Dynamic optimal travel strategies in intelligent stochastic transit networks

This paper addresses the search for a run-based dynamic optimal travel strategy, to be supplied through mobile devices (apps) to travelers on a stochastic multiservice transit network, which includes a system forecasting of bus travel times and bus arrival times at stops. The run-based optimal strategy is obtained as a heuristic solution to a Markovian decision problem. The hallmarks of this paper are the proposals to use only traveler state spaces and estimates of dispersion of forecast bus arrival times at stops in order to determine transition probabilities. The first part of the paper analyses some existing line-based and run-based optimal strategy search methods. In the second part, some aspects of dynamic transition probability computation in intelligent transit systems are presented, and a new method for dynamic run-based optimal strategy search is proposed and applied

Integrated and joint optimisation of runway-taxiway-apron operations on airport surface

Airports are the main bottlenecks in the Air Traffic Management (ATM) system. The predicted 84% increase in global air traffic in the next two decades has rendered the improvement of airport operational efficiency a key issue in ATM. Although the operations on runways, taxiways, and aprons are highly interconnected and interdependent, the current practice is not integrated and piecemeal, and overly relies on the experience of air traffic controllers and stand allocators to manage operations, which has resulted in sub-optimal performance of the airport surface in terms of operational efficiency, capacity, and safety. This thesis proposes a mixed qualitative-quantitative methodology for integrated and joint optimisation of runways, taxiways, and aprons, aiming to improve the efficiency of airport surface operations by integrating the operations of all three resources and optimising their coordination. This is achieved through a two-stage optimisation procedure: (1) the Integrated Apron and Runway Assignment (IARA) model, which optimises the apron and runway allocations for individual aircraft on a pre-tactical level, and (2) the Integrated Dynamic Routing and Off-block (IDRO) model, which generates taxiing routes and off-block timing decisions for aircraft on an operational (real-time) level. This two-stage procedure considers the interdependencies of the operations of different airport resources, detailed network configurations, air traffic flow characteristics, and operational rules and constraints. The proposed framework is implemented and assessed in a case study at Beijing Capital International Airport. Compared to the current operations, the proposed apron-runway assignment reduces total taxiing distance, average taxiing time, taxiing conflicts, runway queuing time and fuel consumption respectively by 15.5%, 15.28%, 45.1%, [58.7%, 35.3%, 16%] (RWY01, RWY36R, RWY36L) and 6.6%; gated assignment is increased by 11.8%. The operational feasibility of this proposed framework is further validated qualitatively by subject matter experts (SMEs). The potential impact of the integrated apron-runway-taxiway operation is explored with a discussion of its real-world implementation issues and recommendations for industrial and academic practice.Open Acces

DATASET2050 D5.1 - Mobility assessment

This document provides documentation on the mobility assessment metrics and methods for use within DATASET2050. On the one hand it describes what the key performance areas, attributes, indicators and metrics such as seamlessness, cost, duration, punctuality, comfort, resilience, etc. incorporated into the model are. On the other, it gives details about mobility metric computation, modelling methodology, visualisations used etc

Bus journey simulation to develop public transport predictive algorithms

Encouraging the use of public transport is essential to combat congestion and pollution in an urban environment. To achieve this, the reliability of arrival time prediction should be improved as this is one area of improvement frequently requested by passengers. The development of accurate predictive algorithms requires good quality data, which is often not available. Here we demonstrate a method to synthesise data using a reference curve approach derived from very limited real world data without reliable ground truth. This approach allows the controlled introduction of artefacts and noise to simulate their impact on prediction accuracy. To illustrate these impacts, a recurrent neural network next-step prediction is used to compare different scenarios in two different UK cities. The results show that a realistic data synthesis is possible, allowing for controlled testing of predictive algorithms. It also highlights the importance of reliable data transmission to gain such data from real world sources. Our main contribution is the demonstration of a synthetic data generator for public transport data, which can be used to compensate for low data quality. We further show that this data generator can be used to develop and enhance predictive algorithms in the context of urban bus networks if high-quality data is limited, by mixing synthetic and real data

ICAO action plan on emissions reduction: Republic of Bulgaria

ICAO environmental action plans present States' measures to reduce emissions from international aviation. Action plans are a practical means for States to communicate to ICAO information on their activities to address CO2 emissions from international civil aviation. The level of detail of the information contained in an action plan demonstrates the effectiveness of actions and will ultimately enable ICAO to measure global progress towards meeting the goals set by Assembly Resolution A37-19

Strategic review of travel information research

Report to The Department for Transport, London, U

DATASET2050 D4.2 - Future supply profile

The purpose of this document, Deliverable 4.2, is to describe the future supply profile of EU mobility in the context of air transport. This includes, but is not restricted to, the evolution of the different travel services detailed in earlier DATASET2050 tasks and their corresponding trade-offs. This deliverable and associated tasks feed the model quantitatively and qualitatively via WP5, representing a key milestone for the DATASET2050 model

Historical Layers of Refugee Reception in Border Areas of Italy: Crossroads of Transit and Temporalities of (Im)mobility

In border areas, time and space are constantly suspended from the usual rules along a liminal pathway transforming status and identity. In order to understand how different regimes of mobility and reception influence the experience of time and the subjective actions of both asylum seekers arriving via the so-called Balkan route and Ukrainian refugees fleeing from the war, the paper puts forward an analysis of the multiple scales of migration and reception policies as historically situated practices. How and to what extent has the increasing role of the humanitarian regime contrib- uted to improving or worsening the lives of asylum seekers in borderland places where the memory of wars, civil conflicts, and experiences of refoulement is very much alive? Building on a multilocal ethnography of the temporalities of migrants’reception, the paper aims at disentangling the historical layers of hospitality in the northeastern Italian border areas of Trieste and Bolzano and the intersecting forms of (im)mobility at play. By addressing “reception” as an entanglement of spatial andtemporal practices carried out by migrants, institutional, and humanitarian actors, we discuss not only how time reduces the existence of asylum seekers and Ukrainian refugees to an empty and meaningless human condition by exerting control over the subjective experiences, but also how the migrants’ experience of waiting translates into an active state of being with the creative potential to trigger new forms of sociality, solidarity, and senses of belonging