Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Quirks and Challenges in the Design and Verification of Efficient, High-Load Real-Time Software Systems

International audienceExisting concepts for ensuring the correctness of the timing behavior of real-time systems are often based on schedulability analysis methods using exact proofs. Due to the complexity of the scheduling problem, today typically worst case approximations are used to judge the reliability of the timing behavior in software systems. In industrial practice, however, this leads to large safety margins in the design of products which are commercially unacceptable in many application domains. For such highly-efficient systems, schedulability analysis methods that are too pessimistic are of limited benefit. As a consequence, penetration of real-time analysis is suboptimal in the industrial software development, which possibly leads to insufficient quality of the developed products. Therefore, new approaches are needed to support the design and validation of high-load real-time systems with an average CPU load of 90% or above to improve the situation

Why we measure period fertility

Four reasons for measuring period fertility are distinguished: to explain fertility time trends, to anticipate future fertility, to construct theoretical models and to communicate with non-specialist audiences. The paper argues that not all measures are suitable for each purpose, and that tempo adjustment may be appropriate for some objectives but not others. In particular, it is argued that genuine timing effects do not bias or distort measures of period fertility as dependent variable. Several different concepts of bias or distortion are identified in relation to period fertility measures. Synthetic cohort indicators are a source of confusion since they conflate measurement and forecasting. Anticipating future fertility is more akin to forecasting than to measurement. Greater clarity about concepts and measures in the fertility arena could be achieved by a stronger emphasis on validation. Period incidence and occurrence-exposure rates have a straightforward interpretation. More complex period fertility measures are meaningful only if a direct or indirect criterion can be specified against which to evaluate them. Their performance against that criterion is what establishes them as valid or useful

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings