scholarly journals Exploratory Analysis of Pedestrian Road Trauma in Finland

2021 ◽  
Vol 13 (12) ◽  
pp. 6715
Author(s):  
Steve O’Hern ◽  
Roni Utriainen ◽  
Hanne Tiikkaja ◽  
Markus Pöllänen ◽  
Niina Sihvola
Keyword(s):  
Cluster Analysis ◽  
Motor Vehicle ◽  
Seasonal Effects ◽  
Unique Element ◽  
Driver Behaviour ◽  
Crash Data ◽  
Safety Issues ◽  
Key Issues ◽  
Development Goals ◽  
Pedestrian Crashes

In Finland, all fatal on-road and off-road motor vehicle crashes are subject to an in-depth investigation coordinated by the Finnish Crash Data Institute (OTI). This study presents an exploratory and two-step cluster analysis of fatal pedestrian crashes between 2010 and 2019 that were subject to in-depth investigations. In total, 281 investigations occurred across Finland between 2010 and 2019. The highest number of cases were recorded in the Uusimaa region, including Helsinki, representing 26.4% of cases. Females (48.0%) were involved in fewer cases than males; however, older females represented the most commonly injured demographic. A unique element to the patterns of injury in this study is the seasonal effects, with the highest proportion of crashes investigated in winter and autumn. Cluster analysis identified four unique clusters. Clusters were characterised by crashes involving older pedestrians crossing in low-speed environments, crashes in higher speed environments away from pedestrian crossings, crashes on private roads or in parking facilities, and crashes involving intoxicated pedestrians. The most common recommendations from the investigation teams to improve safety were signalisation and infrastructure upgrades of pedestrian crossings, improvements to street lighting, advanced driver assistance (ADAS) technologies, and increased emphasis on driver behaviour and training. The findings highlight road safety issues that need to be addressed to reduce pedestrian trauma in Finland, including provision of safer crossing facilities for elderly pedestrians, improvements to parking and shared facilities, and addressing issues of intoxicated pedestrians. Efforts to remedy these key issues will further Finland’s progression towards meeting Vision Zero targets while creating a safer and sustainable urban environment in line with the United Nations sustainable development goals.

scholarly journals Trends in school-age pedestrian and pedalcyclist crashes in the USA: 26 states, 2000–2014

2019 ◽  
Vol 26 (5) ◽  
pp. 448-455 ◽  
Author(s):  
Katherine C Wheeler-Martin ◽  
Allison E Curry ◽  
Kristina B Metzger ◽  
Charles J DiMaggio
Keyword(s):  
Hierarchical Linear Modeling ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
School Age Children ◽  
School Age ◽  
Vehicle Crashes ◽  
Crash Data ◽  
Crash Rates ◽  
The Usa ◽  
Pedestrian Crashes

BackgroundDespite substantial progress, motor vehicle crashes remain a leading killer of US children. Previously, we documented significant positive impacts of Safe Routes to School interventions on school-age pedestrian and pedalcyclist crashes.ObjectiveTo expand our analysis of US trends in motor vehicle crashes involving school-age pedestrians and pedalcyclists, exploring heterogeneity by age and geography.MethodsWe obtained recent police-reported crash data from 26 states, calculating population rates of pedestrian and pedalcyclist crashes, crash fatality rates and pedestrian commuter-adjusted crash rates (‘pedestrian danger index’) for school-age children as compared with other age groups. We estimated national and statewide trends by age, injury status, day and travel hour using hierarchical linear modeling.ResultsSchool-age children accounted for nearly one in three pedestrians and one in two pedalcyclists struck in motor vehicle crashes from 2000 to 2014. Yet, the rates of these crashes declined 40% and 53%, respectively, over that time, on average, even as adult rates rose. Average crash rates varied geographically from 24.4 to 100.8 pedestrians and 15.6 to 56.7 pedalcyclists struck per 100 000 youth. Crash rates and fatality rates were inversely correlated.ConclusionsDespite recent increases in adult pedestrian crashes, school-age and younger pedestrians experienced ongoing declines in motor vehicle crashes through 2014 across the USA. There was no evidence of displacement in crash severity; declines were observed in all outcomes. The growing body of state crash data resources can present analytic challenges but also provides unique insights into national and local pedestrian crash trends for all crash outcomes.

scholarly journals Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

2019 ◽  
Vol 11 (19) ◽  
pp. 5194 ◽  
Author(s):  
Natalia Casado-Sanz ◽  
Begoña Guirao ◽  
Antonio Lara Galera ◽  
Maria Attard
Keyword(s):  
Risk Factors ◽  
Injury Severity ◽  
Motor Vehicle ◽  
Weather Conditions ◽  
Crash Data ◽  
Factors Associated ◽  
The Road ◽  
Pedestrian Injury ◽  
On The Road ◽  
Pedestrian Crashes

According to the Spanish General Traffic Accident Directorate, in 2017 a total of 351 pedestrians were killed, and 14,322 pedestrians were injured in motor vehicle crashes in Spain. However, very few studies have been conducted in order to analyse the main factors that contribute to pedestrian injury severity. This study analyses the accidents that involve a single vehicle and a single pedestrian on Spanish crosstown roads from 2006 to 2016 (1535 crashes). The factors that explain these accidents include infractions committed by the pedestrian and the driver, crash profiles, and infrastructure characteristics. As a preliminary tool for the segmentation of 1535 pedestrian crashes, a k-means cluster analysis was applied. In addition, multinomial logit (MNL) models were used for analysing crash data, where possible outcomes were fatalities and severe and minor injured pedestrians. According to the results of these models, the risk factors associated with pedestrian injury severity are as follows: visibility restricted by weather conditions or glare, infractions committed by the pedestrian (such as not using crossings, crossing unlawfully, or walking on the road), infractions committed by the driver (such as distracted driving and not respecting a light or a crossing), and finally, speed infractions committed by drivers (such as inadequate speed). This study proposes the specific safety countermeasures that in turn will improve overall road safety in this particular type of road.

Experimental Application of Global Positioning system To Locate Motor Vehicle Crashes: Impact on Time and Accuracy

1998 ◽  
Vol 1625 (1) ◽  
pp. 41-49 ◽  
Author(s):  
John S. Miller ◽  
Duane Karr
Keyword(s):  
Global Positioning System ◽  
Human Error ◽  
Motor Vehicle ◽  
Motor Vehicle Crash ◽  
Positioning System ◽  
Gps Receivers ◽  
Crash Data ◽  
Vehicle Crash ◽  
Global Positioning ◽  
Conventional Methods

Motor vehicle crash countermeasures often are selected after an extensive data analysis of the crash history of a roadway segment. The value of this analysis depends on the accuracy or precision with which the crash itself is located. yet this crash location only is as accurate as the estimate of the police officer. Global Positioning System (GPS) technology may have the potential to increase data accuracy and decrease the time spent to record crash locations. Over 10 months, 32 motor vehicle crash locations were determined by using both conventional methods and hand-held GPS receivers, and the timeliness and precision of the methods were compared. Local crash data analysts were asked how the improved precision affected their consideration of potential crash countermeasures with regard to five crashes selected from the sample. On average, measuring a crash location by using GPS receivers added up to 10 extra minutes, depending on the definition of the crash location, the technology employed, and how that technology was applied. The average difference between conventional methods of measuring the crash location and either GPS or a wheel ranged from 5 m (16 ft) to 39 m (130 ft), depending on how one defined the crash location. Although there are instances in which improved precision will affect the evaluation of crash countermeasures, survey respondents and the literature suggest that problems with conventional crash location methods often arise from human error, not a lack of precision inherent in the technology employed.

scholarly journals A systematic review of definitions of motor vehicle headways in driver behaviour and performance studies

2021 ◽  
Vol 77 ◽  
pp. 38-54
Author(s):  
Raaj Kishore Biswas ◽  
Rena Friswell ◽  
Jake Olivier ◽  
Ann Williamson ◽  
Teresa Senserrick
Keyword(s):  
Systematic Review ◽  
Performance Studies ◽  
Motor Vehicle ◽  
Driver Behaviour ◽  
And Performance

Does Displaying Safety Messages on Dynamic Message Signs have Measurable Impacts on Crash Risk?

2021 ◽  
pp. 036119812110444
Author(s):  
Megat-Usamah Megat-Johari ◽  
Nusayba Megat-Johari ◽  
Peter T. Savolainen ◽  
Timothy J. Gates ◽  
Eva Kassens-Noor
Keyword(s):  
Negative Binomial ◽  
Driver Behavior ◽  
Field Research ◽  
Crash Risk ◽  
Traffic Crashes ◽  
Crash Data ◽  
Safety Issues ◽  
Dynamic Message Signs ◽  
Safety Message ◽  
Message Signs

Transportation agencies have increasingly been using dynamic message signs (DMS) to communicate safety messages in an effort to both increase awareness of important safety issues and to influence driver behavior. Despite their widespread use, evaluations as to potential impacts on driver behavior, and the resultant impacts on traffic crashes, have been very limited. This study addresses this gap in the extant literature and assesses the relationship between traffic crashes and the frequency with which various types of safety messages are displayed. Safety message data were collected from a total of 202 DMS on freeways across the state of Michigan between 2014 and 2018. These data were integrated with traffic volume, roadway geometry, and crash data for segments that were located downstream of each DMS. A series of random parameters negative binomial models were estimated to examine total, speeding-related, and nighttime crashes based on historical messaging data while controlling for other site-specific factors. The results did not show any significant differences with respect to total crashes. Marginal declines in nighttime crashes were observed at locations with more frequent messages related to impaired driving, though these differences were also not statistically significant. Finally, speeding-related crashes were significantly less frequent near DMS that showed higher numbers of messages related to speeding or tailgating. Important issues are highlighted with respect to methodological concerns that arise in the analysis of such data. Field research is warranted to investigate potential impacts on driving behavior at the level of individual drivers.

scholarly journals Imitating a Safe Human Driver Behaviour in Roundabouts Through Deep Learning

2020 ◽  
Vol 19 (1) ◽  
pp. 85-88
Author(s):  
A. S. J. Cervera ◽  
F. J. Alonso ◽  
F. S. García ◽  
A. D. Alvarez
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Driver Behaviour ◽  
Safety Issues ◽  
Current State ◽  
Surrounding Environment ◽  
Human Driver ◽  
State Of The Environment

Roundabouts provide safe and fast circulation as well as many environmental advantages, but drivers adopting unsafe behaviours while circulating through them may cause safety issues, provoking accidents. In this paper we propose a way of training an autonomous vehicle in order to behave in a human and safe way when entering a roundabout. By placing a number of cameras in our vehicle and processing their video feeds through a series of algorithms, including Machine Learning, we can build a representation of the state of the surrounding environment. Then, we use another set of Deep Learning algorithms to analyze the data and determine the safest way of circulating through a roundabout given the current state of the environment, including nearby vehicles with their estimated positions, speeds and accelerations. By watching multiple attempts of a human entering a roundabout with both safe and unsafe behaviours, our second set of algorithms can learn to mimic the human’s good attempts and act in the same way as him, which is key to a safe implementation of autonomous vehicles. This work details the series of steps that we took, from building the representation of our environment to acting according to it in order to attain safe entry into single lane roundabouts.

scholarly journals Development of a Crash Risk-Scoring Tool for Pedestrian and Bicycle Projects in Oregon

2018 ◽  
Vol 2672 (32) ◽  
pp. 30-39 ◽  
Author(s):  
Yi Wang ◽  
Christopher M. Monsere ◽  
Chen Chen ◽  
Haizhong Wang
Keyword(s):  
Risk Model ◽  
Motor Vehicle ◽  
Research Effort ◽  
Google Earth ◽  
Risk Scores ◽  
Crash Risk ◽  
Scoring Method ◽  
Risk Scoring ◽  
Pedestrian Crashes ◽  
Scoring Tool

Methods for identifying and prioritizing high-crash locations for safety improvements are generally crash-based. There are fewer reported crashes involving non-motorized users and, in most states, reported crashes must involve a motor vehicle. This means that minor, non-injury events are not reported and those crashes that are reported tend to be more severe. Selecting projects based only on crash performance is sometimes limiting for these crash types and predicting where these crashes will occur next is also a challenging task. An alternative to crash-based selection is to develop risk-based criteria and methods. This paper presents the results of a research effort to develop a risk-scoring method with weights derived from data for use in project screening and selection in Oregon. To develop the risk model, data were collected from 188 segments and 184 intersections randomly selected on both state and non-state roadways. Geometric, land use, volume, and crash data were collected from Google Earth, EPA’s Smart Location Database, and the Oregon Department of Transportation crash database from 2009 to 2013. The sample included 213 bicycle and pedestrian crashes on the segments and 238 at intersections. Logistic regression models were developed and the outputs used to create pedestrian and bicycle risk-scoring tools for segments and intersections. The risk-scoring tool was applied to safety projects identified in the 2015 All Roads Transportation Safety (ARTS) project lists from Oregon. The risk scores for the case study applications aligned reasonably well with the project’s benefits-costs estimates.

A Novel Approach for Identifying, Diagnosing, and Treating Active Transportation Safety Issues

2019 ◽  
Vol 2673 (11) ◽  
pp. 813-823 ◽  
Author(s):  
Ahmed Osama ◽  
Tarek Sayed
Keyword(s):  
Land Use ◽  
Active Transportation ◽  
Transportation Safety ◽  
Crash Risk ◽  
Distance Method ◽  
Traffic Demand ◽  
Safety Issues ◽  
Novel Approach ◽  
Traffic Exposure ◽  
Pedestrian Crashes

There has been an increasing interest in active transportation because of its many health, environmental, and economical benefits. However, active commuters are subjected to an elevated level of severe crash risk, which can be a deterrent to many road users to shift to active transportation. Therefore, there is a need for developing systematic approaches to improve the safety of active commuters. This paper presents a new approach for identifying, diagnosing, and remedying active transportation safety issues. The approach is demonstrated through a case study of the City of Vancouver’s 134 traffic analysis zones. Comprehensive GIS data related to traffic exposure, socio-economics, land use, built environment, street network, and cyclist and pedestrian networks were used in the analysis. A multivariate full Bayesian spatial mixed crash model (CM) was developed incorporating cyclist and pedestrian crashes as well as motorized and non-motorized traffic exposure measures. The CM was used to identify the top 10% active transportation crash-prone zones (CPZs) and safe zones (SZs) using the novel Mahalanobis distance method. CPZs were found clustered in the Downtown. Sixteen trigger variables were statistically investigated for each CPZ and SZ. Lastly, remedies, related to land use, traffic demand, and traffic supply management, were proposed using the trigger variable analysis and literature consultation.

scholarly journals Aquaponics and Global Food Challenges

2019 ◽  
pp. 3-17 ◽  
Author(s):  
Simon Goddek ◽  
Alyssa Joyce ◽  
Benz Kotzen ◽  
Maria Dos-Santos
Keyword(s):  
Supply Chain ◽  
Circular Economy ◽  
Nutrient Recycling ◽  
Chain Management ◽  
Key Issues ◽  
Development Goals ◽  
Food Challenges ◽  
Reliable Methods ◽  
Land Water ◽  
Global Food

AbstractAs the world’s population grows, the demands for increased food production expand, and as the stresses on resources such as land, water and nutrients become ever greater, there is an urgent need to find alternative, sustainable and reliable methods to provide this food. The current strategies for supplying more produce are neither ecologically sound nor address the issues of the circular economy of reducing waste whilst meeting the WHO’s Millennium Development Goals of eradicating hunger and poverty by 2015. Aquaponics, a technology that integrates aquaculture and hydroponics, provides part of the solution. Although aquaponics has developed considerably over recent decades, there are a number of key issues that still need to be fully addressed, including the development of energy-efficient systems with optimized nutrient recycling and suitable pathogen controls. There is also a key issue of achieving profitability, which includes effective value chains and efficient supply chain management. Legislation, licensing and policy are also keys to the success of future aquaponics, as are the issues of education and research, which are discussed across this book.

Pedestrian Injury Severity vs. Vehicle Impact Speed: Uncertainty Quantification and Calibration to Local Conditions

2019 ◽  
Vol 2673 (11) ◽  
pp. 583-592 ◽  
Author(s):  
Gary A. Davis ◽  
Christopher Cheong
Keyword(s):  
Uncertainty Quantification ◽  
Injury Severity ◽  
Likelihood Estimation ◽  
Monte Carlo Sampling ◽  
National Sample ◽  
Local Conditions ◽  
Impact Speed ◽  
Crash Data ◽  
Vehicle Impact ◽  
Pedestrian Crashes

This paper describes a method for fitting predictive models that relate vehicle impact speeds to pedestrian injuries, in which results from a national sample are calibrated to reflect local injury statistics. Three methodological issues identified in the literature, outcome-based sampling, uncertainty regarding estimated impact speeds, and uncertainty quantification, are addressed by (i) implementing Bayesian inference using Markov Chain Monte Carlo sampling and (ii) applying multiple imputation to conditional maximum likelihood estimation. The methods are illustrated using crash data from the NHTSA Pedestrian Crash Data Study coupled with an exogenous sample of pedestrian crashes from Minnesota’s Twin Cities. The two approaches produced similar results and, given a reliable characterization of impact speed uncertainty, either approach can be applied in a jurisdiction having an exogenous sample of pedestrian crash severities.

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