The merging of main road and on-ramp traffic is known to lead to congestion under heavy traffic conditions. This is mainly due to the underutilization of the road infrastructure and the lack of efficiency in the way the in which the merging manoeuvre is performed by human drivers. We propose a merging algorithm based on our previous work on slot-based driving which employs cooperation between vehicles within the main motorway as well as between motorway and onramp vehicles to achieve a highly efficient merging. The results of the evaluation show that our algorithm achieves a very high throughput and low delay on the on-ramp and clearly outperforms the merging performed by VISSIM's human driver model.

Abstract-Autonomous vehicles seem to be a promising approach to both reducing traffic congestion and improving road safety. However, for such vehicles to coexist safely, they will need to coordinate their behaviour to ensure that they do not collide with each other. This coordination will typically be based on (wireless) communication between vehicles and will need to satisfy stringent real-time constraints. However, realtime message delivery cannot be guaranteed in dynamic wireless networks which means that existing coordination models that rely on continuous connectivity cannot be employed.In this paper, we present a novel coordination model for autonomous vehicles that does not require continuous real-time connectivity between participants in order to ensure that system safety constraints are not violated. This coordination model builds on a real-time communication model for wireless networks that provides feedback to entities about the state of communication.The coordination model uses this feedback to ensure that vehicles always satisfy safety constraints, by adapting their behaviour when communication is degraded. We show that this model can be used to coordinate vehicles crossing an unsignalised junction.

Abstract. Recently, a wide range of dating applications has emerged for users of smart mobile devices. Besides allowing people to socialize with others who share the same interests, these applications use the location services of these devices to provide localized mapping of users. A user is given an approximation of his proximity to other users, making the application more attractive by increasing the chances of local interactions. While many applications provide an obfuscated location of the user, several others prefer to provide quantifiable results.This paper illustrates that the user's location can be disclosed, with various degree of approximation, despite the obfuscation attempts. Experimenting with four of these applications, namely MoMo, WeChat, SKOUT and Plenty of Fish, we show that an attacker can easily bypass the fuzziness of the results provided, resulting in the full disclosure of a victim's location, whenever it is connected.

The presence of (partially) automated vehicles on the roads presents an opportunity to compensate the unstable behaviour of conventional vehicles. Vehicles subject to perturbations should (i) recover their equilibrium speed, (ii) react not to propagate but absorb perturbations. In this work, we start with considering vehicle systems consisting of heterogeneous vehicles updating their dynamics according to realistic behavioural car-following models. Definitions of all types of stability that are of interest in the vehicle system, namely input-output stability, scalability, weak and strict string stability, are introduced based on recent studies. Then, frequency domain linear stability analyses are conducted after linearisation of the modelled system of vehicles, leading to conditions for input-output stability, strict and weak string stability over the behavioural parameters of the system, for finite and infinite systems of homogeneous and heterogeneous vehicles. This provides a solid basis that was missing for car-following model-based control design in mixed traffic systems where only a proportion of vehicles can be controlled. After visualisation of the theoretical results in simulation, we formulate an optimisation strategy with LMI constraints to tune the behavioural parameters of the automated vehicles in order to maximise the L ∞ string stability of the mixed traffic flow while considering the comfort of automated driving. The optimisation strategy systematically leads to increased traffic flow stability. We show that very few automated vehicles are required to prevent the

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Abstract-To address the goal of providing drivers on highways with guaranteed arrival times, we propose a traffic management system that combines virtual slots with semiautonomous driving to shape traffic and prevent congestion. Two algorithms that address aligning vehicles into slots and efficient merging from three to two lanes are proposed. Furthermore, an implementation and evaluation of these algorithms using the VISSIM traffic simulator is presented. Our initial results indicate that a slot-based system has the potential to be used to guarantee arrival times and provide a significant overall increase in efficiency when compared against a human driving model.

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