In this article, we are going to examine some areas in which data analytics and artificial intelligence (AI) can help to increase traffic safety.
In the past 200 years, the development of the motorized vehicle has elevated civilization to new heights and given us the ability to explore the earth’s plains and hills. The development of self-driving autonomous vehicles has advanced thanks to the current age in the fields of technology, science, and analytics. This has also enabled vehicles to make decisions that save the lives of occupants, pedestrians, and all other living things during unforeseen traffic conditions or accidents. We can now go farther and more safely from point A to point B thanks to this level of technology.
The number and severity of accidents have, however, substantially grown in recent years due to the introduction of powerful and faster automobiles. Around 1.35 million people die in traffic accidents annually, or 3,700 people on average per day, according to the Association for Safe International Road Travel. Each year, an additional 20–50 million people suffer non-fatal injuries, many of which leave them permanently disabled.
Up until 2010, according to a variety of statistics, the number of road accidents, accident-related deaths, and injuries in India increased steadily. Since then, the number of accidents has stabilized with minor fluctuations. This saturation resulted from the adoption of safety technologies and systems that make use of artificial intelligence (AI) and data analytics, such as the anti-skid braking system (ABS), as well as from the installation of speed detection cameras and vehicle movement surveillance cameras.
About 449,002 accidents occurred in India in 2019, which is a worrying statistic. Transport authorities around the world are now working extremely hard to reduce traffic accidents and raise road safety as a result of these trends.
Why do traffic collisions happen?
Road accidents, injuries, and fatalities are caused by a number of reasons, including:
- poor maintenance and management of roads
- Unsafe state of vehicles with faulty safety features
- ineffective or nonexistent traffic regulations
- unsafe driving practices
- A lack of post-crash care
These alarming factors make it necessary for us to enhance current road safety practices, which is where cutting-edge technology like data analytics come into play. Let’s examine some areas where data analytics and artificial intelligence (AI) can help to increase traffic safety.
Using data analytics to reduce auto accidents
The location of accident hotspots
Road accidents can occur everywhere and at any time due to a variety of circumstances, but a careful examination of accident statistics shows that some regions experience more accidents than others. They are referred to as “accident-prone zones.”
Finding these hotspots and taking the required steps to reduce accidents there are made more effective by data analytics. Additionally, having this knowledge aids in the implementation of safety measures like speed limits and barricades, which usually lower the likelihood of accidents and thereby improve road safety. By detecting accident-prone areas and potential accident dates, this helps prevent road accidents in the future by applying predictive analytics. The main difficulty is gathering a huge volume of data. Predictive analytics, however, can save lives and provide significant benefits.
The main causes of accidents in large cities are an increase in the number of vehicles and heavy traffic flow. Traffic management is organized and efficient with the use of data analytics, and the following tasks are carried out by the authorities using data analytics and AI:
- to schedule the length of the halt at signals and guarantee traffic flow
- Install speedbumps and speed detection cameras to limit the speed in specified locations, particularly on motorways.
- Identify locations for the installation of speed limit signs,
- To escape traffic, direct the automobiles to roads with fewer traffic.
The speed detection cameras can notify authorities when a driver exceeds the posted speed limit or drives recklessly, and their insurance may be docked as a result. These steps lessen the likelihood of accidents while assisting with traffic flow during peak times.
Emergency vehicles can be assisted by artificial intelligence (AI) in getting there quickly and safely. However, because of the heavy traffic in urban areas, these rescue vehicles sometimes struggle to make progress, which is problematic because every minute counts in an emergency. The use of AI to recognize approaching ambulances and other rescue vehicles utilizing GPS and LTE mobile communication technologies is now being researched and tested in Germany. This enables communication between the vehicles and the traffic infrastructure, which turns on the traffic lights and enables emergency vehicles such as ambulances and fire trucks to proceed when a stoplight appears without stopping at the signal, enabling them to get to their destination more quickly and safely.
Supporting safety equipment in contemporary automobiles
An autonomous car can generate up to 3600 gigabytes of data every hour, according to a German telecom company, which is more than the average modern vehicle’s 25 gigabytes per hour. These data include the information gathered by the drivetrain sensors that power the car as well as information on the driving style of the driver, the positions and movements of nearby objects and people, and the state of the road.
Accidents can be decreased thanks to the wealth of information available. It provides an opening for the automakers to create safety technologies that would safeguard the occupants and other road users. Several of the available safety features include:
- The likelihood that a sleepy or fatigued motorist may cause an accident owing to slow reactions or dozing off can be decreased with the help of driver alert systems. These systems are made to recognize the telltale indicators of an intoxicated or sleepy driver and then inform the user or take corrective action utilizing advanced analytics and artificial intelligence.
- Utilizing the data produced by the sensors, systems like electronic brake distribution, adaptive cruise control, traction control, and torque vectoring react at critical moments to prevent accidents.
- AI-powered dashcams are being used to measure eye movements, observe driving behavior, and monitor drivers. This cutting-edge technology assists in identifying drunk drivers and responds by sending out warning messages or, if necessary, halting the car.
Other Department Personnel related to Vehicles and Road Safety who use Data and Analytics are:
- Insurers – Insurers are using AI technologies to analyze the condition of the car and determine the appropriate insurance premium rate using telematics data from the onboard diagnostics of the vehicle and information from the service and repair shops. The state of the car may therefore affect the premium prices. If the environment is hazardous, accidents may be inevitable. The insured person will therefore always keep the car in good condition to keep the premium amount low, which results in fewer accident scenarios.
- Policymakers should establish goals for reducing accidents, track their progress, and create action plans for improving road safety.
- Police identify local accident-prone regions and keep track of compliance with enforcements
- For resource planning, health promotion, and injury prevention initiatives in the health sector
- Research community — to publish studies that lower hazards and collisions, to test and enhance the strategies for improving road safety
- Data to be used as evidence by the prosecution
Data analytics actively works to increase traffic safety
Although the development of motorized cars is one of the most amazing achievements in human history, the rise in traffic accidents in recent years has resulted in a substantial amount of harm and loss to people, but with analytics and data-driven insights, it’s possible to improve traffic safety and save countless lives.