Election Reflections

It’s been four weeks since the stunning election of Donald Trump as the next president of the US. Every day since then, I’ve woken up feeling, to quote Kevin de León and Anthony Rendon, like a stranger in a foreign land. The result is only not depressing in the moments that it’s terrifying.

I’ve been trying to think of something to say (though that doesn’t explain the silence on the blog, I just haven’t had time). There are some transportation & housing posts in the works, but it just doesn’t seem right to carry on as if nothing is different. Sometimes you have plans, but sometimes larger events intervene. If you were an aqueduct engineer in 410 AD, you’d probably want to pay attention to Rome being sacked, even though it’s not your department.

The outcome of the election was swung by a ridiculously small number of votes – not even half the population of Glendale. No matter what anyone says, they didn’t predict this. It is simply unprecedented for someone to lose the popular vote by such a wide margin (2%, likely over 2 million votes) and yet win the electoral college, excluding the 1876 election which was wracked by fraud, voter intimidation, and political dealing. Because the margin of victory was so small, many seemingly minor things could have affected the outcome, and many people can plausibly claim that their pet issue made the difference. Everything mattered.

Now, on that slim margin of victory, despite Democrats getting far more votes for president, we are set to lurch into the unknown. The obvious short-term problem is a budding kleptocracy; Trump has already been using the presidency to further his business interests. In the long term, it’s hard to know what to expect, though there’s little reason to expect anything good.

Trump’s unexpected win has temporarily suppressed ideological disagreements that had riven the Republican Party throughout the primary and general election. On some issues, like reproductive rights and climate change, Trump and traditional Republicans are in agreement and the only question is how much damage they’ll manage to do. But for others, Trump’s ability to implement his proposals may be restricted. Will Republicans who favored positive immigration reform go along with Trump’s cruel and demented deportation and wall proposals? Will influential lobbying groups like the US Chamber of Commerce and American Enterprise Institute sit idle if Trump tries to impose tariffs or restrict trade? How much of Paul Ryan’s agenda to slash the safety net will be implemented? How much of Obamacare will be repealed, and what, if anything, will replace it?

Trump is a master of deflection and has manipulated the media to great success so far. However, once he takes office, success through propaganda will become much more difficult. Trump made many outlandish promises, and the people who voted for him chose to selectively believe the ones they like and disregard the others. Thus there are Trump voters who want to build the wall, and others who think that was just bluster. There are Trump voters who hope he won’t touch some Obamacare provisions or Medicaid. There are Trump voters who think coal and manufacturing jobs will come back, and there are Trump voters who thought he would buck Wall Street.

How will Trump voters react if no action is taken on immigration? If Obamacare and Medicaid are cut? When the coal industry remains moribund? When Hillary isn’t put in jail? When he deregulates Wall Street and enables predatory financial products?

I’m not sure if Trump actually cares about any of these things, or anything beyond self-promotion. But there are a lot of people who voted for him who do, and Trump has spent the last 18 months whipping them into a fury. If they feel betrayed by Trump, their rage will only grow, paving the way for someone even worse to seize power, the way the Tea Party grew on the supposed betrayal of Bush-era Republicans. Trump seems perfectly content to let the wave of racism and hate he’s called forth roll on, but could he stop it if he wanted to?

In light of all that, it seems a little macabre to focus only on what Trump’s presidency will mean for transportation. The selection of Elaine Chao as secretary of transportation is at least not perplexing or worrying, since it means the post will be held by someone who (a) knows what it is and (b) isn’t dedicated to destroying the agencies under its control. Most likely this means a return to Bush administration policies favoring rural freeways, and reduced federal money for transit. There are probably enough Republicans who want to bring home the bacon to ensure some money for transit, but Trump’s legendary vindictiveness may be bad news for blue state cities that try to fight his terrible policies on other fronts. But again, transportation just seems so inconsequential at the moment.

I’m not quite sure where to go with things from there, but perhaps it can be worked out over the coming months. In the meantime, there are some good transportation & housing posts on the way, and it will feel nice to write about something I can comprehend.

Zoning Constraints & Housing Types

We all know zoning restricts housing supply in cities. However, the type of housing produced will be different for different kinds of zoning regulations. In this post, we’ll explore the impact of three common kinds of zoning regulations: density controls (number of units), height and setback requirements, and floor area ratio (FAR maximums). As we’ll see, while variety of housing is often a stated goal of planning, zoning regulations and market conditions often work to the contrary. Height and setbacks work in the same way as FAR, with one always being more constraining than the other for a given lot.

Method of Analysis

To simplify things, we’ll look at the impact of these three types of regulations on a 50’x150’ (7,500 square foot) lot, which can be found all over LA and Glendale. For LA, we’ll consider the R1, RD3, RD2, RD1.5, R3, R4, and R5 zones as defined by the city of LA. For Glendale, we’ll consider the R1, R3050, R2250, R1650, R1250, and SFMU zones (which roughly correspond to R1, RD3, RD2, RD1.5, RD1.5, and R4). We will look at the number of units and size of building possible on a 50’x150’ lot in each zone, and see the impact on the type of housing produced.

In general, we will see that the lower density zones are constrained by permitted density, which tends to result in the production of only large, expensive housing units. High density zones are constrained by height & setbacks or FAR, which tends to result in the production of only one bedroom (1BR) and two bedroom (2BR) units, leading to the charge that apartment developers don’t build for families.

Los Angeles

The table below summarizes the maximum permitted density, setbacks, and FAR in common residential zones in LA, assuming height district 1L, except for R5 where we assume height district 2, for reasons explained below.


Again, assuming a 50’x150’ lot, the maximum number of units, maximum floor area, and average floor area per unit are as follows. Assumed efficiency means the percentage of building floor area that’s actually usable for apartments. For single-family structures, it can be assumed to be 1.00. For apartments we assume 0.80 for a low-rise apartment in the R3 zone, and 0.70 for mid-rise apartments in the R4 and R5 zones. Efficiency for apartments is less than 1.00 because of space lost to hallways, elevators, common areas, trash rooms, and so on.


LA’s FAR is very generous for low density zones, so height & setbacks rather than FAR end up constraining maximum floor area for all zones except R4. If we had used height district 1L for R5, it would also be constrained by FAR instead of height & setbacks, and would only have an average unit size of 425 SF.

As a practical matter, in the R1, RD3, and RD2 zones, actual building size will be constrained by market conditions. There just isn’t that much demand for houses over about 3,500-4,000 SF. These zones are purely constrained by density, meaning that developers will max out the number of units possible and build the largest units they think the market will accept. Purple City once ran the numbers to show you why developers won’t put small houses on big lots.

The RD1.5 and R3 zones are more or less equally constrained by density and building height & setbacks. For R3, density has increased to the point that average unit sizes have been driven down to about 2,000 SF for a small lot subdivision of free-standing houses and about 1,600 SF for apartments, housing unit sizes that are in high demand. This is probably one reason the R3 zone is popular with small lot developers; the combination of permitted density and floor area doesn’t force the units to be smaller than people want, nor does it force much of the lot to remain as open space.

The R4 and R5 zones are constrained by floor area, whether in the form of maximum FAR or height & setback requirements. If the developer maxes out the number of units, they will only be able to get about 800-900 SF average unit size. This is why large apartment buildings in LA are almost all studios, 1BRs, and 2BRs. If you tried to make a decently-sized 3BR unit, say 1,400 SF, it would have to offset by two units of only 500 SF, or a reduction in total units.

Note that if a development is FAR constrained, parcel assembly doesn’t help with unit size at all, only with making it easier to configure parking ramps, elevators, and other common spaces. If a development is height & setback constrained, parcel assembly will help with unit size by eliminating setbacks between lots, until the point FAR constraints take over.


The analysis is similar for Glendale, but maximum FAR in Glendale is much less, and setbacks and heights are more restrictive. The table below summarizes the maximum permitted density, setbacks, and FAR in common residential zones in Glendale. Setbacks are averages because Glendale has step back requirements for second and third floors.


Again, assuming a 50’x150’ lot, the maximum number of units, maximum floor area, and average floor area per unit are as follows. I’m assuming 0.90 efficiency for townhouses.


Except for R1250, the multi-family residential zones in Glendale are in the sweet spot for townhouses (1,500 SF to 2,000 SF). The R1250 zone would work for small townhouses or 2BR apartments.

For lots over 90’ wide, Glendale allows additional density and another story of height in the R2250, R1650, and R1250 zones. There’s also a mixed-use zone, SFMU, that requires 100’ wide lots. Therefore, the analysis is modified if you assemble two lots. The SFMU zone has maximum height of 60’/4 stories and density 87 units/acre when abutting another multi-family zone, and 75’/6 stories and 100 units/acre when not, so results are presented for both cases. In practice, it is very rare for an SFMU zone to not abut another multi-family zone. The given story heights for SFMU assume half of the first floor is retail space and while max FAR is not specified it can be inferred from story height multiplied by 0.9, since 10% of the lot must be landscaped.


Because density is increased but FAR is not, the average unit size is actually driven down, despite being allowed to make the building one story taller. Of the few multi-lot townhouse projects I’ve followed in Glendale, many of them have not maxed out the density in these situations, electing to build fewer, but larger units. A motivating decision here is probably Glendale’s requirements for 2 subterranean parking spaces per unit, so density may actually be maxed out based on the number of parking spaces you can build in one underground level.

The SFMU zone ends up with larger average unit size than LA’s R4 and R5 zones, and sure enough, you do see some 3BRs in new developments in downtown Glendale. (While not actually in the SFMU zone, most of these buildings are in zones that allow 90-100 units/acre and up to 6 stories by right, so they’re a reasonable proxy.)

Encouraging Housing Diversity

Certainly, cities could increase the diversity of housing production by liberalizing zoning. Increasing allowable density and FAR, and eliminating minimum unit sizes, would allow different developers to try more different kinds of projects. After all, it was more liberal zoning regimes that produced neighborhoods that have a wide variety of housing types, like South Glendale.

Failing that, there are some other policies that might help. The primary concerns seem to be that apartment builders do not build enough family-sized apartments, while townhouse and small-lot builders do not build enough small homes. Some possibilities:

  • Give apartment developers free FAR for every bedroom beyond the second, for a certain percentage of units. Height and setbacks would have to be generous enough to make the extra FAR usable.
  • Add a density bonus for providing 3BR or 4BR apartments; for example, allow 0.20 additional units for every 3BR and 0.30 additional units for every 4BR, up to a maximum. FAR, height, and setbacks would have to be generous enough to make the extra FAR usable.
  • For townhouses and small-lot subdivisions, rezone outlying R1 areas as RD1.5 or R1250. Land in outlying areas is cheaper, reducing the need to max out FAR.
  • Add a density bonus for building small townhouses or small lots; for example, in the RD1.5 zone, allow 1000 SF lot area per unit up to certain percentage of units if they are smaller units.


LACMTA Valley Bus Ridership – September 2016

Here’s our fourth update on ridership on some of the main bus routes in the San Fernando Valley. As a reminder, for north-south corridors, we have San Fernando, Van Nuys, Sepulveda, and Reseda; for east-west, Ventura, Sherman, Roscoe, and Nordhoff.

For more detail on the sausage-making involved in converting routes that cover multiple corridors to a number for a single arterial road, see the first post.

Here’s the raw data. As always, highlighted cells represent top 10 ridership months since January 2009. All routes put up their best months in the 2009-2010 period; this may be due to the recession reducing car ownership.


Here are the 12-month rolling averages for weekdays.


Saturday and Sunday 12-month rolling averages largely reflect weekday trends, as shown below. The previously noted uptick in Reseda ridership on weekends has reversed.


As discussed previously, the configuration of rapid routes on Van Nuys was changed in late 2014. Route 761, a rapid that went from Van Nuys in the Valley through Sepulveda Pass to UCLA in Westwood, was eliminated. At the same time, Route 734, the Sepulveda rapid, was extended from its previous terminus in Sherman Oaks through Sepulveda Pass to Westwood. Rapid service on Van Nuys was replaced with Route 744, a U-shaped route on Van Nuys, Ventura, and Reseda. An express rapid service, Route 788, serving the northern part of Van Nuys and connecting to the Orange Line, then running express on the 405 to Westwood, was also created.


Here is the breakdown of weekday ridership on Van Nuys and Sepulveda by local and rapid on each corridor, and total local and total rapid on the two corridors combined.


Since a longer time has passed, we can now also start to look at the 12-month rolling averages.


The rapid route shuffle seems to have not had much impact on overall ridership trends. Weekday local ridership had already begun to trend down when the shuffle took place.

In contrast, it seems possible that weekend ridership has suffered. While Route 761 ran on weekends, Route 734 never has, and this was not changed when 761 was eliminated. Route 744 runs on weekends, but Route 788 does not; thus on weekends there is now no rapid service from the Valley to the Westside.


Again, we are speculating, but it appears that with the elimination of 761, riders who couldn’t cancel their trips and had no other option to get from the Valley to the Westside shifted to the Sepulveda local route, 234, producing a sudden jump in ridership. The increase in local ridership was smaller than the drop in rapid ridership, so overall ridership has trended down. However, the background trend has been a decline in ridership, so while possible, it is cannot be said with any certainty that the rapid route shuffle caused a decline.

Transit, Ride-Hailing, & Class-Mixing

As venture capital-backed ride-hailing services like Uber and Lyft continue to expand, there has been a lot of speculation on the impact of these services on transit. Will they replace transit services, as riders defect to faster car trips, or will they complement transit services, as riders use them for last mile connections? And, if riders who can afford to defect to ride-hailing services do so, will that lead to a vicious cycle of worsening transit, as decreasing ridership and political leverage cause further reductions in service?

On the first question, time will tell, but it seems like things could go either way. In congested cities, transit has considerable geometric advantages over cars, provided it has its own exclusive or semi-exclusive guideway. However, if transit does not have its own right-of-way or lanes, it offers little advantage over driving, and ride-hailing trips might replace transit trips. This could lead to a socially suboptimal Nash equilibrium, where everyone would be better off if some people took transit but no individual has the incentive to do so. (Ignore, for simplicity’s sake, the potential to introduce congestion charges, or the question if ride-hailing services will be able to scale and be profitable.)

In addition, many smaller cities in the US do not suffer from appreciable congestion, and in these places transit’s geometric advantages are less relevant. Again assuming they can be operated profitably, ride-hailing services might be able to capture some trips in these cities as well.

Does that spell disaster for transit services? I don’t think so. Voters in many US cities have shown their willingness to increase their own taxes to fund capital improvements to transit, even in cities with relatively low transit mode share like Los Angeles, Denver, and San Jose. While funding for operations and maintenance remains a major issue for many agencies, it doesn’t seem unreasonable to think that voters could be persuaded to fund O&M as well. (In LA, at least, some funds from voter-approved measures do go to operations.)

There is also concern that loss of ridership to ride-hailing services would reduce mixing of classes that occurs on transit but not in other transportation modes. Transit itself usually already has an informal hierarchy that separates classes, with commuter rail at the top, followed by rapid transit, and then local bus. (There’s even stratification within modes; I’ve had people tell me why the Ventura County Line is a better Metrolink line to ride than then Antelope Valley Line.) So ride-hailing services may reduce class mixing, though mixing and interaction are not the same thing. A person is probably more likely to talk to their taxi driver or ride-sharing companion than a random person on a transit vehicle.

However, even interaction does not compel understanding. It’s usually remarkably easy to get people to open up and talk about their lives if you want to listen. It’s even easier to just make small talk, or not talk at all. Meaningful interaction with different people only happens if we want it. Expecting a transportation technology to make it happen seems about as fruitful as expecting ride-hailing technology to solve our poor land-use policies.

LACMTA Bus Ridership Update – August 2016 Edition

Six months have passed, so it’s time for another LACMTA bus ridership update. As always, we start with the raw data. Highlighted cells represent the top 10 months for that route (since January 2009).


Since the Expo Line to Santa Monica opened during this time, I thought it might be good to look at the monthly data in addition to 12-month rolling averages. Here are the weekday, Saturday, and Sunday raw data graphs.


Here are the weekday, Saturday, and Sunday 12-month rolling averages.


It’s impossible to say what the impact of the Expo Line is without polling riders; however, there is not a large change in the trend for any line except Wilshire. There is a seasonal drop in Wilshire ridership data during the summer, but it looks larger than normal this year. Looking at the Wilshire split data between routes 18, 20, and 720, it looks like there was a drop of a few thousand riders in 720 ridership after the Expo Line extension opened. The Expo Line would be a shorter ride from downtown LA to Santa Monica than route 720. Again, we cannot say if this is what happened without actually asking riders.


There’s not much else new to say, so we’ll keep it short. Lines that have seen slight decreases continue to decrease; those that are steady seemed to keep holding. The Silver Line continues to grow slowly.

Here’s the percentage of trips on each arterial being served by the rapid route.


The share of riders served by the rapid routes continues to slowly rise on most corridors. This doesn’t necessarily mean increasing ridership on the rapid – it could be that both the rapid and local declined, but the rapid was more resilient.

That’s it for now; next up, Valley bus ridership.

Ride-Sharing and Innovation in Transportation

Though they are funded by venture capital and make apps, ride-hailing companies like Uber and Lyft are different from traditional tech companies. One of their biggest innovations was political: creating large enough constituencies of drivers and riders fast enough to be able to get the regulations over taxi service changed in many cities and states. Regulation, not technology, limited the number of taxis available in most places.

Improved taxi dispatching is an innovation, since computers should be able to dispatch better than a human. But much of ride-hailing companies’ apparent advantage in dispatching is from having more drivers, not allocating the pool of drivers more efficiently. Treating drivers as contractors instead of employees, combined with surge pricing, made short wait times possible. These practices allow ride-sharing companies to supply drivers for peak periods without accruing costs of paying employees during off-peak periods. (Scheduling driver shifts around peak periods is one of the biggest challenges for transit agencies.) Of course, it remains to be seen if regulators and labor organizations will let either of practices stand in the long run.

However, I wonder if ride-hailing apps could have a larger impact on carpooling than expected.

The biggest impediment to carpooling is that it requires all the participants to set a rigid schedule. You have to leave for work or school or home at the same time as everyone else in your carpool every day. The rigid schedule requirements make carpooling much less appealing than driving alone. You can’t get to work 15 minutes early if you have an east coast conference call, you can’t stay 15 minutes late if you’re in a meeting, you can’t go out for a drink or coffee after work.

Most trips are repeated trips – that is, we make the same trips to work or school or home day after day after day – but our desired departure times vary day to day, just enough to make it hard to carpool. We know there are many people making the same trip as us, but we don’t know who they are, and we can’t possibly know enough of them to allow flexibility to depart whenever we want. Could a widely use ride-sharing app change that? Perhaps. If enough people are using the service, it should be possible to match riders and drivers.

This is sort of the idea behind Uber Pool and Lyft Line, but they are still based on the premise that the driver is just a driver, carrying around people whose trips are close enough to be put together. In a true carpool, the driver is making the trip for their own utility. I carpool to work with the person I live with. They aren’t driving for the sole purpose of getting me to work; they’re driving to get themselves to work, and my trip is piggybacking on. In a true carpool, the driver is already deriving utility from the trip. So a carpooling app would not be dispatching paid drivers to carry people around, it would be matching potential riders with potential drivers.

On the other hand, I know there are lots of people downtown who are driving to Glendale. Why need an app? Why don’t I just go stand on the corner, stick my thumb out, and shout “Glendale”?

As it happens, we have an existing case study of where this type of carpooling does happen in real life. Many years ago, the Washington DC area built HOV lanes on their freeways that required 3 or more occupants. A spontaneous system of flexible carpooling arose, known as slugging. You can read all of the fascinating details here, but the idea is simple. Potential passengers line up in a few known pick up points (park-and-ride lots, major business areas, and so on), and potential drivers go to those spots and pick up two passengers going to the same destination.

In other words, potential drivers and potential passengers created an informal system of very flexible carpooling. The requirement for 3 occupants is thought to have been key, because it makes everyone feel safer. Picking up one stranger feels more dangerous than picking up two, in the same way that a full transit vehicle often feels safer than a vehicle with only one or two other riders.

In the case of slugging, no money is exchanged – this is one of the informal rules. The driver benefits by getting to use the HOV lane and the passengers benefit by being able to get to work. For a broader casual carpooling app, there would probably need to be some payment to the driver, since not all trips have carpool lanes available. Since the driver is already deriving utility from the trip, their cost would be low, and the relationship between the app-maker and drivers would not need to be employer-employee. (On the other hand, you wouldn’t want the system to become a de facto below minimum wage taxi service with desperate people acting as driers for very low wages, something that would need to be addressed.)

The shared ride services being offered by the ride-hailing companies are fairly labor intensive, requiring a driver to serve only two or three trips at a time. The companies clearly intend to move to autonomous vehicles in the future, but that will simply trade a labor intensive operation for a capital intensive one. A true flexible carpooling app might offer the possibility to increase mobility by making better use of trips that are already being made.

LACMTA Rail Ridership Update – August 2016 Edition

Six months have passed, so it’s time for another LACMTA rail ridership update. Well, actually seven months, so we’ll throw August ridership in as well. As a reminder, bus ridership for the Westside and San Fernando Valley has been broken out into separate posts.

The last few ridership updates were snoozers because they just showed continuations of previous trends – generally, decent performance on the Expo and Gold Lines, and concerning ridership declines on the Red/Purple, Blue, and Green Lines. This time, we have more to talk about with two new LRT extensions; the Gold Line to Azusa opened in March, and the Expo Line to Santa Monica in May.

First, the raw data. Highlighted cells represent the top 10 months for that line (since January 2009).


Unsurprisingly, the Gold and Expo Lines both had top 10 months for every month after their extensions open. The Gold Line was already at all-time highs and the Expo Line was close. The Gold Line’s increase in ridership after the extension opened was very modest – about 4,000 riders, or 9%. The Expo Line jumped about 13,000 riders, over 40%.

Ridership declines on the Blue, Green, and Red/Purple Lines have reversed themselves a little recently, perhaps due to the better network effects created by the opening of the Gold and Expo Line Extensions. While ridership has remained well below peaks, it has increased enough to  nudge the 12-month averages up.

Here’s the rolling 12-month average of weekday ridership. Note that the rolling 12-month averages for the Gold and Expo Lines will understate the ridership increases due to sudden jumps occurring when the extensions opened, so we’ll include the raw monthly graphs too. Raw weekday ridership:


Rolling 12-month average weekday ridership:


Saturday and Sunday trends largely reflect the weekdays. Here’s the Saturday and Sunday rolling 12-month averages. Again, raw monthly graphs are included to show Gold and Expo changes. Raw Saturday/Sunday ridership:


Rolling 12-month average Saturday/Sunday ridership:


One very interesting thing about weekend ridership is that the Gold and Expo Line extensions have arguably been even more successful on weekends than on weekdays. The Gold Line has seen Saturday and Sunday ridership jump by about 6,000 riders, or 20% on Saturday and 24% on Sunday. This is a greater ridership gain than weekdays not only in percentage, but in absolute terms, surely an unusual outcome. The Expo Line data is even more remarkable, with ridership increasing by about 13,000 riders (60%) on Saturday and 16,000 riders (100%) on Sunday.

Lastly, here’s the update for the boardings per mile, again both raw monthly graph and rolling 12-month average. Raw weekday boardings per mile:


Rolling 12-month average weekday boardings per mile:


The Gold and Expo Lines both saw a decrease in productivity, not unusual for lines where extensions just opened. As ridership grows on the extensions, these trend lines will climb back up. The Blue and Red/Purple Lines have ticked back up a little bit, perhaps reminding us that extending the transit network increases ridership on existing lines too.

Gold Line and Expo Line Thoughts

While there’s been both excitement and concern about the Gold and Expo Line extensions, it’s important to remember that it’s very early in the game for these lines. Four months after the opening of Expo Phase 1, ridership was at about 20,000, and continued to rise to over 30,000 by two years after opening. Gold Line ridership was at about 32,000 six months after the Eastside Extension opened, and had risen to over 45,000 by the time the Azusa extension opened. We’re still very much in the adjustment period.

Still, the initial weekday ridership increase for the Gold Line extension of 4,000 is less than I’d hoped for. Traffic on the 210 is very bad during peak periods, and downtown Pasadena is a large enough business district to generate trips in its own right, so demand shouldn’t have to all be people making a long trip to downtown LA. It is especially surprising that the weekday ridership gain was smaller than the weekend ridership gain. Considering the length of the extension (11 miles and 6 stations) and the nature of development in the area, I don’t think it would be unreasonable to hope for around 12,000 riders in the future – about 1,000 boardings per mile or 2,000 per station.

The Expo Line extension opened to even more fanfare, fulfilling the dream of restoring rail transit service between downtown LA and the beach. This created a lot of excursion trips in the first month or so after opening, with people riding just to see the line. The initial ridership increase of 13,000 was respectable and we should expect it to continue growing. The Saturday and Sunday ridership increases were more impressive and are indicative of the strength and variety of travel demand along the corridor. Saturday and Sunday ridership is now at about 75%-80% of weekday ridership. Considering the Expo Line has been running 12 minute headways during the day and 20 minute headways late, there should be considerable gains to be had just by getting enough vehicles to run 6 minute peak headways. In addition, restoring 10 minute headways during evenings and nights would also be helpful.

Next up will be central LA and Westside bus ridership. It won’t be as interesting as rail ridership, but perhaps we’ll see some impact from the Expo Line extension.