scholarly journals Prediction of Fatalities in Vehicle Collisions in Canada

2021 ◽  
Vol 33 (5) ◽  
pp. 661-669
Author(s):  
Liza Babaoglu ◽  
Ceni Babaoglu
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Prediction Models ◽  
Machine Learning Techniques ◽  
Lasso Regression ◽  
Contributing Factors ◽  
Vehicle Collisions ◽  
Road Design ◽  
The World ◽  
The Individual

Traffic collisions affect millions around the world and are the leading cause of death for children and young adults. Thus, Canada’s road safety plan is to reduce collision injuries and fatalities with a vision of making the safest roads in the world. We aim to predict fatalities of collisions on Canadian roads, and to discover causation of fatalities through exploratory data analysis and machine learning techniques. We analyse the vehicle collisions from Canada’s National Collision Database (1999–2017.) Through data mining methodologies, we investigate association rules and key contributing factors that lead to fatalities. Then, we propose two supervised learning classification models, Lasso Regression and XGBoost, to predict fatalities. Our analysis shows the deadliness of head-on collisions, especially in non-intersection areas with lacking traffic control systems. We also reveal that most collision fatalities occur in non-extreme weather and road conditions. Our prediction models show that the best classifier of fatalities is XGBoost with 83% accuracy. Its most important features are “collision configuration” and “used safety devices” elements, outnumbering attributes such as vehicle year, collision time, age, or sex of the individual. Our exploratory and predictive analysis reveal the importance of road design and traffic safety education.

scholarly journals Portuguese two-lane highways: modelling crash frequencies for different temporal and spatial aggregation of crash data

Transport ◽  
2015 ◽  
Vol 33 (1) ◽  
pp. 92-103 ◽  
Author(s):  
Jocilene Otilia da Costa ◽  
Alice Prudêncio Jacques Maria ◽  
Paulo António Alves Pereira ◽  
Elisabete Fraga Freitas ◽  
Francisco Emanuel Cunha Soares
Keyword(s):  
Traffic Safety ◽  
Prediction Models ◽  
Road Traffic ◽  
Statistical Modelling ◽  
Original Data ◽  
Northern Region ◽  
Contributing Factors ◽  
Road Traffic Safety ◽  
Contributory Factors ◽  
The Impact

The identification of contributory factors to crash frequencies observed in different highway facilities can aid transportation and traffic management agencies to improve road traffic safety. In spite of the strategic importance of the national Portuguese road network, there are no recent studies concerned with either the identification of contributory factors to road crashes or Crash Prediction Models (CPMs) for this type of roadway. This study presents an initial contribution to this problem by focusing on the national roads NR-14, NR-101 and NR-206, which are located in Northern region of Portugal. They are two-lane single carriageway rural roads. This study analysed the crash frequencies, Average Annual Daily Traffic (AADT) and geometric characteristics of 88 two-lane road segments. The selected segments were 200-m-long and did not cross through urbanized areas. The fixed length of 200 meters corresponds to the road length used in Portugal to define a critical point. Data regarding the annual crash frequency and the AADT were available from 1999 to 2010. Due to the high number of zero-crash records in the initial database, the data were explored to identify the best statistical modelling approach to be adopted. The Generalized Estimating Equations (GEE) procedure was applied to 10 distinctive databases formed by grouping the original data in time and space. The results show that the different observations within each road segment present an exchangeable correlation structure type. This paper also analyses the impact of the sample size on the model’s capability of identifying the contributing factors to crash frequencies. The major contributing factors identified for the two-lane highways studied were the traffic volume (expressed in AADT), lane width, vertical sinuosity, and Density of Access Points (DAP). Acceptable CPM was identified for the highways considered, which estimated the total number of crashes for 400-m-long segments for a cumulative period of two years.

scholarly journals The Development of Data Warehouse to Support Data Mining Technique for Traffic Accident Prediction

2018 ◽  
Vol 73 ◽  
pp. 12007
Author(s):  
Budiawan Wiwik ◽  
Singgih Saptadi ◽  
Ary Arvianto
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Prediction Models ◽  
Data Access ◽  
Design Data ◽  
Accident Prediction ◽  
The World

Traffic accidents are one of the major health problems that cause serious death in the world and ranks 9th in the world. Traffic accidents in Indonesia ranks 5th in the world. One effort to improve traffic safety is to design traffic accident prediction models. Prediction models will utilize accident-related data in traffic through data mining processing. The data warehouse offers benefits as a basis for data mining. Building an effective data warehouse requires knowledge and attention to key issues in database design, data acquisition and processing, as well as data access and security. This study is the first step in the development of data mining accidents based prediction system. The output of this initial stage is the design of data warehouses that can provide periodic and incidental data to the data mining process, especially in the prediction of accidents. The method used to design data warehouse is Entity Relationship Diagram (ERD).

scholarly journals Analysis of Intersection Traffic Safety in the City of San Antonio, 2013–2017

2021 ◽  
Vol 13 (9) ◽  
pp. 5296
Author(s):  
Khondoker Billah ◽  
Qasim Adegbite ◽  
Hatim O. Sharif ◽  
Samer Dessouky ◽  
Lauren Simcic
Keyword(s):  
High Risk ◽  
Traffic Safety ◽  
Traffic Control ◽  
Injury Severity ◽  
San Antonio ◽  
Binary Logistic Regression ◽  
Bivariate Analysis ◽  
Crash Severity ◽  
Contributing Factors ◽  
Late Night

An understanding of the contributing factors to severe intersection crashes is crucial for developing countermeasures to reduce crash numbers and severity at high-risk crash locations. This study examined the variables affecting crash incidence and crash severity at intersections in San Antonio over a five-year period (2013–2017) and identified high-risk locations based on crash frequency and injury severity using data from the Texas Crash Record and Information System database. Bivariate analysis and binary logistic regression, along with respective odds ratios, were used to identify the most significant variables contributing to severe intersection crashes by quantifying their association with crash severity. Intersection crashes were predominantly clustered in the downtown area with relatively less severe crashes. Males and older drivers, weekend driving, nighttime driving, dark lighting conditions, grade and hillcrest road alignment, and crosswalk, divider and marked lanes used as traffic control significantly increased crash severity risk at intersections. Prioritizing resource allocation to high-risk intersections, separating bicycle lanes and sidewalks from the roadway, improving lighting facilities, increasing law enforcement activity during the late night hours of weekend, and introducing roundabouts at intersections with stops and signals as traffic controls are recommended countermeasures.

Integrated Modeling Approach for Non-Motorized Mode Trips and Fatal Crashes in the Framework of Transportation Safety Planning

2018 ◽  
Vol 2672 (32) ◽  
pp. 49-60 ◽  
Author(s):  
Jaeyoung Lee ◽  
Mohamed Abdel-Aty ◽  
Qing Cai ◽  
Ling Wang ◽  
Helai Huang
Keyword(s):  
Traffic Safety ◽  
Prediction Models ◽  
Census Bureau ◽  
Integrated Modeling ◽  
Transportation Safety ◽  
Safety Planning ◽  
Contributing Factors ◽  
Modeling Approach ◽  
Exposure Variable ◽  
Safety Models

In recent decades, considerable efforts have been made to incorporate traffic safety into long-term transportation plans (LTTPs), a process which is often termed transportation safety planning (TSP). Although some researchers have attempted to integrate transportation plans and safety by adopting transportation planning data (e.g., trip generation) for estimating traffic crash frequency at the macroscopic level, no studies have attempted to develop trip and safety models in one structure simultaneously. A Bayesian integrated multivariate modeling approach is suggested for estimating trips and crashes of non-motorized modes (i.e., walking and cycling). American Housing Survey (AHS) data were collected from the U.S. Census Bureau and were used for the proposed approach. In the first part of the proposed model, the probabilities of choosing walking and cycling modes were estimated, and the estimated probabilities were converted to trips by multiplying the number of sampled households. In the second part, the estimated trips were fed into crash prediction models (or safety performance functions) as an exposure variable. The modeling result revealed many contributing factors for pedestrian/bicycle trips and crashes. Possible shared unobserved features between pedestrian and bicycle trips, and between pedestrian and bicycle crashes, were accounted for by adopting a multivariate structure. In addition, it was found that the crash models with the estimated exposures outperform those with the observed exposures. It is expected that the integrated modeling approach for trips and crashes in this study will provide great insights into the future directions of TSP.

Machine Learning Approach to Short-Term Traffic Congestion Prediction in a Connected Environment

2018 ◽  
Vol 2672 (45) ◽  
pp. 185-195 ◽  
Author(s):  
Amr Elfar ◽  
Alireza Talebpour ◽  
Hani S. Mahmassani
Keyword(s):  
Machine Learning ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Historical Data ◽  
Machine Learning Techniques ◽  
Short Term ◽  
Congested Traffic ◽  
Vehicle Trajectories ◽  
Congestion Prediction ◽  
The Individual

Traffic congestion is a complex phenomenon triggered by a combination of multiple interacting factors. One of the main factors is the disturbances caused by individual vehicles, which cannot be identified in aggregate traffic data. Advances in vehicle wireless communications present new opportunities to measure traffic perturbations at the individual vehicle level. The key question is whether it is possible to find the relationship between these perturbations and shockwave formation and utilize this knowledge to improve the identification and prediction of congestion formation. Accordingly, this paper explores the use of three machine learning techniques, logistic regression, random forests, and neural networks, for short-term traffic congestion prediction using vehicle trajectories available through connected vehicles technology. Vehicle trajectories provided by the Next Generation SIMulation (NGSIM) program were utilized in this study. Two types of predictive models were developed in this study: (1) offline models which are calibrated based on historical data and are updated (re-trained) whenever significant changes occur in the system, such as changes/updates to the infrastructure, and (2) online models which are calibrated using historical data and updated regularly using real-time information on prevailing traffic conditions obtained through V2V/V2I communications. Results show that the accuracy of the models built in this study to predict the congested traffic state can reach 97%. The models presented can be used in various potential applications including improving road safety by warning drivers of upcoming traffic slowdowns and improving mobility through integration with traffic control systems.

The Application of Traffic Conflict Technique as a Road Safety Evaluation Method: A Case Study of Hasselt Intersection

2016 ◽  
Vol 845 ◽  
pp. 394-403 ◽  
Author(s):  
Fardzanela Suwarto ◽  
Kami Hari Basuki
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Evaluation Method ◽  
Prediction Models ◽  
Safety Evaluation ◽  
Road User ◽  
The Road ◽  
Traffic Conflict ◽  
Accident Data

The majority of traffic safety evaluations in the world generally have been conducted by colecting historical accident data. The data will then being analyzed using risk prediction models or before-after study that required an exact and reliable data. Meanwhile, the availability of accident data is rare where the rest actually consist of near-crashes and abnormal behaviour, which is mostly underreporting and lack of detail concerning the behavioural and situational of the event. Therefore, traffic conflict technique, is needed to assess traffic safety as another approach rather than waiting for several years until a number of accidents happen in a certain area. Hence the aim of this study is to make a safety evaluation towards a specific intersection in Hasselt Belgium using traffic conflict technique. The observation of conflict (near crashes) was carried out in intersection of Manteliusstraat – Dorpsstraat – Thonissenlaan in the Hasselt, Belgium. In order to differentiate slight conflict and serious conflict, the TA-value (Time of accident) was defined based on the estimated speed of the road user and estimated distance from the road user when conflict occurred. From the observation, it was found that the conflicts between car and pedestrian were the most frequent conflict, with 50% of the total conflict, and that the conflict between car with car and the conflict between car with cyclist were high in terms of severity level based on the TA-value. By taking these into consideration, it can be concluded that unsafe crossing for pedestrian and cyclist, different speed, and peak hour traffic were the causes of conflict. Therefore, it was concluded that traffic conflict technique can be used to assess and measure traffic safety in a certain road segment. Furthermore, in term of safety, the Manteliusstraat – Dorpsstraat – Thonissenlaan intersection should be modified with some alternatives; signalized intersection with toucan crossing and traffic control devices improvement

New walls to keep the bad out: populism and the totalitarian psyche

2019 ◽  
Vol 1 (2) ◽  
pp. 120-130
Author(s):  
Coline Covington
Keyword(s):  
Cold War ◽  
Balance Of Power ◽  
Berlin Wall ◽  
Group Solidarity ◽  
Freedom Of Movement ◽  
Psychological Understanding ◽  
Psychic Development ◽  
The World ◽  
The Individual ◽  
The Cold War

The Berlin Wall came down on 9 November 1989 and marked the end of the Cold War. As old antagonisms thawed a new landscape emerged of unification and tolerance. Censorship was no longer the principal means of ensuring group solidarity. The crumbling bricks brought not only freedom of movement but freedom of thought. Now, nearly thirty years later, globalisation has created a new balance of power, disrupting borders and economies across the world. The groups that thought they were in power no longer have much of a say and are anxious about their future. As protest grows, we are beginning to see that the old antagonisms have not disappeared but are, in fact, resurfacing. This article will start by looking at the dissembling of a marriage in which the wall that had peacefully maintained coexistence disintegrates and leads to a psychic development that uncannily mirrors that of populism today. The individual vignette leads to a broader psychological understanding of the totalitarian dynamic that underlies populism and threatens once again to imprison us within its walls.

Virginia Woolf and Being-in-the-world

2017 ◽  
Author(s):  
Emma Simone
Keyword(s):  
Virginia Woolf ◽  
Historical Context ◽  
The Political ◽  
Cartesian Dualism ◽  
Self And Other ◽  
The World ◽  
Binary Oppositions ◽  
The Individual ◽  
The Relationship ◽  
Existential Perspective

Virginia Woolf and Being-in-the-world: A Heideggerian Study explores Woolf’s treatment of the relationship between self and world from a phenomenological-existential perspective. This study presents a timely and compelling interpretation of Virginia Woolf’s textual treatment of the relationship between self and world from the perspective of the philosophy of Martin Heidegger. Drawing on Woolf’s novels, essays, reviews, letters, diary entries, short stories, and memoirs, the book explores the political and the ontological, as the individual’s connection to the world comes to be defined by an involvement and engagement that is always already situated within a particular physical, societal, and historical context. Emma Simone argues that at the heart of what it means to be an individual making his or her way in the world, the perspectives of Woolf and Heidegger are founded upon certain shared concerns, including the sustained critique of Cartesian dualism, particularly the resultant binary oppositions of subject and object, and self and Other; the understanding that the individual is a temporal being; an emphasis upon intersubjective relations insofar as Being-in-the-world is defined by Being-with-Others; and a consistent emphasis upon average everydayness as both determinative and representative of the individual’s relationship to and with the world.

“Utopia First!” A Machiavellian Conception of Solidarity in More's Utopia

Moreana ◽  
2018 ◽  
Vol 55 (Number 209) (1) ◽  
pp. 79-93
Author(s):  
Marie-Claire Phélippeau
Keyword(s):  
At Risk ◽  
Human Beings ◽  
Farm Work ◽  
The World ◽  
Social Difficulties ◽  
The Republic ◽  
The Individual ◽  
Democratic Elections ◽  
Communal Organization

This paper shows how solidarity is one of the founding principles in Thomas More's Utopia (1516). In the fictional republic of Utopia described in Book II, solidarity has a political and a moral function. The principle is at the center of the communal organization of Utopian society, exemplified in a number of practices such as the sharing of farm work, the management of surplus crops, or the democratic elections of the governor and the priests. Not only does solidarity benefit the individual Utopian, but it is a prerequisite to ensure the prosperity of the island of Utopia and its moral preeminence over its neighboring countries. However, a limit to this principle is drawn when the republic of Utopia faces specific social difficulties, and also deals with the rest of the world. In order for the principle of solidarity to function perfectly, it is necessary to apply it exclusively within the island or the republic would be at risk. War is not out of the question then, and compassion does not apply to all human beings. This conception of solidarity, summed up as “Utopia first!,” could be dubbed a Machiavellian strategy, devised to ensure the durability of the republic. We will show how some of the recommendations of Realpolitik made by Machiavelli in The Prince (1532) correspond to the Utopian policy enforced to protect their commonwealth.

Drowning in negativism, self-hate, doubt, madness: Linguistic insights into Sylvia Plath’s experience of depression

2015 ◽  
Vol 11 (1) ◽  
pp. 41-54 ◽  
Author(s):  
Zsófia Demjén
Keyword(s):  
Lived Experience ◽  
Medical Humanities ◽  
Sylvia Plath ◽  
Individual Experience ◽  
Qualitative And Quantitative ◽  
The World ◽  
The Individual ◽  
Linguistic Methods ◽  
Linguistic Approach

This paper demonstrates how a range of linguistic methods can be harnessed in pursuit of a deeper understanding of the ‘lived experience’ of psychological disorders. It argues that such methods should be applied more in medical contexts, especially in medical humanities. Key extracts from The Unabridged Journals of Sylvia Plath are examined, as a case study of the experience of depression. Combinations of qualitative and quantitative linguistic methods, and inter- and intra-textual comparisons are used to consider distinctive patterns in the use of metaphor, personal pronouns and (the semantics of) verbs, as well as other relevant aspects of language. Qualitative techniques provide in-depth insights, while quantitative corpus methods make the analyses more robust and ensure the breadth necessary to gain insights into the individual experience. Depression emerges as a highly complex and sometimes potentially contradictory experience for Plath, involving both a sense of apathy and inner turmoil. It involves a sense of a split self, trapped in a state that one cannot overcome, and intense self-focus, a turning in on oneself and a view of the world that is both more negative and more polarized than the norm. It is argued that a linguistic approach is useful beyond this specific case.

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