Anders Peterson Fahimeh Khoshniyat Dept. of Science and Technology Linköping University, Norrköping, Sweden 6 th May 2014 Effects of Travel Time Dependent.

Slides:



Advertisements
Similar presentations
Airport ATC Capacity Research Programme
Advertisements

Capacity Studies on Transportation Network Presented by Rakesh Ambre ( ) Under Guidance Of Prof. Narayan Rangaraj.
CE 515 Railroad Engineering Capacity Source: REES Module 6 & An Enhanced Parametric Railway Capacity Evaluation Tool
RELATION BETWEEN DEMAND AFTER TRAIN PATHS AND CAPACITY OF RAILWAY TRANSPORT INFRASTRUCTURE Ing. Josef Bulíček, Ph.D. Ing. Lukáš Fiala University of Pardubice,
Real Time Train SNCF. 1 Agenda Essentials Basic Model Applications Traffic density is getting very high in several networks and management.
Abstract The SEPTA Regional Rail system serves as an important network for the Philadelphia region, moving many commuters during the peak hours on suburb-to-city.
Robusta tidtabeller för järnvägstrafik + - Ökad robusthet i kritiska punkter Emma Andersson Anders Peterson, Johanna Törnquist Krasemann.
INFORMS 2012 Shared Corridor Railway Maintenance Scheduling Brennan M. Caughron Graduate Research Assistant Rail Transportation and Engineering Center.
Miroslav Vujic University of Zagreb Faculty of Transport and Traffic Sciences Zagreb, 10 October 2013 CIVITAS-ELAN 8.2. Public Transport Priority and Traveler.
1 February 2009 Analysis of capacity on double-track railway lines Olov Lindfeldt February 2008.
10 December J/ESD.204J Lecture 13 Outline Real Time Control Strategies for Rail Transit Prior Research Shen/Wilson Model Formulation Model Application.
BRAVE University of Birmingham Railway Virtual Environment Background
Stochastic optimization of a timetable M.E. van Kooten Niekerk.
Erasmus Center for Optimization in Public Transport 1 Shunting passenger train units: Practical planning aspects Ramon Lentink, Pieter-Jan Fioole, Dennis.
3rd ARRIVAL Review Meeting [Patras, 12 May 2009] – WP3 Presentation ARRIVAL – WP3 Algorithms for Robust and online Railway optimization: Improving the.
3rd ARRIVAL Review Meeting [Patras, 12 May 2009] – WP3 Presentation ARRIVAL – WP3 Algorithms for Robust and online Railway optimization: Improving the.
Operation-driven Scheduling Approach for Fast, Frequent and Reliable Railway Services Alfons A.M. Schaafsma, Vincent A. Weeda ProRail, Department of Traffic.
The Potential BRT in Asia
Inline Path Characteristic Estimation to Improve TCP Performance in High Bandwidth-Delay Networks HIDEyuki Shimonishi Takayuki Hama Tutomu Murase Cesar.
Capacity for Rail KAJT Dagarna, Dala-Storsund Pavle Kecman - LiU Anders Peterson - LiU Martin Joborn – LiU, SICS Magnus Wahlborg - Trafikverket.
Passenger travel behavior model in railway network simulation Ting Li Eric van Heck Peter Vervest Jasper Voskuilen Dept. Of decision and information sciences.
Quadratic Programming Model for Optimizing Demand-responsive Transit Timetables Huimin Niu Professor and Dean of Traffic and Transportation School Lanzhou.
Slide 1 ILLINOIS - RailTEC Capacity of Single-Track Railway Lines with Short Sidings to Support Operation of Long Freight Trains Ivan Atanassov, C. Tyler.
Federal Aviation Administration FOR OFFICIAL USE ONLY (Public availability to be determined under 5USC 552) Data Communications Program DCL Benefits Modeling.
Rail Related Research at IIT Madras
Odysa ® Experiences with an individual “green wave” Marcel Willekens / Arjan Bezemer / Kristiaan Langelaar.
Bruxelles Ansaldo STS – Company Profile nShield ARTEMIS Call
Computational Experiments Algorithm run on a Pentium IV 2.4 GHz Instances from “Rete Ferroviaria Italiana” For each station: - minimum interval between.
 Classes of trains  Fundamental principles of track authority  Impact of power/ton ratios  Drivers of dispatch priority 22 September 2010 SCORT/TRB.
Materials developed by K. Watkins, J. LaMondia and C. Brakewood Service Planning & Standards Unit 4: Service Planning & Network Design.
UIC ERTMS World Conference
Transportation Engineering
From frequencies to timetables: user-friendly improvements without expenses for the tramway system in Oradea Antal Gertheis
0 Christopher A. Pangilinan, P.E. Special Assistant to the Deputy Administrator Research and Innovative Technology Administration, ITS Joint Program Office.
Q/.r NSRZKLA4-P1 Capacity planning for railway systems Leo Kroon Jan 17, 2002.
Indonesian Timetabling Conference Introducing Timetabling and Train Control where there a Multiple Operators 31 May 2011.
Railway Operations: Issues and Objectives Capacity management Infrastructure planning Timetable preparation Management of day-to-day movement of trains.
Measuring Travel Time Reliability of Transportation Systems Abstract When traveling people want to be on time and avoid any traveling delays. We worked.
Traffic Based Pathway Optimization Michael LeGore TJHSST CSL.
HŽ Passenger Transport – overviewBUCHAREST HŽ PASSENGER TRANSPORT.
Hamed Pouryousef ; Pasi Lautala, Ph.D, P.E. Hamed Pouryousef ; Pasi Lautala, Ph.D, P.E. Michigan Tech. University Michigan Tech. University PhD Candidate.
DLR-Institute of Transport Research Testing and benchmarking of microscopic traffic flow simulation models Elmar Brockfeld, Peter Wagner
Institute of Transportation Systems > OPTIMISATION OF POINT LIFE CYCLE COSTS THROUGH LOAD-DEPENDENT MAINTENANCE > Slide 1 OPTIMISATION OF POINT LIFE CYCLE.
Both road vehicles and travelers vary in a number of characteristics. Vehicles differ in the road space they occupy, the visual obstruction they impose.
V. Cacchiani, A. Caprara and P. Toth DEIS, University of Bologna TIMETABLING FOR CONGESTED CORRIDORS.
1 Challenge the future Robust train routing in station areas with reducing capacity utilization Rotterdam, CASPT 2015 Nikola Bešinović, Rob.
Q/.r NSRZKLA4-P1 EUR team: Leo Kroon (EUR / NS)Timetable, rolling stock, crew Gabor Maroti (EUR / ARRIVAL)Timetable, rolling stock Ph.D. student (EUR /
June 6-7, th European EMME/2 Users' Group Conference Madrid Measuring the quality of public transit system Tapani Särkkä/Matrex Oy Mervi Vatanen/Helsinki.
TRAVEL TIME ANALYSIS Use of Data IN-KY-OH Traffic Incident Management Conference October 9, 2015 Dayton, OH.
12/08/ J/ESD.204J1 Real-Time Control Strategies for Rail Transit Outline: Problem Description and Motivation Model Formulation Model Application.
© APTA and AREMA D Introduction to Railway Capacity C. Tyler Dick, P.E. University of Illinois at Urbana-Champaign.
Q/.r NSRZKLA4-P1 Timetable planning Leo Kroon Sept 9, 2003.
Helsingin seudun liikenne -kuntayhtymä Ticket survey – the way to share the costs of public transport for HSL’s member municipalities Matleena Lindeqvist.
Motion Definition Speed A change in position over time Measures the rate of motion (how fast something is going) Speed = distance (miles, km, m, in, cm,
Initial proposals for the promotion of eco-mobility in the Austro-Hungarian border region EMAH project Álmos VIRÁG, project leader.
in Croatian Track access charging system
Analysis of capacity on double-track railway lines
ISP and Egress Path Selection for Multihomed Networks
Motion.
ITTS FEAT Tool Methodology Review ITTS Member States Paula Dowell, PhD
Nikola Ivanov, Fedja Netjasov, Radosav Jovanovic
Speed Distance Time. Intermediate 1. Unit 2..
How to Describe & Recognize Motion
Speed, Distance, Time Calculations
Speed, Distance, Time Calculations
An object travels 40 miles in 2 hrs. Calculate its speed?
Speed, Distance, Time Calculations
Calculating and Graphing Speed
Speed Notes.
Speed Distance Time. Intermediate 1. Unit 2..
Presentation transcript:

Anders Peterson Fahimeh Khoshniyat Dept. of Science and Technology Linköping University, Norrköping, Sweden 6 th May 2014 Effects of Travel Time Dependent Headway on Railway Timetable Robustness: an Application to the Swedish Southern Mainline

Robustness in a railway timetable? To “deal as well as possible with relatively small disturbances in the real-time operations” (Kroon et al., 2008) To “avoids delay propagation as much as possible” (Cacchiani et al., 2012) “Not to be sensitive to disturbances” (Shafia et al., 2012) To “allow operators to cope with unexpected disruptions” (Salido et al., 2012) 2

On-time performance en route Dotted line = average performance Doubled line = 75th percentile

Increasing buffer times Decreasing average speed Decreasing the capacity usage Decreasing the heterogeneity Robust Timetable Strategies Applied Methods Optimization Simulations Total Secondary Delays Average Secondary Delays Recovery Time Number of Delayed Trains Selecting Measurement Indicators Planning Perspective Tactical Operational Re-scheduling

Purpose To implement extra time separation between succeeding trains in a timetable and correlate them with trains’ travel times. 1 min / hr or 1,7 % A B 8:00 12:00 Time

Implementation Approach Minimum technical time separation Existing MILP model Changed MILP model Existing scheduled timetable Infrastructure Conflict free timetable New calculated timetable with extra time separations J. Törnquist Krasemann & J.A. Persson, 2007

7 Case study: Swedish Southern Mainline Source: The Swedish Transport Administration Alvesta–Lund (a part of the Southern Mainline) – Ca. 200 km long. – Double track. – Mixed traffic, fast and slow passenger trains and cargo. – Timetable period is between 11:00-13:00 and peak afternoon hours 16:00-18:00, regular weekday in 2011 and the same periods in 2014

Some preliminary results of the ongoing work…

2011, All trains, Minimum technical headway= 3 min, α =0.03

2011, All trains, Minimum technical headway= 3 min, α =0.03 (extra)

Thank you!