VISUAL ANALYTICS PROJECT
(OPIM 5501)

Project Report on FUTURE OF CARS

Team 3 Project 2 Members:
Ankit Agrawal
Mownika Chalichama
Phanindra Musunuri
Long Phan

1. INTRODUCTION AND DATA
Future of Cars visualization project shows the story to predict the future generation of cars. Ten years from now, in 2025, cars will be different, the drivers will be different, the market will be different, and the producers will certainly be different. The team believe that these changes will affect billions of people – from soccer moms to automotive executives, from taxi drivers to investment bankers.
The data tells us that consumers are demanding greener, safer, more convenient and affordable cars. Most of these new consumers will come from emerging markets like China and India. Consequently, new trends will force car producers to modernize their supply chain, become more competitive and make lighter cars. Moreover, technology will play a huge part in changing the overall automotive landscape. Self-driving cars, car-cab services (Uber, Lyft, etc.), car pooling and the Internet of Cars all seemed like science-fiction will not remain not so long ago. Now many of them have become reality.
There were a lot of data available online since countless research is being carried on cars. Major data source was data.gov for example, the website had an entire section on transportation data. Unsurprisingly, cleaning the data took a lot of time. Most of the data came from many different sources and each dataset required a few hours to clean. Rest all other data are searched & linked accordingly in the story.
There are many parts of the database which are collected. It was divided into four parts. These are the internet technology which will affect the future of cars, the convenience and safety of the passenger, the emission control and weight of the future cars and then lastly the competition, supply chain demand and price in the market.
The first set of data contains deals with the population growth estimates, the GDP of the country to know about the emerging markets and the emission control in that region. GDP plays the vital role to make sure the type of car major population looking for. Then next data set gives idea about the traffic situation, convenience, demand of the car. It has been a general trend people look for compact car where there is a traffic problem or huge congestion in the city specially in market like India. The next data set deals with the safety of the car. The number of road accidents, the type of accident, the control measures like speed, vision, better control that are required to make the future generation car more safe. Then the last set deals with the innovative technology like self-driving car & effect of internet on the commute by car. Self-driving car testing reports are available which shows that the commercial utilization of the self-driving technique will soon become reality to the public. App based services has now ease the transport of the people by car as it is very easy and convenient to book a cab rather than rely on the rental car which required lot of paper work and time consuming. Carpooling is now an emerging trend & more people trying to choose the carpooling option which saves a lot of money for the two parties. 2. PROCESS
Initially the team organized several meetings to make the shape & skeleton of the project. Once the skeleton is prepared, the team distributed the responsibilities and then have review meetings periodically. The team met once a week to check on the progress of each team member, and to share knowledge and experience with each other. As the data is obtained from different sources, it takes lot of time to compile and reshape the data to be used properly in tableau. Then start creating the worksheet. There were many calculations tried while preparing the tableau parameter and filter. Many of them were discarded which did not give good visualization. But many calculation gives good insights specially the rental car data set. The data shows that there is an increase in the revenue of rental car. But after reshaping it was found that the per car revenue on the rental car is declining since three years. This is due to the fact of internet and app based car services like Uber, Lfyt. 3. CHALLENGES
When the team finished with individual worksheets, the team proceeded to make the dashboards, and finally put all the dashboards together to create a story book. Creating the story book did not take much time since the team had a clear idea of the story and what wanted to tell. However, it took long hours to polish every minute detail – any simple modification could potentially result in rearranging the entire story book. The major challenges face is the resolution of the story book. The dashboard resolution was getting changed when it was added in the story board. Fortunately, all team members got along well and were on the same page. Hence, the final stage of the project went smoothly.
Overall, the team was glad to work on this project. Visualization with Tableau is a fun, exciting, and effective way to tell stories. Team had learnt many new tools and tricks within Tableau from each other. Now, the team members are confident that these skills and experience will benefit greatly in professional career.

References: 1. www.data.gov 2. http://www.goldmansachs.com/our-thinking/technology-driving-innovation/cars-2025/ 3. http://www.autorentalnews.com/content/research-statistics.aspx 4. https://www.google.com/selfdrivingcar/ 5. http://statisticstimes.com/economy/countries-by-projected-gdp.php 6. http://www.nrcan.gc.ca/energy/efficiency/transportation/cars-light-trucks/buying/16755 7. Many pics from google images & many other facts by google search