A Critical Look at the Abstraction Based on Macro-Operators

Abstraction can be an effective technique for dealing with the complexity of planning tasks. This paper is aimed at assessing and identifying in which cases abstraction can actually speed-up the overall search. In fact, it is well known that the impact of abstraction on the time spent to search for a solution of a planning problem can be positive or negative, depending on several factors -including the number of objects defined in the domain, the branching factor, and the plan length. Experimental results highlight the role of such aspects on the overall performance of an algorithm that performs the search at the ground-level only, and compares them with the ones obtained by enforcing abstraction

Hybrid choice model for propensity to travel and tour complexity

During the last years cities around the world have invested important quantities of money in measures for reducing congestion and car-trips. Investments which are nothing but potential solutions for the well-known urban sprawl phenomenon, also called the “development trap” that leads to further congestion and a higher proportion of our time spent in slow moving cars. Over the path of this searching for solutions, the complex relationship between urban environment and travel behaviour has been studied in a number of cases. The main question on discussion is, how to encourage multi-stop tours? Thus, the objective of this paper is to verify whether unobserved factors influence tour complexity. For this purpose, we use a data-base from a survey conducted in 2006-2007 in Madrid, a suitable case study for analyzing urban sprawl due to new urban developments and substantial changes in mobility patterns in the last years. A total of 943 individuals were interviewed from 3 selected neighbourhoods (CBD, urban and suburban). We study the effect of unobserved factors on trip frequency. This paper present the estimation of an hybrid model where the latent variable is called propensity to travel and the discrete choice model is composed by 5 alternatives of tour type. The results show that characteristics of the neighbourhoods in Madrid are important to explain trip frequency. The influence of land use variables on trip generation is clear and in particular the presence of commercial retails. Through estimation of elasticities and forecasting we determine to what extent land-use policy measures modify travel demand. Comparing aggregate elasticities with percentage variations, it can be seen that percentage variations could lead to inconsistent results. The result shows that hybrid models better explain travel behavior than traditional discrete choice models

On the treatment of repeated observations in panel data: efficiency of mixed logit parameter estimates

Travel demand models are often estimated using cross-sectional data. Although the use of panel data has recently increased in many areas, there are still many aspects that have not been analyzed fully. Some examples of unexplored topics are: the optimal length of panel surveys and the resulting issue of how to model panel data correctly in the presence of repeated observations (for example, several trips per week, by people in a panel with waves every six months) and whether, and to what extent, this affects the efficiency of the estimated parameters and their capability to replicate the true situation. In this paper we analyse this issue and test the effect of including journeys made, with the same characteristics, several times in a week. A broad variety of models accounting for fixed parameters but also for random heterogeneity and correlation among individuals were estimated using each of real and synthetic data. The real data come from the Santiago Panel (2006-2008), while the synthetic data were appropriately generated to examine the same problem in a controlled experiment. Our results show that having more observations per individual increases the probability of capturing effects (different types of heterocedasticity), but having identical observations in a data panel reduces the capability to reproduce true phenomena. Consequently, the definition of panel survey duration requires us to consider the implicit level of routine that is present as represented in the proportion of identical observations

Inertia and shock effects on mode choice panel data: implications of the Transantiago implementation

The mode choice process, especially in the case of commuter trips, reflects the strong tendency people have to simplify the assessment of their options when confronted with successive well-known decisions. Thus, it is common to repeat the “habitual” choice over time involving a potentially important inertia element. However, while inertia effects increase the probability of maintaining the same choice in a stable situation, in a changing environment i.e. one that is disrupted by a radical or significant policy intervention, user behaviour may be affected by a specific response to abrupt changes. Shock effects of this kind could increase the probability of individuals leaving their habitual choices. Temporal effects have been commonly ignored in practical studies, as most demand models to date have been based on cross-sectional data. A few recent studies dealing with panel data have managed to incorporate inertia effects, but there are no studies that have included both inertia and shock effects. To address this, we started by building a data panel around the introduction of a new and radical policy for the conurbation of Santiago de Chile. The final aim was to develop mode choice models incorporating the effects of three main forces involved in the choice process: (1) the relative values of the modal attributes, (2) the inertia effect, and (3) the shock resulting from and abrupt policy intervention. This paper presents the formulation of an inertia-shock model and its application to each of simulated and real data. The results confirm that changing systems should be modelled respecting the presence of both inertia and shock effects, otherwise serious errors in model estimation may arise

Role of car segment and fuel type in the choice of alternative fuel vehicles: A cross-nested logit model for the English market

\ua9 2023 The Authors. In this article, we study the role of car segment and fuel type in the choice of alternative fuel vehicles and in the prediction of its market. For this purpose, we propose a joint choice cross-nested logit model to understand the demand for alternative fuel vehicles (AFV) and to study substitutional patterns between fuel types and vehicle segments with a full revealed preference approach, using only publicly available real data at disaggregate (household) level in England. Our results show that, as hypothesised, fuel type choice is not independent from car segment choice. The correlation patterns in the chosen specification reveal that individual car alternatives belonging to the same car segment are strongly correlated, while a weaker correlation exists between alternatives from different segments which share the same fuel type. The results suggest that creating awareness for cleaner fuel alternatives might be more effective if a targeted approach that considers these substitutional patterns is used. From a policy standpoint, while purchase prices play an important role and government policies have been concentrated in reducing the gap between ICE vehicles and AFVs in this dimension, our models stress the relevance of the operating cost variable, suggesting that its effect might also be crucial in the purchase decision

On fitting mode specific constants in the presence of new options in rp/sp models

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Conducting Stated Choice Experiments within an Immersive Virtual Reality Environment: An Application to the Discrete Choice of Automated versus Normal Taxi

\ua9 2024 Elsevier BV. All rights reserved. This paper describes the methodology set up to measure consumers\u27 preferences in a choice between a fully automated and normal taxi, using a Stated Choice (SC) experiment embedded in an immersive Virtual Reality (VR) environment. VR represents an important tool to allow respondents to "live" their choice with the potential to reduce the typical problem of lack of realism in SC experiments. This paper describes the work done to build the VR-based SC experiment, and discusses challenges and potentialities. The study is applied to the choice of taxi in the city centre of Newcastle upon Tyne in the UK

Workshop synthesis: Virtual reality, visualization and interactivity in travel survey, where we are and possible future directions

\ua9 2024 Elsevier BV. All rights reserved. This paper summarizes the discussion of the workshop B16 "Virtual reality, visualization and interactivity in travel survey, where we are and possible future directions". The workshop involved three sessions over the course of the conference. First two sessions discussed the current state of research, challenges, and possible future directions. The last session focused on synthesis of a research agenda for the next five years. It was concluded that the VR/AR tools and platforms provide a unique opportunity to proactively investigate the travel behaviour changes that are expected to happen due to the development and adoption of disruptive mobility technologies and services as well as virtual worlds and digital twins

Preferences for automated taxis. A comparison between immersive virtual reality and screen-based stated choice experiments

\ua9 2024 The Author(s)Automated Taxi (AT) services, as a promising business model for Autonomous Vehicles (AVs), have paved the way for novel mobility options. Understanding users’ preferences for this innovative alternative is crucial for its success but proves to be challenging, as the lack of a real market mostly requires setting hypothetical situations to elicit respondents’ preferences. Recent applications have seen an increasing use of Virtual Reality (VR), as a way to control the context, or to provide visual representation of some attributes. Research is however still in its infancy, in particular in the transport context, and results often are not comparable or show opposite effects. In this research, we aim to contribute to this limited research by studying the impact of the immersive VR environment in the preferences for AT elicited with Stated Choice (SC) experiments. Differently from previous studies, our experiment is built to ensure that the SC experiment in the VR-based environment is perfectly comparable with the standard SC screen-based, for internal validity. A control group is also used to test the order effect in the presentation of the two surveys, and to control for the carryover effect. Using data collected from a quite large sample, compared to the existing studies, joint mixed logit models are estimated allowing to assess the impact of the immersive VR environment on the choice bias, heterogeneity in the preferences for specific attributes, as well as panel effect, and order effect. Our results show that the immersive VR-based experience has no impact on the preferences for level-of-service attributes, travel time and cost, unless respondents can, to some extent, experience them, like waiting time in our study. On the other hand, the hints and cues provided by the immersive VR environment seem to affect the evaluation of the social aspects, descriptive norms and customers’ reviews. This highlights a significantly high heterogeneity in the preferences, not revealed in the screen-based SC experiment. Finally, differently from previous literature, our results show no difference in the choice bias between VR- and screen-based environment, but only if differences in the preferences for specific attributes between the two environments are properly taken into account