modelled conflicts among human-operated cars and cyclists increased with the introduction of AVs due to cyclists' adjusted expectations of the behaviour and capability of human-operated and autonomous cars. Similarly, when human-operated cars were replaced with AVs over time in experiment 2, cyclist conflict rates did not follow a linear reduction consistent with the replacement rate but decreased more slowly in the early stages of replacement before 50% substitution. It is concluded that, although flawlessly performing AVs might reduce total conflicts, the introduction of AVs into a transport system where humans adjust to the behaviour and risk presented by AVs could create new sources of error that offset some of AVs assumed safety benefits. Practitioner summary: Ergonomics is an applied science that studies interactions between humans and other elements of a system, including non-human agents. Agent-Based Modelling (ABM) provides an approach for exploring dynamic and emergent interactions between agents. In this article, we demonstrate ABM through an analysis of how cyclists and pedestrians might interact with Autonomous Vehicles (AVs) in future road transport systems. Abbreviations: ABM: agent-based model; AV: autonomous vehicle; ODD; overview, design concepts and details; RW: rescorla-wagner.


Asunto(s)
Accidentes de Tránsito , Automatización , Conducción de Automóvil , Ciclismo , Simulación por Computador , Ergonomía , Humanos , Análisis de Sistemas
7.
Lancet Planet Health ; 4(1): e32-e42, 2020 01.
Artículo en Inglés | MEDLINE | ID: mdl-31999952

RESUMEN

BACKGROUND: Death and injury due to motor vehicle crashes is the world's fifth leading cause of mortality and morbidity. City and urban designs might play a role in mitigating the global burden of road transport injury to an extent that has not been captured by traditional safe system approaches. We aimed to determine the relationship between urban design and road trauma across the globe. METHODS: Applying a combined convolutional neural network and graph-based approach, 1692 cities capturing one third of the world's population were classified into types based on urban design characteristics represented in sample maps. Associations between identified city types, characteristics contained within sample maps, and the burden of road transport injury as measured by disability adjusted life-years were estimated through univariate and multivariate analyses, controlling for the influence of economic activity. FINDINGS: Between Mar 1, 2017, and Dec 24, 2018, nine global city types based on a final sample of 1632 cities were identified. Burden of road transport injury was an estimated two-times higher (risk ratio 2·05, 95% CI 1·84-2·27) for the poorest performing city type compared with the best performing city type, culminating in an estimated loss of 8·71 (8·08-9·25) million disability-adjusted life-years per year attributable to suboptimal urban design. City types that featured a greater proportion of railed public transport networks combined with dense road networks characterised by smaller blocks showed the lowest rates of road traffic injury. INTERPRETATION: This study highlights the important role that city and urban design plays in mitigating road transport injury burden at a global scale. It is recommended that road and transport safety efforts promote urban design that features characteristics inherent in identified high-performance city types including higher density road infrastructure and high rates of public transit. FUNDING: See acknowledgments.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Entorno Construido , Costo de Enfermedad , Ciudades , Humanos
8.
Int J Inj Contr Saf Promot ; 27(1): 20-26, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31870197

RESUMEN

Over the past four decades considerable efforts have been taken to mitigate the growing burden of road injury. With increasing urbanisation along with global mobility that demands not only safe but equitable, efficient and clean (reduced carbon footprint) transport, the responses to dealing with the burgeoning road traffic injury in low- and middle-income countries has become increasingly complex. In this paper, we apply unique methods to identify important strategies that could be implemented to reduce road traffic injury in the Asia-Pacific region; a region comprising large middle-income countries (China and India) that are currently in the throes of rapid motorisation. Using a convolutional neural network approach, we clustered countries containing a total of 1632 cities from around the world into groups based on urban characteristics related to road and public transport infrastructure. We then analysed 20 countries (containing 689 cities) from the Asia-Pacific region and assessed the global burden of disease attributed to road traffic injury and these various urban characteristics. This study demonstrates the utility of employing image recognition methods to discover new insights that afford urban and transport planning opportunities to mitigate road traffic injury at a regional and global scale.


Asunto(s)
Accidentes de Tránsito/prevención & control , Heridas y Lesiones/epidemiología , Heridas y Lesiones/prevención & control , Accidentes de Tránsito/estadística & datos numéricos , Ciudades , Humanos , Transportes/estadística & datos numéricos
9.
Inj Prev ; 25(5): 379-385, 2019 10.
Artículo en Inglés | MEDLINE | ID: mdl-30315090

RESUMEN

The safety in numbers (SiN) effect for cyclists is widely observed but remains poorly understood. Although most studies investigating the SiN phenomenon have focused on behavioural adaptation to 'numbers' of cyclists in the road network, previous work in simulated environments has suggested SiN may instead be driven by increases in local cyclist spatial density, which prevents drivers from attempting to move through groups of oncoming cyclists. This study therefore set out to validate the results of prior simulation studies in a real-world environment. Time-gap analysis of cyclists passing through an intersection was conducted using 5 hours of video observation of a single intersection in the city of Melbourne, Australia, where motorists were required to 'yield' to oncoming cyclists. Results demonstrated that potential collisions between motor vehicles and cyclists reduced with increasing cyclists per minute passing through the intersection. These results successfully validate those observed under simulated conditions, supporting evidence of a proposed causal mechanism related to safety in density rather than SiN, per se. Implications of these results for transportation planners, cyclists and transportation safety researchers are discussed, suggesting that increased cyclist safety could be achieved through directing cyclists towards focused, strategic corridors rather than dispersed across a network.


Asunto(s)
Accidentes de Tránsito/prevención & control , Ciclismo/lesiones , Planificación Ambiental , Seguridad , Planificación Ambiental/estadística & datos numéricos , Humanos , Modelos Estadísticos , Medición de Riesgo
10.
Accid Anal Prev ; 119: 68-79, 2018 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-30005270

RESUMEN

Recent studies have demonstrated that financial incentives can improve driving behaviour but high-value incentives are unlikely to be cost-effective and attempts to amplify the impact of low-value incentives have so far proven disappointing. The present study provides experimental evidence to inform the design of 'smart' and potentially more cost-effective incentives for safe driving in novice drivers. Study participants (n = 78) were randomised to one of four financial incentives: high-value penalty; low-value penalty; high-value reward; low-value reward; allowing us to compare high-value versus low-value incentives, penalties versus rewards, and to test specific hypotheses regarding motivational crowding out and gain/loss asymmetry. Results suggest that (i) penalties may be more effective than rewards of equal value, (ii) even low-value incentives can deliver net reductions in risky driving behaviours and, (iii) increasing the dollar-value of incentives may not increase their effectiveness. These design principles are currently being used to optimise the design of financial incentives embedded within PAYD insurance, with their impact on the driving behaviour of novice drivers to be evaluated in on-road trials.


Asunto(s)
Conducción de Automóvil , Motivación , Recompensa , Asunción de Riesgos , Seguridad , Adulto , Análisis Costo-Beneficio , Femenino , Humanos , Seguro , Masculino , Conducta Social , Adulto Joven
11.
Inj Prev ; 24(1): 89-93, 2018 02.
Artículo en Inglés | MEDLINE | ID: mdl-28073949

RESUMEN

BACKGROUND: Road injury is the leading cause of death for young people, with human error a contributing factor in many crash events. This research is the first experimental study to examine the extent to which direct feedback and incentive-based insurance modifies a driver's behaviour. The study applies in-vehicle telematics and will link the information obtained from the technology directly to personalised safety messaging and personal injury and property damage insurance premiums. METHODS: The study has two stages. The first stage involves laboratory experiments using a state-of-the-art driving simulator. These experiments will test the effects of various monetary incentives on unsafe driving behaviours. The second stage builds on these experiments and involves a randomised control trial to test the effects of both direct feedback (safety messaging) and monetary incentives on driving behaviour. DISCUSSION: Assuming a positive finding associated with the monetary incentive-based approach, the study will dramatically influence the personal injury and property damage insurance industry. In addition, the findings will also illustrate the role that in-vehicle telematics can play in providing direct feedback to young/novice drivers in relation to their driving behaviours which has the potential to transform road safety.


Asunto(s)
Prevención de Accidentes , Accidentes de Tránsito/prevención & control , Conducción de Automóvil/psicología , Simulación por Computador , Seguro , Prevención de Accidentes/economía , Prevención de Accidentes/métodos , Accidentes de Tránsito/economía , Accidentes de Tránsito/psicología , Adolescente , Adulto , Factores de Edad , Análisis Costo-Beneficio , Retroalimentación , Femenino , Humanos , Masculino , Motivación , Reembolso de Incentivo , Conducta de Reducción del Riesgo , Asunción de Riesgos , Análisis y Desempeño de Tareas , Adulto Joven
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA