Bike sharing systems have been recently adopted by a growing number of cities as a new means of transportation offering citizens a flexible, fast and green alternative for mobility. Users can pick up or drop off the bicycles at a station of their choice without prior notice or time planning. This increased flexibility comes with the challenge of unpredictable and fluctuating demand as well as irregular flow patterns of the bikes. As a result, these systems can incur imbalance problems such as the unavailability of bikes or parking docks at stations. In this light, operators deploy fleets of vehicles which re-distribute the bikes in order to guarantee a desirable service level. Can we engage the users themselves to solve the imbalance problem in bike sharing systems? In this paper, we address this question and present a crowdsourcing mechanism that incentivizes the users in the bike repositioning process by providing them with alternate choices to pick or return bikes in exchange for monetary incentives. We design the complete architecture of the incentives system which employs optimal pricing policies using the approach of regret minimization in online learning. We investigate the incentive compatibility of our mechanism and extensively evaluate it through simulations based on data collected via a survey study. Finally, we deployed the proposed system through a smartphone app among users of a large scale bike sharing system operated by a public transport company, and we provide results from this experimental deployment. To our knowledge, this is the first dynamic incentives system for bikes re-distribution ever deployed in a real-world bike sharing system.

ABSTRACT:Pavement roughness evaluation of airport runways/taxiways and scheduling of maintenance operations should be done according to well-defined procedures. Survey of geometric features of airport pavements is performed to verify the flow of water from the surface and to assure a level of roughness that allows the airplane to maneuver in the safest and most comfortable conditions. In particular the evaluation of longitudinal and transversal evenness of the runway and taxiway is carried out through topographic survey. The tachymetric survey has been carried out according to traditional topographic technique, which allows the evaluation of geometric position of isolated points with very high accuracy, but it is not very productive. Moreover it returns the pavement surface model through only few measured points. An alternative survey method, characterized by a good accuracy, high speed of acquisition and very high surveyed point density, is Terrestrial Laser Scanning (TLS), in static mode. In this paper we describe our experience aimed to validate the use of time-of-flight (TOF) TLS, based on a survey on a 200 m length segment of an international airport taxiway. From the acquired data we extracted the parameters of interest, especially the slope, and compared them with the values obtained from the traditional topographic survey. We also developed a proprietary software package to evaluate the slope and to analyze the statistical data. The software allows users to manage the flow of a semi-automatic calculation.

The conditions of airport movement-area pavements play a primary role on safety and regularity of airport operations; for this reason, the aerodrome operator needs to periodically survey their condition and provide their maintenance and rehabilitation in order to ensure the required operational characteristics. To meet these needs efficiently and effectively, the Airport Pavement-Management System (APMS) has proved to be a strategic tool to support decisions, aimed at defining a technically and economically sustainable management plan. This paper aims to investigate the theoretical elements and structure of the APMS; the appropriate methodologies to guarantee a constant updating of the system in all its aspects are presented, focusing on the specific case study of a medium-dimension Italian airport. The article describes the methods and the equipment used for the high-performance surveys and the condition indexes used for collecting and analyzing the data implemented to populate the APMS of Cagliari airport. Two major survey campaigns were carried out: the first in 2016 and the second in 2019. Both surveys were carried out using the same subdivision into sample units, following the ASTM D5340-12 criteria, to correctly compare data collected in different years. In order to sufficiently populate the APMS database, the measured and back-calculated data were stored and integrated using daily acquired pavement reports since 2009 and stored with the specific intention to develop customized decay curves for Cagliari Airport pavements. Preliminary results on the sustainable use of the APMS were reported even with data collected in a limited period and successfully applied to runway flexible pavement.