Prevent Road Accidents and Everyone Benefits
Road accidents come with a huge human and financial cost.
Consider these statistics:
- 2018: 36,560 lives lost, 1,894,000 injury and 4,807,000 property damage only crashes in the U.S.
- 2019: $184B+ in incurred losses for private and commercial auto insurance
- 2016: 1,099,032 injury accidents in the E.U. with more than 25,000 lives lost
Road accident prevention brings significant benefits to individual drivers, pedestrians, property owners, insurance companies, emergency service providers, and the government departments of transportation that want to keep traffic moving on their roads. And since road accidents are major sources of congestion, reducing their number could also have an impact on pollution and other urban challenges.
Let’s dig into the causes of road accidents and look at how data from connected cars can help with both prediction and prevention.
#1: Human Error
The U.S. National Highway Transportation Administration (www.nhtsa.gov) states that 94% of serious crashes are caused by human error. It says the key to preventing these accidents in the automated driver assistance technologies that are now available in more car models. Intelligent, in-vehicle software uses data from cameras and ultrasonic sensors to warn drivers about safety risks, such as a lane departure or a slow-moving vehicle ahead. And increasingly, they’re able to act on the drivers’ behalf to prevent a crash. As cars become fully automated, they will both increase safety and extend mobility to new populations.
#2: Vehicle Condition
Vehicle condition, from underinflated or worn out tires to faulty brakes, are a second significant factor in road accidents. Car manufacturers now offer more in-vehicle alerts on vehicle condition. However, connected vehicles generate even more trouble codes that contain the keys to accident prevention. Today, fleets can take advantage of remote diagnostics services that turn raw trouble codes into actionable insights and alert fleet operators about potential problems. These same types of services may become available for individual drivers as well; and OEMs will continue to enrich their in-vehicle diagnostics and alerting.
#3: Weather and Visibility Conditions
According to the U.S. Department of Transportation, 21% of crashes are weather related. In particular, weather and visibility play a role in multiple vehicle collisions, which are especially dangerous and have a significant effect on congestion. There’s a lot of work being done to identify relationships and build predictive models that help us understand when a road accident may happen, so that transportation agencies can take action. These actions could include short-term risk mitigation through dynamic signage, speed controls, traffic light timing, sanding or plowing, or other road treatments. Long-term, accident prediction models can help agencies prioritize road improvements. However, according to a 2017 survey by the U.S. Federal Highway Administration, U.S. states have limited adoption rates for most of these tools.
Connected cars generate richer inputs for predictive models than what has been readily available in the past. For example, crowdsourced data from connected cars can identify rain and measure its intensity. They can detect the presence of fog based on when drivers turn their headlights on.
#4: Other Road Hazards
There are other road hazards that also cause accidents, especially when drivers don’t have a way to anticipate them. These include uneven pavement, stalled vehicles, or objects in the road. Data generated from connected cars can also alert agencies to these types of hazards, through abnormal braking patterns and other hazard data.
Numerous studies have shown a relationship between congestion and road accidents, and alerting drivers to traffic jams helps with accident prevention. Many agencies have deployed dynamic signage that alerts drivers, and navigation apps like Google Maps or Waze include traffic alerts. Today, much of this traffic data comes from in-road sensors, toll payment devices, or cell phone data. Connected car data can generate traffic data that’s highly accurate and offers low data collection costs. It’s also much safer than asking drivers to self-report incidents in an app— and take their eyes off the road in order to do so.
Integrate Connected Car Data into Your Road Accident Prevention Efforts Today
Whether you’re a transportation agency working on road accident prevention or a researcher working on accident prediction models, Otonomo can help you.