Today, several research groups, vehicle manufacturing companies and policymakers across the world are working together to find an efficient Advance Driver Assistance System (ADSS) which is very important for road safety and for Intelligent Transport Systems (ITS).
In ADSS, safe and secure cooperative Vehicle-to-Vehicle (V2V) communication is the most important parameters for next-generation driverless cars. This is to be employed to avoid accidents, specifically those involving collisions and changing lanes by enabling each individual vehicle to exchange location information.
The driver safety aids in vehicles are becoming standard equipment to prevent serious injury on our roads but there are still many parameters which are vital for safety and security of all road users. This includes traffic congestion, excessive pollution due to high energy consumption, which ultimately affects human lives living in the urban world or nearby the area usually experiences traffic congestion, this is something where the next generation ITS can work in favour of the green environment.
The autonomous or driverless cars are receiving a great deal of attention, with many automotive companies expending time, money and resources to research and development in this area. The importance of autonomous or semi-autonomous vehicles for intelligent transport systems (ITS) is increasing.
In particular, the rationale of ITS is to utilise advances in wireless communication systems for vehicles within a vehicular network (radius of 1-2 km) to alleviate major problems on road traffic systems, such as the prevention and mitigation of accidents, energy efficiency and infrastructure utilisation. The problematic subset of traffic is on safety and efficiency, where the vehicle must coordinate common resources such as junctions, roundabouts and slip-roads. These are most responsible for fatal accidents and injuries on the road [1] and studies have found that 90% of traffic accidents are due to human error [2].
The progressive shift of responsibilities from driver to machine control systems aims to provide a safe and congestion-free traffic system. According to the society of automotive engine (SAE) and vehicular communication standards (IEEE Wireless Access in Vehicular Environment (WAVE)), vehicles within the vehicular network must communicate efficiently within ten milliseconds of latency, which is a great challenge.
Information to be exchanged between vehicles for establishing the optimal coordination includes the vehicle dynamics, state measurement, road geometry and static and dynamic road map information. However, there are still many challenges that need to be addressed before autonomous cars can be allowed on the public highway.
Collision avoidance is one of the main challenges and this requires accurate localisation information to be available to the vehicle at all time. Generally, this is obtained from GPS satellites, but there are many environments where the GPS signal is weak or lost and alternative sources of location information are needed. The accuracy of GPS is affected by various sources of errors, such as ionospheric, tropospheric, multipath, receiver and satellite clock noise and tall building canopies which cause signal blockage. These sources of errors, in total, lead to an error of 10-20 m which will be detrimental in avoiding collisions. Technologies such as LiDAR, inertial navigation systems, 5G and Wi-Fi can all be utilised, as well as the internet of vehicles (IoV), but the reception of GPS signals are still important because it is the only one of way establishing clock synchronization between the neighbouring vehicles. It is, therefore, important to design a protocol that can apply data fusion techniques to ensure the vehicle always knows its location under any conditions.
In addition to internal challenges, communication with infrastructure or any unit (V2X) can be significantly affected by impairments associated with wireless channels, including the inherent randomness of the channel, multipath fading and limited communication range. As a consequence, packet drop and random latencies in packet arrivals occur. The solutions to these problems depend on signal processing to estimate optimal coordination. Wireless communication using 5G can cope with the massive number of vehicle connections in a given area, almost reducing latency completely.
In this project, the student will work on designing a protocol for transmission and signal conditioning and reception according to the 5G standard. In the intelligent sensing lab, Newcastle University, we recently obtained a massive MIMO kit which includes 32 universal software defined radios (USRPs) that can test WAVE based V2V, V2I communication standards using 5G. We are also working on designing low-cost sensors for precise real-time positioning for moving vehicles which can update and work with changing environmental scenarios. For traffic safety technologies, including V2V, V2X, it is very important to have improved positioning technology capable of mitigating environmental challenges.
In urban environments, satellite signal blockage or multipath fading due to tall vegetation, high-rise building and dense road infrastructures are commonly known to degrade the quality of satellite signal reception and consequently results in inaccurate positioning information. Figure 1 illustrates one of the cases we did in an experiment in Newcastle where two cars followed each other at the UK’s national speed, suffered degradation in their performances. So, as with urban environments in the UK, a generic GPS receiver with an INS sensor will also no longer be reliable.
Using arrays of dual polarised antennas for GNSS signal reception, instead of a dual frequency GNSS antenna, is a novel way to reduce the effects of multipath or loss of satellite lock. The latest GNSS software receivers now have a self-adjusting carrier-tracking loop and are enabled with the ability to process new European GNSS-based location system. When assisted by an array of dual polarised antennas we obtain a promising solution for the next generation of positioning systems.
Finally, in order to further mitigate the worst-case scenarios of a loss of positioning due to an insufficient number of GNSS satellites, the GNSS software receiver is equipped with additional receivers, a processor for future 5G networks, WiFi enabled positioning sensors, INS and Lidar will be utilised by a data fusion model for an onboard unit (OBU) to deliver high-quality traffic and travel information as well as business services to support travellers.
However, in addition to precise positioning and the communication between vehicles within the network, the sharing of location data between neighbouring vehicles is susceptible to security attacks or threat to freedom of privacy. Different ideas addressing these problems have been proposed, such as lightweight cryptographic algorithms [3] [4] and selective use of information [5]. Thus, the field of security in vehicle-to-vehicle (V2V) communication networks is receiving much attention and emerging standards such as IEEE802.11i, p and r allow data connectivity for fast moving devices. However, much of the data being carried across the vehicular network will be confidential only for a short time due to location information of the vehicle changing so rapidly. This project will focus on obtaining precise positioning in real-time and providing solutions that minimize the security overhead.Figure 1 On left, the trajectory of our experiment when one vehicle followed exactly another one in Newcastle, both cars lost location information when it passes through an overbridge; wherein the right, both cars lost location on various situation due to high-rise building and trees canopy.
- -H. Choi, “Crash factors in intersection-related crashes: An on-scene perspective,” National Traffic Highway Safety Association, report no. HS-811 366, Washington, DC. 2010.
- “National motor vehicle crash causation survey,” National Traffic Highway Safety Association, report no. DOT HS 811 059, 2008.
- B. Shemaili, Yeun, Mubarak, Zemerly, “A new lightweight hybrid cryptographic algorithm for the Internet of Things, ICITST-2012.
- H. Jokhio, and A. H. Kemp, “Node capture attack detection and defense in wireless sensor networks”, IET Wireless Sensor Systems, Vol 2 (3), 2012.
- H. Arisar, and A. H. Kemp, “Secure Location Estimation in Large Scale Wireless Sensor Networks”, Third International Conference on NGMAST ’09.
