Podcast: Get 3 Days of Your Life Back Every Year with Smart Stoplights

In this episode, we discuss how researchers at the University of Michigan were able to reduce traffic in a small city - to the extent of saving ~3 days per person per year - using GPS data from connected cars and smart stoplights. 

This podcast is sponsored by Mouser Electronics. 

EPISODE NOTES

(4:10) - Get 3 Days of Your Life Back Every Year with Smart Stoplights

This episode was brought to you by Mouser, our favorite place to get electronics parts for any project, whether it be a hobby at home or a prototype for work. Click HERE to learn more about how IoT can be leveraged in smart cities of the future to optimize traffic management.

Become a founding reader of our newsletter: read.thenextbyte.com

Transcript

What's going on, friend? What are you doing right now? The odds are you're sitting in traffic listening to this podcast because, let's be honest, you hate traffic and you're not alone. We hate it too. In fact, did you know that the average American loses 10 days of their life just sitting in traffic every year? Well, I think you're going to like this one. I mean, you're already probably buckled up, but the University of Michigan is going to give you three days of your life back every year. So, let's get into it.

I'm Daniel, and I'm Farbod. And this is the NextByte Podcast. Every week, we explore interesting and impactful tech and engineering content from Wevolver.com and deliver it to you in bite sized episodes that are easy to understand, regardless of your background. 

Farbod: Alright peeps, like you heard, it's all about traffic and how much time we lose to traffic today. Before we jump into the episode though, let's talk about today's sponsor, Mouser Electronics. You folks already know about Mouser, one of the world's biggest electronics suppliers. They got the cold connects with industry and academia. They are hip to what's going on, the technology trends, and they write articles about it sometimes, and sometimes they're so spot on that they kind of predict the future. So, we're sharing one with you today. It's linked to the show notes, but they talked about traffic management and IoT in the smart city. They start off by saying how much of a hassle traffic really is and how we're bad at managing it properly. In fact, they share a stat that the average American driver lost almost 100 hours every year due to congestion before the pandemic. That is miserable. That is awful. But they went on to say that there's a lot of solutions that could potentially come up in the next couple years because of IoT technology, internet of things. They talked about how vehicle interactions could prevent one driver who's driving so aggressively and one that's driving so slow. So, you could mitigate some of that. You could have vehicle to infrastructure communication. That means your car talking to the cloud, sending data, and then that data getting processed to make some sort of change in the flow of traffic to make it better. And then they talked about smart traffic signals and how they could talk to each other so that when you see congestion ahead or behind, the context here is a little fuzzy, but the other stop lights could update their timing to make sure that the flow is as smooth as it can possibly be.

Daniel: Well, and I mean, that's the worst thing possible when you're stuck in traffic and you're sitting at a green light and you can't go because it's already all the way backed up to the next light in front of you. And then the light turns red just before that one opens up. They're talking about the opportunity to use vehicles communicating with the infrastructure to highlight when there's a congestion problem and then help alleviate that and then also allowing the traffic signals to talk to each other to exchange data about congestion and then try and alleviate congestion, try and remove traffic wherever possible. And like you said, it's this, this team at Mouser just got their finger so well positioned on the pulse of technology that they wrote this article before the article that we're going to talk about today is the meat of today's episode, but they pretty much called it.

Farbod: Like straight on.

Daniel: Well, so I love that. So, go read this article in the show notes as a primer and then check out what we're going to talk about today as the meat of the episode, which is how and why you can get three days of your life back every single year with smart stoplights. And that exactly hits the part that Mouser was talking about just to go back to that, the vehicle to infrastructure communications and smart traffic signals. That's exactly what a team, I think it was at University of Michigan.

Farbod: University of Michigan.

Daniel: Has been doing, right? Vehicle to infrastructure communication, and smart stoplights to help alleviate traffic.

Farbod: But that is a testament to just how well Mouser has her finger on the pulse. That's one of the reasons we love working with them.

Daniel: For sure.

Farbod: Because the stuff that they have access to and the way we can incorporate it in our show is just so seamless and so wonderful. And like you said, it adds a nice little primer to what we're gonna be talking about. And with that said, let's get into today's article. We already talked about it. We're gonna make life better somehow by making traffic flows a lot smoother. But let's build some context here. So common knowledge, at least in America, traffic light timing just sucks, right? Like you said, you're sitting in traffic, you're waiting, it turns green, just like, and you're stuck, and when it turns red before you can really get some flow going, so everyone's upset all the time. Understandable. Now there has been some innovation on the front, there's adaptive traffic system lights, traffic signals, where it has sensors that detect cars coming and cars going so that they can change their timing to make sure that they're as efficient as they could possibly be.

Daniel: You know, it's crazy, though. Average cost to one of those adaptive traffic signals.

Farbod: Fifty thousand dollars.

Daniel: Ridiculous.

Farbod: Fifty grand. That's a two Fisker Ocean ones, you know? Too soon.

Daniel: That's a five-volt Toyota Camry. That's a lot of beans, man. Yeah. Just to turn one traffic light adaptive, obviously, if I could pick one, I'd pick the one closest to my house, but it's...

Farbod: What are we all?

Daniel: It's untenable to try and fix every single traffic light and make them adaptable, even though there's a lot of known benefits around making traffic lights adaptive to reduce traffic. So, this team at University of Michigan's like, what if there's a smarter way?

Farbod: But wait, no, because we can't set up these adaptive systems, what do we do? We sent out the manual ones.

Daniel: Yeah, either like fixed timing, I think they call it.

Farbod: Exactly. It's fixed timing, which means someone has to program, OK, like on Mondays between 9 AM to 10 AM, keep changing the light color every 30 seconds, and then during rush hour do this.

Daniel: And it's a lot cheaper than doing the adaptive system, but that's why a lot of intersections have cameras.

Farbod: Exactly. And what was a surprise to me is that even though the installation of the original setup is a lot more cost effective. To update that because traffic flows are changing, it ends up being costly because they have to send a person out that monitors, manually monitors how these are going and then they update the timing. So, most cities don't do it more than every two to five years, which is again why we have to have the timing.

Daniel: Or if someone complains about it.

Farbod: Or if someone complains. Or if enough people complain, yeah. So that's why we are in the situation that we are. And a couple other stats that I think are relevant. There's 320,000 traffic lights in the United States. Most of them probably aren't the adaptive solution. Most of them are probably this cheaper alternative. And it is estimated that inefficiency from traffic signals, that means people getting to work late or just losing time in general, cost the US approximately $23 billion every year.

Daniel: Just in the US. Crazy.

Farbod: That's a lot of dollars. But more importantly, a lot of human life just being wasted away because of inefficiencies in the system.

Daniel: Well, and we were talking about this, but like we're warming up before this episode, right? You liken it to like the Steve Jobs thing in his biography when they're designing the MacBook, right? They're like, he's, I think he was trying to target them to make a MacBook be able to wake up from sleep in under five seconds.

Farbod: Yeah, yeah. And then the engineers were like, well, why would we care? Like, who cares about that?

Daniel: That's impossible. We're already at 10 seconds. It's as fast as it possibly could be.

Farbod: And he was like, well there's X number of people that are gonna be using this computer. If you shave five seconds from every wake up, assuming X number of wake ups every year, you'd be saving this amount of their life. You're literally giving them life back. And that is the frame that we should all be thinking about problems like this. Because I mean, you tease it at the beginning of the episode, the average American is losing three days of their life every year because of inefficiencies being stuck in traffic. Crazy. Now, these folks at University of Michigan, you can already tell, I got the energy on this one. I’m hyped because we did the math and I'm losing some time too. You work remotely but I'm hybrid, oof, I'm amped up. But these folks at the University of Michigan, they've come up with a very novel solution for this that is not only effective but also very cost effective. It makes sense that, it's the University of Michigan by the way, given their relationship with the auto industry and the involvement of General Motors with this one. General Motors, most of their, I'm assuming newer cars, let's say what? 2015-18 onward probably. They're collecting GPS data and they're sending it to their cloud. And that data is being shared with the University of Michigan in case they wanna do research with it. I think they do like autonomous driving stuff. I don't know.

Daniel: Yeah, we've talked about University of Michigan doing a lot of…

Farbod: Collaboration with these American auto manufacturers.

Daniel: Yeah, and it makes sense, right? They're all based in the Michigan area. It's really easy for them to collaborate, but I think, was it Michigan? I think they had an M-city, right? They were the ones with like a whole simulated city to try and improve connected cars and try and improve autonomous driving, right? They're at the forefront of this. But like you're saying, most of these cars, at least the newer cars out on the road, have this connected car capability, right? They've got GPS capability, they've got the ability to communicate with the cloud and tell the world what that car is doing, where it is, whether it's backed up at a traffic light or if it's going around, going along, cruising at 45 miles an hour. So, by being able to basically capitalize on data that's art already exists, functionality that already exists in a good percentage of cars on the road. They were like, what if we were able to connect this right and do what Mouser called out vehicle to infrastructure communication? What if we can use this as a signal to make fixed traffic light signals right now that pay no mind to whether there's traffic or pay no mind to whether someone's waiting at the light for 15, 20 minutes, what if we can use vehicle data from these connected cars to communicate with the cloud and create adaptive traffic signals that address traffic congestion when it happens? And basically, again, uses the data we already have, but in the most efficient way possible to help reduce traffic.

Farbod: And they would, in theory, they would effectively be installing these adaptive traffic lights at every intersection in America because now it will be intelligent and conscious of what's going on around it. But it's even better than that because what you're getting out of this GPS data is how many times is this car stopping? What kind of route is it taking? And generally, the only thing the adaptive traffic lights would tell you is are there a lot of cars in front of me, yes or no, if so, do this. This is giving you extra data that allows you to take a step back, get that high level look on what's going on in a portion of the city, and streamline the process as a whole, optimize the timing as a whole. So that's what's so impressive about it. And it's also worth noting that, by the way, they're using GM's data. GM apparently only accounts for about 6% to 10% of the cars on US roads. So, you don't need a ton of data either. You just need to have certain data points. And the way I think about it is, I use Waze navigation on my phone. It's pretty accurate, like even for long distance trips, down to the minute of when I'm gonna get there, but not everyone is using Waze. As long as there's enough people using Waze on like a certain route, the algorithm's able to tell you generally how well you're gonna do on your way of getting there. So, this is working the same way.

Daniel: I think they said they, during their test, and just kinda to spill the beans here, right? They did an 18-month pilot study in Birmingham, Michigan, which by the way, my old boss used to live in Birmingham. It's a really, really nice place he took me by. But they used only 6% of total traffic, the GM vehicles with only 6% of these vehicles being connected. They were able to successfully gather real time insights about how many vehicles were positioned, where they were positioned, how fast they were going, when they were stopping at intersections, the routes that they were taking, like you were saying to see if they were wasting fuel, to see if they were congested in traffic, to see if there were increased emissions, to see if drivers were getting frustrated, right? You can determine all that from just 6% of the drivers, which is crazy. And on top of all that, that the way I like to think about it is, remember that $50,000, really, really expensive, turning a traditional signal system into an adaptive signal system. The whole goal of those adaptive systems, they set up a sensor network, right? Pressure sensors in the ground and sensors up on the lights that point at the intersection to detect whether or not there's a bunch of cars waiting there or not, and then be able to have some type of algorithm to change the signal pattern to accommodate the congestion that's happening. Well, instead of spending a lot of money with these extensive sensor arrays, trying to find out where the cars are, why not just let the cars tell you where they are with these sensors and with this functionality that's already built into cars for other reasons, right? That we don't make connected cars just for traffic detection, but with less than, you know, there's just about 6% of the cars on the road, they were able to effectively mitigate traffic using functionality that's already built into these cars for other reasons, instead of spending tons of money to try and detect where the cars were, they just said, hey cars, tell us where you are, and it worked.

Farbod: Now, when I'm thinking about what the future holds for this data, and by the way, yeah, no, no, I'm gonna talk about this and then we can get to it. So many thoughts. I could see people being hesitant to share their data with the government or some third party to help you calculate traffic light signals, but I'm sure there's a way to anonymize it and if it becomes one of those things that makes everyone's lives a little bit easier, like, I would do it. I mean, I have a Corolla that definitely does not send GPS data to the cloud, but if I had a car that could, I would, that's a service that I would sign up for.

Daniel: Well, and just even to think about this, right? You don't need a hundred percent adoption. Let's talk about kind of the achievement that they have with this 18-month pilot study. So, I think they changed 34 different traffic lights from this traditional timed system, fixed timing system to the smart adaptive patterns.

Farbod: Yesterday we're analyzing this like segment that had these 34 stoplights.

Daniel: And again, using only 6% of the total traffic that were smart cars communicating with these traffic lights in Birmingham, Michigan in the real world, right? But that's notable, it's not just inside like a little university, but it's in the real world, real people driving their real cars to and from work. They're able to reduce the number of stops at intersections by 20 to 30%, making substantial improvements in traffic flow and reduction in stop and go driving. So, imagine just the impact on people's lives, right? The time, 20 to 30% less time spent waiting at a stoplight. 20 to 30% less stop and goes. That's a huge for emissions. That's huge for wear on your car. And again, they were able to achieve that with only 6% adoption. So, I imagine, maybe there's some level of marginal returns that maybe they only need 20 to 30% of adoption to maximize the amount of benefit that you get from it. And you don't need everyone to opt in. You just need enough people to opt in to get a full understanding of what's going on from a traffic picture perspective.

Farbod: And imagine what you can do with that 20 or 30% of community time that you get back now. Start a new hobby, spend more time with your loved ones, catch up on that show that you haven't been watching.

Daniel: Well, we did some quick napkin math before starting this, right? The average American spends 10 days of their life every single year commuting to work. That's pretty depressing, but that's 52 weeks out of the year traveling for one hour a day, 30 minutes to and from work. That seems pretty reasonable, and when you add it up, you spend 10 days of your life sitting in your car commuting to work. Imagine you're able to shorten that by 20 to 30%. We put it in the title of the episode, folks, but this team from Universal Michigan is gonna give you three days of your life back, every single year, just by having Smart Stoplights, which is pretty sick.

Farbod: Yeah, so let's summarize it real quick. Folks, do you like commuting? Of course you don't, no one does, it sucks. In fact, the average American spends about 10 days every single year just commuting. And that happens because our system is actually quite inefficient. These traffic lights that we're using, they could be better, but the reality is that the adaptive solutions, they're way more costly. So, it's just not gonna scale. But don't give up hope. Please don't, because the University of Michigan has a solution. They're able to use GPS data from cars to calculate the number of times that these cars are stopping, flow of traffic, and what kind of routes that people are using, and then update these timers on a regular basis to make sure that traffic is as optimized as possible. And you might be wondering, well, is it really gonna be that valuable? Yes, it can save up to 20 to 30% of your time, meaning you can get three days of your life back. And that's why this is a life-changing solution.

Daniel: Love it. I love it, dude.

Farbod: I try. Again, I'm passionate about this one, as you can tell. It's a fiery one.

Daniel: Yeah, I can tell. Again, we were doing some napkin math. I think we think for both because he goes into the office about 60% of the time. He loses only six days of his life every single year in the car.

Farbod: But the gains, the gains could be quite nice for me.

Daniel: Yeah, that's incredible. Before we wrap up today, I have two things that I wanna shout out. The first of which is a new review. We made a promise a long time ago that we would share every single review that we get on the podcast, good or bad. And I'm happy to say this time that it's a good review. We got a five-star review from Michael Bublé fan, which by the way…

Farbod: I love Michael Bublé.

Daniel: I am a big Michael Bublé fan. I promise it wasn't you.

Farbod: Was it you?

Daniel: It wasn't me that wrote this review. Michael Bublé fan says, I'm a pre-engineering student, love listening to this podcast to keep me up to date on technological and engineering advances delivered in a conversational and easy to follow format. Thank you for your hard work on this Daniel and Farbod.

Farbod: Michael Bublé fan.

Daniel: Man, you warmed my heart.

Farbod: You warmed my heart.

Daniel: You warmed my heart like listening to Michael Bublé at Christmas time.

Farbod: Wow, what, I wish we could do more to thank you. That's very kind, thank you.

Daniel: Yeah, but the least we can do is give a shout out.

Farbod: Absolutely, yeah. You know, comments like that, feedback like that is what keeps us going, right?

Daniel: And, I will say if you made it this far in the podcast, we'd really appreciate if you could leave us a review if you haven't already. We think we deserve five stars. We're working really hard to make this the best podcast possible. We'd appreciate if you leave us a review. That's one of the best ways you can help other people find us is by leaving reviews. It lets the podcasting platform you're on know that we're doing good work and to share it with other people. The other thing I wanted to shout out, I said I had two. You did have two. Is that we're launching something new. We're launching a newsletter. If you've been listening to a couple episodes of the podcast, you might've heard this spiel, maybe not, but we've worked really, really hard over the last three years. We've published an episode every single Tuesday for over three years straight to help us become experts at turning really, really complex technical topics that are gonna go change the world into the most interesting, impactful bits that you need to know and make it easy to understand. And we're gonna take the same chops that we've developed by doing this in the audio format and try and deliver the best newsletter focusing on an interesting and impactful tech that you've ever read. So, we'd really appreciate if you go check out the link in the show notes or go to read.thenextbyte.com and sign up. You can be one of our founding readers. We'll find a way to appreciate you. We're not sure exactly what that is yet, but we'd appreciate you joining and being with us, joining from the early parts of the ride on the newsletter as we try and make it the best newsletter you've ever read.

Farbod: Perfect. And with that said, folks, thank you so much for listening. As always, we'll catch you in the next one.

Daniel: Peace.

As always, you can find these and other interesting & impactful engineering articles on Wevolver.com.

To learn more about this show, please visit our shows page. By following the page, you will get automatic updates by email when a new show is published. Be sure to give us a follow and review on Apple podcasts, Spotify, and most of your favorite podcast platforms!

--

The Next Byte: We're two engineers on a mission to simplify complex science & technology, making it easy to understand. In each episode of our show, we dive into world-changing tech (such as AI, robotics, 3D printing, IoT, & much more), all while keeping it entertaining & engaging along the way.