How can cities use mobility analytics to accomplish their Vision Zero goals?

The goal of Vision Zero is to achieve zero road fatalities. But eliminating all traffic deaths requires a strategic and multipronged approach. Each city that strives towards this goal employs its own strategy, but regardless of approach, there’s one tool that can inform more impactful decisions across the board: Transportation analytics.

Historically, departments of transportation (DOTs) have relied on post-crash reports from law enforcement to guide road safety decisions. However, an estimated 60% of property-damage-only crashes and 32% of injury crashes are not reported to law enforcement. With the introduction of large-scale driving data into the public sector, cities may be able to accelerate Vision Zero progress with a more proactive and data-driven approach. Here’s how.

#1 Identify high-risk areas proactively

One of the key ways cities can leverage transportation analytics is to pinpoint and fix risky road segments before crashes even occur. Aggregated and historical data on driver behaviors – such as speeding, distracted driving, and hard braking – can reveal areas most prone to dangerous driving patterns that may not be obvious from crash reports alone. In fact, an estimated 60% of property-damage-only crashes and 32% of injury crashes are not reported to law enforcement.

In addition to capturing some of those missed crashes, frequent hard braking in one location can indicate a pattern of “near-misses.” This insight gives cities a chance to proactively diagnose and treat the problem before a crash happens. The cause may be as simple as confusing signage, poor street lighting, or a lack of traffic slowing measures — all of which can create a risky environment for drivers.

By flagging these potential hazards early, rather than waiting for reports from law enforcement or complaints from residents, cities can target areas for infrastructure improvement to reduce the likelihood of future accidents.

#2 Understand historical driving behavior patterns

Along with identifying high-risk areas, understanding how driving behaviors may have changed historically and seasonally can help cities plan for periods that tend to have a higher level of risk. For example:

Identifying roadways more prone to collisions during icy conditions can help organizations prioritize weather-related risk mitigation projects. Cities could use this data to understand where best to place temporary signage to encourage drivers to slow down and drive cautiously.

Levels of distracted driving may be heightened on New Year’s Eve. To deter risky driving behavior and prevent crashes, cities can increase law enforcement presence in high-risk areas on this date.

Hosting a big event, like a football game, can alter typical traffic flows and potentially influence an uptick in risky driver behaviors. By analyzing how similar events have impacted nearby driving patterns in the past, cities can better plan for future events.

The ability to predict these fluctuations enables cities to stay one step ahead, ensuring the appropriate road safety measures are in place when they are needed most.

#3 Improve real-time traffic management

Near real-time driving data can promptly alert cities to road hazards, congestion, or accidents to enable more efficient responses. For instance, if a multi-vehicle crash occurs on a major highway, cities can act quickly to block off the lane and address the emergency. Or if a road obstruction is causing severe traffic delays, cities can divert traffic and address the issue.

The sooner cities can respond to incidents like these, the more they may be able to minimize traffic risk and enhance safety for all road users.

#4 Enhance infrastructure planning with driving behavior insights

Driving data at scale can give a clearer picture into individual road segments’ usage and risk, highlighting the busiest and most dangerous areas to determine where road safety projects will have the greatest impact. This can ultimately help bring focus into resource allocation decisions.

In addition, this data can be combined with other types of data to fuel more effective infrastructure decisions for both drivers and vulnerable road users (VRUs) alike. Data on VRU incidents or points of interest (POIs), for example, could help identify the most ideal places for future bike lanes or pedestrian crossings.

#5 Track progress and optimize strategies

One major challenge in the public sector is knowing whether road safety initiatives are working. Again, while crash reports from law enforcement could provide some insight, there is usually a delay to submit, process, and analyze them and not all accidents are reported.

With ongoing, near real-time data collection to serve as ground truth, cities can monitor the effectiveness of their projects over time and adjust as needed. For example, once a countermeasure like a speed enforcement camera is put into place, cities can monitor changes in the frequency of speeding, crashes, and near-misses.

This feedback loop empowers cities to evaluate the success of their safety projects to not only demonstrate return on investment to communities and stakeholders, but also to adjust as needed and continually optimize their approach to Vision Zero.

Achieve Vision Zero faster

We all deserve to live in a world with zero traffic fatalities. Leveraging driving data at scale can accelerate all parts of road safety planning – from identifying risk, to prioritizing risk, to mitigating risk, and beyond. For any city’s strategy or approach, telematics data is a tool that enables targeted, impactful decisions to accelerate Vision Zero progress.

About Arity

Arity is a mobility data and analytics company that provides data-driven solutions to companies invested in transportation, enabling them to deliver mobility services that are smarter, safer, and more economical. Arity collects and analyzes trillions of miles of driving data to create a greater understanding of how people move. With the world’s largest driving dataset tied to insurance claims collected through mobile devices, in-car devices, and vehicles themselves, Arity derives unique insights that help insurers, developers, marketers, and communities understand and predict driving behavior at scale.