Developing an Adaptive Strategy for Connected Eco-Driving Under Uncertain Traffic and Signal Conditions

The Eco-Approach and Departure (EAD) application has been proved to be environmentally efficient for a Connected and Automated Vehicles (CAVs) system. In the real-world traffic, traffic conditions and signal timings are usually dynamic and uncertain due to mixed vehicle types, various driving behaviors and limited sensing range, which is challenging in EAD development. This research proposes an adaptive strategy for connected eco-driving towards a signalized intersection under real world conditions. Stochastic graph models are built to link the vehicle and external (e.g., traffic, signal) data and dynamic programing is applied to identify the optimal speed for each vehicle-state efficiently. From energy perspective, adaptive strategy using traffic data could double the effective sensor range in eco-driving. A hybrid reinforcement learning framework is also developed for EAD in mixed traffic condition using both short-term benefit and long-term benefit as the action reward. Micro-simulation is conducted in Unity to validate the method, showing over 20% energy saving.View the NCST Project Webpag

An Individual-based Probabilistic Model for Fish Stock Simulation

We define an individual-based probabilistic model of a sole (Solea solea) behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA), a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Towards a Formal Verification Methodology for Collective Robotic Systems

We introduce a UML-based notation for graphically modeling systems’ security aspects in a simple and intuitive way and a model-driven process that transforms graphical specifications of access control policies in XACML. These XACML policies are then translated in FACPL, a policy language with a formal semantics, and the resulting policies are evaluated by means of a Java-based software tool

Intelligent simulation of coastal ecosystems

Tese de doutoramento. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto, Faculdade de Ciência e Tecnologia. Universidade Fernando Pessoa. 201