TuST: from Raw Data to Vehicular Traffic Simulation in Turin

Traffic simulations are becoming a standard way to study urban mobility patterns, to evaluate new traffic policies and to test modern vehicular technologies. For this reason, in recent years, mobility projects pushed towards an increase in the demand of traffic simulators and towards an extension of their area of investigation, aiming at covering a whole city and its suburbs. In this paper we describe the methodology we followed in the creation of a large-scale traffic simulation of a 400-Km^2 area around the Municipality of Turin. Our preliminary results demonstrate that a complete modeling of such a wide tool is possible at the expense of minor simplifications

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

In this paper, we present an enhanced Collision Avoidance (eCA) service that leverages vehicle connectivity through a cellular network to avoid vehicle collisions and increase road safety at intersections. The eCA service is assumed to be deployed at the edge of the network, thus curbing the latency incurred by the communication process. The core of the eCA service is composed of a Collision Avoidance Algorithm (CAA), and a Collision Avoidance Strategy (CAS). The former predicts the vehicle's future trajectory through the positional information advertised by periodic beacons and detects if two vehicles are on a collision course. The latter decides which of the vehicles potentially involved in a collision should yield. The vehicles are then notified of both the impending danger and of the actions needed to avoid it. We have simulated our solution using SUMO (Simulation of Urban MObility) and ns-3 (network simulator 3) with the LENA (LTE-EPC Network simulAtor) framework on a Manhattan-grid road topology, and observed its good performance in terms of avoided collisions percentage as a function of vehicle speed and different vehicles densities.This work was supported by the EU Commission through the H2020 5G-TRANSFORMER project (Grant No. 761536) and the H2020 5GROWTH project (Grant No. 856709), by the CARS Interdepartmental Lab at Politecnico di Torino, by the Spanish MINECO Grant TEC2017- 88373-R (5G-REFINE), and by the Generalitat de Catalunya Grant 2017 SGR 1195

Multicenter, Prospective Trial of Selective Drain Management for Pancreatoduodenectomy Using Risk Stratification

Objective: This multicenter study sought to prospectively evaluate a drain management protocol for pancreatoduodenectomy (PD). Background: Recent evidence suggests value for both selective drain placement and early drain removal for PD. Both strategies have been associated with reduced rates of clinically relevant pancreatic fistula (CR-POPF) - the most common and morbid complication after PD. Methods: The protocol was applied to 260 consecutive PDs performed at two institutions over 17 months. Risk for ISGPF CR-POPF was determined intraoperatively using the Fistula Risk Score (FRS); drains were omitted in negligible/low risk patients and drain fluid amylase (DFA) was measured on postoperative day 1 (POD 1) for moderate/high risk patients. Drains were removed early (POD 3) in patients with POD 1 DFA 645,000 U/L, whereas patients with POD 1 DFA >5,000 U/L were managed by clinical discretion. Outcomes were compared with a historical cohort (N = 557; 2011-2014). Results: Fistula risk did not differ between cohorts (median FRS: 4 vs 4; P = 0.933). No CR-POPFs developed in the 70 (26.9%) negligible/low risk patients. Overall CR-POPF rates were significantly lower after protocol implementation (11.2 vs 20.6%, P = 0.001). The protocol cohort also demonstrated lower rates of severe complication, any complication, reoperation, and percutaneous drainage (all P < 0.05). These patients also experienced reduced hospital stay (median: 8 days vs 9 days, P = 0.001). There were no differences between cohorts in the frequency of bile or chyle leaks. Conclusions: Drains can be safely omitted for one-quarter of PDs. Drain amylase analysis identifies which moderate/high risk patients benefit from early drain removal. This data-driven, risk-stratified approach significantly decreases the occurrence of clinically relevant pancreatic fistula