The recent events related to pedestrians killed by self-driving cars have driven the attention to the risks and potentialities of the new automotive technologies and to the relative ethic and legal issues.
However, it is by now clear that an autonomous vehicle is safer and more efficient than a human-driven car, since it has no reaction time and it can instantaneously brake, thus also increasing the road capacity and the traffic efficiency.
But actual on-board sensors, even if advanced, neither allow to see around the corner, nor to alert the other road users of potential risks.
In this context, international associations are moving to understand the impact of connectivity on board of future vehicles: the 5G Automotive Association (5GAA) pushes the 5th generation cellular systems (Cellular-V2X) to easy the communication among the different road users (vehicles, pedestrians, bikes, infrastructures) whereas the Car-to-Car Consortium claims that a largely tested and consolidated technology such as Wi-Fi for mobility (ITS G5 in EU and IEEE 802.11p in US) could be the starting point for future vehicular communications.
In this highly competitive scenario, it is of increasing importance to have a powerful evaluation tool able to estimate and compare the performance of the different wireless access technologies in safety and non-safety scenarios.
Hence, the researchers of CNR-IEIIT have developed an open simulation tool (http://www.wcsg.ieiit.cnr.it/products/LTEV2Vsim.html) able to simulate the exchange of messages between vehicles and between vehicles and infrastructures in realistic urban and not-urban environments. Depending on how many and how frequently messages are exchanged, vehicles change their awareness of the surrounding scenario and exploit it to cooperatively share also intentions, improving the efficiency and the safety of the transport system.
The tool is open and available for both the scientific and industrial communities that aim at testing the behavior of the different technologies toward different vehicular applications.
For info: barbara.masini@ieiit.cnr.it
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