1 00:00:01,920 --> 00:00:07,800 Speaker 1: Welcome to brain Stuff, a production of iHeart Radio. Hey 2 00:00:07,840 --> 00:00:11,400 Speaker 1: brain Stuff, Lauren Vogelbaum here. If you've ever been in 3 00:00:11,400 --> 00:00:14,800 Speaker 1: a motor vehicle in a city or suburb, you've likely 4 00:00:14,880 --> 00:00:18,279 Speaker 1: experienced the frustration of being stuck in a long line 5 00:00:18,320 --> 00:00:21,479 Speaker 1: of vehicles at a traffic light. You wait for what 6 00:00:21,640 --> 00:00:24,720 Speaker 1: seems like forever until the red turns to green, but 7 00:00:24,840 --> 00:00:27,720 Speaker 1: then only crawl forward a few feet before the light 8 00:00:27,800 --> 00:00:31,480 Speaker 1: turns yellow and red again. Once it's finally your turn 9 00:00:31,520 --> 00:00:34,199 Speaker 1: to get across the intersection, you may only get to 10 00:00:34,360 --> 00:00:37,640 Speaker 1: roll a few hundred yards before you're confronted by another 11 00:00:37,760 --> 00:00:41,559 Speaker 1: light about to turn red. Even in the year, a 12 00:00:41,640 --> 00:00:45,320 Speaker 1: year in which the pandemic shutdowns reduced traffic, drivers in 13 00:00:45,360 --> 00:00:49,440 Speaker 1: the United States experienced slowdowns that added twenty seven hours 14 00:00:49,560 --> 00:00:52,839 Speaker 1: to their commuting time and increased their fuel costs by 15 00:00:52,840 --> 00:00:56,880 Speaker 1: six hundred and five dollars per driver. And that was 16 00:00:57,040 --> 00:01:01,440 Speaker 1: down considerably from non pandemic years of slowdowns added fifty 17 00:01:01,440 --> 00:01:05,679 Speaker 1: four hours to commutes in twenty nine. With streets and 18 00:01:05,720 --> 00:01:10,080 Speaker 1: highways returning to normal traffic density and gasoline costs soaring, 19 00:01:10,560 --> 00:01:14,640 Speaker 1: this year's numbers are likely to be much higher. There's 20 00:01:14,800 --> 00:01:19,000 Speaker 1: got to be a better way. Unfortunately, engineering visionaries have 21 00:01:19,120 --> 00:01:21,800 Speaker 1: been thinking the same thing for years and have developed 22 00:01:21,800 --> 00:01:27,399 Speaker 1: a potential answer, smart traffic lights. These monitor incoming traffic 23 00:01:27,480 --> 00:01:31,400 Speaker 1: and continuously adjust their timing to keep vehicles flowing as 24 00:01:31,400 --> 00:01:35,200 Speaker 1: smoothly as possible, communicating with other lights along routes, and 25 00:01:35,280 --> 00:01:40,480 Speaker 1: working together to prevent log jams from developing. Numerous companies, 26 00:01:40,560 --> 00:01:44,080 Speaker 1: large and small, are pushing smart traffic light technology ahead. 27 00:01:45,520 --> 00:01:48,120 Speaker 1: For the article this episode is based on how Stuff Works, 28 00:01:48,120 --> 00:01:51,920 Speaker 1: spoke with Carnegie Mellon University research professor Stephen Smith, who 29 00:01:51,960 --> 00:01:54,640 Speaker 1: began working on the problem back in two thousand nine. 30 00:01:54,880 --> 00:01:57,640 Speaker 1: That's when a local Pittsburgh business leader approached him with 31 00:01:57,720 --> 00:02:01,120 Speaker 1: concerns that worsening grid luck might interfere with the city's 32 00:02:01,120 --> 00:02:04,400 Speaker 1: efforts to transform itself from a smokestack city into a 33 00:02:04,480 --> 00:02:08,160 Speaker 1: technology and healthcare hub. A Smith, a faculty member at 34 00:02:08,200 --> 00:02:11,520 Speaker 1: Carnegie Mellon's Robotics Institute who studies the use of artificial 35 00:02:11,600 --> 00:02:16,520 Speaker 1: intelligence to coordinate large systems in transportation, manufacturing, and other fields, 36 00:02:16,919 --> 00:02:21,320 Speaker 1: developed traffic signals equipped with individual computers and software that 37 00:02:21,440 --> 00:02:25,720 Speaker 1: have AI capabilities, which can use cameras, radar, or inductive 38 00:02:25,720 --> 00:02:29,160 Speaker 1: loop detectors in the pavement to spot approaching vehicles and 39 00:02:29,200 --> 00:02:33,359 Speaker 1: adjust the signals timing. When Smith installed a few experimental 40 00:02:33,400 --> 00:02:37,519 Speaker 1: prototypes at intersections in East Liberty, a heavily congested area 41 00:02:37,560 --> 00:02:42,480 Speaker 1: on Pittsburgh's East End, he immediately got results. Drivers average 42 00:02:42,480 --> 00:02:46,640 Speaker 1: travel time to get to their destinations decreased by and 43 00:02:46,680 --> 00:02:51,240 Speaker 1: they spent forty percent less time idling and traffic jams. 44 00:02:51,240 --> 00:02:55,240 Speaker 1: Since then, Smith's company, called rapid Flow Technologies, has installed 45 00:02:55,320 --> 00:02:59,400 Speaker 1: its smart traffic management technology in twenty two North American cities. 46 00:03:00,440 --> 00:03:03,799 Speaker 1: Smith said, we generate the timing plans in real time, 47 00:03:04,280 --> 00:03:07,239 Speaker 1: and so we watch the traffic that's approaching the intersection, 48 00:03:07,760 --> 00:03:10,640 Speaker 1: and then in real time we generate a signal timing 49 00:03:10,639 --> 00:03:14,280 Speaker 1: plan for moving that traffic through the intersection, and so 50 00:03:14,400 --> 00:03:18,720 Speaker 1: we're actually scheduling the actual traffic on the road. A 51 00:03:18,840 --> 00:03:21,440 Speaker 1: Once an intersection builds up a timing plan and starts 52 00:03:21,440 --> 00:03:24,160 Speaker 1: to execute it, it will send to its downstream neighbors, 53 00:03:24,200 --> 00:03:26,760 Speaker 1: for example, what traffic it expects to be sending their 54 00:03:26,800 --> 00:03:31,400 Speaker 1: way according to its schedule. Smart traffic lights like these 55 00:03:31,400 --> 00:03:34,760 Speaker 1: could become even more powerful as increasing numbers of cars 56 00:03:34,760 --> 00:03:38,800 Speaker 1: and trucks employ connected vehicle technology, which could enable them 57 00:03:38,800 --> 00:03:41,960 Speaker 1: to communicate both with one another and with infrastructure such 58 00:03:41,960 --> 00:03:46,640 Speaker 1: as traffic signals. Instead of smart traffic lights relying upon 59 00:03:46,800 --> 00:03:49,960 Speaker 1: spotting vehicles as they come in range of cameras, for example, 60 00:03:50,320 --> 00:03:53,240 Speaker 1: they could make decisions based on messages that they're receiving 61 00:03:53,280 --> 00:03:56,920 Speaker 1: from the cars about their location and direction, or even 62 00:03:56,960 --> 00:04:02,120 Speaker 1: their entire planned route. In advance. Smart traffic signals may 63 00:04:02,200 --> 00:04:04,760 Speaker 1: even make it safer for cars and trucks to share 64 00:04:04,800 --> 00:04:08,840 Speaker 1: streets with cyclists, pedestrians, and people using mobility devices such 65 00:04:08,880 --> 00:04:12,080 Speaker 1: as scooters. A smart traffic light could have the ability 66 00:04:12,120 --> 00:04:15,440 Speaker 1: to detect pedestrians at street corners and calculate how much 67 00:04:15,480 --> 00:04:19,080 Speaker 1: time they'll need to get across an intersection safely. Smith said, 68 00:04:19,400 --> 00:04:21,719 Speaker 1: if you're moving with a walker or something like that, 69 00:04:21,960 --> 00:04:24,120 Speaker 1: it knows how long you need to get across the street, 70 00:04:24,520 --> 00:04:27,480 Speaker 1: so it communicates that to the signal in advance, so 71 00:04:27,520 --> 00:04:29,600 Speaker 1: that when you do get the green light, you'll be 72 00:04:29,640 --> 00:04:33,640 Speaker 1: assured to get enough time to cross. Meanwhile, an Israeli 73 00:04:33,680 --> 00:04:38,000 Speaker 1: company called No Traffic takes a somewhat different approach. Instead 74 00:04:38,000 --> 00:04:41,960 Speaker 1: of decentralized smart traffic signals, it provides cities with plug 75 00:04:42,000 --> 00:04:45,479 Speaker 1: and play Internet of Things sensors for intersections, which include 76 00:04:45,520 --> 00:04:48,719 Speaker 1: cameras and radar, and combines them with a cloud based 77 00:04:48,839 --> 00:04:53,160 Speaker 1: virtual management center. The effect is the same though, autonomous 78 00:04:53,200 --> 00:04:56,560 Speaker 1: optimization of traffic flow for everyone on the road, reducing 79 00:04:56,560 --> 00:05:00,480 Speaker 1: emissions and making roads safer. How stuff Works also spoke 80 00:05:00,560 --> 00:05:04,279 Speaker 1: via email with Vera Resnik, the company's vice president of marketing. 81 00:05:04,960 --> 00:05:08,520 Speaker 1: He said, we demonstrated how our platform can potentially reduce 82 00:05:08,600 --> 00:05:11,280 Speaker 1: the number of drivers driving through a red light by 83 00:05:11,279 --> 00:05:16,159 Speaker 1: an average of almost also by eliminating time wasted and 84 00:05:16,200 --> 00:05:19,680 Speaker 1: clogged traffic, smart traffic lights could play a significant role 85 00:05:19,720 --> 00:05:24,599 Speaker 1: in combating climate change. Study by Juniper Research found that 86 00:05:24,640 --> 00:05:28,240 Speaker 1: smart traffic management systems could lower global emissions by two 87 00:05:28,760 --> 00:05:34,000 Speaker 1: twenty six million tons by However, although the idea of 88 00:05:34,040 --> 00:05:38,000 Speaker 1: adaptive signal control systems is gaining traction in the United States, 89 00:05:38,400 --> 00:05:43,000 Speaker 1: it's still far from being universally accepted and implemented. Part 90 00:05:43,040 --> 00:05:45,720 Speaker 1: of the reason maybe the cost. According to the U 91 00:05:45,839 --> 00:05:49,480 Speaker 1: S Department of Transportation, the cost of deploying certain intelligent 92 00:05:49,520 --> 00:05:54,600 Speaker 1: transportation systems technologies is upward of twenty thousand dollars per intersection, 93 00:05:55,160 --> 00:05:58,160 Speaker 1: and the numbers for these systems vary widely depending on 94 00:05:58,200 --> 00:06:01,880 Speaker 1: location and any intersect and remodels or upgrades that might 95 00:06:01,920 --> 00:06:05,680 Speaker 1: be necessary. As Smith thinks it will take a couple 96 00:06:05,680 --> 00:06:08,520 Speaker 1: of decades for this technology to become the norm, and 97 00:06:08,720 --> 00:06:11,520 Speaker 1: even that could be a generous estimate and depending on 98 00:06:11,600 --> 00:06:15,320 Speaker 1: how companies and municipalities alike are able and willing to 99 00:06:15,360 --> 00:06:24,279 Speaker 1: adopt the technology and cooperate with each other. Today's episode 100 00:06:24,320 --> 00:06:27,240 Speaker 1: is based on the article going Nowhere Fast Smart traffic 101 00:06:27,320 --> 00:06:29,800 Speaker 1: lights can help ease gridlock on how stuff works dot com, 102 00:06:29,839 --> 00:06:32,640 Speaker 1: written by Patrick J. Keiger. Brain Stuff is production of 103 00:06:32,680 --> 00:06:35,000 Speaker 1: I Heart Radio in partnership with how stuff works dot Com, 104 00:06:35,080 --> 00:06:38,040 Speaker 1: and it's produced by Tyler Klang. For more podcasts from 105 00:06:38,040 --> 00:06:41,160 Speaker 1: my heart Radio, visit the iHeart Radio app, Apple Podcasts, 106 00:06:41,240 --> 00:06:43,080 Speaker 1: or wherever you listen into your favorite shows.