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Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS.\ud

The interaction between discrete components of Internet of Things (IoT) and Intelligent Transportation Systems (ITS) is vital for a collaborative system. The secure and reliable use of Cruise Control (CC) with Cloud and Edge Cloud to achieve complete autonomy for a vehicle is a key component and a major challenge for ITS. This research unravels the complications that arise when Adaptive Cruise Control (ACC) is incorporated into a collaborative environment. It mainly answers the question of where to securely compute Collaborative Cruise Control's (CCC) data in a connected environment. To address this, the paper initially reviews previous research in the domain of Vehicular Cloud, ITS architecture, related threat modelling approaches, and secure implementations of ACC. An overview application model for CCC is developed for performing a threat analysis with the purpose of investigating the reasons why a vehicle suffers collision. Through the use of interviews, the research analyses and suggests the location of computational data by creating a taxonomy between the Edge Cloud, Cloud and the On-board Unit (OBU) while validating the model.

The performance of Johnson and Thermal noises in the Line-Of-Sight (LOS) optical wireless channels has been monitored in a previously implemented application-specific genetic algorithm. The latter achieves sensible selection requirements of link parameters in different weather conditions and link characteristics, and the changes in thermal and Johnson noises are recorded correspondingly. The work is established based on OOK modulation, and a Johnson-noise limited channel is considered during darkness, where the ambient light effect is minimal, and a shot-noise limited channel during daylight. The paper shows that, in order to achieve an acceptable BER at the receiver photodiode, it is possible to maximize the channel link control margin by using an Application- Specific Genetic Algorithm (ASGA). The analysis shows that the transmitted power is not the only penalty, and minimum noise at the receiver photodiode does not always mean a better performance.

In previous work the PPA was shown to behave more optimally with a load resistance which was much lower than normally used in the common optical wireless receiver-amplifiers, such as the High Impedance- or Transimpedance type. This paper discusses the use of a zero bias mode combined with low load impedance, which results in further enhancements in receiver performance. An optimised load is usually a pure resistance, typically several ohms, giving around 8.6 dB improvement in gain over a 50 Ω standard load impedance, but output impedance matching to 50 Ω can permit a similar optimum gain over a wider range of frequencies.

In automotive applications, the ability of optical wireless receiver amplifiers to detect fleeting signals at low energy is crucial. A new Photoparametric Amplifier (PPA) mode of operation is discussed in which the applied bias to the photodetector is minimised to maximise sensitivity for such applications. This is shown to be advantageous in terms of the desirable characteristics for PPA operation, leading to improved conversion efficiency and the potential for low noise operation. Furthermore, in experimental configuration, a nondegenerate mode is discussed which leads to optimum high gain at idler frequency. The original optical modulated signal at baseband frequency can be recovered again at high gain.

The Photoparametric Amplifier, or PPA, is a useful concept in the possible approaches to low noise optical detection, combining optoelectronic conversion with gain in a potentially very low noise manner. The process is conventionally associated with frequency changing as well, and operates in the frequency upconversion mode, leading to a gain which is dependent on the ratio of pump frequency to signal modulation frequency. In the work reported here, we demonstrate a dual approach in which there is a second stage mixer, which restores the original signal spectrum to baseband at the output, with an overall conversion gain of around 10 dB using passive mixing, and typically 21 dB if an active mixer is used.