–Traffic congestion is habitually described as real mess, but rarely analyzed for the different messes that it is.
–To see how, start with a simplified assumption to be problematized shortly: The net monetary value of any transportation system aggregated across all car users increases with the number of cars using that system up to the system’s carrying capacity for cars, which if exceeded leads to a decline in net value. This is shown in Figure 1’s net monetary value curve, AA’, which falls after reaching the system’s limit in carrying more automobiles (CC):
Assume the only value of interest is the value of the transportation system to car users. Assume initially that CC is fixed and that the current number of cars on system roadways exceeds that value. It may be possible to add new roads and new lanes over time, thus moving CC to the right (“supply management”). It may also be possible to reduce the number of cars to the left of CC by congestion pricing, vehicle taxing, and other tolls (“demand management”). Assume, however, that such interventions are not possible anytime soon (or if possible, their effects are not to be realized soon).
What can the transportation professional do instead in the face of congestion?
–By way of answer, we must better understand key terms. Just what is the “value” of the transportation system from the perspective of the car user? The benefits and costs are difficult to monetize fully, but assume the vertical axis of Figure 1 indicates their net positive value. Further benefits follow from the other ways to increase the value of the transportation system, even when it is not possible to increase the number of cars on the roads, e.g., through reducing average car size or narrowing lanes. Value also increases, ceteris paribus, when the number of passengers in a car increases (this being, the important issue of shared mobility and/or the number of uses to which the car is being put by its users increases).
Once other net benefits are added, the net monetary value curve rises, illustratively, to AB in Figure 1, with a gradual, delayed decline after CC being reached. More multiple-use vans on the road, especially if they replace existing vans and vehicles, increase the value curve before carrying capacity is reached. Once carrying capacity is exceeded, the time lost being stuck in traffic will be offset for some period by being able to do more things in one’s vehicle than before.
Diagrammatically, the increment in value between AA’ and AB, particularly after CC, is the value car users attach to a good mess coming out of the bad mess of the formal transportation system.
This is the value car users attach to producing a mess (AB) better than the one (AA’) that would have happened instead. Other thing equal, the aim of transportation professionals is to enlarge that increment. For example, not only do professionals want people “to get their best ideas” while stuck in traffic, they want many more people to do so.
–The simplified figure suggests two other ways to change net value. One is to redefine carrying capacity; the other is to redefine the “transportation system” and its services of interest. Carrying capacity has been a popular concept in modeling traffic congestion, its intuitive appeal being that there must be a limit to the number of cars that a system can accommodate, other things constant. As other factors are rarely constant, carrying capacity is necessarily a variable rather than a given.
This leads to the second way to alter net value. Just what is the “transportation system” being evaluated in terms of a good or bad mess? It need not only be the official system discussed of far. It is possible to redefine the transportation system of interest by changing the scope and knowledge bases for the “system” being analyzed and managed.
Imagine you are a professional in the Regional Transportation Authority (RTA). You have just undertaken a stratified random sample survey of RTA residents as to what they perceive to be locally successful transportation interventions about which they have first-hand knowledge. Focus groups and public meetings have subsequently been held, identifying other perceived successful interventions in the region. The currently preferred approach of RTA professionals is to pick from the list, say, interventions 3, 57 and 72—all of which fit in with ongoing planning and business as usual—and seek to extend them elsewhere in the region.
You however take a different tack with respect to the list. Assume it identifies interventions that include traffic calming sites in some RTA neighborhoods, increased off-street parking in others, widening streets at different sites, adding bicycle lanes in another set, and so on. Your task is to determine an implied or de facto “transportation system(s)” that link these discrete (groups of) sites together.
–The implied systems, if any, are more than road networks that connect the sites concerned. The existing availability and distribution of garages for cars, both above and below ground, connects sites as well. Yet the Region’s transportation system, like many RTAs, does not consider the de facto, informal network of public and private garages to be a major point of intervention in improving the formal, official transportation system. In this way, the informal system(s) can be conceived as lying in the domain of the traffic professionals between system patterns they perceive and localized scenarios that they never thought about until this point.
The challenge in the constructed example is to ask, What are we missing by focusing only on the formal transportation system and in answer to see what could or does connect sites of successful interventions into a system or network that can be supported by transportation professionals.
–One such informal system is illustrated in Figure 1. Here the transportation system is an informal one, i, implied by the connected sites, with its value curve ACi and its carrying capacity, CCi (which would now be cast in terms of local knowledge and familiarity with specific traffic patterns).
Diagrammatically, ACi is the net value car users attach to a good mess that could go bad at some point near or after CCi. If traffic professionals cannot squeeze good messes out of the bad mess that congestion has become (i.e., realize and increase a value increment between AA’ and AB), they can identify, protect and enhance different systems that are not (yet) bad messes.
What should the professionals do if there are neither informal systems to be improved nor any value increment to be realized in the formal transportation system? The “best” they can do under such circumstances is to try to keep Figure 1’s AA’ as “close” to the left of CC as possible or on the non-declining portion of AA’, should it exist, after breaching CC. Barring either, the professional is left with trying to halt or delay the further decline of AA’.
–Four kinds of good messes are, in other words, to be distinguished in the constructed example. They are the product of two states and transitions, namely, what start out as good or bad messes and what end up as more of a good mess or less of a bad one. Table 1 summarizes the four positions:
Table 1: Four Types of Good Messes in Traffic Congestion
In case it needs saying, each is a good mess in its own right, though perceptions and expectations about the four cells vary considerably.