This project is about increasing safety and efficiency in Intelligent Transportation Systems through a novel vehicular localization system GreenLoc. Safer transportation and autonomous driving relies on determining the position and relative velocity of surrounding vehicles and road infrastructures, while energy-efficiency of localization is critical for the sustainability of our planet. The state-of-the-art autonomous driving localization technology suffers from the following serious limitations: 1) Limited maximum speeds when other vehicles exist around due to delay in collecting and processing of location information by the mixed locatlization system of video cameras, LIDAR and radar systems, road markers, ultrasonic sensors, Wi-Fi fingerprinting data, V2V communications through protocols such as WAVE, etc. 2) Ineffectiveness in visual localization due to difficult weather conditions (such as heavy rain and fog) or optical illusions (for example, perceiving a straight road although it bends), stemming from LIDAR and video camera based visual localization of surrounding vehicles. Moreover, energy-efficiency is not provided by the current locatlization systems used in state-of-the-art autonomous vehicles.
This project aims to develop GreenLoc, which is a high-sensitive, fast and green localization platform among vehicles in a multihop vehicular ad-hoc network (VANET).
Crash safety involves taking actions in order to prevent any possible accidents. Accurate localization and determining the position of surrounding vehicles and road-side units with high sensitivity is a necessity for providing crash-safe autonomous vehicles. Reducing delay of localization is also necessary in order to act fast enough before significant position changes occur in presence of high-speed autonomous vehicles. Furthermore, reducing energy costs introduced by the continuous localization process is required for reducing the frequency to charge a high-speed autonomous vehicle, which is the major factor shrinking the average speed. Hence, crash-safe high-speed autonomous vehicles require accurate, fast and energy-efficient localization. Current autonomous vehicle localization technology is insufficient in meeting these three performance measures at the same time, requiring a different approach.
The main goal of this project is providing high-sensitive fast green localization in ITS, serving the ‘Smart, green integrated transport’ focus area of Horizon 2020. GREENLOC aims to localize surrounding vehicles and road-side units (serving instead of conventional traffic lights or stop signs at intersections; or acting as anchors for increasing localization sensitivity in tunnels, closed parking lots and cities), which constitutes a basis for preventing accidents and opening the way to crash-safe high-speed autonomous vehicles.
