Race for Fuel Efficiency

Team members: Paul Choi, Miguel Garrido, Lawrence Sun, Kimberly Yu

The data say that different car models have different fuel economy levels, and the driving speed also affects how fuel efficient the car is. We want to tell this story because fuel efficiency is determined by so much more than just the type of car you drive. Most people are aware that certain cars (e.g. Prius) are more fuel-efficient than other cars (e.g. Ford). However, not everyone is aware that when you drive a car at a speed faster than its optimal speed, the car’s gas mileage decreases, more greenhouse gases are produced, and you end up wasting gas and money. Our audience is car buyers and drivers, and our goals are to teach participants about fuel efficiency for different cars at various speeds, and help them make better driving choices.

Our participatory data game is a digital multiplayer game where the goal is to reach the destination in the least amount of time while spending the least amount of money. Players are given 5 gallons of gas per round, and each gallon costs $3. Each round, a player chooses 1) a car model from four options (or keeping their current car) and 2) speed (ranging from 30 mph to 90 mph). After each round, the player’s balance is updated, and the player’s car animates across the screen to reflect the distance traveled and its speed. For each subsequent round, the player can choose to keep the car or choose a different car. A timer keeps track of how long it takes the player to travel 1000 miles, and the amount of money the player has spent is displayed. At the end of the game, a weighted total score is displayed. Choosing the type of car and the speed while attempting to reach a destination within a time limit helps the player discover and learn that the type of car and the speed both affect fuel efficiency, and there is a tradeoff between time and money spent.

We based our data game off of the US Fuel Economy measurements and the MPG for Speed Calculator. Given the MPG values for vehicle models from the 2017 Fuel Economy guide, the MPG for Speed calculator helped us calculate the cost, distance driven, and driving time for each round in the game. The higher the MPG, the more fuel-efficient a car is, and the less greenhouse gas emissions the car will produce. However, if a car is driven faster than its optimal speed, the car becomes less efficient because the air resistance increases. We envision this game being incorporated into websites for car manufacturers, especially those that produce cars with high fuel efficiency, or at car dealerships. Car manufacturers can use this game to playfully inform customers about how fuel-efficient their car is compared to other cars. Car dealers can use this game to help customers make better decisions as well as make waiting time more exciting and beneficial.

Kimberly’s Activity Log of Digital Data Created/Captured on 2-12-17

Time Type of Data Created Type of Data Captured Description
10:30 AM Time Phone alarm rang. Woke up, turned off alarm, and set a new alarm for 11:00 AM
11:00 AM Pictures, Emails Phone alarm rang. Checked email. Browsed Pinterest app on phone and saved pins
11:20 AM Form Submitted Add/Drop form to Registrar
11:30 AM Text Sent messages through Facebook Messenger
11:40 AM Email, Text Video, Links Sent an email that contained text, a video from YouTube, and links to websites
11:45 AM Numbers Went to McCormick’s dining hall. Swiped my ID card and returned a greenbox (logged in techcash.mit.edu)
12:30 PM Text Text Took notes in a Google Doc on the reading assignment for 6.813
1:00 PM Text Sent messages through Slack
1:15 PM Time, Numbers Ran on a treadmill (kept track of distance and time)
2:30 PM Event information Saved a Facebook event and added it to my iPhone Calendar
2:40 PM Text Sent messages through Slack
3:00 PM Text Text, Numbers Examined results/scores from an ultimate frisbee tournament. Visited teams’ Twitter accounts and filled out scouting reports in Google Docs
3:30 PM Monetary transactions Completed a transaction request on the Venmo app
4:00 PM Text Sent messages through LINE
4:45 PM Monetary amounts Monetary amounts Filled out CSS Profile (entered numbers) using data from forms. Paid a fee to submit it (recorded in credit card bill)
5:30 PM Numbers Went to McCormick’s dining hall. Swiped my ID card (logged in techcash.mit.edu)
6:00 PM Text Submitted a Google Form
6:30 PM Text IP addresses, domain names, servers Worked on homework assignment for 6.033. Used athena.dialup.mit.edu and terminal commands for DNS lookups. Submitted assignment on Gradescope
7:00 PM Text Data Worked on this data activity log
7:30 PM Text Text Took notes in a Google Doc on reading assignments for CMS.631
8:30 PM Text Submitted a room reservation form
8:45 PM Text Sent messages through Slack
9:00 PM Videos Watched YouTube videos (recorded in History)
10:00 PM Text Worked on this data activity log

The Story of California’s Drought

I’m from Southern California, and one of the biggest issues in the state recently has been the drought. This series of 259 drought maps shows the drought level in the state of California from December 2011 to February 2017.

At the top of the visualization is a legend assigning a color to different drought levels:


The drought maps are then displayed chronologically in a grid, left to right and top to bottom.

The sheer amount of red on the maps in early 2014 helps viewers easily understand how dire the situation was and why Governor Jerry Brown declared a State of Emergency in January 2014:

Early 2014

Scrolling to the year 2015, California is mostly dark red, indicating a level of “Exceptional Drought”. The shrinking of dark red areas in the spring 2016 maps show that the drought is improving. And then in early 2017, only a small part of California is dark red and in extreme drought:

Early 2017

This visualization clearly tells the story of California’s drought. The yellow-orange-red color scheme connotes fire and heat, which is strongly correlated to drought, and the color gradient for different drought levels reflects light/dark color connotations in society. The viewer can easily identify the year corresponding to the maps, and a date pops up when the viewer hovers over a particular map. Being able to instantaneously see maps from different times really helped me understand when the drought got worse, how bad it was, how long California was in “Extreme Drought” for, and how impactful the storms last month were.

Although the viewer may get lost in the rows of red/orange/yellow sock-like shapes, I think the designer’s choice to lay out the maps really serves its purpose of guiding the viewer through the story of California’s drought. If the designer had used a single map and a scrollbar that, when dragged, alters the map to reflect the drought over time, some parts of the story might have been lost in the time-lapse because the viewer would only be able to make immediate comparisons. This data presentation relies on color connotations and a series of snapshots to enable Californians, people interested in climate change, and others curious about the drought to better understand how drought levels changed in California in the past 4 years.