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An underutilized asset?
Photo credit: autoblog.com |
When it comes to road safety issues there are three basic approaches. One concerns the design and architecture of streets and public spaces: if a street is built like a highway, motorists are unlikely to take it slow, regardless of speed limit signs or pedestrians/cyclists. We can slow down traffic by narrowing the streets and make things safer for pedestrians by constructing bump-outs and other traffic-calming/protective devices. Basically this approach emphasizes how the physical texture of cities and towns affects road safety outcomes.
A second approach seeks to understand road safety outcomes by looking at the intrinsic motivations of individual actors in the system. Are there cultural or social norms that make motorists or pedestrians act in certain ways? How do certain populations vary in their risk factors for road safety behaviors? Common interventions under this framework might be educational awareness programs, signage telling motorists to slow down or share the road with cyclists, etc.
A third approach sits in between these structuralist and motivation-based approaches: enforcement. If we assume every motorist, pedestrian and cyclist has some abstract baseline road behavior that is sub-optimal from a road-safety perspective (i.e. motorists prefer to go faster, pedestrians prefer to cross streets wherever), enforcement can artificially raise the costs of unsafe behavior, changing the internal cost-benefit calculation of individuals.
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Photo credit: wikimedia commons |
Enforcement can work in two ways. One is the probability of getting caught for a violation. Raise the probability that you'll get caught for speeding, and you'll see less speeding, regardless of the fine. This typically requires adding cops or allocating existing ones differently. The second is the magnitude of the punishment. Even if the probability of getting caught for a violation is the same, if the fine goes from $50 to $5,000 you'll see a decrease in violations.
The two dimensions of enforcement interact with psychology in complex and interesting ways, but I tend to subscribe to the "swift and certain" application of enforcement for road safety violations. Basically the idea is to dramatically increase the probability of getting caught for a violation, and implement a small-magnitude punishment as quickly as possible.
This brings us to automated speed cameras. Currently this technology is mostly utilized at dangerous intersections to identify motorists running red lights. If a simple algorithm sees a violation, it snaps a photo of the vehicle's license plate and the driver gets a ticket in the mail. I'm no expert in algorithmic pattern recognition or machine learning, but I suspect it's possible to make these cameras do much, much more. Developing more advanced programs to expand the reach of automated cameras into areas like failing to signal or passing a cyclist too closely would be a major boon to road safety efforts. Even $5.00 tickets for something as minor as blocking a crosswalk would likely result in safer streets if motorists
knew they would get caught.
A major benefit of these enhanced speed cameras is their feasibility: making the physical landscape of cities safer for pedestrians and cyclists is often expensive and always controversial. Changing the culture and norms of motorists, pedestrians and cyclists is really hard and takes time. Setting up a pilot system of enhanced speed cameras and sending out tons of tickets is an intervention that would be fairly invisible and occur largely in the back-office of municipal buildings. Even if privacy concerns bubble up, using probationers or parolees as a test group should be relatively straightforward and uncontroversial. Let's give it a shot.