The main motivation of this work is to assess the validity of a LWR traffic flow model to model measurements obtained from trajectory data, and propose extensions of this model to improve it. A formulation for a discrete dynamical system is proposed aiming at reproducing the evolution in time of the density of vehicles along a road, as observed in the measurements. This system is formulated as a chemical reaction network where road cells are interpreted as compartments, the transfer of vehicles from one cell to the other is seen as a chemical reaction between adjacent compartment and the density of vehicles is seen as a concentration of reactant. Several degrees of flexibility on the parameters of this system, which basically consist of the reaction rates between the compartments, can be considered: a constant value or a function depending on time and/or space. Density measurements coming from trajectory data are then interpreted as observations of the states of this system at consecutive times. Optimal reaction rates for the system are then obtained by minimizing the discrepancy between the output of the system and the state measurements. This approach was tested both on simulated and real data, proved successful in recreating the complexity of traffic flows despite the assumptions on the flux-density relation.

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In service robotics, safe human-robot interaction (HRI) is still an open research topic, requiring developments both in hardware and in software as well as their integration. In UMAY1 and MEDICARE-C2projects, we addressed both mechanism design and perception aspects of a framework for safe HRI. Our first focus was to design variable stiffness joints for the robotic neck and arm to enable inherent compliance to protect a human collaborator. We demonstrate the advantages of variable stiffness actuators (VSA) in compliancy, safety, and energy efficiency with applications in exoskeleton and rehabilitation robotics. The variable-stiffness robotic neck mechanism was later scaled down and adopted in the robotic endoscope featuring hyper-redundancy. The hyper-redundant structures are more controllable, having efficient actuation and better feedback. Lastly, a smart robotic skin is introduced to explain the safety support via enhancement of tactile perception. Although it is developed for a hyper-redundant endoscopic robotic platform, the artificial skin can also be integrated in service robotics to provide multimodal tactile feedback. This chapter gives an overview of systems and their integration to attain a safer HRI. We follow a holistic approach for inherent compliancy via mechanism design (i.e., variable stiffness), precise control (i.e., hyper-redundancy), and multimodal tactile perception (i.e., smart robotic-skins).