Tag Archives: Transit Reliability

Let’s Go Glendale!

Having bid a fond “see ya around” to Palms, we turn our eyes to observing Glendale and getting to know this part of the LA region better. An outcome of LA’s legendary traffic and underpowered transit is that it can be punishing to try to experience parts of the region far from where you live. The Valley isn’t that far from the Westside, but the 405 makes it seem far. That problem certainly applies to travel between Palms (the Westside) and the Burbank-Glendale-Pasadena area, which stands out even among the many difficult trips in the region.

For readers outside Los Angeles and not familiar with its confusing municipal boundaries, we should perhaps first explain where Glendale is located. Glendale is a separate incorporated city, not part of the City of Los Angeles. Downtown Glendale is about 8-9 miles due north of downtown Los Angeles, though the city’s northern reaches extend over 15 miles from downtown LA. Glendale borders the cities of Burbank, Pasadena, and La Canada-Flintridge, along with an unincorporated neighborhood of LA County known as La Crescenta-Montrose. Glendale also shares two borders with the City of LA – Sunland-Tujunga to the northwest, and Atwater Village, Glassell Park, and Eagle Rock to the south. Lastly, Glendale’s northern limits extend up to the Angeles National Forest in the San Gabriel Mountains. The Verdugo Mountains separate downtown and the southern part of the city from the northern part, located in the Crescenta Valley, a narrow valley between the Verdugos and the San Gabriels.

An unconventional way to define Glendale might be as the valley of the Verdugo Wash. This is a short tributary of the LA River that joins the river near where it takes a sharp right turn from running west to east through the SF Valley and heads south to downtown LA. Like the LA River, it is fully contained in a concrete flood control channel. The Verdugo Wash runs east to the north of downtown Glendale, then gradually turns northeast, north, and northwest as it wraps around the mountains of the same name into the Crescenta Valley. Everything south of the 134 – all of downtown Glendale and many residential areas – actually drains away from the Verdugo Wash, but topography makes one suspect that this area is sort of an alluvial fan deposited by the stream. There might be potential for improvements to the Verdugo Wash like those proposed for the LA River.


The primary freeways serving Glendale are the 5, the 2, and the 134, which roughly form an upside down triangle around downtown Glendale. Despite serving Glendale, these portions of the 5 and the 2 are almost entirely in Los Angeles. North of the 134, the 2 continues north through the more mountainous portions of the city, ending at the 210, which serves the Crescenta Valley.

Traffic on the 5 is perhaps not quite as bad as the 10 and the 405 on the Westside, but it’s bad enough. Since the 5 runs the full length of the Golden State, it seems to have a larger volume of background traffic, and a notably higher amount of truck traffic – even if your carpool, like mine, leaves at 5 am. Truck traffic is probably increased by the gap in the 710, which eliminates a potential route around downtown LA between the ports and destinations to the north.

The 134, together with the 101 in the Valley and the 210 east of Pasadena, forms a long, continuous east-west freeway stretching from Ventura to San Bernardino, another heavily used corridor in a region with no shortage of well-used freeways. While the 101 and the 134 in the Valley and the 210 east of Pasadena get heavily congested during peak periods, the 134 between Glendale and Pasadena seems to escape the worst traffic. Astute eyes will note that the short Colorado Street freeway, connecting the 5 to San Fernando Rd and Colorado St in Glendale, looks like an abandoned attempt at routing the 134 through the heart of downtown Glendale. In fact, Caltrans’ small white bridge identifying signs still mark these structures as being located on the 134, so there’s potentially a companion post to Walk Eagle Rock’s post on the 134 being rerouted to avoid downtown Eagle Rock. The selected route for the 134 is not only better for downtown Glendale, but much better for a freeway network than the puzzling location of the Colorado St freeway’s end at Griffith Park.

The 2 is perhaps best known for the portion of the freeway that wasn’t built – the portion from the existing end in Echo Park to the west, through Hollywood, Beverly Hills, and Century City to the Westside. This leaves the extant part in Northeast LA and Glendale as one of the more lightly used parts of LA’s network, though congestion on connecting freeways like the 5 can turn parts of it into a giant queue. It’s also the reason it’s hard to get to the Westside from Glendale in the absence of good transit options.


Ok, enough about freeways, let’s get on to the things that will really interest readers here: transit. At first glance, your LA Metro map makes things look pretty good.


However, what we have here is a classic case of wide coverage with relatively poor frequency. Here’s a look at some important routes serving Glendale.


Routes 90 & 91 serve Glendale Ave, which runs to the east side of downtown and the Crescenta Valley. Route 92 serves Brand Blvd, which is Glendale’s main commercial street. Route 94 & Rapid 794 form a very long route from downtown LA to the independent City of San Fernando, near the northern end of the eponymous Valley. This serves only the western edges of Glendale, but it’s the closest route to me. Finally, Routes 180 & 181, & Rapid 780, serve east-west travel between Pasadena, Glendale, & Hollywood.

Evening and late night headways fall off pretty quickly, making it tough to depend on these routes if you want to do anything other than work your 8 to 5. The two Rapid routes, 780 & 794, don’t run at all late nights or on weekends. Rapid 780 runs with good peak frequencies, and because it’s through-routed as the Rapid for both Routes 180/181 and Route 217 (Fairfax), it sort of functions as the transit route doing what the 2 freeway was supposed to do. (Don’t bother with Route 201, which only runs hourly.) Therefore, when Rapid 780 isn’t running, riders face an additional transfer between Routes 180/191 and Route 217. On top of that; there are the usual reliability issues; on a recent weekday morning my Next Trip app promised 794 service in 42 minutes and 57 minutes. You can sort of see why the BRU complains about this when rail riders get 10-12 minute headways all day, every day.

On the rail side, Metrolink offers a Glendale station at the very southern edge of the city, adjacent to Atwater Village. Frequencies during peak periods are pretty good – there are 30 trains per day – but service ends early, going to hourly or worse at about 6:30pm and ending altogether at 9:30pm. The worst feature of Metrolink is the absurd pricing; a one way ticket from Glendale to Downtown LA is $5.50 to travel a distance of 6 miles, a distance you can double or triple on Metro rail lines for $1.75.

The upside of all of this is that there’s a lot of low-hanging fruit for transit improvements in the area – things that don’t involve, say, building an expensive underperforming light rail line to bridge the gap in the 710 freeway.

As a first take, transit improvements should include improving frequency and spans of service. Options to improve reliability, such as bus lanes and signal priority, should also be explored. On the rail side, Measure R2 plans should explore upgrading these Metrolink Lines to rapid transit frequencies, though that should probably be contingent on upzoning some of the land near the rail corridors.

Development Patterns

Speaking of development, let’s talk a little bit about the built environment in Glendale. As mentioned before, Brand Blvd serves as the heart of downtown, with Glendale’s small skyscraper district (five buildings of 20+ stories, six more of 15-19 stories, almost all outcomes of the late 80s boom) centered on Brand and the 134 freeway. Downtown Glendale has been undergoing a residential and mixed-use mini-boom, with Americana at Brand being the best known development. Since there are many projects in progress or recently completed, it’s probably worth doing two separate posts, one on the commercial projects built in the 1980s and early 1990s, one on the ongoing residential projects. Some people deride Glendale as boring, but having spent a couple evenings on Brand Blvd, I’m willing to say they either don’t know what they’re talking about or are using “boring” as code for “full of retail establishments but not the kind that I like”.

Outside of downtown, there are residential neighborhoods that are actually somewhat similar to, well, to Palms. The residential density of the Census tract I moved to is only a little bit lower than that of the tract I moved from. The biggest difference is that the percentage of single-family residences (SFRs) in my new neighborhood is higher than in Palms, where you might miss the remaining SFRs if you didn’t know where to look. The apartment building stock in Glendale also appears to be newer, with few dingbats and more apartments dating to the 1980s boom, something supported by a casual look at Property Shark. Nevertheless, I’ve done the math, and my apartment building’s 9 units on a 50’x150’ lot are exactly classic R3 dingbat density. When I walk around, though, none of the remaining SFRs are being replaced by apartments, and at first glance the zoning appears to make even existing apartments non-conforming. I’m sure there’s a fascinating story behind that, one we’ll no doubt have to explore in more detail in a future post. . .

H8ers Gon H8: BART Strike Edition

Well, here we are, about a month after my post Shuttle Envy, and with BART transit workers on strike, the shuttles, along with apps like Uber and Lyft, are back in the news. Kevin Roose published a piece postulating that the rise of the shuttles and ride-share apps is contributing to the poor quality of public transportation services, and eliminating the incentives for policy makers to improve service. Matthew Yglesias and Reihan Salam, with an assist from Stephen Smith of Market Urbanism, do most of the dirty work in showing that the shuttles and apps are largely irrelevant to the quality of Bay Area public transit. Salam’s third point is essentially what I was saying in Shuttle Envy.

However, I’d go two steps further. First, it is a dubious proposition that because a wider cross-section of people in NYC use transit, a transit strike would be more effective in getting politicians to improve service. Rich people in New York have other options too – that’s one of the advantages of being rich. And as Salam says, poor people in New York have other options, like the dollar cabs and Chinatown vans. Note that these services are also mercilessly attacked by both the taxi cartel on one side and public transit services on the other, for stealing ridership, but since they serve low-income people instead of Silicon Valley Millenials, they’re not ripe targets for progressive equity and social justice attacks.

But even beyond that, the whole issue at hand here – the BART strike – has literally nothing to do with the quality of public transit services. The unions are asking for higher pay, smaller health care cost increases, better pension benefits, and some tangential safety items. They are not asking for proof-of-payment fare collection, or modern signaling and driverless trains, or better maintenance practices, or any of the many things that would have a positive impact for riders. If management gives in to all of the union’s demands, the quality of BART will be exactly the same as it was June 30.

And that brings us to one of the real problems with public transit in the US, the heart of the Shuttle Envy post: the first step to fixing a problem is to admit that you have a problem and that not exercising control is part of the problem. Public transit services in the US are not poor because Mark Zuckerberg runs private shuttles, they’re not poor because Lyft stuck a bunch of pink mustaches on the fronts of cars, and they’re not poor because BART management is holding out against the unions. They’re poor because we allow them to be and don’t demand any accountability.

Transit Performance Metrics

A recent tweet from Market Urbanism about bus bunching early along the route of the B35 got me thinking about the ways we measure transit performance. Given the bias towards big capital projects in the US, it’s not surprising that our service performance metrics can be a little underpowered. I couldn’t find a service policy for NYCMTA on their website, but I did scare up LACMTA’s 2011 Transit Service Policy for here in Los Angeles and the MBTA’s 2010 Service Delivery Policy for Boston. If anyone knows where to find a similar standard for NYCMTA, I’d be happy to update this post to include it.

Note: for this post, I’m talking only about measuring the operational quality of the transit services we have chosen to provide, not the quality derived from things like span of service, frequency of service, and coverage of service, and not measures of efficiency that are also sometimes conflated with quality.

LACMTA’s policy on service quality is remarkably brief (see page 33 of the pdf). Quality is measured by on-time performance (OTP), with a  target threshold of 80%, and the volume of customer complaints, relative to an established baseline that references complaints on the poorest performing routes in 2008. This shows that the tools for measuring transit performance in Los Angeles have not yet caught up to our increasing dedication to expanding the system, as manifested by Measure R.

OTP is the easiest thing to measure, but unfortunately, for many transit services, it’s the least relevant to passengers. On-time departures and arrivals are important for long headway services, like commuter rail and low-frequency bus, where passengers time their arrivals at the stop to a published schedule. If you use a service that comes every hour or half-hour, like say Metro Local 158, you don’t just roll up to the stop whenever and wait for a bus. In this case, the bus being late translates directly into delays for you.

A Better Way to Measure Long-Headway Service

For long-headway transit, problems during the peak period have more of an impact on the perception of service quality than problems late at night, because more people are riding during peak periods. A late trip during the peak period delays more people than a late off-peak trip. Therefore, for long-headway service, we should look at the passenger-weighted OTP.


Where OTPi is the on-time performance for trip i, and ni is the number of passengers on trip i. For example, consider a commuter rail service with 5 peak period trains carrying 1,500 people each, and 15 off-peak trains carrying 100 people each. Under conventional OTP, if any one of the trains is delayed, OTP will be 95%. With PWOTP, a delay to a peak period train results in performance of 83%. A delay to an off-peak train results in performance of 99%.

Now, you could have 4 off-peak trains be delayed and still meet a 95% PWOTP threshold, and that doesn’t seem like great service either. So I think the way to go for long-headway services is to say both OTP and PWOTP need to meet a policy threshold. The current policy, which is just OTP, lets operators meet their standards by running a bunch of on-time trips late at night to make up for things being fouled up during rush hour.

What’s Important For Short-Headway Service?

If we’re talking about short-headway service, OTP of individual transit vehicles doesn’t really matter. What matters is headway regularity and travel-time reliability.

Headway regularity is important on a short-headway service because passengers don’t time their arrivals at the stop to the schedules for individual trips. The Blue Line runs every 6 minutes during rush hour, so if you need to ride, you just go the station, knowing that it will never be very long until a train comes – as long as the headways are hewing to the schedule. So for the Blue Line during rush hour, a much better performance metric is something that relates to headways. Note that if headways have become irregular, not many people are going to be on the trips with a short headway, but a lot of people are going to be stuck waiting for the trips with a long headway. Therefore, the long headway trip is more important to perceptions of service quality.

Travel-time reliability is pretty self-explanatory and serves as a substitute for OTP for short-headway services. If a specific trip departs five minutes late and arrives five minutes late, that’s irrelevant from a passenger’s point of view if the headway regularity is good.

Now back to Market Urbanism’s tweet. Note that if your service performance metric is OTP, your dispatchers might be incentivized to pursue operational strategies that make the service worse for your passengers.

Let’s consider a simple example. A bus route operates on 10 minute headways. The buses operating trips A, B, and C are approaching one end of the route, where they will turn for trips A’, B’, and C’. Due to disturbances along the route, trips A and C are 9 minutes behind schedule, meaning that trip B is on-time and only 1 minute behind trip A. The best thing to do for passengers would be to hold the bus operating trip B at the end of the route for 9 minutes, and start trip B’ 9 minutes late, because this would restore 10 minute headways for B’ and C’.

However, if the only performance metric is OTP, this strategy will make the apparent quality of service go down, because now B’ is late as well as A’ and C’. This encourages dispatchers to boost OTP by sending out B’ at the scheduled time, even though it will make things worse for passengers. Note that this strategy is also detrimental to travel-time reliability, because the long headway in front of C’ will ensure that it faces a higher than normal passenger load, further throwing that vehicle off schedule.

How Should We Measure Short-Headway Service?

The MBTA’s policy is a step ahead of LACMTA regarding short-headway service, because it uses headway-related metrics for all rapid transit services, and for bus services that operate at a headway of 10 minutes of less. It also uses trip-time metrics for these service. The MBTA’s policy (see pages 10-11 of the pdf) is for trips to operate within 1.5 times the scheduled headway, and within specified ranges relative to scheduled travel time.

That’s much better than OTP, but it’s not sensitive to the magnitude of headway variability. I can think of a few other things we ought to measure to get a really good picture of service quality. For short-headway service, we should look at the passenger-weighted average wait time (PWAWT), passenger waits exceeding threshold (PWET), passenger-weighted excess wait time (PWEWT), or standard deviation of headway.

Passenger-Weighted Average Wait Time (PWAWT)

PWAWT is just a weighted average of how long passengers weight. An unweighted average would just be equal to half the scheduled headway, regardless of headway variability. The weighted average accounts for the fact that more people wait for the longer headway trip. PWAWT will always be greater than half the schedule headway.


Where ni is the number of passengers on trip i, and hi is the headway on trip i. Note that for the short-headway services, we are assuming uniform passenger arrivals  during each interval between trips, which allows us to assume the average weight time for each trip is 0.5hi. If we assume that passenger arrivals are uniform throughout the entire period in question, then the number of passengers is just a linear function of the headway, and we don’t even need to know how many passengers are on each trip. It should go without saying that the schedule headway must be constant throughout the period in question if we are using PWAWT.

Passenger Waits Exceeding Threshold (PWET)

PWET, the percentage of passengers whose wait exceeds a threshold, could be used if we wanted to look at a period without a constant headway, like the entire day. The threshold could be absolute, e.g. must wait longer than headway plus 2 minutes, or relative, e.g. must wait longer than 1.25 headways. For the example below, I’m going to set the threshold at headway plus 1 minute, because you start to get annoyed about waiting pretty quickly when your wait goes beyond one headway.


This one’s a little more complicated, so a quick explanation: the denominator is just the total number of passengers. The numerator is an if statement that tells us to do nothing if the headway for trip i is less than the threshold, since no passengers for that trip experienced a wait that was too long. If the headway is greater than the threshold, we add the number of passengers who waited for too long, assuming uniform passenger arrivals during that headway period. Note that if we are looking at a period with variable headways, we probably can’t assume that passenger arrivals are uniform for the entire period, so we need to know the number of passengers for each trip.

The weakness of PWET would be that it treats all delays beyond the threshold the same, when the magnitude is obviously important. Passengers are more annoyed if they have to wait an extra 5 minutes versus an extra 1 minute. PWAWT and PWET together might give a good picture.

Passenger-Weighted Excess Wait Time (PWEWT)

PWEWT would allow for a weighted-average metric that emphasizes the importance of very long headways without requiring headways to be constant throughout the period of analysis. It would be a weighted-average of only the excess wait time, and could be defined either with an absolute threshold or a relative threshold. Relative to an absolute threshold, where hsi is the scheduled headway for trip i:


For PWEWT with a relative threshold of bh, just replace every hsi + a in the previous formulation with bhsi.

Standard Deviation of Headway

An alternate to PWAWT, PWET, and PWEWT would be to use the standard deviation of headway*. For example, if the policy guideline for standard deviation of headway was set at 25% of schedule headway, that would result in a service that met the an MBTA type policy with a 95% threshold, and exhibited less variability than is possible under that policy alone. Standard deviation could only be used for periods with constant scheduled headways.

Note that any of these standards would encourage the dispatchers to pursue operational strategies beneficial to passengers. In the past, it might have been difficult to calculate these statistics and figure out the best real-time operational strategies, but with technology like modern AFC and AVI, it shouldn’t be hard.

Enough Theory, Show Me Some Examples

Continuing from the previous example, let’s assume we dispatch B’ on time and C’ is 9 minutes late. For these two trips, OTP is 50%. By the MBTA’s 1.5 times headway standard, 50% of trips meet the policy. The PWAWT is 9.05 minutes. Therefore, if buses are bunched in groups of two along the route, passengers must expect to wait almost an entire published headway for service. The PWET is 40%. Assuming a threshold of h + 1, the PWEWT is 1.6 minutes.

Now let’s assume that the OTP threshold is 5 minutes, and the dispatcher decides to try to help passengers out without hurting OTP stats, so he holds B’ for 4 minutes. Now, B’ departs with a 5 minute headway and C’ with a 15 minute headway. OTP is 50%, but now 100% of trips meet the MBTA’s policy. The PWAWT is 6.25 minutes, a major improvement. The PWET is 20% and the PWEWT is 0.4 minutes.

Finally, if the dispatcher holds B’ for 9 minutes, then both B’ and C’ depart with 10 minute headways. OTP is 0%, but the PWAWT goes down to 5.00 minutes. PWET is 0% and PWEWT is 0 minutes. Note that most of the improvement comes on the front end of the hold, so even holding a bus for a few minutes can do a lot in terms of headway regularity. This is an important insight because it may be desirable to not hold B’ for the full 9 minutes, in order to save some operational flexibility for later in the dispatch period. A bus that is early can always be held more, but it is very difficult for a late bus to catch up to schedule.

Some thoughts: the MBTA standard isn’t a bad proxy, but it’s still imprecise. A service that swung between 5 minute and 15 minute headways would satisfy the MBTA’s policy, and generate PWAWT of 6.25 minutes and PWEWT of 0.4 minutes. The metrics don’t sound that bad, but this doesn’t seem like a great service. That suggests that we are going to use PWAWT and PWEWT, the standard needs to be pretty tight. PWET makes an important contribution here, because PWET of 20% definitely sounds bad.

I’ve also prepared a more detailed example that looks at these metrics under a somewhat random distribution of buses (as random as my mind can make it on the fly), a moderate bunching scenario, and a severe bunching scenario. The premise is a 10-minute headway service, with OTP threshold of 5 minutes and PWET/PWEWT threshold of 11 minutes. Moderate bunching assumes alternating 5 and 15 minute headways. Severe bunching assumes alternating headways of 1 and 19 minutes. Buses are held for a maximum of 4 minutes under partial holds, and for as long as needed to balance headways under full holds. The results are in the table below. (Contact me if you’d like the source spreadsheet.)



OTP metrics are appropriate for long-headway services, but they should be passenger-weighted. They are inappropriate for short-headway services, which should be measured by metrics like the MBTA’s headway variability standard, PWAWT, PWET, and PWEWT. Agencies should set standards and then define dispatcher procedures that will improve these metrics. As was seen in both the brief example and the detailed example, even when bus bunching is bad, short holds can have a significant impact on improving passenger experience.

Of course, we haven’t broached the subject of what the headway and OTP thresholds should be, but that’s a topic for another time.

*In fact, PWAWT, PWET, and PWEWT can be expressed as a function of the standard deviation.