Environment and Planning B: Urban Analytics and City Science

Short-term traffic forecasting is playing an increasing role in modern transport management. Although many short-term traffic forecasting methods have been explored, the spatiotemporal dependency of traffic flow, an important characteristic of traffic dynamics that can benefit the forecasting of traffic changes, is often neglected in short-term traffic forecasting. This paper first investigates the spatiotemporal dependency of traffic flow using cross-correlation analysis and then discusses its implications in terms of traffic forecastability and real-time data effectiveness. This can help us to understand traffic flow, and hence improve the performance of forecasting models.

This paper presents an informal shape grammar that describes Louis Sullivan's system for ornamentation. The goal of the grammar is to serve as an analytical tool to describe Sullivan's existing designs, but also to generate new designs founded in the same logic. Towards this end, the grammar, which is organized into seven groups of rules, is used to generate several of Sullivan's compositions, as well as new designs by the author, as a vehicle both to explore the particular parameters of Sullivan's most intricate work, and to speculate about how Sullivan's system could be implemented in, and impacted by, contemporary technologies.

On the basis of the presumption that the effects of plans for urban development are influenced highly by the decision mechanisms under which plans function, we compare deductively four interactive strategies derived from three regimes of policies, namely, fixed, emergent, and no policies, based on the two-person iterated prisoner's dilemma game. The four strategies under consideration are tit for tat (TFT), always defect (AD), always cooperate (AC), and random actions (RA). The results show that TFT is the best strategy followed by RA, AC, and AD. The implications are that policies that take into account contingencies yield higher expected payoffs than those that do not, and that emergent policies are more effective than either fixed or no policies. The model provides an analytical approach to the issue of evaluating the potential effects of the plans.

This paper introduces a new method, known as small-graph matching, and demonstrates how it may be used to determine the genotype signature of a sample of buildings. First, the origins of the method and its relationship to other ‘similarity’ testing techniques are discussed. Then the range of possible actions and transformations are established through the creation of a set of rules. The next section of the paper suggests which real-world actions would be represented by such transformations, were the graph representing a building. By considering the real-world equivalent actions, as opposed to transformations at the level of the graph abstraction, a system of costs or weightings is developed and subsequently applied to the range of possible actions. Next, in order to fully explain this method, a technique of normalizing the similarity measure is presented in order to permit the comparison of graphs of differing magnitude. The last stage of this method is presented, this being the comparison of all possible graph pairs within a given sample and the mean distance calculated for all individual graphs. This results in the identification of a genotype signature. Finally, the paper presents an empirical application of this method and shows how effective it is, not only for the identification of a building genotype, but also for assessing the homogeneity of a sample or subsamples.

Accessibility analysis usually requires finding the closest facility within a certain category—for example, the nearest hotel, hospital, or gas station. Along with the development of location-based services, users also wish to find the optimal route to the closest facility, based on network distance. Furthermore, the best route should be adjusted in a dynamic traffic environment. Most traditional methods solve the nearest-neighbor (facility) problem using Euclidian distance or network distance without consideration of dynamic traffic conditions. In this paper we propose a novel incremental parallel Dijkstra's algorithm, IP-Dijkstra, to construct and maintain a dynamic network Voronoi diagram for time-dependent traffic networks. The experimental results demonstrate that the proposed IP-Dijkstra's algorithm considerably outperforms the traditional methods, which recompute the shortest path from scratch without utilization of the previous search results. Consequently, this algorithm is capable of accommodating a large number of mobile clients in search of their respective nearest facilities and the routes to reach such facilities in a dynamic traffic environment, thereby facilitating real-time accessibility analysis.

The property rights approach to urban development has recently been proposed in the planning literature to explain how urban systems self-organize spatially and institutionally. The land-tenure system is one of the key factors affecting land use and thus urban development. It is not clear, however, how such a factor affects the process of urban development. This research aims to provide reasonable explanations as to how the land-tenure system in China in general affects urban development, by building game-theoretic models which include plans as a manifestation of information and property rights as a manifestation of land-use rights. Viewing regulated development as a collective good, the model is based on the prisoner's dilemma game, where the local government regulates and the developer makes development decisions. Preliminary results show that land rights in the transitional economy of China are of paramount importance and must be clearly specified in order to make the land development process efficient at reducing transaction costs.

The mathematical model of urban dynamics introduced in an earlier paper is applied to a case study in a small region in the southern part of Switzerland. The model mixes the point of view of cellular automata (cellular decomposition of the space, neighbourhood relations among cells, dynamics based on local evolution rules) with the approach to multiagent systems: the dynamics of the urban system are described in terms of decision processes of agents formalized using fuzzy-decision-theory methods. The region chosen for the case study evolves under the pressure of the nearby city of Lugano, owing to several factors: the accessibility of the area from Lugano, the availability of spatial resources for new development, the high level of quality of space, and the high level of congestion of Lugano. Local changes in the master plan from agricultural to residential use are taken into account, by introducing suitable memory variables that keep track of the demand of spatial resources for building in the recent past. Computer simulations showing the time evolution of the spatial distribution of the population and the real estate value are presented. The use of measures of attractiveness based on a fuzzy logic approach, and of Poisson-distributed events, enables us to introduce new effective approaches to parameter calibration and model validation.

We introduce two measures of connectivity that are applicable to standard GIS-based representations of street networks. The reach of a point measures the total street length covered by all paths extending out from that point that are no longer than a given threshold value. The directional distance of a street network from a point is measured according to the minimum number of direction changes required to reach any part of the network from that point, consistent with typical measures used in space syntax. However, our measure of directional distance requires no prior commitment as to the relational elements that make up the network. Any part of the network which is accessible from a point without a change of direction greater than a given threshold angle is treated as a single directional element for the purposes of computation. Street segments are characterized by the reach and directional distance of their midpoints. Networks are characterized by the average directional distance of the corresponding street segments. The measures render explicit the interplay between metric and topological properties of networks. Preliminary studies show that the measures discriminate well between different morphologies of street networks. When used to compare urban morphologies they are well correlated with standard measures used in the literature, with the added advantage that they can discriminate between street segments within the same urban area. Using field observations we also show that the measures can be used to model the effect of spatial configuration upon movement in ways which compare favorably to standard space syntax.

As the global population becomes increasingly urbanised, so interest has grown in the potential climate change impacts on city infrastructure, services, and environmental quality. However, urban areas are only beginning to be represented explicitly in the land-surface schemes of dynamical climate models through modified energy and moisture budgets. This paper summarises recent evidence of urban impacts on climate and vice versa. The technique of statistical downscaling is then introduced through exemplar studies of London's future urban heat island and peak ozone concentrations. Projections of both indices are derived from atmospheric variables supplied by four general circulation models, driven by a medium-high (A2) emissions scenario for the 2050s. The results show further intensification of the nocturnal heat island and higher ozone concentrations that are most pronounced in summer. These changes reflect sensitivity to variations in regional climate alone, so omit other factors such as changes in land use, emissions, climate feedbacks, or synergies between air quality and heat islands. Nonetheless, the downscaled scenarios are consistent with an emerging picture of increasing risks to human health in urban areas unless appropriate adaptation measures are taken.

The aim of this paper is to offer a contribution to the study of the relationship between the physical elements of a sidewalk and people's perception of it by applying the rough sets approach. In previous studies in this context statistical methods such as variance analysis and regression analysis are the most used techniques, and these suffer from the limitations of large sample sizes and rigorous statistical assumptions. However, the rough sets approach, as a nonparametric method of artificial intelligence, can handle this problem. In this study, twenty civil-engineering students and twenty noncivil-engineering students took part in an image preference survey assessing photographs of sidewalks. Then the rough sets approach was conducted by a four-step procedure to analyze the survey results. Finally, the output of the rough sets approach is used to express people's perception of good and bad features of sidewalk space. The results will hopefully help planners to make effective decisions about sidewalk features.

Automated or semiautomated surveillance monitoring involves movement tracking and sensor handoff. In order to track moving objects over a large area, sensor coverage needs to overlap significantly. Overlapping coverage can be modeled using the concept of backup coverage, a location modeling approach that seeks to maximize primary and backup coverage simultaneously. This kind of sensor placement problem belongs to the class of NP-hard combinatorial optimization problems, so computational difficulty is expected when solving large problem instances, not to mention the need for dealing with multiple objectives. Beyond this, backup coverage for supporting sensor placement actually brings about confounding problem instances for branch-and-bound approaches because of the trade-off between primary and backup coverage. To address these difficulties, this paper develops a multiobjective evolutionary algorithm for the backup coverage problem to support sensor placement. The solutions of this algorithm are evaluated in terms of computational requirements and solution quality.