1 00:00:01,520 --> 00:00:05,080 Speaker 1: Hey, Welcome to Sign Stuff, the production of iHeartRadio More. Hey, 2 00:00:05,120 --> 00:00:08,799 Speaker 1: cham and today we're answering the question what really makes 3 00:00:08,840 --> 00:00:14,800 Speaker 1: traffic so bad? It turns out it's not careless drivers 4 00:00:14,880 --> 00:00:19,880 Speaker 1: or accidents or roadwork. It's something much more surprising. We're 5 00:00:19,920 --> 00:00:22,880 Speaker 1: going to talk to two experts on traffic engineering. We're 6 00:00:22,920 --> 00:00:25,760 Speaker 1: going to step us through the history of traffic, the 7 00:00:25,800 --> 00:00:28,400 Speaker 1: real causes of it, and what we can do to 8 00:00:28,440 --> 00:00:32,479 Speaker 1: make commuting easier. To hit the accelerator because we are 9 00:00:32,640 --> 00:00:36,200 Speaker 1: clearing the road to answer the question what really makes 10 00:00:36,240 --> 00:00:48,440 Speaker 1: traffic that enjoy? Hey everyone? So, like most people, I 11 00:00:48,560 --> 00:00:51,560 Speaker 1: hate traffic. I always feel like I'm wasting my life 12 00:00:51,560 --> 00:00:54,320 Speaker 1: away sitting in my car, hitching my way across the 13 00:00:54,400 --> 00:00:57,560 Speaker 1: highway or a busy road. And the worst part is 14 00:00:57,560 --> 00:01:02,200 Speaker 1: that sometimes there's no clear reason for it. You've probably 15 00:01:02,240 --> 00:01:04,639 Speaker 1: had the experience of sitting in traffic for a while 16 00:01:04,800 --> 00:01:07,160 Speaker 1: and then all of a sudden, the traffic clears up, 17 00:01:07,240 --> 00:01:12,199 Speaker 1: and you think was it all for nothing? What's going on? Well, 18 00:01:12,280 --> 00:01:14,800 Speaker 1: to find out why that happens and to answer all 19 00:01:14,840 --> 00:01:18,080 Speaker 1: my traffic related questions, I reached out to two traffic 20 00:01:18,160 --> 00:01:22,400 Speaker 1: engineering experts. The first one is doctor Maria Lauda de 21 00:01:22,520 --> 00:01:26,160 Speaker 1: la Monice, a professor of civil and environmental engineering at 22 00:01:26,160 --> 00:01:29,280 Speaker 1: the University of California at Berkeley who works at the 23 00:01:29,680 --> 00:01:35,120 Speaker 1: no pun intended intersection between traffic science and math. She's 24 00:01:35,160 --> 00:01:37,720 Speaker 1: going to tell us why these random traffic jams happen, 25 00:01:38,080 --> 00:01:40,319 Speaker 1: but first I wanted to know a little bit about 26 00:01:40,360 --> 00:01:43,919 Speaker 1: the history of traffic. So here's my conversation with doctor 27 00:01:43,959 --> 00:01:49,600 Speaker 1: Maria Lauda de la Monique. Well, thank you, doctor de 28 00:01:49,680 --> 00:01:50,880 Speaker 1: le Monique for joining us. 29 00:01:51,080 --> 00:01:52,560 Speaker 2: Thank you, it's a pleasure to a here. 30 00:01:52,920 --> 00:01:55,400 Speaker 1: Well, I kind of have to apologize for being laid. 31 00:01:55,440 --> 00:01:57,200 Speaker 1: I was stuck in traffic. 32 00:01:57,360 --> 00:02:00,440 Speaker 3: That seems to be a problem for everybody these days, 33 00:02:01,280 --> 00:02:03,160 Speaker 3: especially in the Bay Area where we are. 34 00:02:03,960 --> 00:02:06,160 Speaker 1: Actually, I'm just kidding. I work from home, so I 35 00:02:06,240 --> 00:02:08,840 Speaker 1: haven't had to deal with traffic in a long time. 36 00:02:09,200 --> 00:02:11,880 Speaker 3: I bike to avoid the traffic. I have an electric bike. 37 00:02:11,960 --> 00:02:12,840 Speaker 3: That's my commute. 38 00:02:13,200 --> 00:02:16,400 Speaker 1: Oh that's smart. Wow, at least for now, until everybody 39 00:02:16,400 --> 00:02:19,440 Speaker 1: gets an electric bike, Yes, then there might be bike traffic. 40 00:02:19,639 --> 00:02:23,080 Speaker 3: Yeah, there's still is some places in Europe. Alreadia experience 41 00:02:23,080 --> 00:02:26,160 Speaker 3: in traffic with bikes in the Netherlands. In Paris, it 42 00:02:26,200 --> 00:02:27,160 Speaker 3: was a problem for a bit. 43 00:02:27,440 --> 00:02:29,600 Speaker 1: Oh wow, all right, we'll get into that, but I 44 00:02:29,600 --> 00:02:31,919 Speaker 1: thought way we could start by asking you to tell 45 00:02:32,000 --> 00:02:34,000 Speaker 1: us a little bit of the history of traffic, Like 46 00:02:34,040 --> 00:02:36,520 Speaker 1: when did traffic become a problem for humans. 47 00:02:36,800 --> 00:02:40,280 Speaker 3: Well, people tend to think that traffic was born, let's say, 48 00:02:40,360 --> 00:02:43,560 Speaker 3: with cars, but in reality it's something that all does 49 00:02:43,919 --> 00:02:46,720 Speaker 3: humans and cities. So we can go as far back 50 00:02:46,760 --> 00:02:50,400 Speaker 3: as ancient Rome and we still have traffic and congestion. 51 00:02:50,600 --> 00:02:54,960 Speaker 3: There's Julius sister, even have the regulatory intervention to avoid 52 00:02:55,040 --> 00:02:58,519 Speaker 3: that commercial trucks or commercial cars will go on through 53 00:02:58,520 --> 00:03:02,079 Speaker 3: the city during daytai because they would cause congestion and 54 00:03:02,120 --> 00:03:05,079 Speaker 3: they would make too much noise. So it's a very 55 00:03:05,120 --> 00:03:09,480 Speaker 3: whole problem and we're still here trying to solve it. 56 00:03:07,440 --> 00:03:14,320 Speaker 1: It's oldest Roman empire, yes, yes, And then a city 57 00:03:14,440 --> 00:03:18,000 Speaker 1: started to grow, we also started to experience more and 58 00:03:18,080 --> 00:03:20,200 Speaker 1: more traffic and different type of traffic. 59 00:03:20,520 --> 00:03:23,480 Speaker 3: Obviously, with the advent of cars is when the problem 60 00:03:23,520 --> 00:03:26,400 Speaker 3: became very big because a lot of cars that are 61 00:03:26,480 --> 00:03:29,119 Speaker 3: in the road, and also became apparent that the road 62 00:03:29,120 --> 00:03:32,839 Speaker 3: cannot be shared anymore between pedestrians and cars, right where 63 00:03:33,040 --> 00:03:36,360 Speaker 3: before it was the case everybody was in their pedestrian, bicycle, 64 00:03:36,840 --> 00:03:40,880 Speaker 3: animal power vehicles, and then since the cars were there, 65 00:03:41,120 --> 00:03:44,080 Speaker 3: and then it became a very chronic problem. And now 66 00:03:44,120 --> 00:03:46,920 Speaker 3: it became a problem of everybody going to work in 67 00:03:46,960 --> 00:03:49,440 Speaker 3: the morning at the same time and being stuck in traffic. 68 00:03:50,120 --> 00:03:51,960 Speaker 2: When we built freeways. 69 00:03:51,400 --> 00:03:54,400 Speaker 3: In the fifties, now people didn't live anymore in the city, 70 00:03:54,520 --> 00:03:56,160 Speaker 3: but now they had to take the freeway to go 71 00:03:56,240 --> 00:03:59,200 Speaker 3: to the world, and now freeway became congested. And so 72 00:03:59,800 --> 00:04:02,440 Speaker 3: it's a problem that we've been dealing for a long time. 73 00:04:02,720 --> 00:04:05,280 Speaker 1: Who it seems like any time you try to do 74 00:04:05,320 --> 00:04:07,600 Speaker 1: something about it, it still manages to come back. 75 00:04:07,880 --> 00:04:10,120 Speaker 3: Yes, because it seems the more we make it better, 76 00:04:10,200 --> 00:04:12,520 Speaker 3: the more we make people want to use the cars, 77 00:04:12,920 --> 00:04:16,240 Speaker 3: and so instead like we build more roads and then 78 00:04:16,279 --> 00:04:19,839 Speaker 3: people use more cars instead of like fixing what we 79 00:04:19,920 --> 00:04:20,480 Speaker 3: had before. 80 00:04:20,600 --> 00:04:25,160 Speaker 1: And so that seems like a very human problem, is 81 00:04:25,440 --> 00:04:27,240 Speaker 1: it is, Well, can you take me back a little 82 00:04:27,240 --> 00:04:29,360 Speaker 1: bit on the history of I guess, trying to manage 83 00:04:29,400 --> 00:04:31,960 Speaker 1: traffic or trying to deal with traffic, Like what did 84 00:04:31,960 --> 00:04:32,560 Speaker 1: the Romans do? 85 00:04:33,600 --> 00:04:36,440 Speaker 3: So before the cars, what people were trying to do, 86 00:04:36,520 --> 00:04:40,000 Speaker 3: it's mostly intervened like on the human behavior. So it's 87 00:04:40,120 --> 00:04:44,000 Speaker 3: like forbid the use of cars during daytime, right, and 88 00:04:44,080 --> 00:04:46,960 Speaker 3: so you can only go in the city during nighttime 89 00:04:47,320 --> 00:04:51,000 Speaker 3: when there was animal power vehicles. So there may be 90 00:04:51,120 --> 00:04:53,400 Speaker 3: a road becomes a one way road, or you had 91 00:04:53,400 --> 00:04:56,960 Speaker 3: a policeman at an intersection that decides, like you know, 92 00:04:57,000 --> 00:05:00,159 Speaker 3: now it's animal power flow that goes through the intersection, 93 00:05:00,320 --> 00:05:01,480 Speaker 3: then it's pedestrian. 94 00:05:01,680 --> 00:05:02,920 Speaker 2: Then as whatever else. 95 00:05:03,480 --> 00:05:07,599 Speaker 3: As technology has gotten better and better, we're also getting 96 00:05:07,760 --> 00:05:10,960 Speaker 3: better and better and managing traffic. So as car came on, 97 00:05:11,400 --> 00:05:15,040 Speaker 3: also traffic light came on because now we were suddenly 98 00:05:15,080 --> 00:05:18,359 Speaker 3: able to measure traffic. And the way to measure traffic 99 00:05:18,360 --> 00:05:20,680 Speaker 3: at the beginning of the nineteen hundred was a man 100 00:05:20,760 --> 00:05:23,279 Speaker 3: standing on the side of the road and literally counting 101 00:05:23,360 --> 00:05:24,480 Speaker 3: car as time. 102 00:05:24,279 --> 00:05:27,960 Speaker 1: Passed, right, And so graduate student, I imagine. 103 00:05:27,600 --> 00:05:30,560 Speaker 3: At the time it was actually scientists, like there's this 104 00:05:30,640 --> 00:05:33,520 Speaker 3: famous picture of Bruce Greenshield as one of the fathers 105 00:05:33,560 --> 00:05:36,000 Speaker 3: of traffic flow theory, that's standing on the side of 106 00:05:36,080 --> 00:05:38,680 Speaker 3: the road with a camera and counting cars in the 107 00:05:38,760 --> 00:05:42,039 Speaker 3: nineteen thirties or something. And so the idea it became 108 00:05:42,240 --> 00:05:45,320 Speaker 3: managed traffic. The same way as we can measure traffic, 109 00:05:45,400 --> 00:05:48,839 Speaker 3: we place traffic lights and traffic lights allow us to 110 00:05:48,960 --> 00:05:52,360 Speaker 3: have a certain amount of cars per hours. And if 111 00:05:52,360 --> 00:05:55,680 Speaker 3: they are in the cities, you have traffic light and intersection. 112 00:05:55,839 --> 00:05:57,400 Speaker 3: If we are in freeway, then you're going to have 113 00:05:57,440 --> 00:05:59,839 Speaker 3: a traffic light at the entrance of an intersection. 114 00:06:00,160 --> 00:06:03,080 Speaker 2: And it becomes what is known as from metering. 115 00:06:03,800 --> 00:06:06,560 Speaker 3: As we've gotten better and getting data and we have 116 00:06:06,640 --> 00:06:09,839 Speaker 3: more information. So now we have, for example, data on 117 00:06:10,080 --> 00:06:14,279 Speaker 3: sensors on roadsides, or for example, we have vehicles that 118 00:06:14,520 --> 00:06:17,719 Speaker 3: give us information about the GPS or the phone. Then 119 00:06:17,920 --> 00:06:21,200 Speaker 3: we've gotten also better and managing traffic, and so now 120 00:06:21,480 --> 00:06:24,919 Speaker 3: you have city wide traffic lights plans, or you had 121 00:06:24,960 --> 00:06:27,680 Speaker 3: for example, what is variable to p limit, which I'm 122 00:06:27,720 --> 00:06:31,040 Speaker 3: sure everybody at some point you saw this message panel 123 00:06:31,200 --> 00:06:34,560 Speaker 3: on the freeway that says slow down and go at forty. 124 00:06:34,279 --> 00:06:34,920 Speaker 2: Miles an hour. 125 00:06:35,720 --> 00:06:38,880 Speaker 3: And so how we manage traffic has evolved throughout the year, 126 00:06:38,960 --> 00:06:41,599 Speaker 3: and it's going to evolve as we have different types 127 00:06:41,640 --> 00:06:44,359 Speaker 3: of measurements and different ways of estimating traffic. 128 00:06:45,200 --> 00:06:47,880 Speaker 1: It seems like the traffic light was a big innovation. 129 00:06:48,200 --> 00:06:50,479 Speaker 1: Do we know anything about the history of the traffic light? 130 00:06:51,200 --> 00:06:54,400 Speaker 3: So the first traffic light that I know of dates 131 00:06:54,480 --> 00:06:56,719 Speaker 3: back to the beginning of the nineteen hundred and I 132 00:06:56,720 --> 00:07:00,400 Speaker 3: think it's in Cleveland. At the beginning was exactly that, 133 00:07:00,560 --> 00:07:04,239 Speaker 3: like a single traffic light that would just manage traffic 134 00:07:04,279 --> 00:07:08,120 Speaker 3: at a single intersection. And then as things have evolved 135 00:07:08,279 --> 00:07:11,720 Speaker 3: nowadays we're able also to have traffic lights that are 136 00:07:11,760 --> 00:07:14,280 Speaker 3: synchronized and have the so called the green waves in 137 00:07:14,320 --> 00:07:17,400 Speaker 3: which you hit green at first traffic lights and then 138 00:07:17,400 --> 00:07:20,440 Speaker 3: you're able to go through all the intersections with that 139 00:07:20,560 --> 00:07:21,880 Speaker 3: green light and all of that. 140 00:07:22,280 --> 00:07:26,360 Speaker 1: I see. So that's a little bit of the history 141 00:07:26,400 --> 00:07:30,080 Speaker 1: of traffic science and engineering. But here's the big question, 142 00:07:30,720 --> 00:07:34,080 Speaker 1: why is this problem so hard to fix? Can we 143 00:07:34,240 --> 00:07:37,480 Speaker 1: just build wider roads? Well, it turns out there is 144 00:07:37,520 --> 00:07:41,400 Speaker 1: an answer to that question, and it's something that totally shocked. 145 00:07:41,800 --> 00:07:44,160 Speaker 1: I learned it while talking to the next expert on 146 00:07:44,200 --> 00:07:48,720 Speaker 1: our show today, Callin Mees. Well, thank you so much 147 00:07:48,760 --> 00:07:49,960 Speaker 1: for joining us, Miss mess. 148 00:07:50,080 --> 00:07:52,400 Speaker 4: Thanks for having me. I'm excited to be here. 149 00:07:52,520 --> 00:07:53,680 Speaker 1: Can you please tell U who you are and what 150 00:07:53,720 --> 00:07:54,000 Speaker 1: you do. 151 00:07:54,200 --> 00:07:57,240 Speaker 4: Sure. My name is Colin Mess and I am a 152 00:07:57,240 --> 00:08:01,040 Speaker 4: PhD candidate at the University of Delaware in the Civil, 153 00:08:01,240 --> 00:08:05,920 Speaker 4: Environmental and Construction Engineering Department. My research focuses on traffic 154 00:08:05,960 --> 00:08:10,200 Speaker 4: congestion and applying new methods such as artificial intelligence to 155 00:08:10,880 --> 00:08:14,440 Speaker 4: enhance traffic management and response to incidents. 156 00:08:14,760 --> 00:08:17,720 Speaker 1: Very cool, bite the start us off. He tell us 157 00:08:18,000 --> 00:08:20,320 Speaker 1: why is traffic so bad? Sometimes? 158 00:08:20,520 --> 00:08:25,200 Speaker 4: Sure, traffic congestion is bad generally as a cause of, 159 00:08:25,520 --> 00:08:28,200 Speaker 4: you know, at the highest level, a mismatch between supply 160 00:08:28,280 --> 00:08:32,080 Speaker 4: and demand. So we can't build our way out of congestion, 161 00:08:32,240 --> 00:08:34,360 Speaker 4: so to speak, as a phrase, you hear a lot 162 00:08:34,400 --> 00:08:37,800 Speaker 4: in traffic engineering, and we try to design the roads 163 00:08:38,040 --> 00:08:41,439 Speaker 4: in a way that we can accommodate a large part 164 00:08:41,520 --> 00:08:45,240 Speaker 4: of the demand we would see even during rush hour periods. 165 00:08:45,280 --> 00:08:48,360 Speaker 4: But we can't design the road for you know, the 166 00:08:48,400 --> 00:08:52,240 Speaker 4: busiest day of the year economically or feasibly. And so 167 00:08:53,000 --> 00:08:55,680 Speaker 4: depending on things you know that are going on, whether 168 00:08:55,720 --> 00:08:59,160 Speaker 4: there's a special event or an incident, or the weather 169 00:08:59,280 --> 00:09:02,280 Speaker 4: is really nice and people are traveling due to the season, 170 00:09:02,920 --> 00:09:06,360 Speaker 4: we will always inevitably have some congestion as a result 171 00:09:06,360 --> 00:09:08,760 Speaker 4: of the fact that we just can't build an infinitely 172 00:09:08,920 --> 00:09:09,520 Speaker 4: sized road. 173 00:09:09,920 --> 00:09:13,280 Speaker 1: Oh that's interesting. I hadn't heard of that idea before. 174 00:09:13,840 --> 00:09:16,559 Speaker 1: So what do you mean by economically we can't build 175 00:09:16,640 --> 00:09:17,600 Speaker 1: the roads beginnough. 176 00:09:17,840 --> 00:09:20,680 Speaker 4: On the one hand, I think the biggest concern regarding 177 00:09:20,679 --> 00:09:22,880 Speaker 4: that would be space, in that we we want to 178 00:09:22,880 --> 00:09:26,360 Speaker 4: build roads, hopefully in a way that has a minimal 179 00:09:26,440 --> 00:09:31,840 Speaker 4: impact on everyday life and people, that minimizes the environmental impact. 180 00:09:32,040 --> 00:09:33,920 Speaker 4: And so it would be nice if we had you know, 181 00:09:33,960 --> 00:09:37,560 Speaker 4: infinite space and could build floating roads that would really 182 00:09:37,600 --> 00:09:40,920 Speaker 4: minimize the impact on the local environment in the region. 183 00:09:41,040 --> 00:09:43,200 Speaker 4: But until we can do that, sadly, we have to 184 00:09:43,240 --> 00:09:47,040 Speaker 4: make a compromise in some respect to how much capacity 185 00:09:47,080 --> 00:09:49,320 Speaker 4: we can build into the road given the you know, 186 00:09:49,440 --> 00:09:52,600 Speaker 4: constraint from the land perspective and the environmental perspective. 187 00:09:53,080 --> 00:09:55,880 Speaker 1: Uh. It's like, even if we know that in a 188 00:09:55,920 --> 00:09:59,400 Speaker 1: certain road or a certain section of a city or 189 00:09:59,559 --> 00:10:02,600 Speaker 1: a town there's going to be two hundred cars going 190 00:10:02,640 --> 00:10:06,560 Speaker 1: through a peak rush hour, we don't typically design the 191 00:10:06,720 --> 00:10:10,400 Speaker 1: road to be able to take two hundred cars an hour. Yes, exactly. 192 00:10:10,559 --> 00:10:13,440 Speaker 4: We would try to get as close to that as 193 00:10:13,440 --> 00:10:16,600 Speaker 4: we possibly could, and in some cases we can build 194 00:10:16,640 --> 00:10:19,560 Speaker 4: to accommodate the expected rush hour congestion. 195 00:10:20,000 --> 00:10:24,520 Speaker 1: Interesting, it's like, even if we let's say, had infinite 196 00:10:24,640 --> 00:10:27,760 Speaker 1: land to build a twenty lane road a, it may 197 00:10:27,760 --> 00:10:31,320 Speaker 1: not make sense to design it so that it can 198 00:10:31,640 --> 00:10:34,640 Speaker 1: take peak rush hour traffic because most of the time 199 00:10:34,720 --> 00:10:36,240 Speaker 1: is not peak rush hour traffic. 200 00:10:36,600 --> 00:10:40,040 Speaker 4: Yes, exactly, And similar to how we build parking lots, 201 00:10:40,120 --> 00:10:43,480 Speaker 4: we try to build for the thirtieth busiest day of 202 00:10:43,520 --> 00:10:47,680 Speaker 4: the year, so hopefully we're encapsulating the vast majority of 203 00:10:47,800 --> 00:10:50,560 Speaker 4: the regular traffic on that road through a model like that. 204 00:10:50,800 --> 00:10:53,600 Speaker 4: But unfortunately, if we built for the you know, for 205 00:10:53,800 --> 00:10:56,360 Speaker 4: the one percent or busiest day of the year, we 206 00:10:56,440 --> 00:10:59,600 Speaker 4: likely it would not be feasible from some perspective, whether 207 00:10:59,640 --> 00:11:02,719 Speaker 4: that's you know, environmental due to the space constraints, or 208 00:11:02,760 --> 00:11:05,240 Speaker 4: maybe it's just an economic cost that would be too 209 00:11:05,360 --> 00:11:08,120 Speaker 4: high to be supported with the resources we have. 210 00:11:08,520 --> 00:11:10,720 Speaker 1: Oh, the parking lot is a really good analogy. What 211 00:11:10,720 --> 00:11:12,760 Speaker 1: do you mean that you might design it for the 212 00:11:12,800 --> 00:11:14,080 Speaker 1: thirty if you said. 213 00:11:14,160 --> 00:11:17,560 Speaker 4: Yeah, So if we look at the entire year, cross 214 00:11:17,559 --> 00:11:21,520 Speaker 4: all seasons and estimate what the demand or usage might 215 00:11:21,559 --> 00:11:23,280 Speaker 4: be of the road or the parking lot, a lot 216 00:11:23,280 --> 00:11:26,320 Speaker 4: of times the planners will pick the thirtieth busiest day 217 00:11:26,440 --> 00:11:29,319 Speaker 4: of the year as a good benchmark. And that's usually 218 00:11:29,480 --> 00:11:31,760 Speaker 4: the reason for that is because the thirtieth busiest day 219 00:11:31,840 --> 00:11:34,720 Speaker 4: is if you look at the pattern in traffic graph, 220 00:11:34,800 --> 00:11:37,200 Speaker 4: it would be where things start to really level off, 221 00:11:37,240 --> 00:11:40,040 Speaker 4: and then you could almost consider the twenty nine other 222 00:11:40,120 --> 00:11:43,840 Speaker 4: days as a rare incident or a rare case. For example, 223 00:11:43,880 --> 00:11:46,360 Speaker 4: by me, we have a lot of travel down to 224 00:11:46,400 --> 00:11:48,840 Speaker 4: the beach for during the summer. A lot of people 225 00:11:48,960 --> 00:11:51,120 Speaker 4: live down at the beach for three or four months 226 00:11:51,160 --> 00:11:53,719 Speaker 4: of the year, and that's a great example of a 227 00:11:53,760 --> 00:11:56,600 Speaker 4: place where we can't really design the road for just 228 00:11:56,760 --> 00:12:00,360 Speaker 4: those two months because the utilization outside of those few 229 00:12:00,400 --> 00:12:03,720 Speaker 4: months it's significantly lower, maybe eighty percent lower, as just 230 00:12:03,760 --> 00:12:06,720 Speaker 4: a really rough estimate, so it wouldn't make sense from 231 00:12:06,720 --> 00:12:10,240 Speaker 4: an investment perspective, especially if we have to divide a 232 00:12:10,280 --> 00:12:13,559 Speaker 4: limited amount of money across many projects throughout the state, 233 00:12:13,679 --> 00:12:14,920 Speaker 4: not just in the beach area. 234 00:12:15,679 --> 00:12:18,559 Speaker 1: Wow, that's fascinating. He just kind of blew my mind, Colin. 235 00:12:20,840 --> 00:12:22,640 Speaker 4: Yeah. You know, a lot of times you'll see, like 236 00:12:22,679 --> 00:12:25,440 Speaker 4: I know, I'll travel down a highway and it'll be 237 00:12:25,520 --> 00:12:28,520 Speaker 4: congested and I'll just see completely empty open space on 238 00:12:28,559 --> 00:12:30,960 Speaker 4: either side while I'm you know, on the road congested, 239 00:12:31,040 --> 00:12:32,480 Speaker 4: and I feel like a lot of people see that 240 00:12:32,520 --> 00:12:34,440 Speaker 4: and think, well, why didn't they just build the road 241 00:12:34,440 --> 00:12:37,280 Speaker 4: with more lanes. Yeah, I wish we could do that 242 00:12:37,360 --> 00:12:39,680 Speaker 4: every time. It would definitely save a lot of headache. 243 00:12:39,760 --> 00:12:44,000 Speaker 4: But yeah, just the real world challenges always make things 244 00:12:44,000 --> 00:12:45,560 Speaker 4: a little more difficult than expected. 245 00:12:46,600 --> 00:12:49,559 Speaker 1: It's kind of like an almost effective life. 246 00:12:49,880 --> 00:12:51,199 Speaker 4: Yeah, I would agree with that. 247 00:12:51,280 --> 00:12:56,719 Speaker 1: Yeah, Okay, this really blew my mind. What Colin you're 248 00:12:56,760 --> 00:12:59,560 Speaker 1: saying is that the real reason we have traffic jams 249 00:12:59,840 --> 00:13:03,320 Speaker 1: is because we want to have them. Yes, the general 250 00:13:03,320 --> 00:13:05,560 Speaker 1: cost of traffic is that there are more cars trying 251 00:13:05,559 --> 00:13:07,640 Speaker 1: to get through a road than the road has space for. 252 00:13:08,080 --> 00:13:11,000 Speaker 1: But then why don't we just build bigger roads? Well, 253 00:13:11,080 --> 00:13:14,520 Speaker 1: the real reason is that we choose not to. It 254 00:13:14,559 --> 00:13:18,359 Speaker 1: doesn't make sense economically to build roads for the absolute 255 00:13:18,480 --> 00:13:21,520 Speaker 1: worst traffic days of the year, because then most of 256 00:13:21,559 --> 00:13:25,079 Speaker 1: the time the roads would be mostly empty. Instead, we 257 00:13:25,160 --> 00:13:28,080 Speaker 1: make a compromise. We accept that there are going to 258 00:13:28,080 --> 00:13:31,120 Speaker 1: be traffic jams some of the time to minimize the 259 00:13:31,160 --> 00:13:34,920 Speaker 1: cost and the burden of building bigger roads. So living 260 00:13:34,920 --> 00:13:38,960 Speaker 1: with traffic is a choice. Okay, So that's kind of 261 00:13:38,960 --> 00:13:43,280 Speaker 1: the real reason traffic exists. There are sometimes too many cars, 262 00:13:43,520 --> 00:13:46,240 Speaker 1: and we choose not to build roads that can take 263 00:13:46,280 --> 00:13:49,200 Speaker 1: all those cars. But here's the thing. As annoying as 264 00:13:49,200 --> 00:13:51,720 Speaker 1: it is to send in your car in a congested road. 265 00:13:52,080 --> 00:13:55,559 Speaker 1: There is something even worse about the problem of traffic, 266 00:13:55,960 --> 00:13:59,320 Speaker 1: and it's something that we definitely can't predict, but that 267 00:13:59,400 --> 00:14:03,520 Speaker 1: AI could potentially help us solve in the future. So 268 00:14:03,600 --> 00:14:05,640 Speaker 1: when we come back, we'll talk about what that is 269 00:14:06,120 --> 00:14:10,000 Speaker 1: and something called phantom traffic jams. So don't get off 270 00:14:10,000 --> 00:14:26,520 Speaker 1: the freeway just yet. Stay with us. We'll be right back. Hey, 271 00:14:26,560 --> 00:14:29,960 Speaker 1: we'll come back. We're talking about the real reasons traffic 272 00:14:30,040 --> 00:14:32,520 Speaker 1: is bad, and so far we talked about how it's 273 00:14:32,560 --> 00:14:36,040 Speaker 1: a basic supply and demand problem. There are sometimes too 274 00:14:36,040 --> 00:14:38,720 Speaker 1: many cars and not enough road to fit them all. 275 00:14:38,960 --> 00:14:42,280 Speaker 1: But here's a shocker. Roads are usually not designed to 276 00:14:42,400 --> 00:14:46,120 Speaker 1: handle peak traffic demand. It would be too expensive and 277 00:14:46,200 --> 00:14:48,960 Speaker 1: take up too much space to make roads and highways 278 00:14:49,000 --> 00:14:53,040 Speaker 1: big enough to handle the worst case traffic scenarios. So 279 00:14:53,160 --> 00:14:55,680 Speaker 1: in a way, traffic jams are sort of built into 280 00:14:55,720 --> 00:14:58,800 Speaker 1: our society, and according to the experts we're talking to 281 00:14:58,680 --> 00:15:01,160 Speaker 1: you today, part of the is that it's hard to 282 00:15:01,240 --> 00:15:04,680 Speaker 1: even know what the worst traffic scenario is going to be. 283 00:15:05,360 --> 00:15:07,960 Speaker 1: Here's traffic science researcher Colin Meess. 284 00:15:10,920 --> 00:15:13,560 Speaker 4: Another issue there is that the roads take time to build, 285 00:15:13,640 --> 00:15:17,880 Speaker 4: and we find that travel demand patterns change very quickly 286 00:15:18,000 --> 00:15:20,600 Speaker 4: and suddenly, and so one issue would be that we 287 00:15:20,680 --> 00:15:23,760 Speaker 4: might design the road for the geek rush hour at 288 00:15:23,760 --> 00:15:26,240 Speaker 4: the time of building, and we'll project out based on 289 00:15:26,440 --> 00:15:29,160 Speaker 4: how we see the population changing and try to get 290 00:15:29,160 --> 00:15:32,160 Speaker 4: it as close as possible. But some road projects might 291 00:15:32,200 --> 00:15:35,240 Speaker 4: take twenty years to build. For example, there's a road 292 00:15:35,280 --> 00:15:38,880 Speaker 4: near me called the four seventy six where they basically 293 00:15:38,960 --> 00:15:41,400 Speaker 4: ran into that issue. It took about twenty years to 294 00:15:41,400 --> 00:15:44,320 Speaker 4: build this project, and by the time the project was built, 295 00:15:44,400 --> 00:15:47,360 Speaker 4: the population had increased to a point where the road 296 00:15:47,480 --> 00:15:52,320 Speaker 4: was instantly congested. It's almost overnight, No, it's open to 297 00:15:52,360 --> 00:15:55,880 Speaker 4: the public, and there's already a congestion on that road 298 00:15:56,000 --> 00:15:56,640 Speaker 4: from day one. 299 00:15:56,960 --> 00:16:00,240 Speaker 1: Oh wow, it was sort of like a it was 300 00:16:00,280 --> 00:16:03,600 Speaker 1: obsolete from the get gode that it was opened exactly. 301 00:16:03,680 --> 00:16:05,920 Speaker 4: And I'm sure the people working on that project, you know, 302 00:16:06,000 --> 00:16:09,400 Speaker 4: projected out thirty years, use the best population models they 303 00:16:09,440 --> 00:16:12,480 Speaker 4: could to try to really estimate how many lanes they 304 00:16:12,480 --> 00:16:14,760 Speaker 4: could build or how many lanes they should build, and 305 00:16:14,800 --> 00:16:17,840 Speaker 4: what the throughput of that road should be. But unfortunately 306 00:16:18,000 --> 00:16:20,720 Speaker 4: the models are not always correct, especially when it comes 307 00:16:20,720 --> 00:16:22,560 Speaker 4: to modeling human traffic. 308 00:16:23,240 --> 00:16:26,520 Speaker 1: Wow, Yeah, sometimes we don't know how much traffic there's 309 00:16:26,560 --> 00:16:28,280 Speaker 1: going to be in the future exactly. 310 00:16:28,480 --> 00:16:30,800 Speaker 4: So in the case of that road, that road was 311 00:16:30,880 --> 00:16:35,040 Speaker 4: built to help specifically commuters coming from a residential area 312 00:16:35,080 --> 00:16:37,200 Speaker 4: that was about forty five minutes away from the central 313 00:16:37,240 --> 00:16:40,480 Speaker 4: business district where they worked, and because the traffic was 314 00:16:40,520 --> 00:16:43,600 Speaker 4: so bad, a lot of people over time changed how 315 00:16:43,600 --> 00:16:45,840 Speaker 4: they got to work, whether that was using maybe some 316 00:16:46,000 --> 00:16:48,840 Speaker 4: kind of carpooling system, or maybe they were using the 317 00:16:48,880 --> 00:16:52,400 Speaker 4: public transit like the metro or trains to get there, 318 00:16:52,680 --> 00:16:55,080 Speaker 4: or they move closer to the city and use they 319 00:16:55,120 --> 00:16:57,520 Speaker 4: bike or something like that. And then when that new 320 00:16:57,600 --> 00:17:01,440 Speaker 4: road opens up, word spreads that hey, this new route 321 00:17:01,480 --> 00:17:03,320 Speaker 4: is great, you can take your car into the city 322 00:17:03,360 --> 00:17:06,440 Speaker 4: again with no problem, and very quickly people will then 323 00:17:06,560 --> 00:17:09,959 Speaker 4: shift their travel patterns from these alternate modes that they 324 00:17:10,000 --> 00:17:13,200 Speaker 4: may have been using. And so when that option becomes available, 325 00:17:13,240 --> 00:17:16,480 Speaker 4: you can see a shift in demand that may not 326 00:17:16,560 --> 00:17:19,200 Speaker 4: have been able to be predicted just looking at things 327 00:17:19,320 --> 00:17:23,840 Speaker 4: like population change and the amount of vehicles being registered 328 00:17:23,960 --> 00:17:24,400 Speaker 4: in area. 329 00:17:24,880 --> 00:17:28,120 Speaker 1: WHOA, it's super dynamic exactly. 330 00:17:28,160 --> 00:17:30,760 Speaker 4: That's a great way to say accounting for human behavior 331 00:17:30,800 --> 00:17:32,359 Speaker 4: can be so difficult. 332 00:17:32,040 --> 00:17:34,360 Speaker 1: Right, That's kind of the problem is trying to predict 333 00:17:34,400 --> 00:17:36,520 Speaker 1: what people are going to do exactly. 334 00:17:36,760 --> 00:17:39,360 Speaker 4: I feel like, well, we will always have this challenge 335 00:17:39,359 --> 00:17:40,520 Speaker 4: to some extent. 336 00:17:42,720 --> 00:17:46,119 Speaker 1: So traffic seems almost like a fact of life. But 337 00:17:46,359 --> 00:17:49,480 Speaker 1: here's the thing. Traffic by itself is not considered the 338 00:17:49,680 --> 00:17:52,800 Speaker 1: real problem. Most people don't mind a little bit of traffic. 339 00:17:53,080 --> 00:17:56,440 Speaker 1: The problem, according to our experts, is something else. 340 00:17:57,880 --> 00:18:00,480 Speaker 4: The interesting thing about congestion to me is that I 341 00:18:00,480 --> 00:18:03,800 Speaker 4: feel like everybody expects congestion, right Like, if you're traveling 342 00:18:04,119 --> 00:18:06,720 Speaker 4: a route during rush hour, you have an expectation that 343 00:18:06,760 --> 00:18:09,080 Speaker 4: you will be sitting in some level of congestion. But 344 00:18:09,119 --> 00:18:13,280 Speaker 4: I think what really frustrates people for good reason is uncertainty. 345 00:18:13,359 --> 00:18:15,399 Speaker 4: And I think if you asked a lot of people, 346 00:18:15,920 --> 00:18:18,560 Speaker 4: would they rather have a trip that they know to 347 00:18:18,640 --> 00:18:21,480 Speaker 4: work their commute's always going to be around thirty five minutes, 348 00:18:21,520 --> 00:18:24,560 Speaker 4: give or take, or some days it's twenty minutes and 349 00:18:24,600 --> 00:18:27,080 Speaker 4: some days it's fifty five. I think they would almost 350 00:18:27,119 --> 00:18:30,119 Speaker 4: always rather have the certainty that they can plan around 351 00:18:30,200 --> 00:18:32,240 Speaker 4: that I know that I'm going to my route's going 352 00:18:32,240 --> 00:18:34,240 Speaker 4: to take thirty five minutes, even if it's a little 353 00:18:34,280 --> 00:18:36,800 Speaker 4: longer than it could take. As long as it's consistent. 354 00:18:36,920 --> 00:18:39,560 Speaker 4: That's really important for people to be able to, you know, 355 00:18:39,640 --> 00:18:42,080 Speaker 4: plan and go about their lives and plan their travel. 356 00:18:42,440 --> 00:18:47,040 Speaker 1: Oh, that's another super fascinating point. The problem with traffic 357 00:18:47,320 --> 00:18:50,760 Speaker 1: is not that there is traffic, because people are to 358 00:18:50,840 --> 00:18:53,960 Speaker 1: some degree okay with planning around it. It's the uncertainty 359 00:18:54,040 --> 00:18:55,440 Speaker 1: that's really frustrating. 360 00:18:55,640 --> 00:18:58,080 Speaker 4: Yeah, I would say from the people that I've talked 361 00:18:58,080 --> 00:19:01,359 Speaker 4: to and just my lived experience, that's what frustrates the 362 00:19:01,400 --> 00:19:03,760 Speaker 4: majority of people, in myself the most. I remember when 363 00:19:03,800 --> 00:19:06,800 Speaker 4: I used to commute into the city. On a good day, 364 00:19:07,000 --> 00:19:08,960 Speaker 4: it would take thirty five minutes to get to work, 365 00:19:09,000 --> 00:19:10,720 Speaker 4: but on a bad day, it could take an hour 366 00:19:10,760 --> 00:19:12,480 Speaker 4: and a half. And you know, when you have it, 367 00:19:12,600 --> 00:19:15,760 Speaker 4: there's an expectation that I'm arriving at a certain time, 368 00:19:15,840 --> 00:19:18,359 Speaker 4: and so when the travel time is that unreliable, it 369 00:19:18,359 --> 00:19:21,520 Speaker 4: becomes unfortunate because I basically have to plan for the 370 00:19:21,560 --> 00:19:24,159 Speaker 4: worst case scenario, and then I may arrive, you know, 371 00:19:24,200 --> 00:19:27,240 Speaker 4: an hour earlier than I needed. And that's you know, 372 00:19:27,400 --> 00:19:30,000 Speaker 4: nobody wants to arrive to work an hour earlier if 373 00:19:30,000 --> 00:19:32,920 Speaker 4: they don't need to, So I feel like that is 374 00:19:32,960 --> 00:19:35,960 Speaker 4: one of the most frustrating pain points of traffic congestion. 375 00:19:36,240 --> 00:19:39,359 Speaker 1: Right right, or the opposite where you know, you plan 376 00:19:39,520 --> 00:19:42,840 Speaker 1: for the average, but then you're late because there's more 377 00:19:42,880 --> 00:19:43,520 Speaker 1: traffic than. 378 00:19:43,480 --> 00:19:47,000 Speaker 4: Usual exactly and maybe nine at a ten times you 379 00:19:47,080 --> 00:19:49,400 Speaker 4: leave with the expectation that it's going to take thirty 380 00:19:49,400 --> 00:19:51,320 Speaker 4: five minutes, and nine out of ten times it does, 381 00:19:51,440 --> 00:19:54,320 Speaker 4: but one out of ten times it's three times as long. 382 00:19:54,359 --> 00:19:56,439 Speaker 4: And I mean, you can only explain that to your 383 00:19:56,480 --> 00:20:00,560 Speaker 4: boss so many times before there's no you know, excuse, 384 00:20:00,640 --> 00:20:02,600 Speaker 4: and you just have to leave earlier and plan for 385 00:20:02,640 --> 00:20:04,320 Speaker 4: the worst case, which is unfortunate. 386 00:20:05,520 --> 00:20:08,239 Speaker 1: Okay, I guess then the question is what causes that 387 00:20:08,320 --> 00:20:10,440 Speaker 1: uncertainty in traffic congestion. 388 00:20:10,800 --> 00:20:13,959 Speaker 4: So I think traffic incidents are one of the biggest 389 00:20:14,040 --> 00:20:18,640 Speaker 4: drivers of cong unexpected congestion. And by a traffic incident, 390 00:20:18,720 --> 00:20:21,119 Speaker 4: in my line of work, we call them non recurrent events. 391 00:20:21,119 --> 00:20:24,159 Speaker 4: So we would call like rush hour recurring traffic, or 392 00:20:24,240 --> 00:20:27,200 Speaker 4: like a seasonal change due to like we talked about 393 00:20:27,200 --> 00:20:29,160 Speaker 4: people going down to the beach, that would be something 394 00:20:29,160 --> 00:20:31,840 Speaker 4: that you could call recurrent traffic because we expect it, 395 00:20:31,880 --> 00:20:33,840 Speaker 4: we can plan for it, and we kind of know 396 00:20:33,920 --> 00:20:36,679 Speaker 4: it's happening. But with an incident we would call that 397 00:20:36,800 --> 00:20:40,600 Speaker 4: non recurring congestion, and that could be anything from unexpected 398 00:20:40,600 --> 00:20:44,280 Speaker 4: inclement weather that reduces visibility and overall would lower the 399 00:20:44,320 --> 00:20:47,480 Speaker 4: average speed traveled on the road, which would then effectively 400 00:20:47,520 --> 00:20:51,600 Speaker 4: lower our capacity temporarily. It could also be, of course, 401 00:20:51,640 --> 00:20:54,720 Speaker 4: things like a traffic accident or a work zone where 402 00:20:54,920 --> 00:20:58,200 Speaker 4: the capacity is essentially temporarily altered. So a vehicle gets 403 00:20:58,240 --> 00:21:00,359 Speaker 4: in an accident and we need time for that vehicle 404 00:21:00,400 --> 00:21:02,920 Speaker 4: to get moved out of the lane that it's blocking. 405 00:21:03,520 --> 00:21:06,280 Speaker 4: And while that's happening, say it's a three lane road 406 00:21:06,359 --> 00:21:09,280 Speaker 4: and one lane's blocked, we're effectively reducing our capacity by 407 00:21:09,359 --> 00:21:12,320 Speaker 4: at least thirty three percent. We can't really plan for 408 00:21:12,359 --> 00:21:15,879 Speaker 4: an unexpected incident, right, These are things where we can't 409 00:21:15,880 --> 00:21:17,879 Speaker 4: plan around them and prevent them. 410 00:21:18,000 --> 00:21:20,560 Speaker 1: I see. It's sort of like there's two sources of 411 00:21:20,680 --> 00:21:25,440 Speaker 1: traffic or congestion, Like there's a base level of traffic 412 00:21:25,720 --> 00:21:29,720 Speaker 1: that's just due to the like you said, the recurring causes, 413 00:21:30,000 --> 00:21:33,120 Speaker 1: which are you know, just not enough supply to meet. 414 00:21:32,960 --> 00:21:34,320 Speaker 4: The demand exactly. 415 00:21:34,400 --> 00:21:34,600 Speaker 3: Yeah. 416 00:21:34,800 --> 00:21:36,159 Speaker 4: I think that's a good way to think about it, 417 00:21:36,200 --> 00:21:39,880 Speaker 4: almost as like two different types of congestion, two distinct 418 00:21:39,880 --> 00:21:42,879 Speaker 4: different types and the non recurring congestion I feel like 419 00:21:42,960 --> 00:21:45,840 Speaker 4: is the most frustrating for people because it really does 420 00:21:45,920 --> 00:21:49,720 Speaker 4: play into the travel time reliability. So you know, it 421 00:21:49,800 --> 00:21:52,679 Speaker 4: really impacts reliability in a way that you're just not 422 00:21:52,920 --> 00:21:53,880 Speaker 4: expecting at all. 423 00:21:55,400 --> 00:21:58,360 Speaker 1: Okay, so there's general traffic just from having too many 424 00:21:58,400 --> 00:22:00,840 Speaker 1: cars in the road, but then that you can have 425 00:22:01,040 --> 00:22:05,320 Speaker 1: extra unexpected traffic because of accidents or cars breaking down, 426 00:22:05,440 --> 00:22:09,960 Speaker 1: or construction or weather. Those can be frustrating, but maybe 427 00:22:10,040 --> 00:22:13,000 Speaker 1: not as frustrating as the congestion that someplace seems to 428 00:22:13,040 --> 00:22:15,720 Speaker 1: happen for no reason at all. You know, when there's 429 00:22:15,760 --> 00:22:18,480 Speaker 1: a big slowdown but there isn't an accident or a 430 00:22:18,600 --> 00:22:21,679 Speaker 1: car broken down, or whether someplace cars just seem to 431 00:22:21,960 --> 00:22:25,480 Speaker 1: jam up, and that is actually a well studied phenomenon 432 00:22:25,520 --> 00:22:32,640 Speaker 1: in traffic science called phantom traffic. To explain this, here's 433 00:22:32,680 --> 00:22:34,520 Speaker 1: doctor Maria Lauda di la Monarky. 434 00:22:37,400 --> 00:22:39,640 Speaker 2: For me, it's much more interesting is what we call 435 00:22:39,760 --> 00:22:41,080 Speaker 2: phantom traffic jams. 436 00:22:41,520 --> 00:22:44,680 Speaker 1: Phantom traffic jams, yes, like a ghost like. 437 00:22:44,720 --> 00:22:47,200 Speaker 2: Ghosts, because they appear out of nowhere. 438 00:22:47,800 --> 00:22:50,560 Speaker 3: I'm sure everybody that is driven in the freeway have 439 00:22:50,840 --> 00:22:53,520 Speaker 3: lived this. At some points, you're stuck in traffic, and 440 00:22:53,600 --> 00:22:58,680 Speaker 3: you start accelerating and breaking, accelerating and breaking constantly, and 441 00:22:58,800 --> 00:23:01,360 Speaker 3: an all a sudden we are out of it and 442 00:23:01,840 --> 00:23:05,840 Speaker 3: there's nothing inside that could have caused us. There's no accident, 443 00:23:06,440 --> 00:23:10,919 Speaker 3: there's no worksite constructions, not even run shower right, And 444 00:23:11,000 --> 00:23:14,720 Speaker 3: this happened just because we assume intend to get distracted. Well, 445 00:23:14,880 --> 00:23:17,560 Speaker 3: we're driving, and then all of a sudden we realized 446 00:23:17,600 --> 00:23:19,960 Speaker 3: that OOPS were too close to the Kara had, so 447 00:23:20,119 --> 00:23:22,879 Speaker 3: we slightly it up on the brake, and that creates 448 00:23:22,880 --> 00:23:25,919 Speaker 3: a ripple effect that fifteen minutes later, someone else is 449 00:23:25,960 --> 00:23:29,439 Speaker 3: crossing the same freeway and alives at that point is 450 00:23:29,440 --> 00:23:31,520 Speaker 3: gonna be stuck in stop and go. 451 00:23:31,680 --> 00:23:35,080 Speaker 1: Traffic fifteen minutes later, even up. 452 00:23:35,000 --> 00:23:36,760 Speaker 2: To fifteen it can be even longer than that. 453 00:23:36,880 --> 00:23:41,760 Speaker 1: Yes, whoa one simple distraction I got a text message 454 00:23:42,119 --> 00:23:45,680 Speaker 1: or I'm scrolling through Instagram and instead of paying attention 455 00:23:45,880 --> 00:23:48,480 Speaker 1: can ruin someone today twenty minutes later. 456 00:23:48,920 --> 00:23:51,560 Speaker 3: Yes, we call it either stopping away more fun on 457 00:23:51,640 --> 00:23:54,639 Speaker 3: traffic jam because they are not caused by any physical rism, 458 00:23:54,720 --> 00:23:57,040 Speaker 3: and there's no physical rism for them to appear, not 459 00:23:57,119 --> 00:23:58,840 Speaker 3: physical obstacle. 460 00:23:58,320 --> 00:24:00,720 Speaker 1: A list in the road, I see, So it's just 461 00:24:00,960 --> 00:24:06,480 Speaker 1: human sloppiness. Yes, let's say traffic gets flowing smoothly. What's 462 00:24:06,520 --> 00:24:08,720 Speaker 1: going to cause it to suddenly not be smooth? 463 00:24:09,119 --> 00:24:12,000 Speaker 3: It's as simple as one driver slightly tapping on the brake. 464 00:24:12,080 --> 00:24:14,840 Speaker 3: He taps on the brake because for whatever reason, and 465 00:24:14,920 --> 00:24:17,439 Speaker 3: let's say it sees that is too close with the 466 00:24:17,480 --> 00:24:19,840 Speaker 3: car ahad, But it can simply be just not come 467 00:24:19,880 --> 00:24:22,280 Speaker 3: from the speed is going, so slightly up on the 468 00:24:22,320 --> 00:24:26,000 Speaker 3: brakes and then like the driver slightly tapping on the 469 00:24:26,040 --> 00:24:31,160 Speaker 3: brake creates basically a little disturbance, and that disturbance can templify. 470 00:24:31,280 --> 00:24:34,280 Speaker 3: That means that the driver behind the first driver is 471 00:24:34,280 --> 00:24:36,680 Speaker 3: gonna have to slightly up on the brake a bit more. 472 00:24:37,080 --> 00:24:39,600 Speaker 3: The third one is gonna tap on the brake harder 473 00:24:39,640 --> 00:24:42,640 Speaker 3: and harder, and harder and harder, until the last one 474 00:24:42,960 --> 00:24:46,560 Speaker 3: is gonna have to basically stop, almost stop or brake 475 00:24:46,680 --> 00:24:50,880 Speaker 3: so hard that the car stopped or you end up stopping, 476 00:24:51,080 --> 00:24:54,080 Speaker 3: and that basically creates the stopping. 477 00:24:56,000 --> 00:24:58,960 Speaker 1: Why does it get worth each time because it's a delay. 478 00:24:59,400 --> 00:25:03,000 Speaker 2: Because there's a delay, there's the reaction time of the drivers. 479 00:25:03,040 --> 00:25:06,040 Speaker 3: There's delay that comes from the kra had to a 480 00:25:06,119 --> 00:25:09,439 Speaker 3: car behind, So by the time you realize that the 481 00:25:09,480 --> 00:25:12,920 Speaker 3: kara had break, you have to break as well, and 482 00:25:13,200 --> 00:25:15,400 Speaker 3: you're still going in the speed of before, so now 483 00:25:15,400 --> 00:25:18,240 Speaker 3: you have to break a bit harder respect the car had. 484 00:25:18,680 --> 00:25:22,800 Speaker 1: Oh it's no balls, it's no balls exactly, yes, And 485 00:25:22,960 --> 00:25:24,880 Speaker 1: is it also the same for accelerating. 486 00:25:25,160 --> 00:25:27,480 Speaker 3: It's the same with accelerating, like if you try to 487 00:25:27,520 --> 00:25:30,280 Speaker 3: catch up with the person in front of you. So 488 00:25:30,320 --> 00:25:32,920 Speaker 3: this is what happened in the phantom traffic jam, right, 489 00:25:32,960 --> 00:25:35,920 Speaker 3: So you go into this period of breaking where everybody 490 00:25:35,960 --> 00:25:38,400 Speaker 3: breaks and the last vehicle has to break the hardest. 491 00:25:38,680 --> 00:25:41,320 Speaker 3: But then everybody tries to catch up with the vehicle 492 00:25:41,400 --> 00:25:44,080 Speaker 3: in front of it. So everybody accelerate, accelerate, and the 493 00:25:44,160 --> 00:25:46,720 Speaker 3: last vehicle acces accelerate the most because it is to 494 00:25:46,760 --> 00:25:51,360 Speaker 3: catch up to the previous vehicle, which is counterintuitive from 495 00:25:51,400 --> 00:25:54,159 Speaker 3: what you're supposed to do. You're supposed to like just 496 00:25:54,640 --> 00:25:57,399 Speaker 3: stay at your constant speed and if it's safe to 497 00:25:57,440 --> 00:25:57,760 Speaker 3: do so. 498 00:25:59,280 --> 00:26:04,919 Speaker 1: It just low everybody down, yes or no, good exactly exactly. 499 00:26:05,080 --> 00:26:07,960 Speaker 1: It's getting distracted or it's just human reaction time. 500 00:26:08,160 --> 00:26:11,080 Speaker 2: It's a mike, sure of both. Sometimes it's because you're distracted. 501 00:26:11,160 --> 00:26:13,359 Speaker 2: Sometimes it's just utilized. 502 00:26:12,880 --> 00:26:15,600 Speaker 1: Too late makes me think we should just let the 503 00:26:15,720 --> 00:26:20,360 Speaker 1: robots drive. Everyone should let the robot car drive. This 504 00:26:20,400 --> 00:26:23,000 Speaker 1: brings us to the next big question about all of this. 505 00:26:24,040 --> 00:26:28,320 Speaker 1: Could robots or AI solve the traffic problem? What if 506 00:26:28,320 --> 00:26:31,119 Speaker 1: everyone drove self driving cars with that get rid of 507 00:26:31,200 --> 00:26:33,679 Speaker 1: traffic jams? Or what if we put an AI in 508 00:26:33,800 --> 00:26:36,720 Speaker 1: charge of our traffic light system? Would that create a 509 00:26:36,920 --> 00:26:40,919 Speaker 1: perfect road system. When we come back, I'll ast car 510 00:26:41,040 --> 00:26:43,960 Speaker 1: experts all these questions and we'll see if it puts 511 00:26:43,960 --> 00:26:46,880 Speaker 1: them in a jam. So stay with us and we'll 512 00:26:46,920 --> 00:27:03,600 Speaker 1: be right back. Hey, welcome back. We're talking about the 513 00:27:03,680 --> 00:27:06,800 Speaker 1: science of traffic, and so far we've talked about what 514 00:27:06,920 --> 00:27:10,359 Speaker 1: really causes traffic and about how the real problem with 515 00:27:10,440 --> 00:27:13,600 Speaker 1: it is the uncertainty of it. We also talked about 516 00:27:13,600 --> 00:27:16,720 Speaker 1: something called phantom traffic, which is a big source of 517 00:27:16,920 --> 00:27:20,600 Speaker 1: unexpected congestion in our roads. Now the question is what 518 00:27:20,640 --> 00:27:23,679 Speaker 1: can we do about all this uncertainty. What are ways 519 00:27:23,840 --> 00:27:27,000 Speaker 1: we can make traffic or tolerable. As it turns out, 520 00:27:27,080 --> 00:27:29,360 Speaker 1: one of our experts today has been at the head 521 00:27:29,400 --> 00:27:32,000 Speaker 1: of a project to use robots to make the flow 522 00:27:32,040 --> 00:27:36,439 Speaker 1: of cars more efficient. Here's Professor Mardy allowed a dile monarking. 523 00:27:41,000 --> 00:27:46,480 Speaker 1: So the idea is that you planned robot cars along traffic, right, yes, 524 00:27:46,600 --> 00:27:50,040 Speaker 1: and somehow they're able to make things better. Can you 525 00:27:50,080 --> 00:27:51,160 Speaker 1: explain that idea a little more. 526 00:27:51,240 --> 00:27:54,000 Speaker 3: Yeah, So this is what we actually do in my live. 527 00:27:54,080 --> 00:27:57,160 Speaker 3: So we try to exploit vehicles of technology to get 528 00:27:57,240 --> 00:28:00,320 Speaker 3: transportation better for everybody and not just for the owner 529 00:28:00,400 --> 00:28:03,120 Speaker 3: of the self driving car. And so the idea is 530 00:28:03,240 --> 00:28:07,320 Speaker 3: that when we're talking, for example, about phantom traffic jams there, 531 00:28:07,400 --> 00:28:11,119 Speaker 3: it happens because we get distracted. So if we instead 532 00:28:11,160 --> 00:28:13,800 Speaker 3: of we assum and getting distructed, we have a self 533 00:28:13,880 --> 00:28:17,399 Speaker 3: driving car, that self driving car doesn't get distracted and 534 00:28:17,440 --> 00:28:19,919 Speaker 3: so doesn't have to slightly tap on the brake. And 535 00:28:19,960 --> 00:28:22,119 Speaker 3: this is in the extreme case where everybody has a 536 00:28:22,119 --> 00:28:25,159 Speaker 3: self driving car, but even the mixed case where we 537 00:28:25,240 --> 00:28:28,400 Speaker 3: have I don't know, five percent self driving cars and 538 00:28:28,880 --> 00:28:33,000 Speaker 3: ninety five percent humans, we can insert those self crime 539 00:28:33,080 --> 00:28:36,480 Speaker 3: car or smart cars anyway in the midst of the humans, 540 00:28:36,800 --> 00:28:40,480 Speaker 3: and what they would do is simply dissipate or smooth 541 00:28:40,520 --> 00:28:44,160 Speaker 3: out traffic so that the disturbance caused by that slight 542 00:28:44,320 --> 00:28:47,800 Speaker 3: up on the brake doesn't amplify it throughout the freeway. 543 00:28:48,800 --> 00:28:52,479 Speaker 1: So then if there's a wave of breaking, having an 544 00:28:52,520 --> 00:28:56,280 Speaker 1: automated car there to not break suddenly can fix it. 545 00:28:56,800 --> 00:28:57,040 Speaker 4: Yeah. 546 00:28:57,080 --> 00:29:00,280 Speaker 3: So the idea there is basically you look at the 547 00:29:00,360 --> 00:29:04,480 Speaker 3: overall traffic. You estimate what would be the best speed 548 00:29:04,560 --> 00:29:07,840 Speaker 3: for that amount of traffic for everybody to go, let's say, 549 00:29:07,880 --> 00:29:10,960 Speaker 3: at a constant speed and not have any breakdown, not 550 00:29:11,040 --> 00:29:14,120 Speaker 3: having any traffic jam. And then you tell this to 551 00:29:14,440 --> 00:29:18,360 Speaker 3: whatever smart vehicle you have there, and basically the goal 552 00:29:18,400 --> 00:29:21,920 Speaker 3: of that vehicle will try is to make sure that 553 00:29:22,000 --> 00:29:25,280 Speaker 3: he does not overreact to what other people are doing. 554 00:29:25,360 --> 00:29:27,520 Speaker 3: So he's not gonna catch up with the vehicle in 555 00:29:27,560 --> 00:29:30,240 Speaker 3: front of it. His skin is gonna keep on going 556 00:29:30,280 --> 00:29:33,920 Speaker 3: at that speed that the vehicle assumed to be the best. 557 00:29:33,960 --> 00:29:39,040 Speaker 3: One kind of try and keep everybody at a constant speed. 558 00:29:39,680 --> 00:29:42,600 Speaker 3: Oh I see, And so then all of a sudden, 559 00:29:42,760 --> 00:29:46,800 Speaker 3: fifteen minutes later, you don't have anymore these huge traffic jams. 560 00:29:47,120 --> 00:29:50,840 Speaker 3: And we did this both in close courts with one 561 00:29:51,040 --> 00:29:53,880 Speaker 3: ab and twenty human drivers, but we did this also 562 00:29:54,200 --> 00:29:57,760 Speaker 3: in freeway. So we had the largest ever experiment in 563 00:29:57,800 --> 00:30:01,000 Speaker 3: which we had one hundred smart cars Floyd and rush hour. 564 00:30:01,480 --> 00:30:04,040 Speaker 3: This was done in Tennessee on nine twenty four. And 565 00:30:04,120 --> 00:30:06,800 Speaker 3: the idea was exactly that can we tell those one 566 00:30:06,840 --> 00:30:09,880 Speaker 3: hundred vehicles to be like a pacer, like going the road, 567 00:30:10,160 --> 00:30:13,080 Speaker 3: maintain a certain speed that we will give it given 568 00:30:13,080 --> 00:30:15,680 Speaker 3: the current traffic condition, and see if they can smooth 569 00:30:15,680 --> 00:30:18,040 Speaker 3: out traffic or at least avoid the creation. 570 00:30:17,880 --> 00:30:23,240 Speaker 1: Of like plant some perfect drivers. Kind of yes, and 571 00:30:23,320 --> 00:30:23,880 Speaker 1: it worked. 572 00:30:24,200 --> 00:30:28,200 Speaker 3: Yeah, it showed that we can with a reasonable penetration rate. 573 00:30:28,280 --> 00:30:30,200 Speaker 3: So then does need to be that big, so it 574 00:30:30,240 --> 00:30:33,360 Speaker 3: can be like up to five percent. You can smooth 575 00:30:33,360 --> 00:30:36,120 Speaker 3: out traffic. And the other thing that you can do, 576 00:30:36,160 --> 00:30:40,360 Speaker 3: which is really cool, it's also reduced energy footprint of traffic. 577 00:30:40,040 --> 00:30:42,760 Speaker 2: Because there's phantom traffic jams. 578 00:30:42,760 --> 00:30:46,360 Speaker 3: What they do is you're currently accelerating and braking, so 579 00:30:46,440 --> 00:30:49,479 Speaker 3: that is what caused the highest farce consumption on your 580 00:30:49,560 --> 00:30:52,600 Speaker 3: vehicle or let's use an electric vehicle, so that caust 581 00:30:52,640 --> 00:30:56,120 Speaker 3: also the highest pollution. And so if you smooth out traffic, 582 00:30:56,240 --> 00:31:00,000 Speaker 3: you're able also to reduce this behavior and so reduce 583 00:31:00,040 --> 00:31:02,000 Speaker 3: U summation caused by transportation. 584 00:31:02,640 --> 00:31:05,440 Speaker 1: I see, well that's fascinating. So what would it take 585 00:31:05,480 --> 00:31:07,920 Speaker 1: to do that, Like the city would have to buy 586 00:31:08,000 --> 00:31:11,000 Speaker 1: some automated cars and for programming, or some people would 587 00:31:11,000 --> 00:31:13,000 Speaker 1: have to volunteer too, like I want to be a 588 00:31:13,040 --> 00:31:13,640 Speaker 1: pacer card. 589 00:31:13,960 --> 00:31:16,600 Speaker 3: I think it's more the second, Like, I think you'll 590 00:31:16,680 --> 00:31:20,280 Speaker 3: need to have some people that are willing to offer, 591 00:31:20,520 --> 00:31:22,480 Speaker 3: like their vehicles, in. 592 00:31:22,480 --> 00:31:23,280 Speaker 2: Order to do this. 593 00:31:23,840 --> 00:31:26,480 Speaker 3: Oh yeah, there are different ways to do this. It 594 00:31:26,560 --> 00:31:29,480 Speaker 3: can be incentive, or it can be simply volunteers, or 595 00:31:29,480 --> 00:31:32,960 Speaker 3: it can be simply some good samaritan sides that they 596 00:31:32,960 --> 00:31:35,160 Speaker 3: want to make life better for everybody else. 597 00:31:35,480 --> 00:31:38,040 Speaker 1: Interesting, it's interesting that you can put robots to kind 598 00:31:38,040 --> 00:31:41,160 Speaker 1: of guide people to behave better Be a car that 599 00:31:41,200 --> 00:31:44,800 Speaker 1: doesn't make the common human mistake yes, overreacting. 600 00:31:45,160 --> 00:31:47,400 Speaker 3: Yes, And also you don't want this car to we 601 00:31:47,440 --> 00:31:50,080 Speaker 3: have two different than in humans, because otherwise, if you 602 00:31:50,120 --> 00:31:53,719 Speaker 3: see some car in the road that behaves fundamentally different 603 00:31:53,800 --> 00:31:56,520 Speaker 3: and how you would expect, then you get scared while 604 00:31:56,520 --> 00:31:59,479 Speaker 3: you're driving, and then then it comes unsafe. So you 605 00:31:59,520 --> 00:32:03,000 Speaker 3: want to have something that does this without the other 606 00:32:03,240 --> 00:32:06,479 Speaker 3: human driving surrounding realizing that is doing this. 607 00:32:06,840 --> 00:32:07,240 Speaker 1: I see. 608 00:32:07,280 --> 00:32:09,080 Speaker 2: So that's the siddle thing to that. 609 00:32:09,480 --> 00:32:13,840 Speaker 1: Okay, well that's fascinating. Okay, So that's one way to 610 00:32:13,880 --> 00:32:17,160 Speaker 1: make traffic flow more efficiently and reduce uncertainty. You can 611 00:32:17,200 --> 00:32:20,720 Speaker 1: have self driving cars sprinkled throughout that talk to each 612 00:32:20,760 --> 00:32:24,440 Speaker 1: other and coordinate to basically hurt everyone along and not 613 00:32:24,640 --> 00:32:29,000 Speaker 1: overreact or get distracted to break those phantom traffic waves. 614 00:32:29,400 --> 00:32:32,719 Speaker 1: Another idea to improve traffic is to basically let computers 615 00:32:33,560 --> 00:32:36,560 Speaker 1: take control of everything. Let's say a car breaks down 616 00:32:36,560 --> 00:32:38,400 Speaker 1: in the middle of a freeway, or if there's a 617 00:32:38,440 --> 00:32:41,719 Speaker 1: car accident that closes down the lane. A central AI 618 00:32:42,120 --> 00:32:45,120 Speaker 1: could take real time data from traffic sensors on the 619 00:32:45,200 --> 00:32:47,880 Speaker 1: road and predict what would be the best way to 620 00:32:47,960 --> 00:32:52,120 Speaker 1: reduce the impact of that unexpected incident. Then that AI 621 00:32:52,200 --> 00:32:55,280 Speaker 1: could tell people's Google Maps or ways where to go, 622 00:32:55,640 --> 00:32:57,960 Speaker 1: and it could change the pattern of traffic lights at 623 00:32:58,040 --> 00:33:02,800 Speaker 1: intersections to optimize flow of cars. Here's how traffic engineer 624 00:33:02,880 --> 00:33:08,120 Speaker 1: Colin Mees puts it. Okay, so let me see if 625 00:33:08,120 --> 00:33:12,240 Speaker 1: I can paint the perfect scenario here, Colin, So we 626 00:33:12,400 --> 00:33:15,560 Speaker 1: have perfect knowledge of everything that's happening on the road, Like, 627 00:33:15,720 --> 00:33:18,600 Speaker 1: first of all, we have historical data of like what 628 00:33:18,640 --> 00:33:21,680 Speaker 1: the baseline congestion is going to be. We have perfect 629 00:33:21,760 --> 00:33:25,080 Speaker 1: data of when accidents happen, and we can use that 630 00:33:25,280 --> 00:33:27,920 Speaker 1: right away to predict the ripple effects of that event 631 00:33:28,240 --> 00:33:31,160 Speaker 1: and then be able to coordinate with the apps people 632 00:33:31,200 --> 00:33:34,719 Speaker 1: are using to divert them and change the traffic lights 633 00:33:34,840 --> 00:33:37,840 Speaker 1: to accommodate those changes to ease that traffic. 634 00:33:38,120 --> 00:33:39,680 Speaker 4: Yeah. I think that that was a great way to 635 00:33:40,600 --> 00:33:43,600 Speaker 4: summarize the perfect scenario. That's really what we're working towards. 636 00:33:43,680 --> 00:33:46,320 Speaker 4: And I hope that once these systems are you know, 637 00:33:46,400 --> 00:33:48,680 Speaker 4: tested more and develop more, and we really have a 638 00:33:48,760 --> 00:33:52,400 Speaker 4: reliable AI driven for example, system, then we can start 639 00:33:52,440 --> 00:33:55,959 Speaker 4: seeing things like an AI agent changes the traffic light 640 00:33:56,080 --> 00:33:58,720 Speaker 4: in response to the incident for us. I think we're 641 00:33:58,760 --> 00:34:01,760 Speaker 4: pretty far away from an area where the AI would 642 00:34:01,840 --> 00:34:06,040 Speaker 4: just fully be controlling the signal system, for example, without 643 00:34:06,120 --> 00:34:10,280 Speaker 4: human interaction. But I think the AI can recommend things, 644 00:34:10,640 --> 00:34:14,440 Speaker 4: simulate things, and then maybe a human says, yes, that 645 00:34:14,520 --> 00:34:18,080 Speaker 4: looks good and will change the light dynamically to accommodate 646 00:34:18,120 --> 00:34:20,319 Speaker 4: this for the next thirty minutes. And one thing I 647 00:34:20,320 --> 00:34:22,080 Speaker 4: guess I will add to that that we didn't talk 648 00:34:22,080 --> 00:34:25,480 Speaker 4: about would be just having better travel options too. So 649 00:34:25,840 --> 00:34:29,480 Speaker 4: really improving the multimodal infrastructure in our nation is something 650 00:34:29,520 --> 00:34:31,480 Speaker 4: that would go a long way. I know there's a 651 00:34:31,480 --> 00:34:34,040 Speaker 4: lot of people that drive that don't even really want 652 00:34:34,040 --> 00:34:36,120 Speaker 4: to drive, Like if they could take a reliable train 653 00:34:36,600 --> 00:34:39,480 Speaker 4: from A to B every day instead of having to 654 00:34:39,960 --> 00:34:42,759 Speaker 4: drive on the roads, then they would prefer to do that. 655 00:34:43,000 --> 00:34:45,759 Speaker 4: If we think about investing more in alternate modes like 656 00:34:45,800 --> 00:34:48,319 Speaker 4: we see in Europe, where the infrastructure exists and it's 657 00:34:48,360 --> 00:34:51,279 Speaker 4: good and it's reliable and it's affordable, people will take 658 00:34:51,280 --> 00:34:53,600 Speaker 4: those alternate modes, and that can also be another way 659 00:34:53,600 --> 00:34:55,840 Speaker 4: that we can relieve some of the stress on the 660 00:34:55,880 --> 00:34:57,360 Speaker 4: existing roadway system. 661 00:34:57,600 --> 00:35:00,800 Speaker 1: I see, But then let me update my optimal optimal scenario. 662 00:35:01,120 --> 00:35:04,840 Speaker 1: It seems like there's an optimal optimal optimal scenario, which 663 00:35:04,880 --> 00:35:08,040 Speaker 1: is that people ride their bicycles and take the train more. 664 00:35:08,400 --> 00:35:09,280 Speaker 4: Yeah, exactly. 665 00:35:09,520 --> 00:35:11,799 Speaker 1: I mean not that sitting in traffic listening to say 666 00:35:11,880 --> 00:35:14,560 Speaker 1: a science podcast is necessarily a. 667 00:35:14,480 --> 00:35:16,959 Speaker 4: Bad No, definitely not. I think if you were sitting 668 00:35:17,000 --> 00:35:18,960 Speaker 4: in traffic, that's probably one of the best ways you 669 00:35:18,960 --> 00:35:20,000 Speaker 4: could be spending your time. 670 00:35:20,800 --> 00:35:25,160 Speaker 1: There, you go. I feel like maybe traffic also points 671 00:35:25,200 --> 00:35:30,240 Speaker 1: to a fundamental human need to come together to gather, 672 00:35:30,560 --> 00:35:32,840 Speaker 1: Like if we didn't have that need and nobody wanted 673 00:35:32,880 --> 00:35:36,359 Speaker 1: to ever align with anybody else's schedule, maybe there would 674 00:35:36,360 --> 00:35:39,080 Speaker 1: be less traffic. But because you know, schools start at 675 00:35:39,120 --> 00:35:41,720 Speaker 1: the same same time, work starts, the business day starts 676 00:35:41,719 --> 00:35:44,880 Speaker 1: at the same time. Everyone wants to work together. We 677 00:35:44,960 --> 00:35:49,160 Speaker 1: have that fundamental human need. Then that just naturally causes traffic. 678 00:35:49,520 --> 00:35:53,200 Speaker 3: Yes, I think that's also part of the I wouldn't 679 00:35:53,200 --> 00:35:55,120 Speaker 3: say a problem because it's not a problem like that. 680 00:35:55,160 --> 00:35:57,000 Speaker 2: We want to be all together. This is part of 681 00:35:57,160 --> 00:35:58,480 Speaker 2: just the situation as it is. 682 00:35:58,560 --> 00:36:01,399 Speaker 3: And so I think it's just we need to be 683 00:36:01,400 --> 00:36:04,480 Speaker 3: better at building public transits so that people will want 684 00:36:04,520 --> 00:36:08,600 Speaker 3: to use public transit stuff taking the car or other 685 00:36:08,719 --> 00:36:10,560 Speaker 3: sorts of transportation. 686 00:36:10,440 --> 00:36:12,600 Speaker 1: Or maybe flying cars. I think that would solve everything. 687 00:36:12,600 --> 00:36:14,480 Speaker 3: What do you think then we're gonna have congestion in 688 00:36:14,480 --> 00:36:17,080 Speaker 3: the skies on the roads. 689 00:36:17,080 --> 00:36:22,759 Speaker 1: But yes, works because of three D problem. Yes, yes, 690 00:36:23,719 --> 00:36:24,920 Speaker 1: it's never gonna ends it. 691 00:36:25,040 --> 00:36:27,239 Speaker 3: I don't know, Like I think it's gonna probably get 692 00:36:27,280 --> 00:36:31,560 Speaker 3: batter us. We are getting better as time passes in theory. 693 00:36:31,680 --> 00:36:34,960 Speaker 3: I hope it's gonna be a batter as time passes. 694 00:36:36,160 --> 00:36:39,040 Speaker 1: All right, Well, if you're sitting in traffic right now 695 00:36:39,080 --> 00:36:42,280 Speaker 1: listening to this, we really appreciate you spending your commute 696 00:36:42,320 --> 00:36:44,600 Speaker 1: with us. I'm sure traffic will clear up for you. 697 00:36:44,600 --> 00:36:47,520 Speaker 1: Pretty soon and hopefully it'll clear up for all of 698 00:36:47,560 --> 00:36:50,439 Speaker 1: us in the future. Thanks for joining us, and hey, 699 00:36:50,560 --> 00:36:53,879 Speaker 1: next week is the season finale of sign Stuff and 700 00:36:53,920 --> 00:36:56,640 Speaker 1: it's going to be a pretty dramatic one, so be 701 00:36:56,680 --> 00:36:58,879 Speaker 1: sure to tune in next week as we tackle one 702 00:36:58,880 --> 00:37:02,720 Speaker 1: of the biggest signs questions facing us today, Isn't AI 703 00:37:03,239 --> 00:37:14,160 Speaker 1: going to kills all? See you? Then you've been listening 704 00:37:14,200 --> 00:37:18,480 Speaker 1: to Science Stuff, the production of iHeartRadio, written and produced 705 00:37:18,480 --> 00:37:22,480 Speaker 1: by me or hitch Ham candidate by Rose Seguda, executive 706 00:37:22,480 --> 00:37:26,320 Speaker 1: producer Jerry Rowland, and audio engineer and mixer Kasey Peckram, 707 00:37:26,480 --> 00:37:28,640 Speaker 1: and you can follow me on social media. Just search 708 00:37:28,719 --> 00:37:31,880 Speaker 1: for PhD Comics and the name of your favorite platform. 709 00:37:32,000 --> 00:37:34,960 Speaker 1: Be sure to subscribe to sign Stuff on the iHeartRadio app, 710 00:37:35,000 --> 00:37:38,240 Speaker 1: Apple Podcasts or wherever you get your podcasts, and please 711 00:37:38,440 --> 00:37:49,839 Speaker 1: tell your friends we'll be back next Wednesday with another episode. Hey, 712 00:37:50,120 --> 00:37:52,080 Speaker 1: please take a second and leave us a review on 713 00:37:52,160 --> 00:37:55,719 Speaker 1: Apple Podcasts, Spotify, or wherever you listen to the podcast. 714 00:37:56,400 --> 00:37:56,919 Speaker 1: Thanks a lot,