Posts tagged service reliability
Operations of zero-emission buses: impacts of charging methods and mechanisms on costs and the level of service
To limit global warming and strive for more liveable and sustainable cities, innovative zero-emission buses are on the rise all around the world. For now, only trolley, battery and fuel-cell electric vehicles can be classified as (on the pipe) zero-emission vehicles. Different charging methods, including different charging systems and power, are available to charge battery electric vehicles. However, scientific literature focused on the operation and charging scheduling of electric vehicles is scarce.
In this study, a comparison of different applied charging methods for electric buses is obtained. A new ZE-bus station simulation method is developed to assess charging methods and charging regulations with regard to their impacts on costs and level of service.
The shift to zero emission bus transport is meant for achieving more sustainable and liveable cities. However, this research concludes that this is involved with higher costs and passenger disturbances. The investment costs increase substantially. Benefits of electric operations, including vehicle propulsion cost savings up to 70 percent, are not able to compensate these high investments. (Slow) depot charging offers opportunities for operations on short distance lines. The depot location should be close to a bus station and additional fleet is required. In order to prevent fleet overcapacity, vehicles should be recharged with high charging power along the line, preferably at combined bus stations and terminals in order to prevent charging related delays. Dynamic/In-motion charging – still in its infancy stage yet – offers opportunities to prevent these delays due to combined charging and operation time.
Robust Control for Regulating Frequent Bus Services: Supporting the Implementation of Headway-based Holding Strategies
Reliability is a key determinant of the quality of a transit service. Control is needed in order to deal with the stochastic nature of high-frequency bus services and to improve service reliability. In this study, we focus on holding control, both schedule- and headway-based strategies. An assessment framework is developed to systematically assess the effect of different strategies on passengers, the operator and transport authority. This framework can be applied by operators and authorities in order to determine what holding strategy is most beneficial to regulate headways, and thus solve related problems. In this research knowledge is gained about what service characteristics affect the performance of holding strategies and the robustness of these strategies in disrupted situations, by using scenarios. The framework is applied to a case study of a high-frequency regional bus line in the Netherlands. Based on the simulation results, we identified the line characteristics that are important for the performance of schedule- and headway-based strategies and determined how robust different strategies are in case of disruptions. Headway-based control strategies better mitigate irregularity along the line, especially when there are disruptions. However, schedule-based control strategies are currently easier to implement, because it does not require large changes in practice, and the performance of both strategies is generally equal in regular, undisrupted situations. In this paper, insights into what the concerns are for operators with respect to technical adaptations, logistical changes and behavioral aspects when using a headway-based strategy are given.
Find the TRB paper and presentation of Ellen van der Werff HERE and HERE
Improving railway passengers experience: two perspectives
This paper describes two perspectives to improve the passenger experience. The passenger satisfaction pyramid is introduced, consisting of the base of the pyramid (dissatisfiers) focusing on time well saved and the top of the pyramid (satisfiers) aiming at time well spent. The challenge in planning and design of public transport services is to find the most efficient (set of) design choices. Depending on the context this might either mean focusing on the top or on the bottom of the pyramid. We found that influencing and enhancing the qualities of the satisfiers is far more important than traditional studies showed us. For stations, regression analyses show that dissatisfiers are responsible for explaining almost half of the total score of the station and satisfiers are responsible for the other half of the scores passengers give for the station. We still have to put a lot of energy in getting the basics right, starting in the planning phase, but then we are not allowed to lean back. We have to keep investing in qualities like ambience, comfort and experience which makes the customers truly happy at the end of the day.
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 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
The wider benefits of high quality of public transport for cities
The full value of public transport is often underestimated. The 5E framework, consisting of effective mobility, efficient city, economy, environment and equity supports assessing and quantifying this value. This paper presents the framework and a wide selection of sources illustrating the wider benefits of high quality of public transport for cities.
Find our ETC conference paper HERE
Data-driven transfer inference for public transport journeys during disruptions
Disruptions in public transport have major impact on passengers and disproportional effects on passenger satisfaction. The availability of smart card data gives opportunities to better quantify disruption impacts on passengers’ experienced journey travel time and comfort. For this, accurate journey inference from raw transaction data is required. Several rule-based algorithms exist to infer whether a passenger alighting and subsequent boarding is categorized as transfer or final destination where an activity is performed. Although this logic can infer transfers during undisrupted public transport operations, these algorithms have limitations during disruptions: disruptions and subsequent operational rescheduling measures can force passengers to travel via routes which would be non-optimal or illogical during undisrupted operations. Therefore, applying existing algorithms can lead to biased journey inference and biased disruption impact quantification. We develop and apply a new transfer inference algorithm which infers journeys from raw smart card transactions in an accurate way during both disrupted and undisrupted operations. In this algorithm we incorporate the effects of denied boarding, transferring to a vehicle of the same line (due to operator rescheduling measures as short-turning), and the use of public transport services of another operator on another network level as intermediate journey stage during disruptions. This results in an algorithm with an improved transfer inference performance compared to existing algorithms.
Find the paper HERE
A data-driven approach to infer spatial characteristics and service reliability of public transport hubs
Public transport hubs play an important and a central role in public transport networks by connecting several public transport lines from one or multiple network levels. Hubs can be characterized by a large relative and absolute number of transferring passengers between public transport services within the same network level and/or between different network levels. Hubs are especially important with respect to service reliability of passenger journeys, since missing connections at hubs can substantially increase the nominal and perceived passenger journey travel time. The availability of AFC and AVL data allows an in-depth analysis of hub definition, identification, characterization and reliability performance evaluation. Such analysis enables optimisation of synchronisation of schedules, thereby increase the level of service reliability.
Find our TransitData2017 presentation HERE
Insights into door-to-door travel patterns of public transport passengers
Public transport enables fast and reliable station to station journeys. To assess passenger travel patterns and to infer actual quality of service, smartcard and AVL data offer great opportunities. There is, however, an increasing interest in insights into access and egress dynamics of public transport riders as well. What is the size of a stop’s catchment area, which modes are used, and how long and reliable are access and egress times? The answers to these and other questions enable optimization of the total mobility system, thereby also increasing public transport ridership and efficiency. Sufficient biking access of public transport stops (routes and parking), for instance, offer opportunities to increase public transport stopping distances, thereby increasing operational speed and reliability, without compromising accessibility of service areas. We developed a methodology to calculate and demonstrate these dynamics by using new and existing data technologies, namely AVL, survey and new promising app.
Find the Transit Data Conference abstract HERE and our presentation 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