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How could we include traffic light status in route planning?

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jnikola
jnikola Oct 17, 2022
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Google keeps AI-powered live track of the traffic by drivers' signal locations. Recently, we have seen an update of Google Maps where now they include traffic lights and STOP sign symbols on your route . That way you can know when to stop, slow down or choose another route, based on looking at the map itself.
However, how could we make these traffic lights actually influence the recommendation algorithm that calculates the best route?
How could we plan the best route with minimum red lights?
Why?
  • it could save a lot of time since faster routes would be suggested
  • superiority over the competitor maps
  • saving a lot of time for taxi service providers or delivery companies = more money
  • recognising broken traffic lights or those not in sync = better traffic regulation
  • recognising traffic jams in advance
Requirements:
  • we should somehow know when the traffic light is green, yellow or red - any ideas?
  • we should be able to calculate the chance of red light for every traffic light on the route - do you know how to calculate this?
  • know the average speed of you in live traffic conditions - is this already implemented in Google Maps?
  • any other requirements, solutions or suggestions to discuss?

[1]https://arstechnica.com/gadgets/2022/04/google-maps-brings-traffic-light-and-stop-sign-icons-to-navigation/

traffic lightsroute planningtraffic traffic systemmapsgoogle mapsnavigation
2
Creative contributions

Traffic light signal transmitters and windshield cameras

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Povilas S
Povilas S Oct 17, 2022
The best way would be to implement signal transmitters into each of the traffic lights and let google know real-time data directly from them. The signal could be transmitted to the nearby cell tower, alternatively, it could be transmitted to the phones of people sitting in cars and thus uploaded to google. The latter option would have to be somehow incentivized by google to get people to willingly participate in such data transfer.
Another way I can think of would be to use security cameras that some people place behind their windshield glass and (again) incentivize those people to provide the data for google. If google came up with a good enough incentives system, maybe more people would start using them.
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Traffic light status determined from the Google Maps live traffic report

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jnikola
jnikola Oct 18, 2022
Since Google already knows where you are in the traffic, this data could be used to calculate the duration of every green and red light on your route. With many cars passing and stopping, we should have enough data to predict green or red lights on the route, even in different periods.
Are there any obstacles to this solution?
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Povilas S
Povilas S2 years ago
The obstacle is those times when there are not enough cars on the road. I assume we want your proposed functions to work at all times, not only during rush hours.
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jnikola
jnikola2 years ago
Povilas S For these times, I think prediction based on historical data could work, since it's the easiest scenario (with the smallest number of factors involved). For example, if every day, for the last 4 years, the green light on the crossroad X turns red at 04:22:54 and turns back to green after 25 seconds, this could be, with high certainty, true for today, too. But for sure some deeper knowledge of how traffic lights work should be included.
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General comments

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Shubhankar Kulkarni
Shubhankar Kulkarni2 years ago
I may be wrong but since Google collects data from the users using a particular route, isn't the signal time automatically incorporated in the time taken to reach a place? For example, if multiple cars seem to be stopping for 30 seconds at a particular cross-section (red light), those 30 seconds are incorporated into their time to reach the destination. Well, an average is calculated. So, if half of the cars get a green light on reaching the cross-section, their wait time is close to zero. So, the average turns out to be +15 seconds. Similarly, for an alternative route, if there are two signals (30 seconds each), then the average time taken by users traveling that route will be +30 seconds. Therefore, when you put in your destination, Google will automatically select the former route, if all other confounders are adjusted for. I have noticed Google gives me the fastest route and the resolution is 1 minute. So, even if an alternative route takes 1 min longer, Google does not suggest that. The 1-min longer route is shown in gray and captioned "1 min slower".
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jnikola
jnikola2 years ago
Shubhankar Kulkarni Heheh that was the way how I started to think about this idea. I understand what you want to say. What I think is happening is that a simple tracking of the signal causes the algorithm to predict the "waiting time". The consequence could be that it might, indirectly (as you mentioned), incorporate traffic light signal status. However, that means the algorithm automatically calculates the average for every traffic light and includes it in the route planning.
What I wanted is to make it even more precise by knowing what time frames of green and red lights are relative to the other traffic lights in the surroundings. In other words, I want Google to tell me, to use this route because I will catch more green lights after the initial one; the other route (although shorter in distance and has the same number of traffic lights) will make you stop at every cross road because it will be red. It could maybe be interpreted as "I want more real-time route planning, not the average".
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Shubhankar Kulkarni
Shubhankar Kulkarni2 years ago
J. Nikola Okay, so you want to personalize the route instead of the average that Google gives.
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Povilas S
Povilas S2 years ago
To answer your question - I think the prediction of the average speed of your vehicle in certain traffic conditions is already implemented into the google maps navigation system. I've noticed that when there's no traffic it presumes your speed to be the maximum speed allowed by the road signs. However, when there's traffic, it still predicts your journey time quite accurately, so that function should be in place.
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jnikola
jnikola2 years ago
Povilas S Maybe I am wrong, but I think it's because of the live traffic tracking (number of cars on the route), not the traffic light status. We could check this by taking a route with no cars (during the night), but with many traffic lights. If we check the navigation a few times in several minutes, we will probably get the same time needed to arrive at place B every time. However, traffic lights were not always green. I guess it may account for the average waiting time on that crossroad, but no live traffic light signal tracking is used for that.
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