Passenger-Aware Real-Time Planning of Short Turns to Reduce Delays in Public Transport

Delays and disruptions are commonplace in public transportation. An important tool to limit the impact of severely delayed vehicles is the use of short turns, where a planned trip is shortened in order to be able to resume the following trip in the opposite direction as close to the schedule as possible. Short turns have different effects on passengers: some suffer additional delays and have to reschedule their route, while others can benefit from them. Dispatchers therefore need decision support in order to use short turns only if the overall delay of all affected passengers is positively influenced. In this paper, we study the planning of short turns based on passenger flows. We propose a simulation framework which can be used to decide upon single short turns in real time. An experimental study with a scientific model (LinTim) of an entire public transport system for the German city of Stuttgart including busses, trams, and local trains shows that we can solve these problems on average within few milliseconds. Based on features of the current delay scenario and the passenger flow we use machine learning to classify cases where short turns are beneficial. Depending on how many features are used, we reach a correct classification rate of more than 93% (full feature set) and 90% (partial feature set) using random forests. Since precise passenger flows are often not available in urban public transportation, our machine learning approach has the great advantage of working with significantly less detailed passenger information

Proactive TCP mechanism to improve Handover performance in Mobile Satellite and Terrestrial Networks

Emerging standardization of Geo Mobile Radio (GMR-1) for satellite system is having strong resemblance to terrestrial GSM (Global System for Mobile communications) at the upper protocol layers and TCP (Transmission Control Protocol) is one of them. This space segment technology as well as terrestrial technology, is characterized by periodic variations in communication properties and coverage causing the termination of ongoing call as connections of Mobile Nodes (MN) alter stochastically. Although provisions are made to provide efficient communication infrastructure this hybrid space and terrestrial networks must ensure the end-to-end network performance so that MN can move seamlessly among these networks. However from connectivity point of view current TCP performance has not been engineered for mobility events in multi-radio MN. Traditionally, TCP has applied a set of congestion control algorithms (slow-start, congestion avoidance, fast retransmit, fast recovery) to probe the currently available bandwidth on the connection path. These algorithms need several round-trip times to find the correct transmission rate (i.e. congestion window), and adapt to sudden changes connectivity due to handover. While there are protocols to maintain the connection continuity on mobility events, such as Mobile IP (MIP) and Host Identity Protocol (HIP), TCP performance engineering has had less attention. TCP is implemented as a separate component in an operating system, and is therefore often unaware of the mobility events or the nature of multi-radios' communication. This paper aims to improve TCP communication performance in Mobile satellite and terrestrial networks.Comment: 5 pages, 2 figure

Multimodal collaborative passenger-centric decision making to mitigate the impact of airside perturbations

Transportation networks constitute a critical infrastructure enabling the transfers of passengers and goods, with a significant impact on the economy at different scales. Transportation modes, whether air, road or rail, are coupled and interdependent. The frequent occurrence of perturbations on one or several modes disrupts passengers' entire journeys, directly and through ripple effects. Collaborative Decision Making has shown significant benefits at the airport level, both in the US and in Europe. This dissertation examines how it could be extended to the multimodal network level, discusses the supporting qualitative and quantitative evidence, and provides recommendations for implementation. A case study on the crisis management following the Asiana Crash at San Francisco International Airport in July 2013 is presented. The resulting propagation of disturbances on the transportation infrastructure in the United States is examined. The perturbation takes different forms and varies in scale and time frames : cancellations and delays snowball in the airspace, highway traffic near the airport is impacted by congestion in previously never congested locations, and transit passenger demand exhibit unusual traffic peaks in between airports in the Bay Area. The crash led to a large number of domestic and international flight diversions to many airports, such as Oakland, San Jose, Los Angeles, but also Denver, Salt Lake City and Seattle for instance. Thousands of passengers found themselves struggling to reach their original destination. Passenger reaccommodation varied greatly from airline to airline and airport to airport.First a passenger-centric reaccommodation scheme is developed to balance costs and delays, for each diversion airport. Second, assuming better information sharing and collaborative decision making, we show that there was enough capacity at the neighboring airports, Oakland and San Jose, to accommodate most of the diverted flights and reoptimize the allocation of flight diversions to the Bay Area airports. The present research paves the way further data-driven research on interdependent infrastructure networks for increased resilience. The end goal is to form the basis for optimization models behind providing more reliable passenger door-to-door journeys and improved transportation performance.Ph.D

Identification and Analysis of National Airspace System Resource Constraints

This analysis is the deliverable for the Airspace Systems Program, Systems Analysis Integration and Evaluation Project Milestone for the Systems and Portfolio Analysis (SPA) focus area SPA.4.06 Identification and Analysis of National Airspace System (NAS) Resource Constraints and Mitigation Strategies. "Identify choke points in the current and future NAS. Choke points refer to any areas in the en route, terminal, oceanic, airport, and surface operations that constrain actual demand in current and projected future operations. Use the Common Scenarios based on Transportation Systems Analysis Model (TSAM) projections of future demand developed under SPA.4.04 Tools, Methods and Scenarios Development. Analyze causes, including operational and physical constraints." The NASA analysis is complementary to a NASA Research Announcement (NRA) "Development of Tools and Analysis to Evaluate Choke Points in the National Airspace System" Contract # NNA3AB95C awarded to Logistics Management Institute, Sept 2013

Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

Abstract The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown