Mauro Benza

A Distributed Information System Prototype to Detect and Monitor the Hazardous Material Transport on the Road in the Territory of Nice-Imperia-Ventimiglia

This paper presents a Decision Support System (DSS) for the detection and monitoring of Hazardous Material (hazmat) transportation on the road infrastructure Nice-Imperia-Savona between France and Italy that was developed in the TMD-NIS Interreg IIIA Alcotra Project. The final objective of the TMD-NIS project was to determine the most effective information and communication technologies and common operation strategies applicable in hazmat management in order to minimize the hazmat transport risk and to improve the road infrastructure safety conditions. An integrated and comparative assessment of the two alternative technologies was performed by the partners of the project: an image processing system to identify the ONU codes on the hazmat plates installed on each truck has been tested in France, while an on-board computer system to store and transmit information related to the hazmat physical conditions, vehicle’s locations and performance measures has been implemented in Italy. The collaboration between the different research institutions and the complementarities of the two specific approaches to define and monitor the hazmat vehicle flows allow comparison and validation of the acquired data related to the type, the amount and the itineraries of the hazmat vehicles which cover the trans-border road infrastructures daily. At present, the TMD-NIS project also provides a GIS utility that is available on the web to track in real-time hazmat vehicles that analyze data about hazmat flow and also to visualize the risk index for the highway from the toolbar barriers of St. Isidore (Nice) to the Ventimille.

Enhancing safety of transport by road by on-line monitoring of driver emotions

Driving while fatigued is dangerous and may result in car accidents. Moreover, adding technology to assist driving can distract the driver. In this work, we present a noninvasive and non-distracting method for monitoring driver emotions and fatigue. To the best of our knowledge, no scientifically agreed definition of emotions exists, as a physical state to be monitored. Emotion recognition is defined as measuring observations of motor system behavior that correspond with high probability to an underlying emotion or combination of emotions. This definition is based on the fact that measuring cognitive influences is currently impossible. In this work we have investigated driving sessions for identifying possible risks at drive in a certain itinerary, analyzing HRV trend. In general, HRV signals can be used as indicators of the responses of the autonomic nervous system (ANS) because the ANS is influenced by the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). The first one (SNS) response to an alarm situation: struggle, stress, drowsiness (and other factors) while PNS, when is activated, produces a slowing down of heart rate and breathing therefore PNS is the normal response to a situation of calmness and absence of danger and stress. For the test, we have collected ECG signals (Electrocardiography) and driver position in 15 trips on 2 daily sessions, by 2 different drivers on the same path. Results show an interesting geospatial relationship of emotions on the travelled path.

Mixed vendor/retailer management of zero-cost multill-inventory systems

In this paper, an original mixed VMI (Vendor Management Inventory)/RMI (Retail Management Inventory) IRP (Inventory Routing Problem) characterized by zero inventory costs is considered, focusing on a quite typical scenario of multiproduct delivery to a network of retailers distributed over the territory. In this scenario, some retailers have the possibility to place orders on their own (pull retailers), while the orders of the other retailers (push retailers) are generated in automatic, through the original methodology here proposed. The objective is to avoid stock-outs, minimize transportation costs, and equalize the use of transportation resources over the considered planning horizon. The proposed MVRMIRP is formulated as a mixed-integer mathematical programming problem. Then, an original two-step algorithm is proposed, for solving the considered problem.

Technical and Functional Standards to Provide a High Quality Service for Dangerous Good Transport on Road

In the last years, the European Commission has increased its effort to improve safety on road infrastructures by adopting new directives to guarantee users a high, uniform and continuous level of service. In this paper, the authors describe the current normative state of the art on Dangerous Good Transport (DGT) by road and introduce innovative initiatives at European level to prevent risk in this context. Then, the authors introduce the architecture of the DGT Information System developed in Italy exploring technological and methodological approaches applied to monitor and detect in real time DG vehicles. The DGT information system can be applied to implement additional decision support systems to manage the fleet routing, the customer orders, and other support tools for drivers including training, resource management and advanced data mining.