Category: Mobility

Can you rely on Metra after hearing a story like this?

February 7, 2014 / / 6 Comments

Tweet shows a different Metra line but is representative of experiences since #Chiberia began in January. 

My friend Shaun relayed this story to me about his coworker who rides Metra’s BNSF line from the Aurora/Naperville area, the commuter train in Chicagoland that carries over 300,000 people each weekday but fractions on weekends (because it rarely runs).

The train he was about to board Wednesday morning with several other people arrived and when the doors opened only one of the two sliding doors opened. The other one was stuck shut. So he “touched” it to get it to open up and the conductor yelled at him.

The conductor said “we’ve told you several times to not do that!” seemingly referring to other people who had done so, not my coworker himself. The conductor told him a guy at the last stop did that and it “broke the door.” (sounds like it already was!])

The conductor told him it would be a $500 fine if it happened again. At that point my coworker said he just shut up. When my boss tried to get on the train the conductor told him he wasn’t allowed to board! There was apparently plenty of room to get on so this was at the “conductor’s discretion.” Coworker had to wait 20 min for the next train [in single digit temperatures, no less], missed a meeting, etc…

Just completely shocked me that they wouldn’t let him on the train for pushing the door open (no sign, conductor wasn’t at the broken door to tell people not to touch it, etc.).

This started a conversation about our perceptions of Metra.

Steven: “It’s right that the new Metra CEO [Don Orseno]* wants to work on communication, but I think he needs to emphasize customer service overall.”

Shaun: “In Ogilvie Transportation Center tonight, same announcement played: ‘some trains are delayed. We will continue to update you.’

Every few minutes — no actual information. Lot of work to do I’m guessing. Wonder how many Metra people in charge ride their trains.”

Steven: “I rarely ride Metra for ‘important’ reasons (like going to work or for meetings). The last time was on the Electric to a meeting in South Shore in October.

Every time I ride I feel that the lumbering of the trains as they exit the stations (switching tracks, they sway side to side) is analogous to how Metra operates: ‘move in a slow, heavy, awkward way’.”

Shaun: “It reminds me of a novelty train ride. Like at an amusement park.

I only take it from work to home. To work is too risky. CTA is consistent (lately actually, Red Line at morning rush is so frequent I don’t even check the arrival times while walking to the station).

Kind of funny how you say you can’t rely on Metra for work or meetings, considering that’s what people use it for.

* Orseno, who’s been there for decades, said at the Metra board meeting where he was promoted to executive director from his interim position that he drives to work because the SouthWest Service “doesn’t get him to the office early enough, or home late enough” (Chicago Tribune).

However, Orseno lives in Manhattan so you can see how the infrequency would be a problem: this station only has three trains per direction per day. Remember from my previous post that Chicago rapid transit service has only shrunk since 1950. I wonder what he can do about that…

Chicagoland transit funding has no traction

February 7, 2014 / / 2 Comments
Two maps showing the extent of the rapid transit network in 1950 and 2010.

I reviewed Metropolitan Planning Council’s short and easy-to-read report about existing funding conditions of Chicagoland transit (CTA, Metra, and Pace) for Streetsblog Chicago. It was more eye-opening that I expected, mainly because I didn’t realize how poorly we fund transit here compared to cities nationwide and around the world.

The bit about only Atlanta spending less than Chicago when you compare our regions’ funding levels to what it was 20 years ago really caught some people’s attention.

The other part of the report, co-authored by Yonah Freemark (who also writes the blog The Transport Politic), that got some attention was the above map that showed how the Chicago region had more rapid (frequent) rail transit in 1950 than 2010. Lower mileage and funding over the past three decades meant fewer riders – that part is obvious and has been known to me, transit planners and managers. But this much? I had no idea.

My tweet about this map – to which Eric Fischer, Mapbox map designer and map historian responded with a map from one of the predecessor departments* of the current Chicago Department of Transportation – was retweeted ten times and clicked on over 100. That more than 70% of Chicagoland workers drive to work alone is not surprising given that our rapid transit network is built around rush hour service to downtown, where a minority of jobs are located.

* The department name on the map, published in 1939, is listed as Department of Subways and Traction, headed by commissioner Philip Harrington. This became the Department of Subways and Superhighways. The map shows two cross-Loop (east-west) subways linking Michigan Avenue businesses and intercity electric trains (that travel south, southeast, and near southwest) with the Union and Northwestern train stations (where people board trains to the west, northwest, north, and southwest).

Wayfinding signs at Van Buren Street Metra station are incomplete

January 13, 2014 /

New RTA interagency transfer signage near Van Buren Street Metra Electric station

“B” marks a new bus boarding area near the Van Buren Street Metra Electric station.

The Regional Transportation Authority has spent $2 million to improve wayfinding between CTA, Metra, and Pace train stations and bus stops in a needed effort to connect newbies and long-time residents to their next transfer.

Some of the signs need to show better information, though. The RTA installed signs at the Van Buren Street Metra Electric station at Michigan Avenue that create “bus loading groups,” similar to bus bays at suburban park & rides.

It works like this: you come across the nearest bus stop – I happened upon boarding area B – hoping to find the route you need. Instead, though, that route stops at boarding area A. The sign at boarding area B points you in the direction of A and from where you stand you can see a sign that identifies A.

RTA’s signs have two issues. First, they don’t tell you that boarding area C is across the street – unless you inspect the small map – and instead point you in the direction of A (from B). If you walk in the direction of the arrow from boarding area B you will not run into boarding area C or a sign that tells you where to cross the street in order to access C.

The first issue creates the second problem: by reading and relying upon the sign’s text you can’t know at which boarding area, A or C, you should board a bus route that stops at both boarding areas. (Those who also study the maps on another side of the sign will have better luck.) That’s because the same route operates in both directions and if you’re not familiar with the route, you won’t know which direction takes you towards your destination.

New RTA interagency transfer signage near Van Buren Street Metra Electric station

Both boarding areas A and C will get you on the 3, 4, J14, and 26, but only the map on the other side tells you which direction they go. Also, while the arrow points in the direction of boarding areas A and C, only the map tells you that A is across the street.

The fix seems an easy one. First, point the arrows on A and B across the street instead of north or south towards B or A, and add an intermediary sign along the walking path that communicates that “boarding area C is across the street.” Then, update the signs to indicate which direction the bus routes are going so that travelers are assured they need to visit C across the street for King Drive buses going towards Bronzeville or A for King Drive buses going toward Streeterville.

The RTA has installed other signage in this program at 95th and Western (CTA & Pace), Joliet Union Station (Metra & Pace), and Davis Station in Evanston (CTA, Metra, & Pace).

Smartphones replace cars. Cars become smartphones.

January 6, 2014 / / 10 Comments

Teens’ smartphone use means they don’t want to drive. Car makers’ solution? Turn cars into smartphones.

The Los Angeles Times reported in March 2013, along with many other outlets, that “fewer 16-year-olds are rushing to get their driver’s licenses today than 30 years ago as smartphones and computers keep adolescents connected to one another.”

Smartphones maintain friendships more than any car can. According to Microsoft researcher Danah Boyd, who’s been interviewing hundreds of teenagers, “Teens aren’t addicted to social media. They’re addicted to each other.” (Plus not every teen needs a car if their friends have one. Where’s Uber for friends? That, or transit or safe cycle infrastructure, would help solve the “I need a ride to work at the mall” issue.)

Driving is on the decline as more people choose to take transit, bike, walk, or work from home (and not unemployment).

intel cars with bicycle parts

Marketing images from Intel’s blog post about cars becoming smartphones.

What’s a car maker to do?

The first thing a car maker does to fight this (losing) battle is to turn the car into a smartphone. It’s definitely in Intel’s interest, and that’s why they’re promoting the story, but Chevrolet will soon be integrating National Public Radio – better known as NPR – as an in-dash app. It will use the car’s location to find the nearest NPR affiliate. Yeah, my smartphone already does that.

The second thing they do is to market the product differently. Cars? They’re not stuck in traffic*, they’re an accessory to your bicycle. Two of the images used in Intel’s blog post feature bicycles in some way. The first shows a bicycle helmet sitting on a car dashboard. The second shows how everyone who works at a proposed Land Rover dealership is apparently going to bike there, given all the bikes parked at an adjacent shelter.

The new place to put your smartphone when you take the train.

* I’m looking at you, Nissan marketing staff. Your commercial for the Rogue that shows the mini SUV driving atop a train full of commuters in order to bypass road congestion (and got a lot of flack) is more ridiculous than Cadillac’s commercial showing a car blowing the doors of other cars, while their drivers look on in disbelief, in order to advertise the 400+ horsepower it has (completely impractical for driving in the urban area the commercial showcases).

Developing a method to score Divvy station connectivity

January 4, 2014 / / 2 Comments

A Divvy station at Halsted/Roscoe in Boystown, covered in snow after the system was shutdown for the first time to protect workers and members. Photo by Adam Herstein.

In researching for a new Streetsblog Chicago article I’m writing about Divvy, Chicago’s bike-share system, I wanted to know which stations (really, neighborhoods) had the best connectivity. They are nodes in a network and the bike-share network’s quality is based on how well (a measure of time) and how many ways one can move from node to node.

I read Institute for Transportation Development Policy’s (ITDP) report “The Bike-Share Planning Guide” [PDF] says that one station every 300 meters (984 feet) “should be the basis to ensure mostly uniform coverage”. They also say there should be 10 to 16 stations per square kilometer of the coverage area, which has a more qualitative definition. It’s really up to the system designer, but the report says “the coverage area must be large enough to contain a significant set of users’ origins and destinations”. If you make it too small it won’t meaningfully connect places and “the system will have a lower chance of success because its convenience will be compromised”. (I was inspired to research this after reading coverage of the report in Next City by Nancy Scola.)

Since I don’t yet know the coverage area – I lack the city’s planning guide and geodata – I’ll use two datasets to see if Chicago meets the 300 meters/984 feet standard.

Dataset 1

The first dataset I created was a distance matrix in QGIS that measured the straight-line distance between each station and its eight nearest stations. This means I would cover a station in all directions, N, S, E, W, and NW, NE, SE, and SW. Download first dataset, distance matrix.

Each dataset offers multiple ways to gauge connectivity. The first dataset, using a straight-line distance method, gives me mean, standard deviation, maximum value, and minimum value. I sorted the dataset by mean. A station with the lowest mean has the greatest number of nearby stations; in other words, most of its nearby stations are closer to it than the next station in the list.

Sorting the first dataset by lowest mean gives these top five best-connected stations:

  1. Canal St & Monroe St, a block north of Union Station (191), mean of 903.96 feet among nearest 8 stations
  2. Clinton St & Madison St, outside Presidential Towers and across from Northwestern Train Station (77), 964.19 feet
  3. Canal St & Madison St, outside Northwestern Train Station (174), 972.40
  4. Canal St & Adams St, north side of Union Station’s Great Hall (192), 982.02
  5. State St & Randolph St, outside Walgreens and across from Block 37 (44), 1,04.19

The least-connected stations are:

  1. Prairie Ave & Garfield Blvd (204), where the nearest station is 4,521 feet away (straight-line distance), or 8.8x greater than the best-connected station, and the mean of the nearest 8 stations is 6,366.82 feet (straight-line distance)
  2. California Ave & 21st St (348), 6,255.32
  3. Kedzie Ave & Milwaukee Ave (260), 5,575.30
  4. Ellis Ave & 58th St (328), 5,198.72
  5. Shore Drive & 55th St (247), 5,168.26

Dataset 2

The second dataset I manipulated is based on Alex Soble’s DivvyBrags Chrome extension that uses a distance matrix created by Nick Bennett (here’s the file) that estimates the bicycle route distance between each station and every other station. This means 88,341 rows! Download second dataset, distance by bike – I loaded it into MySQL to use its maths function, but you could probably use python or R.

The two datasets had some overlap (in bold), but only when finding the stations with the lowest connectivity. In the second dataset, using the estimated bicycle route distance, ranking by the number of stations within 2.5 miles, or the distance one can bike in 30 minutes (the fee-free period) at 12 MPH average, the following are the top five best-connected stations:

  1. Ogden Ave & Chicago Ave, 133 stations within 2.5 miles
  2. Green St & Milwaukee Ave, 131
  3. Desplaines St & Kinzie St, 129
  4. (tied) Larrabee St & Kingsbury St and Carpenter St & Huron St, 128
  5. (tied) Clinton St & Lake St and Green St & Randolph St, 125

Notice that none of these stations overlap with the best-connected stations and none are downtown. And the least-connected stations (these stations have the fewest nearby stations) are:

  1. Shore Drive & 55th St, 11 stations within 2.5 miles
  2. (tied) Ellis Ave & 58th St and Lake Park Ave & 56th St, 12
  3. (tied) Kimbark Ave & 53rd St and Blackstone Ave & Hyde Park Blvd and Woodlawn Ave & 55th St, 13
  4. Prairie Ave & Garfield Blvd, 14
  5. Cottage Grove Ave & 51st St, 15

This, the second dataset, gives you a lot more options on devising a complex or weighted scoring system. For example, you could weight certain factors slightly higher than the number of stations accessible within 2.5 miles. Or you could multiply or divide some factors to obtain a different score.

I tried another method on the second dataset – ranking by average instead of nearby station quantity – and came up with a completely different “highest connectivity” list. Stations that appeared in the least-connected stations list showed up as having the lowest average distance from that station to every other station that was 2.5 miles or closer. Here’s that list:

  1. Kimbark Ave & 53rd St – 13 stations within 2.5 miles, 1,961.46 meters average distance to those 13 stations
    Blackstone Ave & Hyde Park Blvd – 13 stations, 2,009.31 meters average
    Woodlawn Ave & 55th St – 13 stations, 2,027.54 meters average
  2. Cottage Grove Ave & 51st St – 15 stations, 2,087.73 meters average
  3. State St & Kinzie St – 101 stations, 2,181.64 meters average
  4. Clark St & Randolph St – 111 stations, 2,195.10 meters average
  5. State St & Wacker Dr – 97 stations, 2,207.10 meters average

Back to 300 meters

The original question was to see if there’s a Divvy station every 300 meters (or 500 meters in outlying areas and areas of lower demand). Nope. Only 34 of 300 stations, 11.3%, have a nearby station no more than 300 meters away. 183 stations have a nearby station no further than 500 meters – 61.0%. (You can duplicate these findings by looking at the second dataset.)

Concluding thoughts

ITDP’s bike-share planning guide says that “residential population density is often used as a proxy to identify those places where there will be greater demand”. Job density and the cluster of amenities should also be used, but for the purposes of my analysis, residential density is an easy datum to grab.

It appears that stations in Woodlawn, Washington Park, and Hyde Park west of the Metra Electric line fare the worst in station connectivity. The 60637 ZIP code (representing those neighborhoods) contains half of the least-connected stations and has a residential density of 10,468.9 people per square mile while 60642, containing 3 of the 7 best-connected stations, has a residential density of 11,025.3 people per square mile. There’s a small difference in density but an enormous difference in station connectivity.

However, I haven’t looked at the number of stations per square mile (again, I don’t know the originally planned coverage area), nor the rise or drop in residential density in adjacent ZIP codes.

There are myriad other factors to consider, as well, including – according to ITDP’s report – current bike mode share, transit and bikeway networks, and major attractions. It recommends using these to create a “demand profile”.

Station density is important for user convenience, “to ensure users can bike and park anywhere” in the coverage area, and to increase market penetration (the number of people who will use the bike-share system). When Divvy and the Chicago Department of Transportation add 175 stations this year – some for infill and others to expand the coverage area – they should explore the areas around and between the stations that were ranked with the lowest connectivity to decrease the average distance to its nearby stations and to increase the number of stations within 2.5 miles (the 12 MPH average, 30-minute riding distance).

N.B. I was going to make a map, but I didn’t feel like spending more time combining the datasets (I needed to get the geographic data from one dataset to the other in order to create a symbolized map).