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"content": "\u003cp>If you're braving the \"friendly,\" crowded skies this holiday season, brace yourself for the inevitably glacial pace of the boarding process.\u003c/p>\n\u003cp>The boarding methods of most commercial airlines are not quite the gold standard of efficiency.\u003c/p>\n\u003cp>So, what's the fastest way to get in your seat? I mean, come on, we're not exactly talking rocket science here.\u003c/p>\n\u003cp>As it turns out, it's actually a fairly complicated puzzle to decipher: a intricate enough problem to tantalize the likes of an astrophysicist.\u003c/p>\n\u003cfigure id=\"attachment_15443\" class=\"wp-caption alignnone\" style=\"max-width: 889px\">\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2015/01/vox_boarding.png\">\u003cimg class=\"wp-image-15443 size-full\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2015/01/vox_boarding.png\" alt=\"Courtesy of Vox\" width=\"889\" height=\"579\" srcset=\"https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding.png 889w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-400x261.png 400w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-800x521.png 800w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-768x500.png 768w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-320x208.png 320w\" sizes=\"(max-width: 889px) 100vw, 889px\">\u003c/a>\u003cfigcaption class=\"wp-caption-text\">Courtesy of Vox.com\u003c/figcaption>\u003c/figure>\n\u003cp>After enduring one too many maddeningly slow boarding experiences, \u003ca href=\"https://www.unlv.edu/news/article/new-faces-jason-steffen\" target=\"_blank\" rel=\"noopener\">Jason Steffen \u003c/a>a professor of physics and astronomy at the University of Nevada Las Vegas, began digging into the unexpectedly complicated mechanics of efficiently ushering passengers onto planes.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>In 2008, Steffen created a computer simulation to evaluate existing boarding methods and ultimately design what he claims is the most efficient option for getting restless passengers into their seats. The results were published several years ago in the Journal of Air Transport Management (\u003ca href=\"http://home.fnal.gov/~jsteffen/airplanes.html\" target=\"_blank\" rel=\"noopener\">summarized here\u003c/a>).\u003c/p>\n\u003cp>In his research, Steffen identified the two most common factors responsible for slowing the boarding process to a painful crawl:\u003c/p>\n\u003cp>1. Passengers typically have to wait in the aisle for those ahead of them to stow luggage.\u003c/p>\n\u003cp>2. Those already seated in aisle or middle seats have to get up and move back into the aisle to let passengers behind them take the seats closer to the window.\u003c/p>\n\u003cp>In fact, the most routine boarding process -- from back to front -- is actually the slowest of them all, Steffen's argues, It's even less efficient than boarding a plane in a completely random order.\u003c/p>\n\u003cp>Steffen claims that his proposed method, which minimizes the former issue and eliminates the latter, could significantly reduce boarding times, thus cutting down on overall door-to-door flight lengths, and ultimately saving airlines hundreds of millions of dollars a year.\u003c/p>\n\u003cp>The news site \u003ca href=\"http://www.vox.com/2014/4/25/5647696/the-way-we-board-airplanes-makes-absolutely-no-sense\" target=\"_blank\" rel=\"noopener\">Vox \u003c/a>recently explored this question and created the above video analyzing various standard boarding methods. The videos below show individual simulations of these different boarding processes, listed from worst (slowest) to best (fastest).\u003c/p>\n\u003cp>Think you have a better idea? Let us know in the comment section below.\u003c/p>\n\u003cp>Here's to safe, relatively painless and highly efficient travels!\u003c/p>\n\u003ch4>5. The dreaded back-to-front method\u003c/h4>\n\u003cp>https://youtu.be/CsRfFhrNtho\u003c/p>\n\u003ch4>4. The random method\u003c/h4>\n\u003cp>https://youtu.be/QJMuXZrV3gY\u003c/p>\n\u003ch4>3. The outside-in method\u003c/h4>\n\u003cp>https://youtu.be/cHFWuP37Ha4\u003c/p>\n\u003ch4>2. The best current option: Southwest's self-selection method\u003c/h4>\n\u003cp>No video simulation for this one, but the basic gist is that Southwest doesn't assign seats. Instead, passengers get on the plane in the order they check in and can sit in which ever seats are available. This method has proven to be the most efficient one currently used because passengers have more freedom to sit where they want and spend less time waiting in the aisle.\u003c/p>\n\u003ch4>1. And finally, the winner (in theory, at least): The Steffen method\u003c/h4>\n\u003cp>Steffen's method is closest to the the outside-in method, with one major difference: rather than having all window seat passengers board first, it creates a choreographed boarding sequence that eliminates any waiting in the aisle by having passengers board in a staggered format. Take a look:\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>https://youtu.be/cHFWuP37Ha4\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>If you're braving the \"friendly,\" crowded skies this holiday season, brace yourself for the inevitably glacial pace of the boarding process.\u003c/p>\n\u003cp>The boarding methods of most commercial airlines are not quite the gold standard of efficiency.\u003c/p>\n\u003cp>So, what's the fastest way to get in your seat? I mean, come on, we're not exactly talking rocket science here.\u003c/p>\n\u003cp>As it turns out, it's actually a fairly complicated puzzle to decipher: a intricate enough problem to tantalize the likes of an astrophysicist.\u003c/p>\n\u003cfigure id=\"attachment_15443\" class=\"wp-caption alignnone\" style=\"max-width: 889px\">\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2015/01/vox_boarding.png\">\u003cimg class=\"wp-image-15443 size-full\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2015/01/vox_boarding.png\" alt=\"Courtesy of Vox\" width=\"889\" height=\"579\" srcset=\"https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding.png 889w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-400x261.png 400w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-800x521.png 800w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-768x500.png 768w, https://ww2.kqed.org/app/uploads/sites/26/2015/01/vox_boarding-320x208.png 320w\" sizes=\"(max-width: 889px) 100vw, 889px\">\u003c/a>\u003cfigcaption class=\"wp-caption-text\">Courtesy of Vox.com\u003c/figcaption>\u003c/figure>\n\u003cp>After enduring one too many maddeningly slow boarding experiences, \u003ca href=\"https://www.unlv.edu/news/article/new-faces-jason-steffen\" target=\"_blank\" rel=\"noopener\">Jason Steffen \u003c/a>a professor of physics and astronomy at the University of Nevada Las Vegas, began digging into the unexpectedly complicated mechanics of efficiently ushering passengers onto planes.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>In 2008, Steffen created a computer simulation to evaluate existing boarding methods and ultimately design what he claims is the most efficient option for getting restless passengers into their seats. The results were published several years ago in the Journal of Air Transport Management (\u003ca href=\"http://home.fnal.gov/~jsteffen/airplanes.html\" target=\"_blank\" rel=\"noopener\">summarized here\u003c/a>).\u003c/p>\n\u003cp>In his research, Steffen identified the two most common factors responsible for slowing the boarding process to a painful crawl:\u003c/p>\n\u003cp>1. Passengers typically have to wait in the aisle for those ahead of them to stow luggage.\u003c/p>\n\u003cp>2. Those already seated in aisle or middle seats have to get up and move back into the aisle to let passengers behind them take the seats closer to the window.\u003c/p>\n\u003cp>In fact, the most routine boarding process -- from back to front -- is actually the slowest of them all, Steffen's argues, It's even less efficient than boarding a plane in a completely random order.\u003c/p>\n\u003cp>Steffen claims that his proposed method, which minimizes the former issue and eliminates the latter, could significantly reduce boarding times, thus cutting down on overall door-to-door flight lengths, and ultimately saving airlines hundreds of millions of dollars a year.\u003c/p>\n\u003cp>The news site \u003ca href=\"http://www.vox.com/2014/4/25/5647696/the-way-we-board-airplanes-makes-absolutely-no-sense\" target=\"_blank\" rel=\"noopener\">Vox \u003c/a>recently explored this question and created the above video analyzing various standard boarding methods. The videos below show individual simulations of these different boarding processes, listed from worst (slowest) to best (fastest).\u003c/p>\n\u003cp>Think you have a better idea? Let us know in the comment section below.\u003c/p>\n\u003cp>Here's to safe, relatively painless and highly efficient travels!\u003c/p>\n\u003ch4>5. The dreaded back-to-front method\u003c/h4>\u003c/p>\u003cp>\u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutube'>\n \u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutubeInside'>\n \u003ciframe\n loading='lazy'\n class='utils-parseShortcode-shortcodes-__youtubeShortcode__youtubePlayer'\n type='text/html'\n src='//www.youtube.com/embed/CsRfFhrNtho'\n title='//www.youtube.com/embed/CsRfFhrNtho'\n allowfullscreen='true'\n style='border:0;'>\u003c/iframe>\n \u003c/span>\n \u003c/span>\u003c/p>\u003cp>\u003ch4>4. The random method\u003c/h4>\u003c/p>\u003cp>\u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutube'>\n \u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutubeInside'>\n \u003ciframe\n loading='lazy'\n class='utils-parseShortcode-shortcodes-__youtubeShortcode__youtubePlayer'\n type='text/html'\n src='//www.youtube.com/embed/QJMuXZrV3gY'\n title='//www.youtube.com/embed/QJMuXZrV3gY'\n allowfullscreen='true'\n style='border:0;'>\u003c/iframe>\n \u003c/span>\n \u003c/span>\u003c/p>\u003cp>\u003ch4>3. The outside-in method\u003c/h4>\u003c/p>\u003cp>\u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutube'>\n \u003cspan class='utils-parseShortcode-shortcodes-__youtubeShortcode__embedYoutubeInside'>\n \u003ciframe\n loading='lazy'\n class='utils-parseShortcode-shortcodes-__youtubeShortcode__youtubePlayer'\n type='text/html'\n src='//www.youtube.com/embed/cHFWuP37Ha4'\n title='//www.youtube.com/embed/cHFWuP37Ha4'\n allowfullscreen='true'\n style='border:0;'>\u003c/iframe>\n \u003c/span>\n \u003c/span>\u003c/p>\u003cp>\u003ch4>2. The best current option: Southwest's self-selection method\u003c/h4>\n\u003cp>No video simulation for this one, but the basic gist is that Southwest doesn't assign seats. Instead, passengers get on the plane in the order they check in and can sit in which ever seats are available. This method has proven to be the most efficient one currently used because passengers have more freedom to sit where they want and spend less time waiting in the aisle.\u003c/p>\n\u003ch4>1. And finally, the winner (in theory, at least): The Steffen method\u003c/h4>\n\u003cp>Steffen's method is closest to the the outside-in method, with one major difference: rather than having all window seat passengers board first, it creates a choreographed boarding sequence that eliminates any waiting in the aisle by having passengers board in a staggered format. 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"content": "\u003cp>\u003cem>Select a car from the bunch, click \"Hit the Brakes\" to slow it down and watch the traffic wave form. The red bars show deceleration levels (braking) and the green, acceleration (speeding up). Mouse over any car to see its velocity and acceleration at any given point during the wave (assuming all the cars are in the same single lane).\u003c/em>\u003c/p>\n\u003cdiv align=\"center\">\n\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/waves/road.html\" width=\"800\" height=\"750\" frameborder=\"0\" scrolling=\"no\" class=\"iframe-class\">\u003c/iframe>\n\u003c/div>\n\u003cp>Who doesn't love sitting in traffic?\u003c/p>\n\u003cp>Especially when there's no apparent reason for it: no crashes, no tolls, no flaming mattresses.\u003c/p>\n\u003cp>Just a sudden, infuriating slowdown that forces you to slam on the brakes, spill coffee all over yourself and slow to a glacial crawl, usually when you're already late for something important -- a job interview, for instance.\u003c/p>\n\u003cp>And then, when all hope seems lost, the congestion breaks as seemingly spontaneously as it began. And you're on your way again ... for a good 2 minutes before the whole thing repeats itself.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>Welcome to the world of traffic waves, a phenomenon that's been exasperating drivers since cars started rolling off Ford's assembly line a century ago.\u003c!--more-->\u003c/p>\n\u003cp>On average, Americans spend upwards of 40 hours a year stuck in traffic, according to Texas A&M's \u003ca href=\"http://mobility.tamu.edu\" target=\"_blank\" rel=\"noopener noreferrer\">annual mobility study\u003c/a>. That figure rises to more than 60 hours in some of the most congested metro areas, like Los Angeles, Washington D.C. and -- yup, you guessed it -- San Francisco. And, contrary to popular belief, much of this congestion is NOT because of major impediments, but simply a result of annoying driving habits that arise when there are just too many cars on the road.\u003c/p>\n\u003cp>The simplest explanation for why traffic waves happen is that we drivers have relatively slow reaction times: if the car in front of you suddenly slows down, it'll likely take you a second or so to hit the brakes. The slower your reaction time, the more you have to brake to keep a safe distance. Same deal for the car behind you, which has to brake even harder than you did in order to slow down that much faster. And so on down the road, like a domino-like effect.\u003c/p>\n\u003cp>To illustrate this concept, Lewis Lehe, a civil engineer and programmer, created the above visualization.\u003c/p>\n\u003cp>The equation he uses is known as the \u003ca href=\"http://en.wikipedia.org/wiki/Intelligent_driver_model\">Intelligent Driver Model\u003c/a>, which was first proposed in 2000 by researchers at Germany's Dresden University of Technology (the designers created \u003ca href=\"http://www.traffic-simulation.de\" target=\"_blank\" rel=\"noopener noreferrer\">this\u003c/a> Java applet demonstration).\u003c/p>\n\u003cp>The formal equations that explain these traffic patterns in terms of individual behavior are called \u003ca href=\"http://en.wikipedia.org/wiki/Microscopic_traffic_flow_model#Car-following_models\">car following models\u003c/a>. They were first developed by researchers at General Motors in the 1950s. This is the simplest such formula:\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/11/lambda-formula.jpg\">\u003cimg class=\"size-medium wp-image-10529 alignnone\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/11/lambda-formula-300x56.jpg\" alt=\"lambda formula\" width=\"300\" height=\"56\">\u003c/a>\u003c/p>\n\u003cp>Here, \u003cem>a \u003c/em>is the car's acceleration, Δ\u003cem>v\u003c/em> is the difference in velocity compared with the car behind it,\u003cem> T \u003c/em>is reaction time and ƛ is some constant that researchers estimate from data. The equation says, \"At time\u003cem> t\u003c/em>, you accelerate at a rate proportional to the difference in speed between your car and the speed of the car you're following, but with a gap of \u003cem>T\u003c/em> seconds.\"\u003c/p>\n\u003cp>Put simply, if you're going faster than the car in front of you, then you slow down. And if you're going slower, you speed up.\u003c/p>\n\u003cp>This equation produces the graph below. At the 10-second mark, the grey car slows down, and the cars that brake later have to slow down to subsequently lower minimum speeds. Each line shows the history of the speed of a different car. Drag the slider to graphically see a traffic wave unfold. Note how the cars at the bottom of the chart get closer together with time, as speeds even out.\u003cbr>\n\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"http://lewis500.github.io/waves/chart.html\" width=\"1000\" height=\"450\" frameborder=\"0\" scrolling=\"no\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003cp>Over time, congestion researchers have developed more complex models of traffic behavior that include realistic conditions and incorporate additional traffic data. For example, our \"simple\" equation assumes that the car in front of you will impact your behavior even if it's a mile away. Some of the first improvements to the equation added terms for the size of that gap and the understanding that cars can slow down much faster than they can speed up. You can read more about the history of car-following models \u003ca href=\"http://ocw.mit.edu/courses/civil-and-environmental-engineering/1-225j-transportation-flow-systems-fall-2002/lecture-notes/carfollowinga.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">here\u003c/a>.\u003c/p>\n\u003chr>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>Lewis Lehe is a PhD student in Civil Engineering at the UC Berkeley, where he researches electronic road tolling and runs the \u003ca href=\"http://vudlab.com\"> Visualizing Urban Data idealab\u003c/a>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cem>Select a car from the bunch, click \"Hit the Brakes\" to slow it down and watch the traffic wave form. The red bars show deceleration levels (braking) and the green, acceleration (speeding up). Mouse over any car to see its velocity and acceleration at any given point during the wave (assuming all the cars are in the same single lane).\u003c/em>\u003c/p>\n\u003cdiv align=\"center\">\n\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/waves/road.html\" width=\"800\" height=\"750\" frameborder=\"0\" scrolling=\"no\" class=\"iframe-class\">\u003c/iframe>\n\u003c/div>\n\u003cp>Who doesn't love sitting in traffic?\u003c/p>\n\u003cp>Especially when there's no apparent reason for it: no crashes, no tolls, no flaming mattresses.\u003c/p>\n\u003cp>Just a sudden, infuriating slowdown that forces you to slam on the brakes, spill coffee all over yourself and slow to a glacial crawl, usually when you're already late for something important -- a job interview, for instance.\u003c/p>\n\u003cp>And then, when all hope seems lost, the congestion breaks as seemingly spontaneously as it began. And you're on your way again ... for a good 2 minutes before the whole thing repeats itself.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>Welcome to the world of traffic waves, a phenomenon that's been exasperating drivers since cars started rolling off Ford's assembly line a century ago.\u003c!--more-->\u003c/p>\n\u003cp>On average, Americans spend upwards of 40 hours a year stuck in traffic, according to Texas A&M's \u003ca href=\"http://mobility.tamu.edu\" target=\"_blank\" rel=\"noopener noreferrer\">annual mobility study\u003c/a>. That figure rises to more than 60 hours in some of the most congested metro areas, like Los Angeles, Washington D.C. and -- yup, you guessed it -- San Francisco. And, contrary to popular belief, much of this congestion is NOT because of major impediments, but simply a result of annoying driving habits that arise when there are just too many cars on the road.\u003c/p>\n\u003cp>The simplest explanation for why traffic waves happen is that we drivers have relatively slow reaction times: if the car in front of you suddenly slows down, it'll likely take you a second or so to hit the brakes. The slower your reaction time, the more you have to brake to keep a safe distance. Same deal for the car behind you, which has to brake even harder than you did in order to slow down that much faster. And so on down the road, like a domino-like effect.\u003c/p>\n\u003cp>To illustrate this concept, Lewis Lehe, a civil engineer and programmer, created the above visualization.\u003c/p>\n\u003cp>The equation he uses is known as the \u003ca href=\"http://en.wikipedia.org/wiki/Intelligent_driver_model\">Intelligent Driver Model\u003c/a>, which was first proposed in 2000 by researchers at Germany's Dresden University of Technology (the designers created \u003ca href=\"http://www.traffic-simulation.de\" target=\"_blank\" rel=\"noopener noreferrer\">this\u003c/a> Java applet demonstration).\u003c/p>\n\u003cp>The formal equations that explain these traffic patterns in terms of individual behavior are called \u003ca href=\"http://en.wikipedia.org/wiki/Microscopic_traffic_flow_model#Car-following_models\">car following models\u003c/a>. They were first developed by researchers at General Motors in the 1950s. This is the simplest such formula:\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/11/lambda-formula.jpg\">\u003cimg class=\"size-medium wp-image-10529 alignnone\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/11/lambda-formula-300x56.jpg\" alt=\"lambda formula\" width=\"300\" height=\"56\">\u003c/a>\u003c/p>\n\u003cp>Here, \u003cem>a \u003c/em>is the car's acceleration, Δ\u003cem>v\u003c/em> is the difference in velocity compared with the car behind it,\u003cem> T \u003c/em>is reaction time and ƛ is some constant that researchers estimate from data. The equation says, \"At time\u003cem> t\u003c/em>, you accelerate at a rate proportional to the difference in speed between your car and the speed of the car you're following, but with a gap of \u003cem>T\u003c/em> seconds.\"\u003c/p>\n\u003cp>Put simply, if you're going faster than the car in front of you, then you slow down. And if you're going slower, you speed up.\u003c/p>\n\u003cp>This equation produces the graph below. At the 10-second mark, the grey car slows down, and the cars that brake later have to slow down to subsequently lower minimum speeds. Each line shows the history of the speed of a different car. Drag the slider to graphically see a traffic wave unfold. Note how the cars at the bottom of the chart get closer together with time, as speeds even out.\u003cbr>\n\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"http://lewis500.github.io/waves/chart.html\" width=\"1000\" height=\"450\" frameborder=\"0\" scrolling=\"no\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003cp>Over time, congestion researchers have developed more complex models of traffic behavior that include realistic conditions and incorporate additional traffic data. For example, our \"simple\" equation assumes that the car in front of you will impact your behavior even if it's a mile away. Some of the first improvements to the equation added terms for the size of that gap and the understanding that cars can slow down much faster than they can speed up. You can read more about the history of car-following models \u003ca href=\"http://ocw.mit.edu/courses/civil-and-environmental-engineering/1-225j-transportation-flow-systems-fall-2002/lecture-notes/carfollowinga.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">here\u003c/a>.\u003c/p>\n\u003chr>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>Lewis Lehe is a PhD student in Civil Engineering at the UC Berkeley, where he researches electronic road tolling and runs the \u003ca href=\"http://vudlab.com\"> Visualizing Urban Data idealab\u003c/a>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"disqusTitle": "Forget Miles per Gallon! The Case for Switching to Gallons per Mile",
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"content": "\u003cp>To begin, a quiz:\u003c/p>\n\u003cp>Bob and Jane Smith have two vehicles: One is a \u003cstrong>15 MPG \u003c/strong>(miles per gallon)\u003cstrong> \u003c/strong>pickup truck that Bob uses for his construction job. The other is a \u003cstrong>28 MPG\u003c/strong> sedan that his wife Jane uses for her work commute. The couple wants to upgrade to something more fuel efficient, but only has the cash to replace one of their vehicles. Assuming each drives \u003ca href=\"http://www.fhwa.dot.gov/ohim/onh00/bar8.htm\">the average American\u003c/a> distance of about 13,500 miles per year, which of the following options would save the most gas?\u003c/p>\n\u003cp> \u003c/p>\n\u003cp>\u003cstrong>a. Replacing the 28 MPG sedan with a 38 MPG \u003c/strong>\u003cstrong>compact\u003c/strong>\u003c/p>\n\u003cp>\u003cem>OR\u003c/em>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cstrong>b. Replacing the 15 MPG truck with a 20 MPG truck\u003c!--more-->\u003c/strong>\u003c/p>\n\u003cp>The first option seems to make the most sense. But -- as you may have predicted -- it's not the right answer. In fact, choice b saves nearly twice as much gas (even though the new truck still requires way more gas than the old car). Here's the math to prove it:\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/fornula1test.jpg\">\u003cimg class=\"alignnone wp-image-10981\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/fornula1test-640x145.jpg\" alt=\"fornula1(test\" width=\"500\" height=\"100\">\u003c/a>\u003c/p>\n\u003cp>If you guessed wrong, you're not alone. In a 2008 \u003ca href=\"http://nsmn1.uh.edu/dgraur/niv/theMPGIllusion.pdf\" target=\"_blank\">study\u003c/a> published in Science Magazine, Richard P. Larrick and Jack B. Soll of Duke University suggest \"there is a systematic misconception in judging fuel efficiency when it is expressed as miles per gallon.\" Namely, most drivers think gas usage falls linearly (in a straight line) as MPG increases. But the actual relationship between the two is curved: one additional MPG has significantly greater impact in the gas consumption of an inefficient vehicle than it does in a more efficient one. Essentially, it's the law of diminishing returns. The authors call this the \"\u003ca href=\"http://www.mpgillusion.com/\">MPG Illusion\u003c/a>,\" and note that encouraging gas guzzlers to upgrade to slightly more efficient vehicles actually has a much more positive impact than is commonly perceived.\u003c/p>\n\u003cp>\"The environment would benefit most if all (car-driving) consumers chased highly efficient cars that get 40 MPG, not 14, and incentives should be tied to achieving such efficiency,\" the authors write. But, they argue, the impact of encouraging people who drive gas guzzling SUVs that get a measly 12 MPG to switch to ones that get a slightly less measly 14 MPG is certainly not negligible. \"The 2 MPG improvement is actually a significant one in terms of reduction in gas consumption.\"\u003c/p>\n\u003cp>That logic is illustrated here:\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart1.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003cp>It's true that 15 to 20 MPG is a bigger \u003cem>percentage\u003c/em> jump than going from 28 to 38 MPG, But even when comparing proportions, the same logic holds true. The chart below shows the savings from a 50 percent boost in MPG. Note that the higher the MPG, the less gas a 50 percent boost saves.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart2.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003ch4>The case for switching to gallons per mile\u003c/h4>\n\u003cp>MPG, the study's authors argue, is a somewhat misleading measurement of fuel efficiency. Because it's a fraction with miles in the numerator and gallons in the denominator, it's a convenient measure for calculating answers in terms of miles. For example: \"If my car has 5 gallons left in the tank, and it gets 30 miles per gallon, how many miles can I go without stopping for gas?\"\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form2a2.jpg\">\u003cimg class=\"size-medium wp-image-11060 alignnone\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form2a2-300x82.jpg\" alt=\"form2a\" width=\"300\" height=\"82\">\u003c/a>\u003c/p>\n\u003cp>In most cases, however, it's more useful to express your calculations in terms of gallons, since it is gallons, after all -- not miles -- that matter to your budget and the environment (especially considering that burning 100 gallons \u003ca href=\"http://www.eia.gov/tools/faqs/faq.cfm?id=307&t=11\">emits one ton\u003c/a> of CO2). Therefore, it makes sense to flip the fraction, converting it to gallons per mile (GPM):\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form3a1.jpg\">\u003cimg class=\"alignnone wp-image-11041\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form3a1-300x71.jpg\" alt=\"form3a\" width=\"320\" height=\"87\">\u003c/a>\u003c/p>\n\u003cp>But because the small numbers can get confusing, it's easier to instead express this as gallons per hundred miles (GPHM):\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form4a.jpg\">\u003cimg class=\"alignnone size-full wp-image-11001\" title=\"\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form4a.jpg\" alt=\"form4a\" width=\"418\" height=\"85\" srcset=\"https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a.jpg 418w, https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a-400x81.jpg 400w, https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a-320x65.jpg 320w\" sizes=\"(max-width: 418px) 100vw, 418px\">\u003c/a>\u003c/p>\n\u003cp>When you put gallons in the numerator, comparing fuel usage is easy. The chart below shows how a 1 GPHM drop \u003cem>always\u003c/em> saves the same amount of gasoline regardless of the vehicle's fuel efficiency.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart3.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003ch4>Policy implications\u003c/h4>\n\u003cp>So does this mean it's fine to buy a new gas guzzler as long as it's just a teeny bit more efficient than your old one?\u003c/p>\n\u003cp>Just the opposite. The higher the fuel efficiency of your replacement vehicle, the more gas you save. That's why Larrick and Soll argue that \"removing the most inefficient vehicles is where policy and popular opinion should be focused.\" Ideally, all drivers of gas guzzlers would make a giant leap and swap their SUVs for very efficient small hybrids ... or bicycles. But that's a pretty unlikely possibility. So, given the restraints of reality, it's more important to encourage drivers of gas guzzlers to switch to normal cars, than it is to nudge drivers of normal cars to switch to hybrids.\u003c/p>\n\u003cp>The federal government has already taken steps in this direction: the Office of Information and Regulatory Affairs this year came out with \"gallons per 100 miles\" stickers, which they're are encouraging car dealerships to start using them in showrooms.\u003c/p>\n\u003cp>\u003ca href=\"http://www.fueleconomy.gov/feg/label/learn-more-gasoline-label.shtml\">\u003cimg src=\"http://lewis500.github.io/miles/styles/gaslabel.jpg\" alt=\"\" width=\"500px\">\u003c/a>\u003c/p>\n\u003chr>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>Lewis Lehe is a PhD student in Civil Engineering at the UC Berkeley, where he researches electronic road tolling and runs the \u003ca href=\"http://vudlab.com\"> Visualizing Urban Data idealab\u003c/a>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>To begin, a quiz:\u003c/p>\n\u003cp>Bob and Jane Smith have two vehicles: One is a \u003cstrong>15 MPG \u003c/strong>(miles per gallon)\u003cstrong> \u003c/strong>pickup truck that Bob uses for his construction job. The other is a \u003cstrong>28 MPG\u003c/strong> sedan that his wife Jane uses for her work commute. The couple wants to upgrade to something more fuel efficient, but only has the cash to replace one of their vehicles. Assuming each drives \u003ca href=\"http://www.fhwa.dot.gov/ohim/onh00/bar8.htm\">the average American\u003c/a> distance of about 13,500 miles per year, which of the following options would save the most gas?\u003c/p>\n\u003cp> \u003c/p>\n\u003cp>\u003cstrong>a. Replacing the 28 MPG sedan with a 38 MPG \u003c/strong>\u003cstrong>compact\u003c/strong>\u003c/p>\n\u003cp>\u003cem>OR\u003c/em>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cstrong>b. Replacing the 15 MPG truck with a 20 MPG truck\u003c!--more-->\u003c/strong>\u003c/p>\n\u003cp>The first option seems to make the most sense. But -- as you may have predicted -- it's not the right answer. In fact, choice b saves nearly twice as much gas (even though the new truck still requires way more gas than the old car). Here's the math to prove it:\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/fornula1test.jpg\">\u003cimg class=\"alignnone wp-image-10981\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/fornula1test-640x145.jpg\" alt=\"fornula1(test\" width=\"500\" height=\"100\">\u003c/a>\u003c/p>\n\u003cp>If you guessed wrong, you're not alone. In a 2008 \u003ca href=\"http://nsmn1.uh.edu/dgraur/niv/theMPGIllusion.pdf\" target=\"_blank\">study\u003c/a> published in Science Magazine, Richard P. Larrick and Jack B. Soll of Duke University suggest \"there is a systematic misconception in judging fuel efficiency when it is expressed as miles per gallon.\" Namely, most drivers think gas usage falls linearly (in a straight line) as MPG increases. But the actual relationship between the two is curved: one additional MPG has significantly greater impact in the gas consumption of an inefficient vehicle than it does in a more efficient one. Essentially, it's the law of diminishing returns. The authors call this the \"\u003ca href=\"http://www.mpgillusion.com/\">MPG Illusion\u003c/a>,\" and note that encouraging gas guzzlers to upgrade to slightly more efficient vehicles actually has a much more positive impact than is commonly perceived.\u003c/p>\n\u003cp>\"The environment would benefit most if all (car-driving) consumers chased highly efficient cars that get 40 MPG, not 14, and incentives should be tied to achieving such efficiency,\" the authors write. But, they argue, the impact of encouraging people who drive gas guzzling SUVs that get a measly 12 MPG to switch to ones that get a slightly less measly 14 MPG is certainly not negligible. \"The 2 MPG improvement is actually a significant one in terms of reduction in gas consumption.\"\u003c/p>\n\u003cp>That logic is illustrated here:\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart1.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003cp>It's true that 15 to 20 MPG is a bigger \u003cem>percentage\u003c/em> jump than going from 28 to 38 MPG, But even when comparing proportions, the same logic holds true. The chart below shows the savings from a 50 percent boost in MPG. Note that the higher the MPG, the less gas a 50 percent boost saves.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart2.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003ch4>The case for switching to gallons per mile\u003c/h4>\n\u003cp>MPG, the study's authors argue, is a somewhat misleading measurement of fuel efficiency. Because it's a fraction with miles in the numerator and gallons in the denominator, it's a convenient measure for calculating answers in terms of miles. For example: \"If my car has 5 gallons left in the tank, and it gets 30 miles per gallon, how many miles can I go without stopping for gas?\"\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form2a2.jpg\">\u003cimg class=\"size-medium wp-image-11060 alignnone\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form2a2-300x82.jpg\" alt=\"form2a\" width=\"300\" height=\"82\">\u003c/a>\u003c/p>\n\u003cp>In most cases, however, it's more useful to express your calculations in terms of gallons, since it is gallons, after all -- not miles -- that matter to your budget and the environment (especially considering that burning 100 gallons \u003ca href=\"http://www.eia.gov/tools/faqs/faq.cfm?id=307&t=11\">emits one ton\u003c/a> of CO2). Therefore, it makes sense to flip the fraction, converting it to gallons per mile (GPM):\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form3a1.jpg\">\u003cimg class=\"alignnone wp-image-11041\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form3a1-300x71.jpg\" alt=\"form3a\" width=\"320\" height=\"87\">\u003c/a>\u003c/p>\n\u003cp>But because the small numbers can get confusing, it's easier to instead express this as gallons per hundred miles (GPHM):\u003c/p>\n\u003cp>\u003ca href=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form4a.jpg\">\u003cimg class=\"alignnone size-full wp-image-11001\" title=\"\" src=\"http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2013/12/form4a.jpg\" alt=\"form4a\" width=\"418\" height=\"85\" srcset=\"https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a.jpg 418w, https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a-400x81.jpg 400w, https://ww2.kqed.org/app/uploads/sites/26/2013/12/form4a-320x65.jpg 320w\" sizes=\"(max-width: 418px) 100vw, 418px\">\u003c/a>\u003c/p>\n\u003cp>When you put gallons in the numerator, comparing fuel usage is easy. The chart below shows how a 1 GPHM drop \u003cem>always\u003c/em> saves the same amount of gasoline regardless of the vehicle's fuel efficiency.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe src=\"https://lewis500.github.io/miles/linechart3.html\" frameborder=\"0\" scrolling=\"no\" width=\"800\" height=\"540\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003ch4>Policy implications\u003c/h4>\n\u003cp>So does this mean it's fine to buy a new gas guzzler as long as it's just a teeny bit more efficient than your old one?\u003c/p>\n\u003cp>Just the opposite. The higher the fuel efficiency of your replacement vehicle, the more gas you save. That's why Larrick and Soll argue that \"removing the most inefficient vehicles is where policy and popular opinion should be focused.\" Ideally, all drivers of gas guzzlers would make a giant leap and swap their SUVs for very efficient small hybrids ... or bicycles. But that's a pretty unlikely possibility. So, given the restraints of reality, it's more important to encourage drivers of gas guzzlers to switch to normal cars, than it is to nudge drivers of normal cars to switch to hybrids.\u003c/p>\n\u003cp>The federal government has already taken steps in this direction: the Office of Information and Regulatory Affairs this year came out with \"gallons per 100 miles\" stickers, which they're are encouraging car dealerships to start using them in showrooms.\u003c/p>\n\u003cp>\u003ca href=\"http://www.fueleconomy.gov/feg/label/learn-more-gasoline-label.shtml\">\u003cimg src=\"http://lewis500.github.io/miles/styles/gaslabel.jpg\" alt=\"\" width=\"500px\">\u003c/a>\u003c/p>\n\u003chr>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>Lewis Lehe is a PhD student in Civil Engineering at the UC Berkeley, where he researches electronic road tolling and runs the \u003ca href=\"http://vudlab.com\"> Visualizing Urban Data idealab\u003c/a>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"info": "Possible is hosted by entrepreneur Reid Hoffman and writer Aria Finger. Together in Possible, Hoffman and Finger lead enlightening discussions about building a brighter collective future. The show features interviews with visionary guests like Trevor Noah, Sam Altman and Janette Sadik-Khan. Possible paints an optimistic portrait of the world we can create through science, policy, business, art and our shared humanity. It asks: What if everything goes right for once? How can we get there? Each episode also includes a short fiction story generated by advanced AI GPT-4, serving as a thought-provoking springboard to speculate how humanity could leverage technology for good.",
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