Posted in June 2019

When science meets practice: fiets+OV

Samen met de TU Delft organiseert Railforum regelmatig een ‘When science meets practice’. Tijdens deze bijeenkomsten wisselen studenten, wetenschappers en professionals uit de sector op een bepaald thema hun kennis en ervaringen uit. Hiermee willen we elkaar inspireren met nieuwe inzichten en betere oplossingen voor de praktijk, naast input voor een gezamenlijke onderzoeksagenda.

Op 3 april stond de combinatie van fiets en ov op het programma. Olaf Jonkeren van het Kennisinstituut voor Mobiliteitsbeleid presenteerde het onderzoek van het KiM i.s.m. Studio Bereikbaar over gecombineerd fiets-treingebruik in Nederland. Dorine Duives en Niels van Oort van de Delftse “Active Modes” en “Smart Public Transport” labs deelden hun inzichten over de gebruikers en de relatie van (deel)fietsen met bus, tram en metro.

De centrale vraag van deze middag was: Welke kennis en begrip hebben we over de keuzes die fiets-treinreizigers maken en hoe kunnen we hen beter faciliteren dan enkel door het bijbouwen van fietsenstallingen? Bij stations gaat bijna 50% van de stallingscapaciteit op aan 2e fietsen die niet dagelijks gebruikt worden.
Genoemde opties zijn het bevorderen van deelfietsen, het anders beprijzen van fietsenstallingen dichtbij het station om lang parkeren tegen te gaan. Belangrijkste conclusie was dat er nog veel marktpotentie is en we vooral de positieve kanten van ov en fiets beter kunnen communiceren, zoals dat bewegen goed is voor onze gezondheid!

De presentaties vind je HIER

Combining Speed Adjustment and Holding Control for Regularity based Transit Operations

Vehicle bunching often occurs in high-frequency transit systems leading to deterioration of service reliability. It is thus necessary to control vehicles during operations. Holding control is a common solution for this situation, but it may result in longer vehicle running times. Speed adjustments can contribute to more regular operations while preventing prolonged trip times. This paper proposes a control strategy, which combines these two strategies to maintain the regularity of transit operations. The findings based on simulation study for trunk bus services in the Netherlands suggest that combining the two strategies implies both the positive and negative attributes of each control.

Find the MT-ITS presentation and paper of Aishah Imram HERE and HERE

Walking and bicycle catchment areas of tram stops: factors and insights

Pollution and congestion are important issues in urban mobility. These can potentially be solved by multimodal transport, such as the bicycle-transit combination, which
benefits from the flexible aspect of the bicycle and the wider spatial range of public transport. In addition, the bicycle can increase the catchment areas of public transport stops. Most transit operators consider a fixed 400m buffer catchment area. Currently, not much is known about what influences the size of catchment areas, especially for the bicycle as a feeder mode.

Bicycles allow for reaching a further stop in order to avoid a transfer, but it is not clear whether travelers actually do this.This paper aims to fill this knowledge gap by assessing which factors affect feeder distance and feeder mode choice. Data are collected by an on-board transit revealed preference survey among tram travelers in The Hague, The Netherlands. Both regression models and a qualitative analysis are performed to identify the factors that influence feeder distance and feeder mode choice. Results show that the median walking feeder distance is 380m, and the median cycling feeder distance is 1025m. The tram stop density and chosen feeder mode are most important in feeder distance. For feeder mode choice, the following factors are found to be influential: tram stop density, availability of a bicycle, and frequency of cycling of the tram passenger. Furthermore, the motives of respondents for choosing a stop further away are mostly related to the quality of the transit service and comfort matters, of which avoiding a transfer is named most often. In contrast, the motives for cycling relate mostly to travel time reduction and the built environment. Three important barriers for the bicycle-tram combination have been discovered: unavailability of a bicycle, insufficient and unsafe bicycle parking places. Infrequent users of the bicycle-tram combination are more inclined to travel further to a stop that suits them better.

Find the MT-ITS paper and presentation of Lotte Rijsman HERE and HERE

Impacts of charging methods and mechanisms of zero emission buses on costs and level of service

To limit global warming and strive for more liveable and sustainable cities, innovative zero-emission (ZE) buses are on the rise all around the world. Different alternative vehicle propulsion methods have been introduced during the last decades. However, for now, only trolley, battery and fuel-cell electric vehicles can be classified as (on the pipe) ZE-buses.

This research focuses on battery electric buses, since they are most cost-efficient and – therefore – the most promising option for the (near) future. An important limitation of battery electric buses is however the limited range of operations due to capacity restrictions of batteries. Batteries should be (re)charged before, during and/or after daily operations.

Different charging methods, including different charging power systems are available to charge battery electric vehicles. As far as known to the authors, scientific literature focusing on the operations and charging scheduling of electric buses is scarce. In this study, a comparison of different applied charging methods for electric buses is obtained.
A ZE-bus station simulation method is developed to assess charging methods and charging regulations with regards to their impacts on a variety of costs and level of service indicators. This simulation-based method is multi applicable, since it is particularly based on general automated vehicle location (AVL) data. To demonstrate our model, a case study at Schiphol (Amsterdam Airport) is performed.
This research concludes that the shift to ZE-bus transit is involved with higher costs and passenger disturbances. Investment costs of ZE-buses increase substantially: Most electric vehicles are around 60 to 80 percent more expensive than conventional diesel engine vehicles and additional charging infrastructure investments are required. Benefits of electric operations, including vehicle propulsion cost savings up to 70 percent, are not able to compensate these high investments.
The charging method choice contain trade-offs between level of service and (vehicle and charging infrastructure) investment costs. (Slow) depot charging offers opportunities for operations on short distance lines. However, additional vehicles are required in order to replace a vehicle which should be recharged. In this respect, conventional timetables could be complied and the level of service remains unchanged.

To prevent fleet overcapacity, vehicles should be recharged fast (with high charging power) along the line. Slight charging related delays could occur, especially when the number of charging systems is not sufficient, and/or the charging times are relatively long. Bus end stations and terminals are suitable as fast charging locations, since charging time could be combined with buffer time there.

Finally, dynamic/in-motion charging offers opportunities to prevent charging related delays completely due to combined charging and operation time. This charging method is still in its infancy stage yet, so focus is more on (innovative) static charging methods now.

Find the MT-ITS presentation wih Max Wiercx and Raymond Huisman: HERE

Does ride-sourcing absorb the demand for car and public transport in Amsterdam?

The emergence of innovative mobility services, is changing the way people travel in urban areas. Such systems offer on-demand service (door-to-door or stop-to-stop, individual or shared) to passengers. In addition to providing flexible services to passengers, past studies suggested that such services could effectively absorb the demand for private cars thereby reducing network congestion and demand for parking. This study investigates the potential of a ride-sourcing service to absorb the demand for public transport and private cars for the city of Amsterdam. Results indicate that a ride-sourcing vehicle could potentially serve the demand currently served by nine privately owned vehicles and that a fleet size equivalent to 1.3% and 2.6% of the total public transport trips, are required to provide door-to-door and stop-to-stop times comparable to those yielded by the current public transport system. Results from the modal shift indicate that most PT trips are substituted by active modes and most car trips are substituted by ride-sourcing service.

Find the MT-ITS paper and presentation of Jishnu Narayan HERE and HERE

Calibrating Route Choice Sets for an Urban Public Transport Network using Smart Card Data

Identifying the set of alternatives from which travellers choose their routes is a crucial step in estimation and application of route choice models. These models are necessary for the prediction of network flows that are vital for the planning of public transport networks. However, choice set identification is typically difficult because while selected routes are observed, those considered are not. Approaches proposed in literature are not completely satisfactory, either lacking transferability across networks (observation-driven methods) or requiring strong assumptions regarding traveller behaviour (uncalibrated choice set generation methodologies (CSGM)). Therefore, this study proposes a constrained enumeration CSGM that applies the non-compensatory decision model, elimination-by-aspects, for choice set formation. Subjective assumptions of traveller preferences are avoided by calibrating the decision model using observed route choice behaviour from smart card data, which is becoming increasingly available in public transport systems around the world. The calibration procedure also returns two key insights regarding choice set formation behaviour: (i) the ranking of different attributes by their importance, and (ii) the acceptable detours for each attribute. To demonstrate the methodology and investigate choice set formation behaviour, the tram and bus networks of The Hague, Netherlands are used as a case study.

Find the MT-ITS paper and presentation of Sanmay Shelat HERE and HERE

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