A Model of the Rise and Fall of Roads

Transportation network planning decisions made at one point of time can have profound impacts in the future. However, transportation networks are usually assumed tobe static in models of land use. A better understanding of the natural growth pattern of roads will provide valuable guidance to planners who try to shape the future network. This paper analyzes the relationships between network supply and travel demand, and describes a road development and degeneration mechanism microscopically at the linklevel. A simulation model of transportation network dynamics is developed, involving iterative evolution of travel demand patterns, network revenue policies, cost estimation,and investment rules. The model is applied to a real-world congesting network – the Twin Cities transportation network which comprises nearly 8,000 nodes and more than 20,000 links, using network data collected since year 1978. Four experiments are carried out with different initial conditions and constraints, the results from which allow us toexplore model properties such as computational feasibility, qualitative implications, potential calibration procedures, and predictive value. The hypothesis that roadhierarchies are emergent properties of transportation networks is confirmed, and the underlying reasons discovered. Spatial distribution of capacity, traffic flow, andcongestion in the transportation network is tracked over time. Potential improvements to the model in particular and future research directions in transportation network dynamicsin general are also discussed.Transportation network dynamics, Urban planning, Road suppl

Preliminary Results of a Multiagent Traffic Simulation for Berlin

This paper provides an introduction to multi-agent traffic simulation. Metropolitan regions can consist of several million inhabitants, implying the simulation of several million travelers, which represents a considerable computational challenge. We reports on our recent case study of a real-world Berlin scenario. The paper explains computational techniques necessary to achieve results. It turns out that the difficulties there, because of data availability and because of the special situation of Berlin after the re-unification, are considerably larger than in previous scenarios that we have treated

Co-Evolution of Transportation and Land Use: Modeling HIstorical Dependencies in Land Use and Decision-Making

The interaction between land use and transportation has long been the central issue in urban and regional planning. Models of such interactions provide vital information to support many public policy decisions, such as land supply, infrastructure provision, and growth management. Both the transportation and land use systems exhibit historical dependencies in policy decisions. For instance, the expansion of a roadway today will change travel demand patterns, and make certain other roads more or less likely to be expanded in the future. A specific land supply decision made at one point in time, by changing the relative attractiveness of other areas in the region, can have a profound impact on future land supply decisions. Today’s land use decisions clearly influence future transportation policies and vice versa. This project examines the land use-transportation interaction from an evolutionary perspective — once a certain set of goals are determined and pursued by politicians and planners, their land supply and transportation investment decisions are, to a large extent, driven by their previous decisions and supply-demand dynamics in the urban system. Built upon this recognition of historical dependency and a transportation network growth model previously developed by the P.I., a model of the co-evolution of land use and transportation is proposed in this project. Different from existing integrated land use and transportation models that assume exogenous network investment decisions, the co-evolution model considers both land use growth and transportation network growth as endogenous and market-driven. The central research question is how market and policies translate into transportation facilities and land use developments on the ground. The co-evolution model achieves an Urban Growth Equilibrium, which is a useful concept for planning and policy analysis. An agent-based simulation approach is employed to integrate an existing land use model and the transportation network growth model

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

No More Freeways: Urban Land Use-Transportation Dynamics without Freeway Capacity Expansion

Observations of the various limitations of freeway capacity expansion have led to a provocative planning and policy question – What if we completely stop building additional freeway capacity. From a theoretical perspective, as a freeway transportation network matures, there exists a saturation point beyond which any additional freeway capacity would only be counterproductive from a welfare point of view, and worsen the existing urban transportation problems. Traditional benefit/cost analysis of individual freeway capacity expansion projects often ignores long-term induced demand and land use changes and does not represent a systems approach to this important theoretical issue. From a practical perspective, a no-more-freeway policy can relieve transportation funds for other potentially more effective usages, such as improving urban arterial street system, improving transit level of service and coverage, implementing demand management and pricing strategies, and facilitating more efficient land use patterns (e.g. high density in-fill and transit-oriented developments). This research answers the following critical land use-transportation planning questions. Improved knowledge on these issues should benefit planers and decision-makers who pursue mobility and sustainability objectives and have the power to shape future cities. (1). Under what conditions will freeway capacity expansion become counterproductive to urban planning objectives (where is the saturation point)? (2). How will land use and transportation evolve under a “No-More-Freeway” policy? (3). What are the implications of such a policy on congestion, land use efficiency, transportation finance, and social welfare? (4). What is the impact of a less restrictive “No-More-Freeway” policy that only allows private-section freeway investments and relieves public-section freeway investments for other compelling transportation needs. The analysis in this project builds upon a modeling tool, ABSOLUTE, developed by the P.I. in previous research projects. ABSOLUTE is an Agent-Based Simulator Of Land Use-Transportation Evolution, which translates planning policies such as the “No-More- Freeway” policy into alternative urban growth paths and possibly urban growth equilibria (land use and transportation system equilibria). Due to the “Small Start” nature of this OTREC project, the analysis focuses primarily on stylized urban areas, and empirical analysis of the “No-More- Freeway” policy is only conducted for one policy scenario on the Twin Cities, MN, area

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c