Search Results - "Ziakopoulos, Apostolos"
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Trip characteristics impact on the frequency of harsh events recorded via smartphone sensors
Published in IATSS research (01-12-2021)“…The Internet of Things (IoT) constantly offers new opportunities and features to monitor and analyze driver behavior through wide use of smartphones, effective…”
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2
Perceptions towards autonomous vehicle acceptance: Information mining from Self-Organizing Maps and Random Forests
Published in IATSS research (01-12-2023)“…The present research investigates a range of factors affecting autonomous vehicle (AV) acceptance of Greek citizens through a questionnaire distributed to 563…”
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3
Pedestrian safety attitudes and self-declared behaviour in Greece
Published in IATSS research (01-04-2023)“…In recent decades, remarkable improvements in road safety have been achieved in the form of reductions of crash numbers. However, the improvement of vulnerable…”
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4
Safety evaluation via conflict classification during automated shuttle bus service operations
Published in European transport research review (27-06-2024)“…The widespread adoption of Connected and Automated Vehicles (CAVs) is being propelled, not only in the realm of private vehicles but also within transit…”
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5
Exploring speeding behavior using naturalistic car driving data from smartphones
Published in Journal of Traffic and Transportation Engineering (English ed. Online) (01-12-2023)“…The present research aimed to identify critical factors that affect speeding behavior. For that purpose, high-resolution smartphone data collected from a…”
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Comparing Machine Learning Techniques for Predictions of Motorway Segment Crash Risk Level
Published in Safety (Basel) (01-06-2023)“…Motorways are typically the safest road environment in terms of injury crashes per million vehicle kilometres; however, given the high severity of crashes…”
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Modelling self-reported driver perspectives and fatigued driving via deep learning
Published in Traffic Safety Research (16-11-2021)“…Driving while fatigued is a considerably understudied risk factor contributing to car crashes every year. The first step in mitigating the respective crash…”
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Exploiting Surrogate Safety Measures and Road Design Characteristics towards Crash Investigations in Motorway Segments
Published in Infrastructures (Basel) (01-03-2023)“…High quality data on road crashes, road design characteristics, and traffic are typically required to predict crash frequency. Surrogate Safety Measures (SSMs)…”
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9
A review of spatial approaches in road safety
Published in Accident analysis and prevention (01-02-2020)“…•This paper reviews spatial analyses in road safety research•Design characteristics of 132 spatial road safety studies are summarized on tables•The various…”
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10
Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data
Published in Accident analysis and prevention (01-11-2024)“…•Factors influencing harsh braking (HB) and harsh acceleration (HA) occurrence are explored.•Naturalistic data from smartphone sensors where combined with…”
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Spatial analysis of harsh driving behavior events in urban networks using high-resolution smartphone and geometric data
Published in Accident analysis and prevention (01-07-2021)“…•This paper exploits smartphone driving behavior data & OpenStreetMap geometric data.•Spatial analyses of harsh driving events are conducted across an urban…”
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12
Predicting VLCC fuel consumption with machine learning using operationally available sensor data
Published in Ocean engineering (01-01-2022)“…In the maritime industry, more accurate predictions of fuel oil consumption (FOC) could yield multidimensional results including more precise bunker…”
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13
Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning
Published in Accident analysis and prevention (01-03-2023)“…•This research explores factors influencing mobile phone use in naturalistic driving.•A smartphone application with 6 feedback phases was the basis for data…”
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14
Spatial predictions of harsh driving events using statistical and machine learning methods
Published in Safety science (01-06-2022)“…•Smartphone driving behavior data & OpenStreetMap geometric data are exploited.•Harsh braking counts are spatially analyzed in an urban road network.•GWPR,…”
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Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting
Published in Journal of safety research (01-09-2021)“…•The impact of COVID-19 on speed, speeding and harsh braking is evaluated.•SARIMA time-series modelling is used for quantifying the pandemic…”
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Combined impact of road and traffic characteristic on driver behavior using smartphone sensor data
Published in Accident analysis and prevention (01-09-2020)“…•This paper exploits high resolution driving behavior data obtained from smartphones.•The analysis is augmented by traffic data at the time of harsh behavior…”
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From conflicts to crashes: Simulating macroscopic connected and automated driving vehicle safety
Published in Accident analysis and prevention (01-07-2023)“…•Estimating CAV crashes by converting microsimulation-generated conflicts.•Crash rates will be significantly lower in higher CAV MPRs.•Crash rates decrease…”
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One year of COVID-19: Impacts on safe driving behavior and policy recommendations
Published in Journal of safety research (01-02-2023)“…•The effect on driving behavior and road safety due to COVID-19 response measures was assessed.•Data prior and during the lockdown periods of the pandemic in…”
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Review and ranking of crash risk factors related to the road infrastructure
Published in Accident analysis and prevention (01-04-2019)“…•SafetyCube analysed the effects of crash risk factors regarding road infrastructure.•A taxonomy of 59 risk factors (alignment, road environment, traffic…”
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Investigation of the speeding behavior of motorcyclists through an innovative smartphone application
Published in Traffic injury prevention (18-08-2021)“…The objective of the present study is twofold: (i) to explore the riding behavior of motorcyclists while speeding, based on detailed riding analytics collected…”
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