Strategic Trip Planning: Striking a Balance Between Competition and Cooperation

In intelligent transportation systems, cooperative mobility planning is considered to be one of the challenging problems. Mobility planning as it stands today is an in- dividual decision-making effort that takes place in an environment governed by the collective actions of various competing travellers. Despite the extensive research on mobility planning, a situation in which multiple behavioural-driven travellers partic- ipate in a cooperative endeavour to help each other optimize their objectives has not been investigated. Furthermore, due to the inherent multi-participant nature of the mobility problem, the existing solutions fail to produce ground truth optimal mobil- ity plans in the practical sense - despite their claimed and well proven theoretical optimality. This thesis proposes a multi-module team mobility planning framework to address the team trip planning problem with a particular emphasis on modelling the inter- action between behaviour-driven rational travellers. The framework accommodates the travellers’ individual behaviours, preferences, and goals in cooperative and com- petitive scenarios. The individual behaviours of the travellers and their interaction processes are viewed as a team trip planning game. For this game, a theoretical anal- ysis is presented, which includes an analysis of the existence and the balancedness of the final solution. The proposed framework is composed of three principal modules: cooperative trip planning, team formation, and traveller-centric trip planning (TCTP). The cooper- ative trip planning module deploys a bargaining model to manage conflicts between the travellers that could occur in their endeavour to discover a general, satisfactory solution. The number of players and their interaction process is controlled by the team formation module. The TCTP module adopts an alternative perspective to the individualized trip-planning problem in the sense that it is being behavioural driven problem. This allows for multitudes of traveler centric objectives and constraints, as well as aspects of the environment as they pertain to the traveller’s preferences, to be incorporated in the process. Within the scope of the team mobility planning frame- work, the TCTP is utilized to supply the travellers with personalized strategies that are incorporated in the cooperative game. The concentration problem is used in this thesis to demonstrate the effectiveness of the TCTP module as a behavioural-driven trip planner. Finally, to validate the theoretical set-up of the team trip planning game, we introduce the territory sharing problem for social taxis. We use the team mobility framework as a basis to solve the problem. Furthermore, we present an argument for the convergence and the efficiency of a coarse correlated equilibrium. In addition to the validation of a variety of theoretical concepts, the territory sharing problem is used to demonstrate the applicability of the proposed framework in dealing with cooperative mobility planning problems

The Government Policy on Online-Based Transportation in the Era of Disruption

The purpose of this study is to analyze the challenges and constraints of government policy on online-based land transportation in the era of disruption. This research uses qualitative research design. The type of data used in this research is seconddary data. Sufficient data is needed as material for analysis in the discussion of this article. The data collection method used in this research is a literature study. Based on the analysis results, it can be concluded that the implementation of online transportation system policies in Indonesia has been able to improve the social welfare of some Indonesian people. However, there are still some obstacles in the social sphere in its implementation, such as government organizational structure, umbrella act, facilities, human resources, and the process. Meanwhile, blocks were also found from the driver's side, such as mobility gaps, differences in inaccessibility, the potential for accidents, and congestion, which can be a waste of energy

Social Space and Social Media: Analyzing Urban Space with Big Data

This dissertation focuses on the key role that big data can play in minimizing the perceived disconnect between social theory and quantitative methods in the discipline of geography. It takes as its starting point the geographic concept of space, which is conceptualized very differently in social theory versus quantitative methodology. Contrary to this disparity, an examination of the disciplinary history reveals a number of historic precedents and potential pathways for a rapprochement, especially when combined with some of the new possibilities of big data. This dissertation also proposes solutions to two common barriers to the adoption of big data in the social sciences: accessing and collecting such data and, subsequently, meaningful analysis. These methods and the theoretical foundation are combined in three case studies that show the successful integration of a quantitative research methodology with social theories on space. The case studies demonstrate how such an approach can create new and alternative understandings of urban space. In doing so it answers three specific research questions: (1) How can big data facilitate the integration of social theory on space with quantitative research methodology? (2) What are the practical challenges and solutions to moving “beyond the geotag” when utilizing big data in geographical research? (3) How can the quantitative analysis of big data provide new and useful insight in the complex character of social space? More specifically, what insights does such an analysis of relational social space provide about urban mobility and cognitive neighborhoods

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

The Cost of Inexperience

Free market entry is vital in preventing concentration of market power and eliminating large deadweight losses Yet in recent years studies show that newcomers are less successful than existing firms that have diversifies their products in the market What might explain this phenomenonThis Article unveils a regulatory catch 22 It reveals that although a regulation may be efficient in correcting a certain market failure its distributional effects may create another It exposes the degree to which economies of experience in regulation create significant disadvantages to newcomers and provide substantial advantages to oldtimers Being wellversed in their marketplace oldtimers possess knowledge familiarity and influence over the rulemaking process New or green entities entering regulated market or dealing with a new rule face proportionally larger costs to obtain regulatory insight Consequently an anomaly exists when government choice may de facto hamper innovation and survival of newcomers the same goals it seeks to promoteTo remedy this inconsistency the Article suggests ways to offset these distributional asymmetries through the use of information cooperatives regulatory sandboxes and compensatory mechanisms These solutions offer policymakers greater regulatory efficiency without resorting to deregulatio

The Cost of Inexperience

Free market entry is vital in preventing concentration of market power and eliminating large deadweight losses Yet in recent years studies show that newcomers are less successful than existing firms that have diversifies their products in the market What might explain this phenomenonThis Article unveils a regulatory catch 22 It reveals that although a regulation may be efficient in correcting a certain market failure its distributional effects may create another It exposes the degree to which economies of experience in regulation create significant disadvantages to newcomers and provide substantial advantages to oldtimers Being wellversed in their marketplace oldtimers possess knowledge familiarity and influence over the rulemaking process New or green entities entering regulated market or dealing with a new rule face proportionally larger costs to obtain regulatory insight Consequently an anomaly exists when government choice may de facto hamper innovation and survival of newcomers the same goals it seeks to promoteTo remedy this inconsistency the Article suggests ways to offset these distributional asymmetries through the use of information cooperatives regulatory sandboxes and compensatory mechanisms These solutions offer policymakers greater regulatory efficiency without resorting to deregulatio

The Cost of Inexperience

Free market entry is vital in preventing concentration of market power and eliminating large deadweight losses Yet in recent years studies show that newcomers are less successful than existing firms that have diversifies their products in the market What might explain this phenomenonThis Article unveils a regulatory catch 22 It reveals that although a regulation may be efficient in correcting a certain market failure its distributional effects may create another It exposes the degree to which economies of experience in regulation create significant disadvantages to newcomers and provide substantial advantages to oldtimers Being wellversed in their marketplace oldtimers possess knowledge familiarity and influence over the rulemaking process New or green entities entering regulated market or dealing with a new rule face proportionally larger costs to obtain regulatory insight Consequently an anomaly exists when government choice may de facto hamper innovation and survival of newcomers the same goals it seeks to promoteTo remedy this inconsistency the Article suggests ways to offset these distributional asymmetries through the use of information cooperatives regulatory sandboxes and compensatory mechanisms These solutions offer policymakers greater regulatory efficiency without resorting to deregulatio