1 00:00:02,040 --> 00:00:07,000 Speaker 1: Welcome to brain Stuff from How Stuff Works. Pay their 2 00:00:07,040 --> 00:00:09,520 Speaker 1: brain Stuff Lauren vocal Bomb here. If you live in 3 00:00:09,640 --> 00:00:11,800 Speaker 1: or near a major city and drive a car, you 4 00:00:11,920 --> 00:00:14,720 Speaker 1: probably can't do much these days to avoid traffic, not 5 00:00:14,760 --> 00:00:18,160 Speaker 1: short of inventing your own vertical takeoff and landing technology anyways. 6 00:00:18,560 --> 00:00:21,240 Speaker 1: But what makes driving in some cities worse than others, 7 00:00:21,360 --> 00:00:25,279 Speaker 1: or one road more congested than another. Well, according to RICS, 8 00:00:25,320 --> 00:00:29,080 Speaker 1: a company that analyzes traffic and infrastructure data, it's traffic 9 00:00:29,120 --> 00:00:32,240 Speaker 1: hot spots. They define these as traffic jams that occur 10 00:00:32,320 --> 00:00:35,360 Speaker 1: at the same locations along a stretch of road. According 11 00:00:35,360 --> 00:00:38,000 Speaker 1: to Mark Burfield, the director of public relations at RICS, 12 00:00:38,120 --> 00:00:40,280 Speaker 1: key elements that define a traffic hot spot are that 13 00:00:40,320 --> 00:00:44,120 Speaker 1: they are reliable and predictable. If a commuter travels along 14 00:00:44,120 --> 00:00:46,120 Speaker 1: the same route at the same time every day and 15 00:00:46,200 --> 00:00:48,720 Speaker 1: it's always backed up at the same intersection or merge point, 16 00:00:49,080 --> 00:00:52,400 Speaker 1: that is a traffic hot spot. A recent study by Enrics, 17 00:00:52,440 --> 00:00:55,520 Speaker 1: released in September of seventeen, named and ranked the worst 18 00:00:55,560 --> 00:00:58,600 Speaker 1: traffic hot spots in the United States, one hundred and 19 00:00:58,640 --> 00:01:01,320 Speaker 1: eight thousand of them in the twenty five most congested 20 00:01:01,400 --> 00:01:05,479 Speaker 1: US cities l A, New York, Washington, d c Atlanta, 21 00:01:05,560 --> 00:01:09,319 Speaker 1: and Dallas were the top five containing the most ENRICS 22 00:01:09,360 --> 00:01:11,480 Speaker 1: conducted the study to learn more about the u S 23 00:01:11,480 --> 00:01:13,959 Speaker 1: transportation network. Is sort of a check up on the 24 00:01:13,959 --> 00:01:16,479 Speaker 1: well being of our roadways. The results will be used 25 00:01:16,480 --> 00:01:18,760 Speaker 1: to help determine the best and most efficient ways to 26 00:01:18,800 --> 00:01:22,840 Speaker 1: allocate money towards the country's transportation infrastructure. In other words, 27 00:01:22,920 --> 00:01:25,760 Speaker 1: by identifying the worst traffic hot spots and how they work, 28 00:01:26,000 --> 00:01:28,039 Speaker 1: public officials can make the upgrades that will have the 29 00:01:28,080 --> 00:01:30,839 Speaker 1: most benefit to drivers. For the purposes of the study, 30 00:01:30,959 --> 00:01:34,440 Speaker 1: ENRICS used its cloud based traffic analysis tool called Roadway 31 00:01:34,480 --> 00:01:38,119 Speaker 1: Analytics to analyze areas with frequent traffic jams and then 32 00:01:38,160 --> 00:01:40,880 Speaker 1: further narrowed those down to spots where speeds were typically 33 00:01:40,880 --> 00:01:44,920 Speaker 1: observed to drop below six of an uncongested reference speed 34 00:01:45,000 --> 00:01:47,760 Speaker 1: for at least two minutes at a time. In other words, 35 00:01:47,760 --> 00:01:50,000 Speaker 1: in a hot spot, traffical slow to less than half 36 00:01:50,040 --> 00:01:52,960 Speaker 1: its usual pace. The study also looked at the economic 37 00:01:53,000 --> 00:01:56,000 Speaker 1: costs in terms of wasted time, lost fuel, and carbon 38 00:01:56,000 --> 00:01:59,240 Speaker 1: emissions over the next decade. Using the data it gathered, 39 00:01:59,320 --> 00:02:02,920 Speaker 1: ENRICS created a global traffic scorecard, which ranks the cities 40 00:02:02,920 --> 00:02:05,640 Speaker 1: with the worst traffic and identifies the time and money 41 00:02:05,680 --> 00:02:09,720 Speaker 1: wasted in traffic congestion. The Global Traffic Scorecard rate cities 42 00:02:09,720 --> 00:02:12,400 Speaker 1: on a metric called the impact factor, which is calculated 43 00:02:12,440 --> 00:02:15,760 Speaker 1: by duration times distance times the number of traffic jams. 44 00:02:16,040 --> 00:02:18,560 Speaker 1: Here are some of the insights from the study. Though 45 00:02:18,600 --> 00:02:20,960 Speaker 1: New York has more traffic hot spots than any other 46 00:02:21,000 --> 00:02:23,679 Speaker 1: city in the study, drivers in Los Angeles pay more 47 00:02:23,840 --> 00:02:26,000 Speaker 1: due to hot spots. In l A, there were more 48 00:02:26,000 --> 00:02:28,680 Speaker 1: than one hundred and twenty eight thousand traffic jams just 49 00:02:28,880 --> 00:02:32,680 Speaker 1: during March and April. Of The worst single hot spot 50 00:02:32,720 --> 00:02:36,160 Speaker 1: in the country is near Fredericksburg, Virginia, on south at 51 00:02:36,200 --> 00:02:39,480 Speaker 1: Exit one three A, and the researchers estimate that it 52 00:02:39,480 --> 00:02:43,440 Speaker 1: will cost drivers there two point three billion dollars through 53 00:02:44,960 --> 00:02:47,239 Speaker 1: a jam in this hot spot lasts thirty three minutes 54 00:02:47,240 --> 00:02:50,200 Speaker 1: on average and stretches about six point five miles that's 55 00:02:50,200 --> 00:02:53,800 Speaker 1: about ten point four kilometers. The report concluded that across 56 00:02:53,840 --> 00:02:56,720 Speaker 1: all twenty five cities studied, traffic hot spots will cost 57 00:02:56,840 --> 00:03:00,200 Speaker 1: drivers four hundred and eighty billion dollars during the next 58 00:03:00,240 --> 00:03:04,240 Speaker 1: ten years. That's in lost time, wasted fuel, and carbon emitted. 59 00:03:04,600 --> 00:03:07,240 Speaker 1: When extrapolated across the country as a whole, the cost 60 00:03:07,280 --> 00:03:09,720 Speaker 1: of these hot spots is expected to reach two point 61 00:03:09,760 --> 00:03:14,880 Speaker 1: to trillion dollars that's trillion with a t through. Connected 62 00:03:14,919 --> 00:03:17,240 Speaker 1: cars and mobile devices are the key to this study 63 00:03:17,360 --> 00:03:20,280 Speaker 1: since they can be tracked by GPS. For example, if 64 00:03:20,280 --> 00:03:23,160 Speaker 1: you're using a smartphone to monitor traffic, researchers can tell 65 00:03:23,200 --> 00:03:25,639 Speaker 1: when and where you speed up, slow down, and come 66 00:03:25,680 --> 00:03:28,679 Speaker 1: to a stop. Though the data is anonymous, Intereacs isn't 67 00:03:28,680 --> 00:03:31,800 Speaker 1: the only company that takes advantage of our connectivity. For example, 68 00:03:31,840 --> 00:03:33,800 Speaker 1: if you use Google Maps to calculate a route and 69 00:03:33,919 --> 00:03:36,960 Speaker 1: get travel time estimates, those estimates are also courtesy of 70 00:03:37,120 --> 00:03:41,000 Speaker 1: real time GPS analytics. In addition to the tangible effects, 71 00:03:41,000 --> 00:03:43,640 Speaker 1: hot spots contribute to hard to measure problems, such as 72 00:03:43,640 --> 00:03:46,920 Speaker 1: a city's overall reputation for being a difficult or expensive 73 00:03:46,920 --> 00:03:49,840 Speaker 1: place to live, work, or visit. After all, no one 74 00:03:49,840 --> 00:03:52,000 Speaker 1: wants to go on vacation and wind up spending most 75 00:03:52,000 --> 00:03:54,640 Speaker 1: of their time in bumper to bumper traffic. That means 76 00:03:54,640 --> 00:03:57,000 Speaker 1: this data is extremely useful to cities that are trying 77 00:03:57,040 --> 00:04:00,320 Speaker 1: to improve their roads or their economics. For ex sample, 78 00:04:00,400 --> 00:04:04,200 Speaker 1: Chicago recently implemented strategies to ease congestion along I ninety, 79 00:04:04,320 --> 00:04:08,360 Speaker 1: which improved rush hour travel times by for westbound commuters. 80 00:04:08,760 --> 00:04:11,120 Speaker 1: A new lane was added on each side of the expressway. 81 00:04:11,320 --> 00:04:14,000 Speaker 1: Buses and emergency vehicles are now authorized to use the 82 00:04:14,040 --> 00:04:17,280 Speaker 1: shoulder lane, and real time traffic data, again gathered from 83 00:04:17,320 --> 00:04:21,840 Speaker 1: GPS enabled cars and mobile devices, is provided to commuters. California, 84 00:04:21,920 --> 00:04:24,480 Speaker 1: New Jersey, and Washington are among states that have recently 85 00:04:24,520 --> 00:04:28,560 Speaker 1: passed legislation to authorize funding for infrastructure upgrades. The goal, 86 00:04:28,720 --> 00:04:31,520 Speaker 1: presumably is to pave the way for smoother traffic when 87 00:04:31,720 --> 00:04:34,520 Speaker 1: or if autonomous cars become the norm, but there's no 88 00:04:34,600 --> 00:04:37,400 Speaker 1: reason that American drivers shouldn't benefit from this technology now. 89 00:04:43,440 --> 00:04:46,120 Speaker 1: This episode was written by Charis three Witt and produced 90 00:04:46,120 --> 00:04:48,359 Speaker 1: by Tristan McNeil. For more on this and lots of 91 00:04:48,360 --> 00:04:51,599 Speaker 1: other big data topics, visit our home planet, pastaff works 92 00:04:51,720 --> 00:05:03,599 Speaker 1: dot com.