Modelling Transport: Ortúzar/Modelling Transport

By Juan de Dios Ortúzar, L. Willumsen. 2011

894 citations recorded by the source corpus.

Subfields: Computational Mechanics, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/285053081a6aae7ff2fd8abb4d9434b2684a5b1e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. John W. Polak
2. Marcello Restelli
3. Stephane Hess
4. Nicolò Daina
5. Aruna Sivakumar

In Control and Systems Engineering

1. John W. Polak
2. Marcello Restelli
3. Diederik Marijn Roijers
4. Peter Vamplew
5. Nicolò Daina
6. Richard Dazeley
7. Luisa M. Zintgraf
8. Aruna Sivakumar

In Transportation

1. Stephane Hess
2. John W. Polak
3. Nicolò Daina
4. Aruna Sivakumar
5. M. Bradley
6. G. Spitz
7. M. Coogan
8. John M. Rose

Citations in the corpus

• Analysis of mode choice for intercity travel: Application of a hybrid choice model to two distinct US corridors (2018, background): “This presents important scope for heterogeneity in mode choice, only part of which is likely to be able to be explained by the analyst (Ortúzar & Willumsen, 2011).”
• Electric vehicle charging choices: Modelling and implications for smart charging services (2017, methodology): “These resulting specifications were chosen to provide a good balance between goodness of fit and parameter interpretability as it is common practice in DCM estimation (Ortuzar and Willumsen, 2011).”
• Analysis of the potential demand of automated delivery stations for e-commerce deliveries in Belo Horizonte, Brazil (2017, background): “R2 value obtained (0.26) is acceptable, considering that values between 0.2 and 0.4 are considered excellent (Ortúzar and Willumsen, 2011).”
• A practical guide to multi-objective reinforcement learning and planning (2021, background): “Deciding on the modes of transportation typically involves a number of objectives, such as minimising travel time and cost whereas maximising comfort and reliability [Ortúzar and Willumsen, 2011, Ramos et al., 2020, Mannion et al., 2016].”
• About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models (2015, neutral): “The last decades have seen discrete choice models (DCM) become a key element in travel demand modelling and forecasting (Ortúzar and Willumsen 2011).”