When it comes to road safety, the common wisdom is that slower is safer. However, research dating back to the 1960s challenges this assumption.
A foundational study by David Solomon, followed by further validation from researchers West and Dunn in 1971, introduced a counterintuitive but critical insight: driving significantly slower than the average speed of traffic can be more dangerous than speeding.
This phenomenon is best illustrated by what's now known as the Solomon Curve, a U-shaped graph that correlates accident risk with deviation from average traffic speed. Let’s explore what this curve reveals and how it continues to influence traffic safety policies today.
The Solomon Study
In the late 1950s and early 1960s, civil engineer David Solomon conducted one of the most influential studies on traffic safety. Analyzing data from over 10,000 crashes on rural highways, Solomon plotted accident involvement rates against the drivers’ speeds relative to the average flow of traffic.
What emerged was a curve showing that both very fast and very slow drivers had higher crash rates than those traveling at or near the average speed.
This U-shaped graph, the Solomon Curve, demonstrated that the safest driving occurred when vehicles were moving close to the mean speed of traffic.
Surprisingly, drivers traveling much slower than average had a higher crash risk than even those driving well above it. This revelation went against the prevailing notion that speed alone was the principal danger on roads.
West and Dunn’s Reinforcement of the Solomon Curve
In 1971, researchers James West and Robert Dunn revisited Solomon’s work using updated crash data and methodologies.
Their findings largely supported the original conclusion: large deviations from the average speed, whether above or below, correlated with increased accident involvement.
The reinforcement of the Solomon Curve through independent analysis added credibility to its implications and further complicated the discussion around speed limits and traffic enforcement.
West and Dunn highlighted that while high-speed collisions tend to result in more severe injuries or fatalities, the actual likelihood of being involved in an accident was more strongly influenced by speed variance than absolute speed.
That is, being out of sync with the flow of traffic, regardless of whether a driver was faster or slower, was a key contributor to crash risk.
Why Driving Slow Increases Risk
There are several reasons why driving below the average speed can be hazardous. The first is speed differential, the difference between the speeds of vehicles on the road.
A slow-moving car forces faster-moving traffic to slow down, change lanes, or overtake, introducing potential conflict points. These interactions increase the risk of side-swipe and rear-end collisions.
Secondly, slow drivers often create unexpected behavior in an environment where drivers typically anticipate a certain speed flow.
This unpredictability leads to abrupt braking or lane changes from other drivers, which can cause chain-reaction crashes, particularly in high-density traffic.
Additionally, slow drivers are often passed more frequently, which means they spend more time interacting with vehicles moving around them, a known risk factor in traffic safety.
This is especially true on highways, where merging, lane changing, and overtaking are frequent. Drivers going well below the speed limit can disrupt these maneuvers and increase the chances of collision.
Context: Urban vs. Rural Roads
It’s important to note that the Solomon Curve was based on data from rural highways, where conditions differ significantly from urban environments.
On rural roads, average speeds are higher, and the range of speeds between the slowest and fastest drivers tends to be wider. This makes speed variance a particularly crucial factor.
In urban areas, the relationship between speed and crash risk is more complex. Lower speeds in cities often reduce the severity of collisions, especially involving pedestrians.
However, the principle that large deviations from the surrounding traffic speed, either fast or slow, can lead to increased crash risk still holds.
Policy Implications and Debate
The findings from Solomon and later from West and Dunn have influenced traffic safety policies, particularly the concept of speed harmonization, the idea that roads are safest when all vehicles travel at roughly the same speed.
This has led to debates over whether speed limits should be set to reflect the 85th percentile speed (the speed at or below which 85% of vehicles are traveling), a method designed to align legal limits with natural traffic flow.
Critics of the Solomon Curve argue that the original studies are outdated and don’t fully account for modern vehicle safety technology or the dynamics of urban driving.
However, the core insight remains widely accepted in traffic engineering: deviation from the average traffic speed, especially on high-speed roads, is a significant risk factor.
