Train timetable design under elastic passenger demand. (May 2018)
- Record Type:
- Journal Article
- Title:
- Train timetable design under elastic passenger demand. (May 2018)
- Main Title:
- Train timetable design under elastic passenger demand
- Authors:
- Robenek, Tomáš
Azadeh, Shadi Sharif
Maknoon, Yousef
de Lapparent, Matthieu
Bierlaire, Michel - Abstract:
- Highlights: We replace the deterministic behavioral model of the passengers in the passenger centric train timetabling problem with a probabilistic one. We use a logit model, that has been calibrated to known demand elasticities, to predict the passenger behavior. We introduce a competing operator as an opt-out option for the passengers. We integrate the timetabling model with a pricing model. We maximize the operator's revenue by solving the Elastic Passenger Centric Train Timetabling Problem with pricing for different timetable designs using the Simulated Annealing heuristic. We use real network of Israeli Railways as our case study. The results show that the passenger behavior is having a significant impact on the operator's revenue. The knowledge of the passenger behavior allows for effective ticket pricing. Abstract: A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use aHighlights: We replace the deterministic behavioral model of the passengers in the passenger centric train timetabling problem with a probabilistic one. We use a logit model, that has been calibrated to known demand elasticities, to predict the passenger behavior. We introduce a competing operator as an opt-out option for the passengers. We integrate the timetabling model with a pricing model. We maximize the operator's revenue by solving the Elastic Passenger Centric Train Timetabling Problem with pricing for different timetable designs using the Simulated Annealing heuristic. We use real network of Israeli Railways as our case study. The results show that the passenger behavior is having a significant impact on the operator's revenue. The knowledge of the passenger behavior allows for effective ticket pricing. Abstract: A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the passenger centric train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15% when taking into account the passengers' behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity. … (more)
- Is Part Of:
- Transportation research. Volume 111(2018)
- Journal:
- Transportation research
- Issue:
- Volume 111(2018)
- Issue Display:
- Volume 111, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 111
- Issue:
- 2018
- Issue Sort Value:
- 2018-0111-2018-0000
- Page Start:
- 19
- Page End:
- 38
- Publication Date:
- 2018-05
- Subjects:
- Passenger centric train timetabling problem -- Railway demand forecasting -- Hybrid cyclicity -- Ticket pricing -- Revenue
Transportation -- Research -- Periodicals
Transportation -- Mathematical models -- Periodicals - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/01912615 ↗ - DOI:
- 10.1016/j.trb.2018.03.002 ↗
- Languages:
- English
- ISSNs:
- 0191-2615
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274610
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11420.xml