Project Objectives
The main objectives of the project are presented next.
1. The definition of the unified sensorial, hardware and software on-board platform. The goal is to define the required data representation standards and communication protocols. The following sub-objectives are derived:
1.1. The unification of the sensorial data representation for the physical sensors and for the virtual sensors built on top of the physical sensors.
1.2. The unification of the environment representation based on the LDM model.
1.3. Defining an application level communication protocol for V2V and V2I aligned to the available proposals/standards, based on the 802.11p wireless communication standard.
2. Choosing a wireless communication solution and experimenting V2X communication protocols, with the goal of finding the optimal solution. The available SMD do not yet support the standard 802.11p protocol for V2X communication. However, on the market there exist custom solutions for the standard wireless V2X communication. Among them we can mention NEC with the LinkBird-MX model, INRIA etc.
– Testing and evaluation of the communication capabilities of the custom solutions based on 802.11p standard at data and network layers.
– Testing and evaluation of the interconnection solution between the SMDs and the custom V2X communication devices.
– Testing and evaluation of the integrated solutions.
– Selection of the optimal wireless communication solution.
– Migration to the final solution based on the SMDs equipped with the 802.11p facilities.
3. On-board components and functions. The Smart Mobile Platform (SMP) consists of a smart mobile device (SMD) and the designed and developed algorithms for sensorial perception, sensor fusion, environment representation, driving assistance applications and communication modules. The following sub-objectives are derived:
3.1. On-board virtual sensors built on the vehicle and SMD standard sensors:
– Input from vehicle standard sensors: average speed, temperature, yaw rate, acceleration, steering angle, wheel speed, accelerating / breaking, ABS, ESP, ASR.
– Input from SMD standard sensors: GPS, mono camera, stereo camera, gyroscope, accelerometers, digital compass.
– Standard sensorial data conversion in the unified format.
– Virtual sensors built on the unified sensorial data.
– Output of the virtual sensors: road friction, tire pressure, driver behavior, hard breaking event, sudden steering, wheel vibration, obstacle detection, lane marking detection, painted road signs detection, collision detection.
3.2. On-board and V2X information fusion and environment representation using a proposed on-board LDM model:
– Input: on-board sensorial information including the virtual sensors, V2I and V2V acquired information.
– Temporal and multi-sensor fusion of the sensorial information and LDM generation and updating.
– Output: updated LDM model; targeted updating rate is of 5 Hz.
3.3. Design and development of the application level protocols for information acquisition and distribution (V2V, V2I, V2I2V):
– The designed application level communication protocol will be based on the most advanced existing standard proposal.
3.4. Design and development of safety, mobility and eco-driving assistance applications:
– Based on the sensorial information and the LDM environment representation a set of cooperative advanced driving assistance applications will be developed in the following directions: road condition warning, intelligent speed adaptation, speed harmonization, collision warning, lane departure warning, eco-routing.
4. Design and development of a general purpose RSU for information gathering, fusion and sharing based on a proposed RSU-level Local Dynamic Map model. The following sub-objectives are derived:
4.1. General purpose RSU specification, design and implementation.
4.2. Design and development of the application level protocols for information acquisition and distribution (V2I, V2I2V, GPRS based):
– The designed application level communication protocol will be based on the most advanced existing standard proposal.
4.3. GIS Map, V2I, I2I, and GPRS information fusion and environment representation using a proposed RSU-level LDM model:
– Defining the LDM model.
– Collecting information through V2I from vehicles, I2I from other infrastructure units, and from traffic information systems (TMC, Fleet Management, etc.).
– Fusing of the collected information.
– Geo-referencing of the fused information to the GIS map.
– Building and updating the LDM model.
– Targeted updating rate is of 5 Hz.
5. Development of the Regional Traffic Information System (RTIS) based on the existing TMC system and by including dynamic information from fleet management systems and weather stations: average speeds on road sectors, road conditions, temperature.
5.1. Collecting live traffic data from various sources including floating cars, live traffic reports from drivers, existing road sensors and national road agency and newly developed RSUs.
5.2. Automatically processing of received data in order to produce relevant traffic reports.
5.3. Traffic report forecasting based on historical data.