Skip to main content

P5: Sustainable Safe Transportation Project with Smart City Elements and Smart Vehicles

Dr. Ahmet Saracoğlu

Principal Investigator

Dr. Ahmet Saracoğlu

LinkedIn Kuartis

Institution(s)

Kuartis (Leader), METU

Strategic Target Name

Developing a multi-sensor sensing, detection and tracking platform for autonomous systems, developing low-latency communication methods that are resistant to cyber-attacks in autonomous systems, developing electric public transportation, safe intersection and smart road technologies for safe transportation with a low carbon footprint, and conducting pilot applications by 2025.

Scope of Activity of the Project

Safety in the Autonomous Driving Environment in the City, Secure and Low Latency Communication for V2X in Autonomous Vehicles, Development of Autonomous Vehicle and Smart Transportation Integration Field.

Project Summary

Our project aims to make transportation in cities more efficient and safer by enabling autonomous vehicles to communicate with each other and smart intersections using safe and low-latency V2V/V2X communication technologies. Within the scope of the project, it is aimed to create environmental perception and awareness by combining information obtained from sensors on autonomous vehicles and smart city elements, interpreted with advanced algorithms and shared between stakeholders with V2V / V2X methods. In this way, many usage scenarios will be realized, from reducing fuel consumption and emissions to ensuring increased pedestrian and passenger safety.

In this project, the sensor data that the vehicles transmit to each other and to the infrastructure will be processed using innovative target tracking algorithms that are ahead of classical approaches, and a larger common picture will be created by combining this processed information. In this way, it is aimed for vehicles to have awareness and predictions about traffic beyond their field of vision. By selecting infrastructure sensors with different and complementary types and capabilities than those on the vehicle, highly accurate and precise estimates of the common picture can be produced.

Thanks to the technologies to be developed in the project, it will be possible to create a high level of environmental perception and awareness, reduce carbon emissions by increasing traffic efficiency, and increase both in-vehicle passenger safety and the safety of other traffic stakeholders.

Project Team

Dr. Osman Serdar Gedik

Dr. Osman Serdar Gedik

Researcher · Kuartis

Research Areas: Sensor fusion and tracking

Dr. Kamil Berker Loğoğlu

Dr. Kamil Berker Loğoğlu

Researcher · Kuartis

Research Areas: Computer vision and machine learning

MSc. Eren Şener

MSc. Eren Şener

Researcher · Kuartis

Research Areas: Computer vision and machine learning

Hilal Köksal

Hilal Köksal

Researcher · Kuartis

Research Areas: Computer vision and machine learning

Uğur Uyanık

Uğur Uyanık

Researcher · Kuartis

Mechanical Design

Assoc. Prof. Emre Özkan

Assoc. Prof. Emre Özkan

Researcher · ODTÜ-RÖMER

Research Areas: Sensor fusion and tracking

Assoc. Prof. Pelin Angın

Assoc. Prof. Pelin Angın

Researcher · ODTÜ-RÖMER

Research Areas: Cyber security

Assoc. Prof. Buğra Koku

Assoc. Prof. Buğra Koku

Researcher · ODTÜ-RÖMER

Research Areas: Robotics and mechatronics

Assist. Prof. Mustafa Mert Ankaralı

Assist. Prof. Mustafa Mert Ankaralı

Researcher · ODTÜ-RÖMER

Research Areas: Mechanical design, sensor fusion and tracking

Support Staff

Botan Kaya

Botan Kaya

Employee · Kuartis

Project Managemet

MSc. Alper Küçükkömürler

MSc. Alper Küçükkömürler

Employee · Kuartis

Research Areas: Software Technologies

← Return to the table

Last updated