The use of Artificial Neural Networks for extending road traffic monitoring data spatially: an application to the neighbourhoods of Benevento

Abstract In this paper, the use of Artificial Neural Networks (ANNs) for spatially extending road traffic monitoring data is studied. The problem consists of estimating the traffic flows on some links of an urban road network knowing the corresponding data on some other links of the network (monitored links). In a previous paper, the authors studied this problem referring to a whole city obtaining promising results. Starting from these results, here we test if to limit the number of monitored links and non-monitored links to a neighbourhood of a city improves or not the results. These results are useful in medium and large cities where other parts do not at all influence some parts of the network and each neighbourhood can be studied independently from the others. To obtain these results, we have partitioned the network of Benevento in six neighbourhoods and trained six different ANNs with simulated data. Numerical results show that to limit the area analysis improves the results significantly with respect to consider the whole network

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

In recent years, the problem of optimal resources management has increasingly led to transportation policies based on the application of Intelligent Transportation Systems (ITS). In this context, the aim of this work was to develop two models to estimate road network performances for supporting transportation management policies through the use of an Automatic Vehicle Location (AVL) system. The first proposed model provides an analytic formulation that combines road traffic conditions with transit conditions in the case of non-exclusive lanes when bus fleets are provided with an AVL system. In real cases, many transit firms aggregate their AVL data to simplify information management. Thus in this case, it is necessary to develop a different model for estimating traffic conditions on the whole network with the use of aggregate AVL data

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

In recent years, the problem of optimal resources management has increasingly led to transportation policies based on the application of Intelligent Transportation Systems (ITS). In this context, the aim of this work was to develop two models to estimate road network performances for supporting transportation management policies through the use of an Automatic Vehicle Location (AVL) system. The first proposed model provides an analytic formulation that combines road traffic conditions with transit conditions in the case of non-exclusive lanes when bus fleets are provided with an AVL system. In real cases, many transit firms aggregate their AVL data to simplify information management. Thus in this case, it is necessary to develop a different model for estimating traffic conditions on the whole network with the use of aggregate AVL data

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

The aim of this paper is to develop an Information Extension Model (IEM) which uses location data of bus fleets (AVL data) to estimate road traffic conditions and provide input for implementing control strategies. The IEM consists of three sub-models: the Link Traffic Condition Model (LTCM), the AVL Adaptation Model (AVLAM) and the Network Traffic Condition Model (NTCM). The first provides road traffic conditions as a function of mass-transit traffic conditions in the case of shared lanes, the second provides mass-transit traffic conditions as a function of AVL data, and the last provides road traffic conditions over the whole road network as a function of mass-transit traffic conditions. The IEM (and its sub-models) were developed and calibrated in the case of real dimension networks and some tests were performed on a trial network. Numerical results show the effectiveness of the proposed method since it allows a reduction in travel demand estimation errors

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

The aim of this paper is to develop an Information Extension Model (IEM) which uses location data of bus fleets (AVL data) to estimate road traffic conditions and provide input for implementing control strategies. The IEM consists of three sub-models: the Link Traffic Condition Model (LTCM), the AVL Adaptation Model (AVLAM) and the Network Traffic Condition Model (NTCM). The first provides road traffic conditions as a function of mass-transit traffic conditions in the case of shared lanes, the second provides mass-transit traffic conditions as a function of AVL data, and the last provides road traffic conditions over the whole road network as a function of mass-transit traffic conditions. The IEM (and its sub-models) were developed and calibrated in the case of real dimension networks and some tests were performed on a trial network. Numerical results show the effectiveness of the proposed method since it allows a reduction in travel demand estimation errors.Control Management information systems Simulation Transportation Travel demand estimation

Understanding bus travel time variation using AVL data

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 89-94).The benefits of bus automatic vehicle location (AVL) data are well documented (see e.g., Furth et al. (2006)), ranging from passenger-facing applications that predict bus arrival times to service-provider-facing applications that monitor network performance and diagnose performance failures. However, most other researchers' analyses tend to use data that they acquired through negotiations with transit agencies, adding a variable cost of time both to the transit agencies and to researchers. Further, conventional wisdom is that simple vehicle location trajectories are not suitable for evaluating bus performance (Furth et al. 2006). In this research, I use data that are free and open to the public. This access enables researchers and the general public to explore bus position traces. The research objective of this Master's Thesis is to build a computational system that can robustly evaluate bus performance across a wide range of bus systems under the hypothesis that a comparative approach could be fruitful for both retrospective and real-time analysis. This research is possible because a large number of bus providers have made their bus position, or AVL, data openly available. This research thus demonstrates the value of open AVL data, brings understanding to the limits of AVL data, evaluates bus performance using open data, and presents novel techniques for understanding variations in bus travel time. Specifically, this thesis demonstrates research to make the system architecture robust and fruitful: " This thesis explores the exceptions in the various datasets to which the system must be robust. As academics and general public look to exploit these data, this research seeks to elucidate important considerations for and limitations of the data. " Bus data are high-dimensional; this research strives to make them dually digestible and informative when drawing conclusions across a long timescale. Thus, this research both lays the foundation for a broader research program and finds more visually striking and fundamentally valuable statistics for understanding variability in bus travel times.by David G. Gerstle.S.M.in Transportatio

Proposta de modelo para controle transporte público baseado em análise de confiabilidade

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis, 2016.Desde os primeiros estudos na área de transporte público a confiabilidade do sistema é reconhecida como um dos principais fatores que determinam a escolha modal, e se mantém ainda hoje como uma das mais importantes características do sistema. Diversas estratégias de controle operacional foram criadas ao longo dos anos com o intuito de aumentar a confiabilidade e manter um nível de serviço satisfatório, mas raros são os casos de sistemas de transporte público no Brasil que utilizem estas estratégias com foco na operação do sistema. Este trabalho tem como objetivo avaliar o impacto da utilização de uma estratégia de reprogramação de veículos na confiabilidade de um sistema de transporte público através de um estudo de caso. Para tanto, analisa-se a operação de duas linhas de ônibus de um sistema de transporte público no estado de São Paulo, comparado a operação atual com o caso em que se aplica a estratégia de controle. A confiabilidade da operação foi usada como critério de comparação e foi possível demonstrar um incremento expressivo neste indicador com a utilização do controle operacional. Como resultado, este trabalho apresenta os benefícios da estratégia de controle analisada num caso específico e oferece um modelo que pode ser implementado de forma simples em sistemas de transporte de passageiros por ônibus.Abstract : Since the first studies on public transportation the reliability of the system is recognized as one of the main factors determining mode choice, and has maintained itself as one of the most important characteristics of the system up to this day. Various operational control strategies were created through the years with the objective of increasing reliability and maintaining a satisfactory level of service, but few are the cases of public transportation systems in Brazil in which these strategies are directed at the system?s operation. This work has the objective of evaluating the impacts of the utilization of a rescheduling strategy on the reliability of a public transportation system by means of a case study. To accomplish that, the operation of two bus lines of a public transportation system in the state of São Paulo are analyzed, comparing the current operation with the case in which the control strategy is deployed. The reliability of the system is used as the comparison criterion and it was possible to demonstrate a significant increment on that indicator with the use of operational control. As a result, this work presents the benefits of the strategy analyzed in a specific case and offers a model that could be easily implemented in public transportation systems based on buses

Interopérabilité des systèmes de planification réactive de la logistique des interventions d’urgence

RÉSUMÉ Le type d’urgences qu’un réseau de transport en commun peut subir est varié. De même, les conséquences sur la compagnie qui rend le service et sur la clientèle qui en fait usage. Bien que les urgences ne puissent pas se planifier, la minimisation des effets négatifs sur le réseau et sur la clientèle doit toujours être une priorité. Dans ce contexte, les systèmes d’information de la société qui gère le service de transport en commun peuvent jouer un rôle très important. Ces systèmes aident à obtenir une connaissance approfondie du fonctionnement du réseau et ils peuvent aussi participer à la résolution des situations inattendues en temps réel. Cependant, la communication entre les systèmes d’information d’une entreprise, et même avec les systèmes informationnels de compagnies partenaires, ne se produit toujours pas d’une manière fluide et efficiente. Le but de ce mémoire est donc d’évaluer l’interopérabilité des systèmes informationnels d’une société de transport en commun. Cette évaluation se fait en regardant spécialement le rôle de ces systèmes dans un contexte de situations d’urgences. Le Réseau de Transport de Longueuil a d’ailleurs collaboré pour la réalisation de ce mémoire. La méthodologie choisie pour faire cette évaluation est la structure d’interopérabilité d’entreprise ATHENA. Cette structure comporte huit étapes dont nous en avons retenu les deux premières. Les deux étapes choisies couvrent en effet la portée de cette recherche en analysant l’interopérabilité interne et l’interopérabilité externe de la société étudiée. Pour mesurer l’interopérabilité interne du RTL, la structure d’interopérabilité ATHENA propose le modèle de maturité d’interopérabilité d’entreprise – EIMM. Ce modèle évalue l’état de l’interopérabilité en cinq domaines d’inquiétude : la stratégie d’affaires, l’organisation et les compétences, les systèmes et la technologie, l’environnement légal, de sécurité et de confiance et, finalement, la modélisation d’entreprise. De plus, ce modèle propose cinq niveaux de maturité d’interopérabilité possibles (du plus bas au plus haut) : effectué, modelé, intégré, interopérable et optimisé.----------ABSTRACT The type of emergencies that affects a public transit network is broad. It is broad as well the type of consequences for the company and for its clients. Even though these emergencies cannot be planned, the minimization of the negatives effects should always be a priority. In this context, the public transit company’s information systems play an important role. These systems help to gather a deep knowledge about the running of the network and they can also participate in the real time solution of unexpected situations. However, the communication between the company’s different information systems, and even more, the communication with others partners’ information systems, is not always performed in a seamless fashion. Thus, the objective of this dissertation is to evaluate the interoperability of a public transit company’s information system. This evaluation is done by observing the roles of these systems under an emergency context. The Réseau de Transport de Longueuil, RTL, has collaborated in the execution of this research. The methodology that was chosen to do this evaluation is the enterprise interoperability framework ATHENA. This framework includes eight steps of which we have developed the first two. These two steps cover the scope of this research by analyzing both the internal and the external interoperability of the studied company. In order to measure the RTL’s internal interoperability, the ATHENA framework proposes the Enterprise Interoperability Maturity Model, EIMM. This model evaluates the state of the interoperability in five areas of concern: business strategy and processes; organization and competences; systems and technology; legal environment, security and trust; and finally, enterprise modelling. Moreover, this model proposes five possible interoperability maturity levels (from the lowest to the highest): performed, modelled, integrated, interoperable and optimising

Modelling of interactions between rail service and travel demand: a passenger-oriented analysis

The proposed research is situated in the field of design, management and optimisation in railway network operations. Rail transport has in its favour several specific features which make it a key factor in public transport management, above all in high-density contexts. Indeed, such a system is environmentally friendly (reduced pollutant emissions), high-performing (high travel speeds and low values of headways), competitive (low unitary costs per seat-km or carried passenger-km) and presents a high degree of adaptability to intermodality. However, it manifests high vulnerability in the case of breakdowns. This occurs because a faulty convoy cannot be easily overtaken and, sometimes, cannot be easily removed from the line, especially in the case of isolated systems (i.e. systems which are not integrated into an effective network) or when a breakdown occurs on open tracks. Thus, re-establishing ordinary operational conditions may require excessive amounts of time and, as a consequence, an inevitable increase in inconvenience (user generalised cost) for passengers, who might decide to abandon the system or, if already on board, to exclude the railway system from their choice set for the future. It follows that developing appropriate techniques and decision support tools for optimising rail system management, both in ordinary and disruption conditions, would consent a clear influence of the modal split in favour of public transport and, therefore, encourage an important reduction in the externalities caused by the use of private transport, such as air and noise pollution, traffic congestion and accidents, bringing clear benefits to the quality of life for both transport users and non-users (i.e. individuals who are not system users). Managing to model such a complex context, based on numerous interactions among the various components (i.e. infrastructure, signalling system, rolling stock and timetables) is no mean feat. Moreover, in many cases, a fundamental element, which is the inclusion of the modelling of travel demand features in the simulation of railway operations, is neglected. Railway transport, just as any other transport system, is not finalised to itself, but its task is to move people or goods around, and, therefore, a realistic and accurate cost-benefit analysis cannot ignore involved flows features. In particular, considering travel demand into the analysis framework presents a two-sided effect. Primarily, it leads to introduce elements such as convoy capacity constraints and the assessment of dwell times as flow-dependent factors which make the simulation as close as possible to the reality. Specifically, the former allows to take into account the eventuality that not all passengers can board the first arriving train, but only a part of them, due to overcrowded conditions, with a consequent increase in waiting times. Due consideration of this factor is fundamental because, if it were to be repeated, it would make a further contribution to passengers’ discontent. While, as regards the estimate of dwell times on the basis of flows, it becomes fundamental in the planning phase. In fact, estimating dwell times as fixed values, ideally equal for all runs and all stations, can induce differences between actual and planned operations, with a subsequent deterioration in system performance. Thus, neglecting these aspects, above all in crowded contexts, would render the simulation distorted, both in terms of costs and benefits. The second aspect, on the other hand, concerns the correct assessment of effects of the strategies put in place, both in planning phases (strategic decisions such as the realisation of a new infrastructure, the improvement of the current signalling system or the purchasing of new rolling stock) and in operational phases (operational decisions such as the definition of intervention strategies for addressing disruption conditions). In fact, in the management of failures, to date, there are operational procedures which are based on hypothetical times for re-establishing ordinary conditions, estimated by the train driver or by the staff of the operation centre, who, generally, tend to minimise the impact exclusively from the company’s point of view (minimisation of operational costs), rather than from the standpoint of passengers. Additionally, in the definition of intervention strategies, passenger flow and its variation in time (different temporal intervals) and space (different points in the railway network) are rarely considered. It appears obvious, therefore, how the proposed re-examination of the dispatching and rescheduling tasks in a passenger-orientated perspective, should be accompanied by the development of estimation and forecasting techniques for travel demand, aimed at correctly taking into account the peculiarities of the railway system; as well as by the generation of ad-hoc tools designed to simulate the behaviour of passengers in the various phases of the trip (turnstile access, transfer from the turnstiles to the platform, waiting on platform, boarding and alighting process, etc.). The latest workstream in this present study concerns the analysis of the energy problems associated to rail transport. This is closely linked to what has so far been described. Indeed, in order to implement proper energy saving policies, it is, above all, necessary to obtain a reliable estimate of the involved operational times (recovery times, inversion times, buffer times, etc.). Moreover, as the adoption of eco-driving strategies generates an increase in passenger travel times, with everything that this involves, it is important to investigate the trade-off between energy efficiency and increase in user generalised costs. Within this framework, the present study aims at providing a DSS (Decision Support System) for all phases of planning and management of rail transport systems, from that of timetabling to dispatching and rescheduling, also considering space-time travel demand variability as well as the definition of suitable energy-saving policies, by adopting a passenger-orientated perspective