Posts tagged modelling
Driver schedule efficiency vs. public transport robustness: A framework to quantify this trade-off based on passive data
More complex, efficient driver schedules reduce operator costs during undisrupted operations, but increase the disruption impact for passengers and operator once a disruption occurs. We develop an integrated framework to quantify the passenger and operator costs of disruptions explicitly as function of different driver schedule schemes. Since the trade-off between driver schedule efficiency and robustness can be quantified, this supports operators in their decision-making.
Read the CASPT paper by Menno Yap HERE and find the presentation HERE
Assessing disruption management strategies in rail-bound urban public transport from a passenger perspective
This paper provides a framework for generating and assessing alternatives
in case of disruptions in rail-bound urban public transport systems,. The proposed
framework considers the passenger perspective as well as the operator perspective,
for the often-used measures of detouring and short-turning. An application of the
framework demonstrates that currently used disruption management protocols often
do not lead to the optimal solution from the passenger perspective. Furthermore, the
optimal choice between alternatives from passenger perspective shows to be
dependent on the passenger flows.
Passenger Route Choice and Assignment Model for Combined Fixed and Flexible Public Transport Systems
The recent technological innovations have given rise to innovative mobility solutions. Public transport systems combining such services need novel models for the design of services. We develop a multimodal route choice and assignment model for combined use of line/schedule based public transport systems (fixed public transport) and demand responsive services (flexible public transport). The model takes into account the dynamic demand-supply interaction using an iterative learning model framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to the test network of Sioux Falls. Results, in terms of modal split, fleet utilization, and passenger waiting times are analysed for scenarios in which fixed and flexible public transport are offered as competing modes as well as potential complementing modes.
Find the CASPT presentation HERE
Assessing and improving operational strategies for the benefit of passengers in rail-bound urban transport systems
Unplanned disruptions in transit can have consequent impacts on passengers. The more inconvenienced passengers are, the more likely operators will be negatively impacted. Yet so far, operators and researchers have addressed the rescheduling problem during disruptions mainly with a supply-side focus – timetable, crews and vehicles – and not with a passenger perspective. Urban rail transit particularly lacks insights in terms of passenger- focused rescheduling. Being able to assess the inconvenience experienced by passengers during disruptions compared with what they normally experience, and being able to compare how different rescheduling strategies affect them are therefore two major challenges.
The framework developed in this study precisely aims at tackling 8 these challenges. A case study of the metro of Rotterdam is used to test the framework developed in this paper. Alternative strategies are developed focusing on the incident phase (from the beginning of the incident until its cause is resolved). The application of the framework reveals that a regularity-focused rescheduling strategy would be beneficial for high-frequency service users. Realistically, yearly savings could amount to around €900,000 in terms of societal passenger costs for the operator in the Rotterdam area alone. However, the omnipresence of the punctuality paradigm, through which most operators plan and analyze operations, makes the implementation of passenger-focused strategies a challenging task for traffic controllers. The results of the study are valuable for transit operators worldwide and the framework can provide insights to decision-makers on the performance of different strategies, bringing to light trade-offs between supply and passenger sides during disruptions.
Read more of this research by Anne Durand: Paper TRB and Poster TRB
Performance assessment of fixed and flexible public transport in a multi agent simulation framework
The emergence of innovative mobility solutions that offer flexible transport services, is changing the way urban public transport systems will be designed. Such mobility solutions offer on demand transport services and hence can solve the problems inherent with traditional line based and schedule based public transport systems. It is essential to understand the dynamics of this new demand-supply market with co-existing and competing fixed and flexible public transport. However, the performance of the system comprising of users and transit services and the factors influencing them, have received limited attention in literature. In this paper a model is developed to analyse the system performance when the modes of fixed public transport and flexible public transport operate in competition. The model is implemented in the multi-agent simulation framework MATSim with dynamic assignment in which the users optimize their travel plan through iterative learning from the service experienced and altering their travel plan. The scenarios in which the flexible public transport offer private and shared services are considered. The system performance is analysed for varying fleet size of flexible public transport and ratio of cost of flexible to fixed public transport.
Find the paper HERE
Modelling Multimodal Transit Networks: Integration of bus networks with walking and cycling
Demand for (public) transportation is subject to dynamics affected by technological, spatial, societal and demographic aspects. The political environment, together with financial and spatial constraints limit the possibilities to address transit issues arising from growing demand through the construction of new infrastructure. Upgrading of existing services and improving integration over the entire trip chain (including cycling) are two options that can address these transport issues. However, transport planners and transport service operators often fail to include the entire trip when improving services, as improvement is normally achieved through the adaptations of characteristics (e.g. speeds, stop distances) of the services.
Our developed framework consists of two parts: one to assess the characteristics of the different bus services and their access and egress modes, and one to assess the effects of integration of these services, which includes the modelling and analysis in a regional transit model. The framework has successfully been applied to a case study showing that bus systems with higher frequencies and speeds can attract twice the amount of cyclists on the access and egress sides. It also shows that passengers accept longer access and egress distances with more positive characteristics of the bus service (higher speeds, higher frequencies).
Find the presentation of Judith Brand at MT-ITS in Napoli HERE
Find our paper HERE
Optimization of a passenger railway transportation plan considering mobility flows and service quality
This research focuses on designing transportation plan for SNCF Transilien (French railway
operator for the Parisian suburban mass transit). The objective is to develop methods
and decision support tools to propose a timetable adapted to the passenger demand in the
Parisian mass transit system, including comfort and reliability criterias.
This paper aims to present the first step of this research. We propose a graph theoretic
ILP formulation for the Line Planning Problem, minimizing both travelers travel time and
operating cost. We furthermore develop a multi-objective method to solve this problem.
This method offers a pool of solutions in order to let the final designer choose the solution.
We report computational results on real world instances provided from SNCF Transilien.
Check the RAIL Lille paper of Lucile Brethome et al. HERE
Inzichten in dynamische effecten van openbaar vervoer door combinatie van statische en dynamische OV modellen
Steden worden steeds populairder om te wonen, werken en te recreëren. Deze trek naar de stad legt steeds meer druk op de hoogwaardige OV-assen in en van/naar de stad. Naast snelheid en frequentie zijn betrouwbaarheid en drukte belangrijke kwaliteitsaspecten voor zowel reiziger als vervoerder. Om deze OV-assen hoogwaardig en efficiënt te kunnen (blijven) exploiteren zijn inzichten in te verwachte effecten van nieuwe ontwikkelingen en maatregelen essentieel. Afgelopen decennium zijn er grote stappen gezet op het gebied van OV modellering. Er zijn goede, statische modellen beschikbaar voor OV prognoses. Desondanks is voor beter inzicht in bijvoorbeeld toekomstige betrouwbaarheid en drukte behoefte aan een meer dynamische modelomgeving, zonder het hoge detailniveau van microsimulatie. TU Delft en Goudappel zijn daarom een verkenning gestart naar toepassing van dynamische OV toedelingsmodellen, (agent-based, mesoscopisch). De basis hiervoor, BusMezzo, is ontwikkeld door KTH Stockholm en wordt daarnaast ook al via TU Delft toegepast in Nederlandse studies.
Deze verkenning richt zich op het modelleren van openbaar vervoer met zowel OmniTRANS, de modelleringsoftware voor het gros van de regionale en stedelijke modellen in Nederland, als BusMezzo, een dynamisch simulatiemodel voor OV toedeling. Het doel van dit project is om te verkennen in hoeverre een dynamisch model waarde kan toevoegen ten opzichte van een statisch model, en welke stappen genomen moeten worden om deze modellen met elkaar te laten communiceren. Naast theoretische analyse is een case studie van de metro van Amsterdam uitgevoerd.
BusMezzo is in staat om elk voertuig en elke reiziger individueel te simuleren en kan daarmee de volledige interactie tussen reiziger en voertuig meenemen in de toedeling. De impact van crowding wordt volledig gemodelleerd, door het toepassen van volume-afhankelijke halteertijden, denied boarding, en door reizigers ervaren reistijd als gevolg van discomfort in drukke voertuigen. Hiermee ontstaat een verrijking ten opzichte van statische modellen.
Een wederzijdse uitwisseling van input en output data tussen de beide modellen is mogelijk. Het ligt voor de hand om een tweetrapsraket te maken van beide modellen, waarbij de kracht van beiden wordt gecombineerd. Hiermee kunnen meer en betere inzichten worden verkregen voor verwachte effecten van ontwikkelingen en/of OV maatregelen. Daarmee wordt een grote verbeterslag in prognoses en bijv. kostenbaten-analyses gemaakt.
Bekijk de Platos presentatie HIER
Improving predictions of the impact of disturbances on public transport usage based on smart card data
The availability of smart card data from public transport travelling the last decades allows analyzing current and predicting future public transport usage. Public transport models are commonly applied to predict ridership due to structural network changes, using a calibrated parameter set. Predicting the impact of planned disturbances, like temporary track closures, on public transport ridership is however an unexplored area. In the Netherlands, this area becomes increasingly important, given the many track closures operators are confronted with the last and upcoming years. We investigated the passenger impact of four planned disturbances on the public transport network of Den Haag, the Netherlands, by comparing predicted and realized public transport ridership using smart card data. A two-step search procedure is applied to find a parameter set resulting in higher prediction accuracy. We found that in-vehicle time in rail-replacing bus services is perceived ≈1.1 times more negatively compared to in-vehicle time perception in the initial tram line. Besides, passengers do not seem to perceive the theoretical benefit of the usually higher frequency of rail-replacement bus services compared to the frequency of the replaced tram line. At last, no higher waiting time perception for temporary rail-replacement services could be found, compared to regular tram and bus services. The new parameter set leads to substantially higher prediction accuracy compared to the default parameter set. It supports public transport operators to better predict the required supply of rail-replacement services and to predict the impact on their revenues.
Read our TRB paper HERE
Find the poster HERE
Data driven enhancement of public transport planning and operations: service reliability improvements and ridership predictions
Automatic Vehicle Location (AVL) and smartcard data are of great value in planning, design and operations of public transport. We developed a transport demand model, which utilizes smartcard data for overall and what-if analyses, by converting these data into passengers per line and OD-matrixes and allowing network changes on top of a base scenario. This new generation model serves in addition to the existing range of transport demand models and approaches. It proved itself in practice during a case study in The Hague, where it helped the operator gain valuable insights into the effect of small network changes, such as a higher frequency.
Data also supports measures to improve service reliability. We introduced a new network design dilemma, namely the length of a transit line vs. its reliability. Long lines offer many direct connections, thereby saving transfers. However, the variability in operation is often negatively related to the length of a line, leading to poorer schedule adherence and additional waiting time for passengers. A data driven case study shows that in the case of long lines with large variability, enhanced reliability resulting from splitting the line could result in less additional travel time. This advantage compensates for the additional time of transferring if the transfer point is well chosen.
Read the full paper here: TRA Conference 2016 Van Oort Data driven enhancement of PT
or check the poster: TRA2016 Conference Poster