Road Rent – On the Opportunity Cost of Land Used for Roads

There are a number of ways to view the cost of automobile travel. For instance

  • We can look at the congestion costs imposed [link].
  • We can allocate infrastructure costs [link].
  • We can assess full costs to consider internal costs, subsidies, and externalities [link].

This post looks at the idea of road rent. At the margins, what is the value of road space, and how might that cost look on a per vehicle-km traveled basis?

Real Estate

Land has value. Land used as roads has value both as a road and potentially for other uses. What if the value for other uses was higher than that for use as a road?

In Greater Sydney land values range from to $AU210,000 per m² in Barangaroo on Darling Harbour to under $AU1000 per m² in Western Sydney [link].  In Minneapolis, we estimated a few years ago that average assessed land value as $144 per m² for roads and $30 per m² for highways. [Junge, Jason and David Levinson (2013) Property Tax on Privatized Roads. Research in Transportation Business and Management. Volume 7. pp. 35-42.] It seems that assessed value is about 2/3 of market value in Minneapolis.

In some places it is much higher, in some places much lower, the examples used herein are simply an illustration.

The idea is that there is land holder (such as a government land agency) that has to decide whether to allocate land to road uses or for other purposes.

Parking Rent

Consider a typical suburban residential neighborhood with `free’ parking in front of houses. The land is valued at $1,000 per m². Each house requires one parking space out front, and parking is permitted 24 h per day. Conservatively, a car takes 10 m² when parked (the road is the access lane, we consider that separately). It would cost $10,000 for the land owner to purchase the land equivalent of the parked car. The annual rent on that would be $400 (at 4% interest).

In this example $400 is how much the car owner should pay annually  to their municipality for a permit to park their car to cover the cost of land (not the cost of infrastructure, or any other costs of roads and mobility, just the cost of land). This is a bit more than $1/day (more precisely $1.095/day). In more expensive neighborhoods, this would be higher, in less expensive neighborhoods, lower.

For Minneapolis, I have previously estimated about 220,000 on-street spaces. At $400/space per year, this would raise $88,000,000 per year, a not inconsiderable share of the city’s $1.3B annual budget. Instead it is mostly given away free.

Consider the implications if property taxes were reduced by up to $88M in total, and parking permits sold at $400/year (payable monthly with the water and trash bill). People would realize the cost of on-street parking, and there would be less of it, and less vehicle ownership at the margins, and fewer trips by car. Space freed up could be re-allocated.

Alternatively, $400 per year is the value of public subsidy from publicly-owned land to private car owners who get `free’ on-street parking. In short from the car-less to the car owners.

Alternative Uses of Road Space

The economic idea of opportunity cost is important here. Opportunity cost is value of the next best alternative. The next best alternative to road space might be renting it out. So for instance an urban US freeway that destroyed blocks of extant development when it was built has an opportunity cost associated with the value of that real estate.

So the question arises as to what other uses  could be made of the road; for if there were no other uses, you might as well store cars for free. Here are several other uses that could be  considered to replacing a parking lane:

  • Park or parklet,
  • Bike lane,
  • Bus lane,
  • Paid parking, via meters,
  • Shared car parking (rented to the car sharing company),
  • Shared bike parking (rented to the station-based or dockless bike sharing company),
  • Taxi or ride-hailing stand,
  • Bus stop,
  • Shared scooter parking (rented to dockless scooter sharing company),
  • Food truck or ice cream vendor,
  • Road for moving motor vehicles (a parking lane could be another moving lane),
  • Sold off for development.

The last item deserves some discussion. Consider that our road with two parking lanes (one on each side) is maybe 10 or 12m wide (~32 to 40ft). This is wider than some houses are long. The city could in principle retain the sidewalks and sell off the roadbed for townhouses or single family homes. Given the houses are already serviced by alleys, and so long as not all roads were sold off, some roads could be. An illustration of this is the Milwaukee Avenue in Seward in Minneapolis, as shown in the figure. You will see there is no paved street in front of the houses. This could be tightened up further or realigned should there be demand.

Milwaukee Avenue, Seward. Source: http://maha2014.dreamhosters.com/history
Milwaukee Avenue, Seward. Source: http://maha2014.dreamhosters.com/history

This is not appropriate for every street. However, (1) there are places this can be done, where roads are in excess and housing scarce, and (2) this illustrates that land currently used as asphalt to store and move cars has value, and that houses have value even in the absence of streets for cars in the front.

There are always excuses — utilities may need to be relocated, fire trucks would need to go slower down narrower sidewalks. But these excuses can be overcome, there are numerous examples of narrow paths that function as roads.

Driving Rent 

Note: 1 are = 100 m² and 1 hectare  (ha) = 10,000 m²

Typically each car is in use 1 – 1.5 hours per day, and parked for the remainder. In the previous section, we considered parking, the `remainder,’ in this section we look at the time in motion.

When in use, the car is occupying not simply its area (the 10m² = 2m x 5m), but also is preventing the use of other space around it. On a freeway with a capacity of 1800 vehicles per hour traveling at a freeflow speed of 100 km/h, (i.e. just before the speed and flow drop due to congestion sets in) there is a critical density of 18 vehicles/km.

18 vehicles per km is 55.5 meters per vehicle. Lane width is 3.65 meters, so the area occupied is 202 m². Let’s round to 200 m². Each moment  a car is in use, it is using 200 m², on which it should pay rent. So for an hour a day, this is 720,000 m² s or 72 ha s.  (The meter-squared by second (or hectare second) is a new unit of measurement (a time-volume) that needs a catchier name).

It is the density that is the relevant number here, since vehicles are occupying space that we are charging rent for in this thought experiment. Though they are moving, and so the space they are occupying moves with them, there is always some space being occupied for the duration of their travel. Each of those vehicles per hour is occupying a moving window of space.

Roads are a Time Share

When roads are less congested, cars are consuming more space per vehicle. So uncongested urban are much more expensive per traveler than congested rural roads.  When traffic breaks down, they are consuming less space, but presumably are occupying that space for more time, since they are going slower. Induced demand [link] and travel time budgets [link] negate that to a significant extent.

B-UkEPIIUAAIhX9
Illustration of space occupied by cars. Note that most cars do not have 2 occupants. This particular layout is, surprisingly, in somewhat congested conditions. Cars often take up more space at higher speeds. Screen still from a 2002 Saturn car company TV commercial. Image source:  The San Francisco ad agency Goodby, Silverstein & Partners.  Article: Raine, George ‘Goodby, Silverstein agency celebrates 25 years’ SF Chronicle.

George Raine https://www.sfgate.com/business/article/Goodby-Silverstein-agency-celebrates-25-years-3285120.php#photo-2434077

In this example, the hourly rent on 200 m² is what we are interested in. Though cars move, over the course of 1 hour of travel in these conditions, they are claiming that much space. The specific space they are claiming moves with the vehicles, but this all balances out as other cars claim the space they vacated.

Empty roads still have to be paid for, and paid for by actual road users. Even when a road is not being used, it is available to be used. Travelers have the option of traveling. Pavements cannot be easily be rolled up and allocated to other purposes on the fly, particularly purposes like buildings. (Roads can occasionally be closed for special events, but this is rare during business hours.)

 

Example

Consider a car trip that uses 3 roads:

  • Road section 1 (suburban residential): l=5 km, w=3.65, v=30 km/h, q=1000 veh/h, k=33.33 veh/km, AADT=10,000 vehicles/day/lane, p= $1000/m².
  • Road section 2 (motorway): l=10 km, w=3.65, v= 100 km/h, q=2000 veh/h, k= 20 veh/km, AADT = 20,000 vehicles/day/lane, p= $5000/m².
  • Road section 3 (downtown): l= 1 km, w=3.65,  v=40 km/h, q=1600, k =40 veh/km , AADT=16,000 vehicles/day/lane, p= $10000/m².

where: l = length (km), w= lane width (m), v=velocity (km/h), q=flow (veh/h), k=density (veh/km), AADT = Average Annual Daily Traffic, p= land value ($/m²), i=interest rate = 0.04, r= land rent ($/year/m²), d = days/year

Consider each road section to be a homogenous pipeline. (With heterogenous traffic, this is obviously far more complicated, and we would make use of the q, k, and v variables to compute an area-time.)

The annual rent (R) for  each road section is the R=p*i*l*w

  • Road 1: R=$1,000/m² y * 0.04 * 5,000 m * 3.65 m  = $730,000/y
  • Road 2: R=$5,000/m² y * 0.04 * 10,000 m * 3.65 m = $7,300,000/y
  • Road 3: R=$10,000/m² y * 0.04 * 1,000 m * 3.65 m = $1,460,000/y

This annual rent is paid by the road agency to the land owner for the use of land as a road. The road agency then wants to recover this cost from its customers, the travelers.

The question of how to allocate always has some subjectiveness to it. Another way of thinking about it is based on elasticity of demand. Peak hour work trips are perhaps the least elastic (least sensitive to price), and so from an economic efficiency perspective should bear the greater cost.

In this example, we take a simpler tack.

The allocation is R/AADT to get cost per year per daily tripmaker, and divide by 365 to get cost per trip, and by section length to get cost per km. In this example:

  • Road 1: $730,000/10000 = $73/y = $0.20/trip = $0.04/km
  • Road 2: $7,300,000/20000 = $365/y = $1/trip = $0.10/km
  • Road 3: $1,460,000/16000 = $91.25/y = $0.25/trip=$0.25/km

The total is thus $529.25/year or  $1.45/trip to cover land rent. `Your mileage may vary,’ as the saying goes.

Implications

The implications of this are several.

  • At an additional $1.45/trip, travel by car (and congestion) will diminish.
  • Road rent is essentially additive with annualized infrastructure costs, which generally does not consider the cost of land (rather, land is often implicitly considered `free’ or a sunk cost).
  • If travel by car diminishes sufficiently, road space can be clawed back and redeployed for other public purposes.
  • Narrower lanes impose less road rent. But not necessarily proportionately so, as the throughput on narrower lanes (with human drivers) may be lower as drivers are less keen to be immediately adjacent to nearby high-speed vehicles.
  • Slower moving vehicles take up less space, but take that space for longer.
  • While pedestrians and bicyclists use space as well, they use much less space. (See discussion of flux.) Sidewalks (footpaths) are often considered part of the adjacent private property, and are thus already paid for with property tax.
  • Land used for roads instead of development is not on the books for property taxes.
  • The revenue raised can be used for many transport purposes or redistributed back to taxpayers through some other means.
  • We expect the additional road rent reduces the effective land rent that landowners can charge. If people have to pay more for travel, they will pay less for real estate.
  • Rural areas have much lower, perhaps negligible, road rent. Though the number of users drops significantly (so there are fewer travelers who must pay the burden of road rent), the cost of land drops even more significantly.
  • Were there no (fewer) roads, land would also have very little (less) value, since it would be difficult to access and egress.
  • If roads were fully built on, views would be terrible and the existing buildings would diminish in value. But none of that is to say we have the correct amount of roads now. Clearly urban roads are undercharged in a real estate sense.

Are Australian Vehicles Getting Bigger?

ABC Radio Sydney called me and asked essentially:

`Are Australian Cars Getting Bigger?’

The short answer is ‘No.’

AustralianNewCarMarket.003

Using data from the Federal Chamber of Automotive Industries that was once freely available online, and is now behind a paywall, I have produced graphs illustrating the Australian vehicle market.  The data show among the passenger cars: medium, small, light, and micro are all gaining in proportion of passenger cars, rising from half the passenger car market to 83% since 2000.

But

`Are Australian Vehicles Getting Bigger?’

The answer here is ‘Yes.’

As will be no surprise to Australians, or North Americans (See Canada data), the share of Sports Utility Vehicles has exploded since the beginning of the Millennium from about 13% to 39%, and now more SUVs are sold each year than passenger cars.

AustralianNewCarMarket.001

AustralianNewCarMarket.002

This trend, which mirrors that in the US, helps explain Ford’s recent decision to exit most of the passenger car business in the US.

Now 50%  of 70% is 35% (small cars share of all vehicles in 2000) while 80% of 38% is 30% (small cars share of all vehicles in 2017), so the share of small and medium cars of all vehicles is falling. But the total market of vehicles sold in Australia is still increasing from 787,000 in 2000 to 1,189,116 in 2017, and 30% of cars sold in 2017 is more than 35% of cars sold in 2000, so there are still more in terms of total number of small and medium cars sold in 2017 in total than 2000, even if it is a declining share of the market.

The Australian government also conducts a Motor Vehicle Census and just as the number of new cars sold each year rises with population growth, the total number of vehicles is also rising. This differs from the US, which has more or less peaked in cars per capita, and perhaps cars. I graphed this data for NSW for selected years (this data, is also, inconveniently, not in one place)

AustralianNewCarMarket.005

The reason for more SUVs vs. large cars are speculative. That is, why do people now prefer SUVs and not station wagons or big cars? It’s not as if people actually do a lot of off-road driving.

One is the idea of the extreme trip. Sometimes (say once a year or even once a month) a very large car would be useful. So instead of renting the specific vehicle when they want it, SUV-owners buy the vehicle they would use 1% of the their trips (or 0.05% of their time – since cars are only used 5% of the day anyway, and at rest the remainder, sleeping more than even cats), but which is too large 99.95% of the time.

One answer is the car Arms Race. In a taller car, the driver can see farther ahead (drivers are less likely to have their view obscured), which lets tall vehicle drivers anticipate better. It makes drivers feel safer, which they are for themselves, even when they are not for others.

More people are killed because of SUVs and light trucks, in the US, Michelle White estimated in 2004 “For each 1 million light trucks that replace cars, between 34 and 93 additional car occupants, pedestrians, bicyclists, or motorcyclists are killed per year, and the value of the lives lost is between $242 and $652 million per year.” Presumably the same logic holds in Australia.

Increasing the mass of vehicles on the road doesn’t do society any favours from an energy consumption, or air pollution perspective either. And of course, larger vehicles use more space, consuming more land in parking lots (which are now often restriped to accommodate more massive vehicles) and roads, where the width of lane consumed by larger cars rises, providing less manoeuvrability for other cars.

With the rise of autonomous vehicles, and especially vehicle sharing, the right sized vehicle will be summonable by app, so when travelers need the specific type of car for a large trip with many people, they can get it. The rest of the time, drivers will be able to use a car fit for purpose, one that holds one person for a one-person trip, and two people for two-person trips, and so on. This opens up the potential for skinny cars, enclosed electric cycles, and many other appropriate vehicles, which take up less road space, making it even easier to improve the environment for other road users, including walkers and bicyclists.

Toyota iRoad one-passenger concept cars, image courtesy Toyota.
Toyota iRoad one-passenger concept cars, image courtesy Toyota.

DEFINITIONS:

Passenger Motor Vehicles Passenger vehicles are classified dependent on size, specification and average retail pricing. Selected vehicle types will be assessed on footprint defined as length (mm) x width (mm), rounded, as follows:
Sports Utility Vehicles Vehicles classified as Sport Utility Vehicles (SUV) meet the FCAI criteria for classifying SUV vehicles based on a 2/4 door wagon body style and elevated ride height. Vehicles typically will feature some form of 4WD or AWD, however, where a 2WD variant of a model is available it will be included in the appropriate segment to that model.
Light Trucks Vehicles designed principally for commercial but may include designs intended for non-commercial applications.
Heavy Trucks Vehicles designed for exclusive heavy commercial application.

Car sizes:

Micro Hatch, sedan or wagon with a footprint < 6,300
Light Hatch, sedan or wagon with a footprint range 6,301 – 7,500
Small Hatch, sedan or wagon with a footprint range 7,501 – 8,300
Medium Hatch, sedan or wagon with a footprint range 8,301 – 9,000
Large Hatch, sedan or wagon with a footprint range 9,001 – 9,500
Upper Large Hatch, sedan or wagon with a footprint range 9,501 >
People Movers Wagon for passenger usage, seating capacity > 5 people
Sports Car, coupe, convertible or roadster

SUV Sizes:

Light Duty 3,501 – 8,000kg GVM
Medium Duty => 8,001kg GVM & GCM < 39,001
Heavy Duty 8,001kg GVM & GCM > 39,000

Light Truck Sizes:

Light bus < 20 Seats 8+ seats, but less than 20 seats
Light Bus > 20 Seats 20+ seats
Vans/CC <= 2.5t Blind/Window vans and Cab Chassis <= 2.5t GVM
Vans/CC > 2.5–3.5t Blind/Window vans and Cab Chassis between 205 and 3.5 tonnes GVM
Pick-up / Chassis 4×2 Two driven wheels, normal control (bonnet), utility, cab chassis, one and a half cab and crew cab
Pick-up / Chassis 4×4  Four driven wheels, normal control (bonnet), utility, cab chassis, one and a half cab and crew cab

Heavy Truck Sizes:

Light Duty 3,501 – 8,000kg GVM
Medium Duty => 8,001kg GVM & GCM < 39,001
Heavy Duty 8,001kg GVM & GCM > 39,000

An empirical study of the deviation between actual and shortest travel time paths

Recently published

DeviationAbstract: This study evaluates routes followed by residents of the Minneapolis–St. Paul metropolitan area, as measured by the Global Positioning System (GPS) component of the 2010/11 Twin Cities Travel Behavior Inventory (TBI). It finds that most commuters used paths longer than the shortest path. This is in part a function of trip distance (+, longer distance trips deviate more), trip circuity (−, more circuitous trips deviate less), number of turns (+, trips with more turns per kilometer deviate more), age of driver (−, older drivers deviate less), employment status (+, part-time workers deviate more), flexibility in work hours (+, more flexibility deviate more), and household income (−, higher-income travelers deviate less). Some reasons for these findings are conjectured.

Author keywords: Global positioning system (GPS); Shortest path; Route choice; Wardrop’s principles; Travel behavior.

Signalling inequity – How traffic signals distribute time to favour the car and delay the pedestrian.

An edited version of this appeared on The Conversation June 11, 2018. The original is below.

Traffic signals are a source of great inequality in the urban realm, giving priority to motor vehicles over pedestrians.  Cities and states say they want to encourage walking and biking for many reasons: it is space efficient, it has less environmental impact, it is healthier, it is safer for other travelers, and, since,  it reduces the numbers of cars on the road, even motorists should be in favour of other people walking. To help achieve that, road management agencies should take the lead in reprioritising traffic signals by redistributing intersection delay from pedestrians to cars.

While planners tend to focus on the long-term decisions, like infrastructure and land development, it is the shortest of short-term decisions, how many seconds of green light each movement gets at an intersection, that shapes daily perception of the feasibility of walking or driving to a destination at a given time, and thus the choice of route, destination, and mode of travel. Traffic signal timing involves math, so it has been historically delegated to the engineers, but it also involves values and priorities, and so is the proper subject of public policy.

Since the early twentieth century dawn of what Peter Norton calls ‘Motordom’ in his book ‘Fighting Traffic‘, street space has steadily been regulated and enclosed, limiting the rights and privileges of pedestrians while promoting those of drivers as a class, in the name of safety and efficiency. But we should ask safety and efficiency for whom? Prior to traffic signals, pedestrians could and did cross the street whenever and wherever they wanted, before the term ‘jaywalking’ was invented and street crossing was regulated. The introduction of signals prioritised the movement of motor vehicles at the expense of pedestrians, whose effective walking speed through the city necessarily slowed. The consequences of making it easier to drive and harder to walk on people’s choice of mode is pretty straight-forward, and consistent with the rise of the automobile in the 20th century.

Phases

Pedestrians take longer to cross streets than cars because they move slower. As a result, the ‘don’t walk’ signal flashes before the light turns red for cars. But at many intersections it is worse than that. In Sydney, the traffic signal policy is set at many intersections to give less green time to pedestrians on a phase (from the time the light turns green to when it turns red, or from ‘walk’ to ‘don’t walk’)  than to automobiles, to give autos a protected left turn without having to yield pedestrians. This guarantees the average pedestrian arriving randomly at the intersection waits longer than a random car.

Cycle length

The cycle length (time from the start of the green light to the start of the next green) tends to be longer at busier intersections (and busier times of day) as a longer cycle length reduces the number of phases per hour, and thus reduces the amount of lost time associated  each phase, when the intersection is not being effectively used by any approach. Lost time can never be reclaimed, so one understands why engineers might want longer cycle lengths if the objective were moving cars.

However long cycle lengths particularly disadvantage pedestrians, who stand out in the open exposed to the elements and the tailpipe emissions of cars, motorcycles, trucks, and buses. Even more significantly, people systematically misperceive travel delay, so waiting at a traffic light feels even longer than it actually is.

Coordination

First introduced in 1922 in New York City, traffic signal coordination aims to ensure vehicles arrive at the traffic signal when it is green, so they don’t have to stop. By correctly timing traffic signals in sequence, platoons of vehicles move together through a ‘green wave’. So let’s say the wave is set for a speed of 40 km/h. Then as long as a car accelerates from the first signal to 40 km/h, and maintains that speed, it should then hit the following lights on their green phase as well.

Typical_Signal_Schedule_and_Traffic_Flow_Diagram,_North-South_across_Market_(1929).png
Typical Signal Schedule and Traffic Flow Diagram, North-South across Market Street, San Francisco (1929). Green wave set to 10.5 MPH (about 17 km/h).

While this is relatively easy to maintain on a single road, it is more difficult on a network, especially a complex, asymmetric network. It also works against the idea of actuation, as interruptions to the pattern (extending or contracting phases) change the window in which cars can successfully hit a green light at a given speed. Of course, just because cars can make a green wave at a speed of 40 km/h doesn’t mean pedestrians will make a green wave unless they travel at exactly a divisor of 40 km/h (e.g. at exactly 5 km/h between intersections). This means that pedestrians will more likely wait at red lights at intersections timed for cars.

Actuation / Beg Buttons

While some signals are ‘fixed time’ which eases coordination at the expense of adapting to conditions, modern signals are ‘actuated’, that is, they respond by adjusting the phasing, and perhaps the cycle time, in response to the presence of vehicles. For vehicles, there is either a camera which detects their presence, or more commonly, a sensor in the road, often a magnetic loop. In either case, this is automatic for the car, and can detect cars upstream of the signal. This allows the signal to stay green longer for a phase if it detects a vehicle approaching, or turn red sooner when there are no vehicles. In contrast, for pedestrians, they are required to push a button to get a walk signal. If they arrive a second too late, they have to wait the entire cycle to get a walk signal. If there are many pedestrians, they don’t get a longer walk signal. Pushing the ‘beg button’ (so nicknamed as the pedestrian must request the signal) twice does not make it come faster or stay green longer. Ten, or a hundred, pedestrians do not make the ‘walk’ light come faster either. The beg button is often positioned out of the way, requiring the pedestrian to walk longer than would otherwise be required. A few seconds here, a few seconds there, add up.

There is a  reason that traffic engineers don’t automatically allocate pedestrian phases. Suppose the car only warrants a six second phase but a pedestrian requires 18 seconds to cross the street at a 1 meter/second walking speed. Giving an automatic pedestrian phase will delay  cars, even if the pedestrian is not there. And there is no sin worse than delaying a car.  But it also guarantees a pedestrian who arrives just after the window to push the actuator passes will wait a full cycle.

The role of signal policy

It turns out that one of the world’s most widely deployed traffic signal control systems, the Sydney Coordinated Adaptive Traffic System (SCATS), was developed here in Australia. Just as Australia led in traffic control to more smoothly move cars, it should lead in pedestrian-oriented traffic control. There are a number of steps that those concerned about pedestrians should insist on. To start:

  • Pedestrians, like vehicles, should be counted automatically at controlled intersections.
  • Pedestrian time must be considered (and prioritised) in the traffic signal timing algorithms so that their weight is equal to or higher than the weight of a passenger car.
  • Pedestrians should get the maximum feasible amount of green time on a phase, rather than the minimum, so that pedestrians arriving on the phase have a chance to take advantage of it, and slower moving pedestrians are not intimidated by cars.
  • Pedestrians should get a ‘leading interval’ so they can step into the street on a ‘walk’ signal before cars start to move on a green light, increasing their visibility to drivers.
  • Pedestrian phases should be automatic, even if no actuator is pushed. Instead, the actuator should make the pedestrian phase come sooner.
  • Many more intersections should have an all-pedestrian phase (what is referred to as a ‘Barnes Dance’) in addition to existing phases so pedestrians can make diagonal intersection crossings without having to wait twice.

There are numerous other steps as well that can improve the life of the pedestrian, and thus increase their number. Certainly we can demand more patience from drivers as well.  The advent of the autonomous vehicles over the next few decades is unlikely, by itself, to eliminate the need for traffic control in cities. There will be places where the number of cars and people are such that they cannot efficiently organize themselves, and where other traffic controls, like stop signs or roundabouts, cannot be effectively implemented. But autonomous vehicles should help get more throughput out of intersections, losing less time than human drivers, and behaving far more safely.

The Transportist: June 2018

Welcome to the June 2018 issue of The Transportist, especially to our new readers. As always you can follow along at the blog or on Twitter.

Transportist Posts

Transport News

AVs

According to Uber, emergency braking maneuvers are not enabled while the vehicle is under computer control, to reduce the potential for erratic vehicle behavior. The vehicle operator is relied on to intervene and take action. The system is not designed to alert the operator.

CVs [Connectivity is the opposite of Autonomy]

SVs/Taxis/Car Sharing

EVs [and Renewable Electricity]

HPVs/Bikes/Pedestrians/Scooters/eBikes/etc

HDVs and Roads

Transit

Ferries/Ports/Maritime

Intercity Rail

Land Use

Science

Economics

Justice/Equity

Fantasy

Retail and Logistics

Technology

Technology History

Research & Data

Books

Dockless bikesharing survey

I have a student who is conducting a survey about dockless bikesharing in Sydney … ​ Please complete, and share.

Inner Sydney Transit Grid – Fantasy Map

While we are doing fantasy transit maps, here is my indicative sketch of an Inner Sydney Transit Grid (i.e. these are new high-frequency transit lines, likely some mix of tram/LRT or arterial Bus Rapid Transit with mostly dedicated lanes, assuming the already existing Sydney Trains and planned LRT and Metro [Red] lines remain, plus something on Parramatta Road [Green]). These are, of course, doodles, I haven’t done any modeling of them yet, and they would certainly replace existing bus routes in places.

The problem I am trying to solve is that the network is too radial in orientation, and even simple lateral movements are difficult on public transport. A clearly defined, not circuitous, high-frequency system that serves Sydney outside the CBD (without having to transfer in the CBD) seems useful. The lines are designed to connect existing and planned stations conveniently, so the routes are run on-street from station to station.

Inner Sydney Grid
Inner Sydney Grid

https://drive.google.com/open?id=1Iy9DKuBz5Qhg3Euy8LyoUMmeYPI&usp=sharing

 

The concept is to provide ring routes to complement the existing and under construction radial train lines

Starting along the Pacific there are 6 major lines (Ocean to River):

  • Bondi – Fish Market (via Paddington ) [Pine Green]
  • Bronte – Glebe (via Moore Park) [Pink]
  • Coogee – White Bay (via UNSW, University of Sydney) [Purple] [The Busful of Knowledge]
  • Maroubra – Balmain (via the Canal Zone) [Orange]
  • Little Bay – Drummoyne / Abbotsford (via the Airport* and Ashfield) [Brown]
  • Brighton Le-Sands – Mortlake (via Campsie and Burwood) [Silver]

There is also an interior branching route

  • Annandale – Alexandria [Avocado Green, Maroon]

There are some “new” thin radial lines shown, which track old tram lines, in particular around the University of Sydney and Newtown. And there are some new shuttle lines in Technology Park (and presumably on the Darlington side as well) (running along the rail lines) to better connect workers to the nearby stations, which are actually relatively far away given the large numbers of workers.

With most of these there is challenge finding right-of-way. I would take it from existing streets (these lines are mostly at-grade) so transit has priority. This assumes that transit service would carry more people than a laneful of cars, which likely will hold if the transit is designed to be effective. This is easier to do where there is on-street parking, harder where there is not.


* The Brown Line as shown, this assumes a rail line sharing tracks with existing rail service in airport tunnel. I am not certain the technical feasibility of this, otherwise it circumnavigates the airport somehow.

 

 

 Accessibility-Oriented Development

Recently published:

Abstract

Access to jobs and the labor force by car within 30 min.
Access to jobs and the labor force by car within 30 min.

Local authorities worldwide have been pursuing transit-oriented development (TOD) strategies in order to increase transit ridership, curb traffic congestion, and rejuvenate urban neighborhoods. In many cities, however, development of planned sites around transit stations has been close to non-existent, due to, among other reasons, a lack of coordination between transit investments and land use at a broader spatial scale. Furthermore, while TOD considers access to transit, it often neglects the access to destinations that is provided by transit.

We contend that accessibility-oriented development (AOD) can overcome these drawbacks of transit-oriented development. The AOD strategy fosters an environment conducive to development by balancing access to both jobs and workers. As such, AOD explicitly considers the connections between TOD locations and destinations that matter, both locally and regionally. Where markets are free to take advantage of accessibility levels, AOD is a naturally occurring process. Planners could therefore use the various tools at their disposal to influence accessibility levels (to jobs and workers) in order to attract urban development in potential AOD areas.

To test the assumptions that guide AOD strategies, access to jobs and workers are calculated in the Greater Toronto and Hamilton Area, Canada in 2001 and 2011. Cross-sectional and temporal regressions are then performed to analyze average commute times and urban development occurring across the region. Results show that residents in neighborhoods with high access to jobs and low access to competing workers experience the shortest commute times in the region, while the relationship also holds for changes in average commute times between the studied time periods. In addition, both access to jobs and access to workers are associated with changes in residential, commercial and industrial development: high labor force accessibility is associated with increases in job density, and high access to jobs is related to increases in population density between 2001 and 2011. Planners can thus leverage accessibility as a tool to direct development in their cities and to strategically adjust commute times, thereby realizing the full benefits of planned transit investments.

Keywords: Transit-oriented development; Accessibility; Travel behavior; Land use

Creating Great Australian Cities

Creating Great Australian Cities
Creating Great Australian Cities

Jonathan Hair reports on ABC Radio “The World Today” (Tue 22 May 2018) about the new study from Australia’s Property Council: Creating Great Australian Cities.

Property Council warns Australia still has work to do on urban liveability by Jonathan Hair on The World Today

Australia’s top cities may rate among the most liveable in the world, but the Property Council of Australia is warning us not to get complacent.

It has commissioned a report which finds that our cities need to improve issues, like infrastructure and public transport, if they want to continue to be attractive places to live.

The segment runs  on the linked .mp3 file. I get to have my say as well, arguing that access is a good, even if congestion is a bad and a feature of people wanting larger homes in the suburbs and commuting by car and population growth in excess of infrastructure growth. (I also talked about road pricing in the interview, but that was cut for time … that’s what I meant when I said “managing”.)

Interview:

JONATHAN HAIR: David Levinson is a Professor of Transport at The University of Sydney.

DAVID LEVINSON: Congestion is only going to get worse as long as there’s people being added to the system faster than infrastructure is added to the system, and as long as people aren’t doing anything to manage it.

People want to live further away from their jobs, and have larger houses, and there’s nothing inherently wrong with that. But the cost of doing that is that there’s more people using the same roads in the same amount of time.

JONATHAN HAIR: He believes the solution to the problem is making it easier to access services without having to travel.

DAVID LEVINSON: Manhattan is more congested than Sydney is but there are more things to do in Manhattan, so the accessibility is higher.

People can reach more things in the same amount of time. What we really care about is not moving quickly on the network, but getting to where we want to go. And if there’s more things around us, that are close to where we want to be, we don’t have to travel as long a distance.

So while growth has costs, it also has benefits in terms of activity, because there’s more stores nearby, there’s more restaurants, there’s more jobs that might be better suited to the kinds of skills that we have.

ELEANOR HALL: That’s University of Sydney’s Transport Professor David Levinson.

 

 

 

Meanwhile, the Sydney Morning Herald breathlessly reports “Sydney’s congestion at ‘tipping point‘” interviewing my colleague Stephen Greaves at ITLS.