It is said the unprotected left turn (right turn in left-hand drive countries like Australia, but I will write as an American here) is hard for autonomous vehicles (AVs). (Even ignoring pedestrians, which magnify the complexity if there were to be treated as full-fledged users rather than an after-thought.)
With an unprotected left turn there is ambiguity about whether gaps between vehicles are large enough for the AV to squeeze through safely, and whether oncoming traffic will yield to an attempt to cross, particularly as the wait gets longer and longer and the passengers in the turning vehicle become more and more impatient.
It is a matter of vehicle delay and storage space. On a one lane per direction road, or even a two lane per direction road, vehicles that are queued to turn could block vehicles that might otherwise go straight (or vice versa) when there is no turn bay and they don’t simultaneously have a green.
We could have a phasing configuration which gave each approach (North, South, East, West (N, S, E, W)) its own green time. In this case, if flows were more or less equal between left turns and through/right movements, this might be the optimal solution. But if flows were dominated by one or the other, then it would be less than efficient.
Alternatively, if we have turn bays (dedicated turn lanes) to keep vehicles out of each other’s way, we could have a configuration (N/S Through/Right, N/S Left, E/W Through/Right, E/W Left) which paired the turns. But turn bays use up lots of space that could be alternatively used for just about anything than temporarily storing cars.
And of course these could be mixed (N/S Through/Right, N/S Left, E, W) depending on relative flows.
But if the North flow > South or East flow > West (or vice versa), then these strategies will leave large gaps that could have been used by crossing traffic, but weren’t because the signal wasn’t timed for it.
With sufficient real-time information about flows, the signals could be adjusted to turn the lower flow approach to red when there are no vehicles approaching to protect the higher flow approach. This information requires knowing total approaches, but would be more accurate if the number on each turn (left, through, right) were also known, but this might be hard to discern simply by their location if the use of turn signals is imperfect, and there are too few dedicated lanes.
Update: We could prohibit left (right) turns. This is down in Moscow, so I understand. The left-turn ban at intersections is useful with low-rate flow turning left, assuming all left-turn vehicles are willing to do right turns several times to get to their destinations. But, this may impose a heavy burden of additional traffic on other road sections.
Or we could just have more roundabouts. These create other issues.
Porsche waiting to make a left turn, despite a presumably high value of time.
Look closely at the traffic lights. What could go wrong?
Imagine an Apple Watch app (Green Pace) that used haptic feedback to pace your walk so you made the “Walk” signal at every traffic light. It would tap faster if walking faster let you make the signal, it would tap slower if you would hit a “Don’t walk” signal anyway. This could save pedestrians perhaps 20% the time wasted standing on corners and breathing in fumes on each walk trip. What’s required for this?
Well, obviously a watch with haptic feedback. Such already exists.
More importantly, we would need a real-time advance feed of when traffic signal phases changed, and their control plan. This is more difficult, since so many signals are “adaptive” to real time traffic. Many however are fixed time and amenable to this. There are a few examples, but they are newsworthy, not widespread. This should be standardized.
We would also need some API that would read the standardized signal feeds and match them against a Directions/Map app, and GPS, on the watch.
So the most interesting thing here is that the simplest of these technologies (the traffic signal) is the last one to be implemented. We have satellites, we have computers on our wrists, we have wireless telecommunications, but we don’t know the timing of timed lightbulbs in most of the world.
NB: This traffic signal timing feed technology also has obvious applications for cars and trucks, which could speed up (potentially, subject to speed limits and prevailing traffic) or slow down (which is more interesting, as they can make a green wave by driving slower, and thus save energy and aggravation), or re-route, if they knew the green lights in advance.
There are some traffic signal feeds out there, but I don’t see standardization, I see proprietary standards. Some articles from a quick search. Mostly related to the company Connected Signals.
Professor of transport at the University of Sydney David Levinson said changing the way Sydney’s traffic signals give priority to cars over pedestrians in busy areas was one way to stem the flow of injuries.
“This inequality [in traffic light phasing] undermines many of the stated goals of transport, health and environment policy,” Professor Levinson said. “Creating an environment that is better for pedestrians with separated footpaths, easy and frequent safe road crossings, generally slower cars and trucks, better trained and more law-abiding drivers (via police enforcement) will reduce the likelihood of fatalities.”
Road deaths have been increasing in both NSW and the US recently, while most other OECD nations are reporting fewer fatalities.
One theory [Referring to: Chi, Guangqing, Jeremy Porter, Arthur Cosby and David Levinson (2013) The Impact of Gasoline Price Changes on Traffic Safety: a Time Geography Explanation. Journal of Transport Geography 28 1-11. [doi] ] is that as more people can afford to be on the road, drivers with less experience, who tend to be younger, and therefore more dangerous, are added to the mix of motorists.
“When there’s economic expansion, people are working more hours and they probably get a bit more aggressive,” Professor Levinson said.
Research [by Wes Marshall] comparing Australian and American drivers found the rate of fatalities was more than twice as high in the US, where more than half of drivers do not stop or yield to pedestrians at crossings.
In Hawaii’s capital Honolulu, fines for pedestrians who text while crossing the road at traffic lights began this year.
In the City of Sydney, one in three people crossing the road is using a mobile phone and it’s time pedestrians “start owning this problem as well”, Pedestrian Council chief executive Harold Scruby said.
“Pedestrian deaths and serious injuries are going through the roof,” Mr Scruby said. “There is nothing that we’re seeing that the government is doing to help pedestrians.”
Hitting pedestrians with a $200 fine for using a mobile phone while crossing the road, even on the green man phase, is on Mr Scruby’s agenda.
“There’s no barrier there just because the light’s green. Half of the drivers coming towards you are on the phone too,” Mr Scruby said. “If you’re hit as a pedestrian, the driver will be automatically drug and breath tested but that’s a box they [police] have to tick, no one then goes looking for the mobile phone, there’s no box to tick.”
Professor Levinson said fining pedestrians was “basically a form of victim blaming”.
“Distracted pedestrians don’t kill drivers or passengers. Distracted drivers kill pedestrians,” he said. “Deaths are due to high speed and high mass, and drivers of two-tonne machines have an obligation to be more alert.”
In the three years to 2017, one pedestrian was killed and 25 were seriously injured while distracted by a mobile phone. But this is likely to be an under-reported issue, as it relies on witnesses telling police and other forms of evidence.
There are no plans to introduce penalties for people using mobile phones while crossing roads in NSW, a Transport for NSW spokesman said.
(The answer is it doesn’t work in the CBD during the day).
My quote:
Monetizing the beg button
Professor David Levinson from the School of Civil Engineering at the University of Sydney said traffic signals in the city should be shifted to be more pedestrian friendly to encourage more walking.
“Traffic signals give priority to motor vehicles over pedestrians. This inequality undermines many of the stated goals of transport, health and environment policy,” Professor Levinson said.
“Sydney uses adaptive signals so that they’re designed to maximise the throughput for cars and so they’ll extend the green light for cars but that results in there being more ‘don’t walk’ time for pedestrians.”
Traffic engineers have developed terminology to aid in communication
The ‘approach’ is the set of lanes that are coming into a particular intersection, from a given direction. So, there might be an eastbound approach of traffic that is moving in the easterly direction. A ‘cycle’ is the complete amount of time that it takes to go from a red light to a red light. We think of it as a clock. ‘Cycle length’ is the amount of time it takes to complete a cycle, measured in seconds. A ‘phase’ is part of a cycle that is allocated to a particular movement, which receives the right-of-way. There might be multiple movements that receive right-of-way simultaneously, as long as they are not conflicting. The northbound and southbound movements might both get the green light at the same time. They’re on the same phase, and they’re not conflicting.
“What do you do with right (left – in right hand drive countries) turns?” Do you give them a separate phase? Or do they share the phase? If they share the phase, then it becomes more complicated. There are many possible patterns, from which traffic engineers aim to select the ‘optimal,’ but that depends on the objectives and conditions.
There are ‘movements’. ‘Protected’ movements have right-of-way, and don’t have to yield to any other conflicting movements, opposing vehicles, or to pedestrians. The ‘permitted’ movement is most common for right turns (in left-hand drive countries like Australia), for instance when making a turn without a green arrow, the driver has the permission to make that movement, so long as it is safe, but is not protected by a red light in the conflicting direction. Left turns are also permitted if there are no conflicting pedestrians or bicyclists.
‘Lost time’ occurs at the start of the phase because the first car has to accelerate from a dead stop, which takes some time: drivers first perceive the green signal, then check to make sure the intersection is clear, and then accelerate from a stop. So the speed at which that first (and second, and third) car goes through the intersection is slower than subsequent vehicles. There is also lost time at the end of the phase as some drivers are reluctant to go through on an amber (yellow) signal. There is also an ‘all red’ phase in some places to make sure the intersection is fully cleared of vehicles and pedestrians.
While working on another piece, I came upon the question of how much time is spent at traffic lights, for which there is not a well-sourced answer. I posted to Twitter and got some useful replies.
Transport Twitter: What percent of total travel time is spent stopped at traffic lights? Empirical results please.
With that and some additional digging, I attempt to answer the question.
As the saying goes: Your Mileage May Vary. This depends on your origin and destination and path and mode and time of day and local traffic signal policies and street design. Tom VanVuren notes: “Much of the impact is in slow moving queues, rather than waiting for the signal cycle to complete. I expect you can make this number smaller than 10% (time at the stop line) or larger than 50% (time affected by traffic lights).” For simplicity, I am considering vehicles that would be stopped if they could either move at the desired speed or must stop (i.e. they are subject to “vertical” or “stacking” queues), but clearly measurement will depend on assumption. Still, there must be a system average. I had heard the number 20% bandied about, which feels right, but let’s first begin with some thought experiment, then look for some empirical results. We take different modes in turn.
Pedestrian Crossing at Broadway and City Road, Sydney. Pedestrians crossing against the light.
Motor Vehicles
Thought Experiments
Thought Experiment 1 A
Imagine an urban grid.
Assume 10 signalized intersections per km.
Assume a travel speed of 60 km/h when in motion. (This is probably too high with so many intersections and no platooning, but we are imagining here that you would not be stopping.)
Time to traverse 1 km=1 minute + signal delay. (Some of the distance traversal time overlaps some of the signal delay time, but we will imagine a stacking queue, rather than one that has physical distance for simplicity, we can correct this later if it matters.)
Assume each intersection has only 2 phases.
Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions. So red time = 1/2 cycle length.
Assume 1 minute cycle length
If a vehicle stops, it waits 1/2 red time.
Vehicles obey traffic signals.
Assume no platooning.
This means that the average vehicle will stop at 5 intersections for 15 seconds each = 75 seconds (or 1.25 minutes) (vs. 1 minute in motion time). In this case, 1.25/2.25 minutes (55.5%) is spent waiting at signals.
Thought Experiment 1 B
In contrast.
Assume near perfect platooning.
In this case, the vehicle will stop at 1 intersection per km, for 15 seconds = 15 seconds. In this case 0.25/1.25 = 20% of the time is spent waiting at signals.
Discussion
Now, not all travel takes place on an urban grid.
Assume 25% of travel is on limited access roads (this is approximately true in the US), 75% on non-limited access roads.
With perfect platooning on the grid, and 25% off-grid, then 15% of travel time is intersection delay with near perfect platooning.
Clearly in practice platooning is far from perfect. My guess is the green wave breaks down after one or two intersections during peak times, but can survive well in the off-peak. As a rule of thumb, about ~10% of travel is in the peak hour, ~30% peak period. ~60% AM + PM Peak.
Data
GPS Studies
Eric Fischer of MapBox was kind enough to offer to run this question on their open traffic data. The results are not yet in. I will update when they are.
Arterial Travel Time Studies
There are a variety of Arterial Travel Time studies for specific corridors, but nothing that is universally generalizable. (And logically where people do arterial travel time studies, there is a congestion problem, otherwise why study it.)
I recall that in my childhood, I did a study in Montgomery County, Maryland using such data (from 1987 traffic counts and a floating car study published by Douglas and Douglas), I did not actually compute the percentage, but fortunately I reported enough data that allows me to compute the percentage now. (The sample is of course biased to what is measured). For the average arterial link, the speed was
Variable
Inside the Beltway
Outside the Beltway
Speed (km/h)
34.88
41.60
Length (km)
0.46
0.72
Time (min)
0.792
1.04
Downstream Delay (min)
0.27
0.24
Percentage of Signal Delay
25%
18.75%
Which is consistent with expectations that signals are more significant in more urbanized areas (inside the beltway is basically Bethesda and Silver Spring, MD), and with our general estimates. Now of course the speed here is impacted by downstream signals, and so is lower than the speed limit and certainly lower than the free-flow speed sans-signals. More details are in the paper.
The percent of time of vehicle idling ranged from 20-25%. (Not all vehicle idling is at signalized intersections).
(Engine idling of course burns fuel without doing work, so if the engine is going to be idling for an extended period, it would save fuel (and reduce air pollution) to turn it off. Turning the engine on and off also has costs, so the estimate was if idling was going to be longer than 10 seconds, it uses more fuel, but considering other wear and tear costs, the recommended threshold is if idling is longer than 60 seconds, then turn off the engine. But at a signalized intersection, how will vehicles know how long they will wait? Smart traffic signals with connected vehicles could provide this, but now they don’t. Eventually this will be moot with a full electric vehicle fleet. Until that time, it matters. I suspect given the longevity and sluggishness of the traffic control sector, smart signals informing trucks will not be widely or systematically deployed before trucks are electrified.)
Pedestrians
Now as noted above, Your Mileage May Vary. If you are a pedestrian, you are unlikely to hit a greenwave designed for cars, though of course your travel speed is slower is well. So redoing the Thought Experiment
Thought Experiment 2
Imagine an urban grid.
Assume 10 signalized intersections per km.
Assume a travel speed of 6 km/h when in motion. (this is a bit on the high side, average pedestrian speed is closer to 5 km/h)
Time to traverse 1 km=10 minutes + signal delay. (Some of the distance traversal time overlaps some of the signal delay time, but we will imagine a vertical stacking queue, rather than one that has physical distance for simplicity, this is a much better assumption for pedestrians than vehicles.)
Assume each intersection has only 2 phases.
Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions. So red time = 1/2 cycle length.
Assume 1 minute cycle length
If a pedestrian stops, she waits 1/2 red time. (That is the “walk” phase for pedestrians is as long as the green phase for cars. Strictly speaking this is not true, it is more true in cities with narrow streets than it is in suburban environments with wide streets, as narrow streets can be crossed more quickly, so the amount of “walk” time allocated can be most of the phase. This is certainly not true in Sydney, where the “walk” phase is cut short so turning cars have fewer conflicts with late pedestrians.)
Pedestrians obey traffic lights. (This is not as good an assumption as vehicles obey signals, pedestrian signal violation is probably higher. This is not a moral judgment one way or the other, people tend to obey authority, even when authority abuses power.)
Assume no platooning. (This is probably too severe, a quick pedestrian with some signal coordination can probably make a couple of lights in a row).
Here the average pedestrian will stop at 5 intersections for 15 seconds each = 2.5 minutes (vs. 10 minute in-motion time). In this case, 2.5/(2.5+10) minutes (or 20%) is spent waiting at signals. Now, this number is probably true for more pedestrians than the vehicle delay estimate is for vehicles, since pedestrians are more likely to be found on an urban grid and less in a suburban or limited access environment. (Self-selection at work).
Bicyclists
If you are a bicyclist, you are unlikely to hit a greenwave designed for cars unless you travel at exactly an integer fraction (1/1, 1/2, 1/3) of the green wave, as your travel speed is slower is well. So redoing the Thought Experiment
Thought Experiment 3
Imagine an urban grid.
Assume 10 signalized intersections per km.
Assume a travel speed of 20 km/h when in motion. (This is a typical for experienced riders). Time to traverse 1 km=3 minutes + signal delay. (Assume a stacking queue)
Assume each intersection has only 2 phases.
Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions. So red time = 1/2 cycle length.
Assume 1 minute cycle length
If a bicyclist stops, she waits 1/2 red time. (That is the ‘bike’ phase for bicyclists is as long as the green phase for cars.)
Bicyclists obey traffic lights. (This is not as good an assumption as ‘motor vehicles obey signals’, bicyclists signal violation is probably higher.)
Assume no platooning. (This is probably too severe, a quick bicyclists with some signal coordination can probably make a couple of lights in a row).
In this case the average bicyclists will stop at 5 intersections for 15 seconds each = 2.5 minutes (vs. 3 minute in-motion time). In this case, 2.5/(3+2.5) minutes (or 45%) is spent waiting at signals in an urban environment.
Strava Data
Strava, an app for tracking bicyclists and runners can produce some useful data. Andrew Hsu, e.g., reports “28 mile bike commute. 1:30-ish moving time. 10-15 minutes waiting at lights.” From this, for him, we estimate 15 / (15+90) = 14%. To be clear, 1:30 is an extreme commute. I don’t have access to the full database, and obviously this is biased by the nature of the trip.
Satellite Image of Improvement of Broadway – City Road Intersection
In the second half of 2017, I supervised a first year undergraduate student Tingsen Xian on an independent student project to redesign the intersection of Broadway and City Road in Sydney.
At one corner of this intersection is Victoria Park (lower left) and the University of Sydney (just off site), at another is the Broadway Shopping Center. This intersection has a high pedestrian count, high bus count, reasonably high car count, is very wide (befitting the name “Broadway”), and has long delays, especially for pedestrians. The proposed alternative removes the free left turn and porkchop island on the southwest corner, gives more space to pedestrians, buses (red), and bicyclists (green), and less space to cars, and the signal retiming reduces total person delay by 1.5% (a lot for pedestrians, while increasing it somewhat for car users), and sends the right incentives. The revised layout is shown in the image.
You can download the full report with more graphics, tables, and yes equations here: broadway-city-road.
[Obviously there are simplifying assumptions in any engineering analysis, and limited measurements and time to conduct the study, but I think the results are better than official results which don’t consider pedestrian delay when timing intersections. It suggests professionals should be able to do a lot better than they have done here.]
“Ultimately, the decision whether or not to implement a system such as this along the Green Line would need to be made by Metro Transit’s project team,” said Kari Spreeman, a spokeswoman with the St. Paul Department of Public Works.
David Levinson, an engineering professor at the University of Minnesota who specializes in transportation issues, has blogged about “Always Green” on his website, Transportationist.org.
“It’s an interesting idea,” Levinson said. “Even if the total travel time is the same in both cases, it’d be better than going fast and then stopping. You might even save some time. After you stop, you have an acceleration-deceleration loss (in travel time).”
Levinson acknowledged one drawback, however. “It’s never been tested,” he said.
David Levinson, a transportation expert at the University of Minnesota, says the Always Green Traffic Control has potential.
“I think it would work best for isolated intersections on rural expressways, but there is no reason it couldn’t work in an urban area,” Levinson said. “Static speed signs have been used for decades on Connecticut Avenue in Washington, D.C. Something dynamic should do even better. I do believe it warrants a field test.”
Musachio faces the challenge of getting somebody to do just that. He’s been bending ears of the St. Paul Public Works Department, but so far they have not bitten.
“In theory the system could work, but it has not been tested in a real environment. Until that happens, we won’t consider it,” said city spokeswoman Kari Spreeman.
“You can either change the lights to match the vehicles,” said David Levinson, a civil engineering professor at the University of Minnesota. “Or you can change the vehicles to match the lights.”
Levinson said keeping cars moving at a steady speed is optimal for traffic flow. But he said it takes a lot of coordination and a tightly-maintained fixed traffic system to create a grid of alternating, forward-moving platoons of cars and trains.
Though Musachio is certain the system would work “perfectly” with the Green Line, David Levinson, associate professor [sic] in the Department of Civil Engineering [double sic], isn’t so sure.
“The Green Line is all tied up in politics,” he said.
Levinson said the system warrants a field test but believes a rural or suburban traffic signal is the place to start before it moves to an urban area.
The development at the intersection of Franklin and Lyndale Avenues in Minneapolis has gotten a lot of attention, but primarily because of buildings proposed at the corners, to replace under-developed buildings at this highly accessible, emerging locale.
The intersection itself has gotten little consideration. It is an at-grade 4-way traffic signal. However, Franklin Avenue finds itself in a valley at Lyndale, such that a 3-dimensional option presents itself.
Urbanists are often aghast at the notion of highway overpasses in cities, and certainly most have been done poorly with no respect for urban form. But that is no reason to throw out the concept altogether.
Using my extensive computer drafting skills, I present two diagrams. The Plan view (from above) and Side view (facing west) illustrate a concept in cartoon fashion. These are, as they say, not-to-scale and obviously not engineering diagrams.
Frank-Lyn conceptual reconfiguration – Plan View
The top diagram shows how the middle two lanes on Franklin Avenue (the left lanes Eastbound and Westbound) bridge over Lyndale Avenue (the blue bar represents the bridge). Since there are already two lanes, additional land required is only for bridge barriers, and hopefully that is minimal. Lanes can be narrowed as necessary.
This does several things. It gets cross-traffic on Franklin (going to or from Hennepin mostly) off of Lyndale. This reduces pressure on Lyndale itself, reduces traffic delay, reduces pedestrian delay, reduces bicyclist delay, reduces pollution at the intersection, reduces street crossing times for pedestrians on Lyndale going North or South (there are two fewer lanes to cross). A median boulevard could be added to Lyndale (the green bars).
The intersection of Franklin and Lyndale thus becomes an urban diamond.
There would be an option to eliminate some or all left turn movements as well, and make Lyndale more Boulevard like with no at-grade cross traffic from Franklin. The intersection could be just right-in/right-out for motor vehicles. Pedestrians could be given a Hawk signal if they wanted to cross Lyndale, with a median refuge island. The purple bar shows this region.
The downside is making it more difficult to access businesses on Lyndale (e.g. The Wedge Co-op) which are already difficult to access by car.
But even if there were left-turns allowed, traffic would be much lighter at the intersection.
Franklin Avenue at Lyndale Avenue looking Westbound (side view)
The second diagram shows a Side view / cross-section. The idea here is not the particular architecture or building heights, but to illustrate that just because there is a 2 lane overpass, the underside of the bridge can have a pedestrian serving business (that is no more than 26 feet wide). (This need not be a cafe, but in every urban rendering I have ever seen, there are cafes, so there must be a reason).
Previous posts have discussed the underside of bridges before (1) (2). We don’t do this well here, but it doesn’t mean it can’t be done well.
Most intersections are not situated such that 3-dimensions is such a natural solution, but there are some, and we should consider the possibilities.
Full disclosure: I don’t live very near there, and only use the intersection occasionally as a motorist.
David Levinson, Transportist 
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