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ICT112 Creative Problem Solving with Programming Assignment - University of the Sunshine Coast, Australia

Task - Generated Web Site for Aussie Road Fatalities

Your task in this assignment is to write a Python program that generates an informative web site about Australian Road Fatalities over the last 30 years, showing summary statistics about the crash types, speed limits, vehicle types, times of day, and the ages and genders of the people who died. This will allow viewers to get insights into the data, and to identify trends that are changing over time.

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Answer - AUSSIE ROAD FATALITIES WEBSITE REPORT WRITEUP

Introduction

The main objective of me in this assignment is to write a python program that generates an informative web site about Australian Road Fatalities over the last 30 years, showing summary statistics about the crash types, speed limits, vehicle types,times of day, and the ages and genders of the people who died. This will allow viewers to get insights into the data, and to identify trends that are changing over time.

Project File Structure

a) HTML Files

  • index.html - for the index page which all other web page links to navigate to.

fatalitiesperyear.html - which maintains details about Fatalities per year, and how this rate is changing over time

  • fatalitiesperstate.html - which maintains analysis about fatalities per australian state

fatalitiesatdifferentimesofday.html - which maintains fatalities at different times of the day(hour)

  • impact.html - The impact of different types of crash (single vehicle, multiple vehicle, pedestrian, etc.);
  • crashcontributionbyvehicle.html -The contribution of crashes involving buses and trucks, compared to other kinds of crashes;
  • impactspeedlimitzones.html - The impact of different speed limit zones on road fatalities;

impactroaduseroles.html - The impact of different road-user roles (driver; passenger; motor cyclist; cyclist, pedestrian, etc.) on road fatalities;

  • impactgender.html - The impact of gender on road fatalities - note that the data shows the gender of the deceased person, not necessarily of the driver;
  • impactage.html - The impact of age (of the deceased) on road fatalities.

b) Jupyter Notebook - Python

This notebook contains python program to run.The Python Program takes the input data in the form of CSV File.The data in the input CSV file is read and processed and inbuilt libraries such as pandas(used for data manipulation), numpy(used for scientific computation),matplotlib(for plotting graphs and charts),etc are used to generate summary statistics and display results in the form of graphs and charts and show the trends.

c) Images folder - img

This folder contains the images of visualizations done on input data including graphs,trends and charts

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Dataset Description

Australian Road Fatalities over the last 30 years, showing summary statistics about the crash types, speed limits, vehicle types, times of day, and the ages and genders of the people who died. This will allow viewers to get insights into the data, and to identify trends that are changing over time.

Here what I have done is I have used python libraries such as numpy, pandas, matplotlib for statistical analysis of the input data and generated the graphs which I just embedded inside the HTML pages.

Analysis and Inference

The key factors that resulted in fatalities are:

1) Heavy Truck involvement- Heavy truck causes more damage as compared to normal vehicles. A range of factors that are important is the "time it takes to respond to unknown road conditions" because of uncertainties in weight.

2) State - analysis of state level data depicts that number of fatalities is fairly proportional to the size of the state population, meaning that higher the population in a state, it is more likely that number of cars would be higher, increasing chances of car crashes. The Northern Territory with the lowest population figures (1%) had about 3.5% of fatalities in Australia between the period 2008-2017. ACT showed the lowest number of fatalities during the same period (0.9%) with the second lowest population. The highest populated state -NSW (32% of the total population) showed the highest number of fatalities (29%).

3) Gender wise analysis showed that majority of road fatalities affected males in Australia (figures suggest about 72$% of road accidents were caused by males) between the period 2013 -2014. Cyclists, drivers and motorcyclists constituted majority of the accidents due to lack of control and risky driving behaviors. This indicated that men were more aggressive in taking risks during driving compared to women. It was also found that men between the age groups of 25 - 34 years were more likely to succumb to a road accident than those from other age groups.

4) Age group analysis reveals that under the age of 40, there has been a reduction in road fatalities. According to data, road accidents have decreased from 56% in 2008 to 44% in 2017. However such incidents among age groups 40 and higher have increases from 48% (2008) to 60% (2017). It is interesting to note that 17-25 years of age showed a 7% decrease in road accidents and people over the age of 75 showed an increase in fatalities. Such outcomes could be a result of efforts to educate younger drivers of road risks and consequences of dangerous driving.

5) Common Causes - Speeding, driver fatigues, alcohol consumption and inattention and/or distraction while driving in Australia appear to be the first four causes contributing road accidents. However, all such factors can be easily handled with proper driving senses and better control. It is expected that in the long run, automated cars may reduce car accidents. The National Road Safety Strategy in Australia has developed an action plan to educate people about possibilities of road accidents and implement stricter measures for more safety. The plan is to also have severe punishment processes for rash drivers who are inclined to rash driving increasing road risks not only for themselves but also others.

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The above chart shows that speeding contributes to the highest number of road accidents. Drivers are more likely to loose control during rash driving with higher chances of colliding with other subjects. Driving at higher speeds increases the risk of crashes because of the shorter response time the driver has to any unexpected road conditions, it also increases the severity of any collision.

Accidents are also more likely to happen when driver is fatigued or sleep deprived. Chances of such accidents increase by almost 4 times as result of fatigue or for driving during normal sleep hours of the night. Fatigue impairs a driver's judgment capacity resulting in inattention and loss of reflex power to deal with traffic situations.

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The most common types of fatalities identified in 2016 were due to tail collisions - a result of distraction and tail gating that happens when drivers does not maintain safe distances with the car or vehicle in front. An interesting observation is that collisions often occur with parked as well as an example of stationary collisions.

Miscalculations with regard to speed of passing or approaching cars often result in clashes as well. Poor visibility or inability to see also results in accidents among elderly men and women. Such accidents fall under the failure to give away category. Accidents caused during reversing a car contribute to about 11% of the cases.

Collision with an animal accounts for about 5% of the accident types and in Australia these are more prevalent with kangaroos. Kangaroo collisions alone account for about 9 to 10% of the fatalities that involve animals.

Australia bears an enormous cost in road expenses - an estimated $27 billion annually and the cost of social damages are even higher. Since 1925, Road Safety Data, Department of Infrastructure, Transport, Cities and regional Development, Australian Government, record 190,000 deaths in Australia. The number of deaths however per year has reduced from 3798 in 1970 to 1226 in 2017 despite a substantial growth in population and a three times surge in registered vehicles.

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