Statistical data

The statistical data available from ELSTAT for the years 2007-2019 have been analyzed and processed, as part of the RARE project. Road safety is encompassed by the tripartite "driver - vehicle - road network". The most important conclusions are summarized below:

DRIVER

  • Oncoming traffic (10%), speeding (9%), driver distraction (8%) and priority violation (6%) are the most common causes of fatal traffic accidents.
  • Male victims are on average four times as many as female victims, while in absolute numbers they are almost equal to the total number of dead as a result of traffic accidents.

  • The age group that has the leading role in road accidents is by far the 25-44, signaling the importance of reducing road accidents in increasing the competitiveness of our country, as this age group constitutes its productive wealth. The 45-64 and 65+ age groups are next, thus indicating the importance of continuous driving training for drivers. They are followed by the age groups 21-24, 15-17 and 0-14, which is mainly attributed to their small population, rather than to the increase in their driving awareness.

CAR

  • 5,552 passenger vehicles, 3,875 motorcycles, 397 mopeds and 218 bicycles, 682 trucks up to 3.5 tons and 142 trucks over 3.5 tons, 25 buses and 2,239 pedestrians were involved in traffic accidents.
  • Car passengers that have a five star rating in Euro NCAP (European New Car Assessment Program) tests have a 68% lower risk of fatal injury and a 23% lower risk of serious injury than occupants of cars rated two stars.
  • Failing to wear a seat belt and helmet is a main characteristic of road fatalities, combined with the fact that 55% (418 of 754) of passenger vehicle fatalities and 43% (306 of 712) of motorcycle and moped fatalities were with an involved vehicle, mainly due to the inappropriately high speed of the vehicles.

ROAD NETWORK

  • 74% of the accidents occurred on municipal roads, 22% were equally divided between national roads and country roads, while only 3% occurred on motorways.
  • 132,928 traffic accidents occurred in residential areas, four times more than the 32,576 that occurred in non-residential areas.
  • The region of Attica holds the lead in the number of traffic accidents, with almost 1 in 2 accidents occurring in Greece occurring within the said region. They are followed by the regions of Central Macedonia (17.84%), Peloponnese (5.25%), Central Greece (4.65%) and Western Greece (4.57%). The regions of Epirus (1.17%) and Western Macedonia (0.92%) recorded the best performance.

  • However, with a conversion of deaths per 100,000 inhabitants, Attica records the best performance, while the South Aegean region the worst.

OTHER FACTORS

  • Traditionally, most accidents occur in July (10%) and the fewest in January-February (7%).
  • There is an indication that most traffic accidents occur on Friday (16%) and the least on Sunday (13%).
  • There is a very clear indication of the time of day when most traffic accidents occur, while the differences between time periods are particularly significant. More specifically, 25% of traffic accidents take place between 13:00 and 16:59, 22% between 17:00 and 20:59 and 21% between 09:00 and 12:59. On the contrary, between 21:00 and 23:59 12%, between 05:00 and 08:59 11% and between 00:00 and 04:59 only 9%.

Future challenges

Responsible road behavior presupposes a safe road network and a citizen with high road awareness.

The main challenge facing road safety policy makers is to transform the tripartite 'driver - vehicle - road network' into 'driving behavior - vehicle - road network'.

Exploiting the possibilities offered by modern digital technologies are at the core of road safety plans. The utilization of new large-scale data (big data) is expected to significantly support road safety actions and measures by:

(a) rapid and reliable collection of large-scale data on accidents and traffic on the roads

(b) exploiting data from special sensors on the road, on vehicles and on smart mobile phones

(c) exploiting the most advanced artificial intelligence and machine learning techniques to transform the data into useful indicators, but also for the multi-level and multi-parametric analysis of the causes of road accidents

(d) real-time support of the authorities' strategic, tactical and operational decisions.

Exploiting the potential of modern digital technologies is at the heart of the Project, the success of which is based on the existence of connected and automated vehicles that will transmit data. This data, combined with the recording and analysis of the data that will be obtained in the cases of traffic accidents, will lead the system to be developed to calculate the dangerousness of each road and, by extension, the alternative routes.

Therefore, the system that will be developed as part of the Project will be able to warn drivers in time about the danger of each route they have chosen with the aim of choosing the least dangerous one with the ultimate aim of increasing the level of driving behavior, and by extension , the reduction of traffic accidents.