Q Qi Han

Route Choice Under Uncertainty: Effects of Recommendations

The provision of travel information may serve as a means of changing the behavior of individual travelers in ways that are beneficial to the transportation system at large. On the basis of the argument that a better understanding of travel behavior in the presence of traffic information is required, this paper reports on the analysis of a computer experiment investigating the effects of recommendations with different underlying control objectives on route choice under uncertainty. The results indicate that when potential congestion is anticipated, travelers use the recommendations provided as an indicator of the choices of other travelers as they conjecture the rate of compliance to reduce the uncertainty when they make decisions.

Conflicts and Cooperation in Brownfield Redevelopment Projects: Application of Conjoint Analysis and Game Theory to Model Strategic Decision Making

AbstractRedevelopment of brownfields is placed high on the political agendas in many countries. However, brownfield redevelopment projects are often problematic, and the frequent occurrence of conflicts between involved and interdependent stakeholders is directly related. To date, there is no insight in the underlying interaction structure of brownfield redevelopment projects and tools are lacking to support the complex decision making between stakeholders. The aim of this article is to theoretically analyze the underlying interaction structures in brownfield redevelopment projects, modeling the process as an interdependent situation and applying game theoretical arguments. The explicit interaction between involved stakeholders is modeled as an interdependent process, using an approach in which conjoint analysis and game theory are combined. Our results show that there is one major source of conflicts—stakeholders choosing not to cooperate based on the presented game-setting. Other possible sources of con...

Modelling strategic behaviour in anticipation of congestion

Congestion in capacity-constrained urban environments is essentially the aggregate outcome of choices that individuals make in self-interest while assuming that others do the same. Existing models in transportation do typically no take the interaction and dependencies between different travellers into account. In this study, a new modelling approach was developed that incorporates an endogenous interaction term in a discrete choice model to describe the strategic choice behaviour of individuals. The approach accounts for different degrees of rationality, and choice situations, reflecting the extent of previous experiences. The choice models are linked to a model of how a control agent acts strategically, dependent on different objectives in optimizing usage of capacity-constrained facilities. The paper summarizes the approach, discusses the results of numerical simulations to assess its face validity and reports some main findings from two experiments that were conducted to empirically estimate the models.

Integrating Prospect Theory and Stackelberg Games to Model Strategic Dyad Behavior of Information Providers and Travelers: Theory and Numerical Simulations

Existing policy models of optimal guidance strategies are typically concerned with single-objective optimization based on reliable forecasts in terms of the consistency between predicted and observed aggregate activity-travel patterns. The interaction and interdependencies between policy objective and individuals have not received much attention. This paper considers how one specific activity schedule choice—namely, the start time of an activity chosen by individual travelers under guidance information—aggregates to form an equilibrium distribution, which in turn influences guidance generation and determines the best possible achievement of the policy objective. These choices are formalized as the outcomes of a Stackelberg game in which a travelers behavior model is integrated with prospect theory. The properties of the model are examined by using numerical computer simulations. The results of the simulations support the face validity of the formulated model.

Brownfield redevelopment features: applying Fuzzy Delphi

Purpose – A brownfield site is well described by various definitions and the idea to redevelop it is supported by identifying numerous benefits for the society. Further, the existing literature covers a broad range of different aspects of the brownfield redevelopment thus elaborating different features. At present, there is no overview of the brownfield features from the real estate development perspective focusing on the physical, legal and financial aspects of a site and property. This paper aims to address these issues.Design/methodology/approach – At first, this paper contributes with the literature survey after which the features were structured according to the real estate development perspective. Additionally, the authors distinguish different expert groups and show the importance of keeping apart their aggregated opinions. Fuzzy Delphi technique is considered as an excellent method to gather such diverse panel data since it supports expert diversity in its procedure and calculation. Additionally, ...

Actors’ Preferences in the Redevelopment of Brownfield: Latent Class Model

AbstractNumerous authors have argued that the redevelopment of a brownfield can provide a range of benefits. For example, the physical improvements of a brownfield result in better site characteristics such as lower contamination levels, better site accessibility, and eventually improve the image of a neighborhood. On the other hand, applying proper legal policies leads to a less complicated ownership structure and might result in a faster approval process. These physical improvements and legal policy endeavors often lead to financial benefits such as value capturing or improved real estate value. However, the necessity to deal simultaneously with physical improvements, legal policies, finances, and the tradeoffs that need to be considered therein may explain why brownfield problems are not easily resolved. In addition, many actors are involved in the redevelopment process. Actors such as the municipality, developer, and landowner might have different preferences regarding the essential physical, legal, a...

Interactive Learning in Transportation Networks with Uncertainty, Bounded Rationality, and Strategic Choice Behavior: Quantal Response Model

Existing learning and adaptive behavior models are typically derived from reinforcement learning from actual experiences in dynamic non-stationary environments. When the dynamics involve uncertainty with respect to the choice behavior of other travelers, travelers might make particular choice options by taking into account their expectations about the behavior of other travelers. Consequently, they will learn not only from their own experiences but also from the extent to which their conjectures about the behavior of other travelers are consistent with actual choices. A general model of interactive learning behavior that evolves toward equilibrium in such strategic situations is described. The properties of the model are examined by using numerical computer simulations. The results of the simulations support the face validity of the formulated model.

Modeling Impact of Emerging Uncertain Time-Dependent Aggregate Activity-Travel Patterns on Individual Activity Participation and Timing Decisions

Existing activity-based models are typically concerned with predicting observed aggregate activity-travel patterns. The interaction and dependencies between individuals have received less attention. Considered here is how one specific schedule choice, namely, the start time of an activity chosen by an agent, aggregates to form an equilibrium distribution, which in turn influences individual decision making. These choices are formalized as the outcomes of a game of incomplete information in which agents have to conjecture the behavior of other agents. The properties of the model are examined by using numerical computer simulations. The results of the simulations support the face validity of the formulated model.

SIRPSS - Sustainable Industrial Site Redevelopment Planning Support System

Abandoned industrial sites should be redeveloped in a sustainable way to reduce waste land. Planning support systems (PSSs) can help in the early planning phase by presenting possible outcomes of various redevelopment scenarios to the planners. This paper presents a PSS to support sustainable industrial site redevelopment decision based on past experiences. Past experiences are recorded as cases in the system. Case-based reasoning (CBR) is applied. For sites needed to be redeveloped, similar redeveloped cases are retrieved from the case library. Strategies that the previous cases have applied are reviewed and the new site is designed based on the comparison study of new case and past experiences, together with the input from planners. Sustainability is dynamically evaluated on site and regional level. A showcase is presented for the system illustration.

A negotiation decision model for public-private partnerships in brownfield redevelopment

Urban development cannot proceed without the commitment of multiple actors, because decision-making processes have become more and more interdependent. This article supports better decision-making in brownfield redevelopment projects in cases where the project realization depends on a public–private partnership between a municipality and a developer. In a broader sense, in this research, we investigate how the negotiation process in brownfield redevelopment projects can be improved by providing an understanding of the characteristics of a brownfield area and the interaction between the parties involved. In order to improve the process, a negotiation decision model is proposed. This is a hybrid model consisting of five phases. Its novelty lies in the combination of a latent class model and a strategic choice model that can be formulated as a prescriptive-interactive approach in decision theory. The hybrid negotiation model is applied to a reconstructed case study in order to present its possibilities. Accordingly, three applications of the model are introduced, and in each application the beneficiary is a municipality. Although using decision models for brownfield redevelopment projects has already been thoroughly studied, there is little evidence concerning the prescriptive-interactive component built into existing models.