People assume that, every spring, due to daylight saving time (DST), losing an hour of sleep leaves drivers sluggish and more prone to accidents. It makes sense: Less sleep may equal more risk on the road. But what if the reality isn’t so clear-cut?

Despite the common belief that spring forward translates to drowsy drivers and riskier roads, our recent driving behavior data may tell a different story. Keep reading to learn how the time change affects U.S. roadways.

#1 Driving behavior data reveals that levels of hard braking remain consistent

As a data and analytics company dedicated to building a safer future of mobility, our team dove deeply into rates of hard braking as a key indicator of risk; hard braking is often a sign of drivers attempting to avoid an accident.

Looking at the past three years of driving behavior data, we found that during the week of DST, drivers don’t stray too far from their usual hard braking patterns. For instance:

• Nationwide, hard braking rates increased less than 1% in the week after the time change, compared to one week prior.
• In Georgia, hard braking rates increased 3.3%.
• In Florida, hard braking rates decreased .6%.

Each of these increases and decreases are well within the “normal” range for day-to-day fluctuations. Even during morning rush hour, when we expect more of that drowsiness to have an impact, this behavior did not meaningfully change.

So, do roads get riskier after the time change? While our driving behavior data suggests otherwise, there are other existing resources and studies worth considering. While Arity measures hard braking as just one behavior that correlates with driver risk, it’s not the only indicator of overall road risk. For instance, a widely cited study looked at 700,000 car accidents from the mid-1990s to 2017 and found a 6% increase in crashes the week after DST.

#2 However, some drivers adjust their commute times

Although spring forward doesn’t seem to significantly impact hard braking rates, there is a shift around when some drivers choose to hit the road that week – likely taking advantage of the extended daylight hours.

The week after DST, we tend to see fewer trips driven during the typical morning rush hour (5:00 a.m. to 9:59 a.m.) and more trips driven later in the day (7:00 p.m. to 10:59 p.m.), after the afternoon rush hour.

In fact, when we look at trip distribution by time of day nationwide:

• 19.4% of trips driven throughout the day occurred in the morning rush hour period prior to DST. This fell to 17.5% after the time change.
• Meanwhile, 13.6% of trips driven throughout the day fell into that 7 p.m. to 10:59 p.m. timeslot, which crept up to 15.5% afterward.

While both time periods only saw about a 2% change, it indicates that some drivers alter their schedules slightly from one week to the next.

Ask an Arity expert: Q&A with Megan Jones, Senior Actuary and Analytics Director

What was the methodology behind this study?

We dove into our massive driving behavior dataset to determine if and how driving behaviors change the week of spring forward. We focused on hard braking, phone distraction, and trip volume from 2022 – 2024, reviewing these trends nationwide and for various states including Virginia, Georgia, Illinois, California, and New York. We also took a closer look at Arizona as a control state since they don’t observe DST.

What signs indicate drivers have fully adjusted to the time shift?

There is an older study that found a 6% increase in crashes after DST. However, over the past three years, we haven’t seen much of a change in hard braking levels during the week of DST, and we even observed lower levels of distracted driving. This may suggest that drivers could be addressing the potential for increased risk.

Whether or not our data indicates drivers have adjusted by day one of spring forward, it’s extremely important for all to be more vigilant and abide by traffic laws to ensure everyone stays safe on our roadways.

What are practical pieces of advice for drivers to adjust more smoothly to the time change and minimize risk?

For one, give yourself extra time on the road. As our data shows, traffic patterns are prone to shift as drivers adjust, so it may be helpful to give yourself extra commute time just in case it’s needed.

And more importantly, understand your own driving behavior patterns. While our hard braking data doesn’t show a significant impact on driver risk due to the time change, one of the most impactful things you can do to reduce risk long-term is to understand how you’re contributing.

In a recent consumer survey by Arity, nearly 80% of respondents said they believe individual drivers are mostly or completely responsible for improving driving safety. However, there’s a knowledge gap when it comes to dangerous driving behaviors. If you choose to do so, insights into your personal driving behavior, through insurance safe driving programs or other safety apps, can be a tool that empowers you to drive smarter and safer.

What are some specific ways driver behavior data can help drivers stay safer during the first week of daylight savings time?

Again, if you choose to do so, tracking your own driving behavior insights through an insurance safe driving program or other safety apps can help you understand how your behaviors – such as using your phone while driving – could be unintentionally impacting your safety. Then, with that information, you can adjust where needed, including during the DST adjustment period.

Other key players in mobility, like city and state departments of transportation (DOTs) can use aggregated, historical driving behavior data to understand trends around how Daylight Savings impacts overall road safety. They can then use those insights to put countermeasures in place, whether that’s through education, enforcement, or engineering initiatives.

About Arity’s source data

Arity’s multi-source dataset, comprising over 45 million active connections, captures anonymized and aggregated driving behavior data from consumer apps and insurance telematics programs. By drawing from diverse sources beyond any single industry, we provide a comprehensive view of how, where, and when people move across the U.S., with representation across all states and demographics.

Our data distinguishes personal trips from gig driving and non-driving impacts, offering insights into trends like speeding, braking, acceleration, phone handling, and time of day. Supported by the largest telematics dataset linked to auto insurance claims, we can accurately predict the impact of shifting dangerous driving behaviors detailed in this report.