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Evaluating the Performance and Benefits of Bus Priority, Operation and Control Measures
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.ORCID iD: 0000-0002-0089-6543
Delft University of Technology, Netherland..ORCID iD: 0000-0002-4506-0459
2016 (English)In: Proceedings of the 95th Transportation Research Board Annual Meeting, Washington DC., 2016Conference paper, Published paper (Refereed)
Abstract [en]

Preferential measures are designed and implemented to improve public transport performance and level-of-service. In the case of urban bus systems, priority, operational and control measures are aimed to elevate bus services to buses with high level of service (BHLS). Even though there is an explosive growth in preferential measures implementation and growing research interest in investigating their impact on performance indicators, there is lack of a systematic evaluation of their benefits. We present an evaluation framework and a detail sequence of steps for quantifying the impacts of public transport preferential measures. The effects of service performance on travel times and costs are assessed by accounting for relations between reliability and waiting times, crowding and perceived travel times, and vehicle scheduling and operational costs. The evaluation integrates the implications of reliability on generalized passenger travel costs and operational costs. We deploy the proposed evaluation framework to a field experiment in Stockholm where a series of measures were implemented on the busiest bus line. The results suggest that the total passenger and operator benefits amount to 47 million Swedish crowns on an annual basis. The overall assessment of the impacts of preferential measures enables the comparison of different implementations, assess their effectiveness, prioritize alternative measures and provide a sound basis for motivating investments.

Place, publisher, year, edition, pages
2016.
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-177485OAI: oai:DiVA.org:kth-177485DiVA: diva2:872971
Conference
The 95th Transportation Research Board Annual Meeting, Washington DC.
Note

QC 20160226

Available from: 2015-11-20 Created: 2015-11-20 Last updated: 2016-04-07Bibliographically approved
In thesis
1. New Opportunities in Urban Transport Data: Methodologies and Applications
Open this publication in new window or tab >>New Opportunities in Urban Transport Data: Methodologies and Applications
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The deployment of Information and Communication Technologies (ICT) is growing in transportation which may contribute to a more efficient and effective service. The data acquired from ICT based systems could be used for many purposes such as statistical analysis and behavior learning and inference. This dissertation addresses the question of how transportation data that was collected for a specific application can be used for other applications. This thesis consists of five separate papers, each addressing a subset of the topic.

The first paper estimates a route choice model using sparse GPS data. This paper demonstrates the feasibility of an Indirect Inference based estimator in a model with random link costs, allowing for a natural correlation structure across paths, where the full choice set is considered.

The second paper presents an estimator for the mean speed and travel time at network level based on indirect inference when the data are spatially and temporally sparse.

The third paper proposes an evaluation framework which outlines a systematic process to quantify and assess the impacts of public transport preferential measures on service users and providers in monetary terms, using public transport data sources.

In the fourth and fifth papers, a methodology is developed and implemented for integrating different prediction models and data sources while satisfying practical requirements related to the generation of real-time information. Then the performance of the proposed prediction method is compared with the prediction accuracy obtained by the currently deployed methods.

Abstract [sv]

Användandet av informations- och kommunikationsteknologier (eng. ICT) ökar inom transportområdet, vilket kan bidra till ökad effektivitet. Insamlad data från system med ICT skulle kunna användas för många ändamål såsom statistisk analys, beteendeinlärning och inferens. Denna avhandling tar upp frågan om huruvida transportdata insamlat för en viss tillämpning kan användas för andra. Avhandlingen innehåller fem forskningsartiklar, var och en inriktar sig på sin del av ämnet.

De två första uppsatserna fokuserar på konsistenta estimatorer för hastighet på länkar och ruttval. För många olika tillämpningar är det viktigt att förutsäga en observerad rutts fortsättning, och, givet att det är glest med data, att även avgöra var individen (eller fordonet) har varit. Att skatta den upplevda restiden (och nyttan) av en vald rutt är ett statistiskt svårt skattningsproblem av flera olika skäl. För det första är valmängden ofta mycket stor. För det andra kan det vara viktigt att ta hänsyn till korrelationen mellan de (generaliserade) kostnaderna för olika rutter och därigenom tillåta realistiska ersättningsmönster. För det tredje, på grund av överväganden gällande teknik och den personliga integriteten, kan data vara temporalt och spatialt gles och med endast partiellt observerade rutter. Slutligen, kan det finnas mätfel av fordonens position. Vi utvecklar en estimator för upplevd nytta av en rutt (i den första artikeln) samt för restid på länkar i vägnätverket (i den andra artikeln).

I den tredje artikeln föreslås ett ramverk för utvärdering innefattande en systematisk process som kvantifierar och bedömer inverkan av preferensstyrmedel inom kollektivtrafiken på tjänsteanvändare och leverantörer.

I fjärde och femte artikeln utvecklas och implementeras en metodologi för att integrera olika prediktiva modeller och data-källor i beaktande av praktiska krav kopplade till skapandet av realtidsinformation. Den resulterande prediktionsmetoden jämförs med de metoder som i nuläget används i Stockholm och Brisbane.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xvii, 24 p.
Series
TRITA-TSC-PHD, 15:008
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
urn:nbn:se:kth:diva-177489 (URN)978-91-87353-80-2 (ISBN)
Public defence
2015-12-11, L1, Drottning Kristinas väg 30, KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20151123

Available from: 2015-11-23 Created: 2015-11-20 Last updated: 2015-11-23Bibliographically approved

Open Access in DiVA

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Other links

http://amonline.trb.org/trb60693-2016-1.2807374/t026-1.2815712/823-1.2815724/16-0458-1.2812780/16-0458-1.2815729?qr=1

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Fadaei, MasoudCats, Oded

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