Long-term transportation planning for larger regions must assess synergies and interference among sets of projects. The objective is the maximization of the overall benefit within specific budget restrictions by finding the most favorable bundle of projects, that is, solving the network design problem. For large numbers of projects, complete enumeration of all combinations is not feasible for detailed networks. The ant colony heuristic is suitable for this kind of problem. According to our knowledge, this article presents the abovementioned heuristic's first application to a realistically sized network. A detailed multimodal network assignment of a substantial Swiss city provides the basis for calculations. First, each infrastructure project is assessed using a cost-benefit analysis. The ant colony heuristic is then successfully executed and the bundles are evaluated. The article provides new insights into applications of the heuristic in large networks and focuses on problematic calibration details as well as the choice of objective function. Suggestions are made for general applications and further research.

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Shape grammars for urban design have attracted much interest in research and practice. Transport and urban planners increasingly deploy shape grammars, especially in simulations and procedural models. Shape grammars have multiple advantages due to their interdisciplinary and straightforward approach and low computational requirements. In addition, a rulebased design method and underlying fundamental research knowledge can potentially support future planning and design guidelines for handbooks and norms. However, little is known about the effectiveness of shape grammars in transport networks and urban environments. e proposed methodology aims at a future development of a robust and effective language for sustainable urban development. e theory of different fields is consolidated for a general grammar definition. Grammars require specified and corresponding objectives and application specifications for enhanced implementation. e proposed methodology for grammar rule assessment is based on elasticities to gain more insights in the effect of the rules. Elasticities allow comprehensive comparisons and verification between grammar rules. e paper reviews and highlights the key achievements and applications of shape grammars in cognate fields of science. Terminology sheds light on the definitions of most relevant terms including a general definition for grammar rules embedded in the language context. e paper differentiates methodological approaches in grammar design assessment and emphasizes a standardized approach for shape grammar definitions. e paper concludes with a detailed example for grammar rule assessment and potential future research.

Grammars, with their generic approach and broad application potential in many planning fields, are accepted as adaptable and efficient tools for design and planning applications, bridging design rules and technical planning requirements. This paper provides a formal introduction of grammars for effective consolidation and application, including a rule-based notation and required specification information. Two proposed grammar evaluation methods -based on technical planning knowledge and using recent computational development -foster understanding of a grammar's effects, often missing in other definitions. Knowledge gained enables efficient grammar rule application, e.g. in burgeoning planning software. This research focuses particularly on urban network design and road intersection grammars to validate proposed grammar evaluation methods. Results are specified in the proposed grammar notation with corresponding application specifications. Results generally show that network topology and intersection type choice both depend on transport mode characteristics and flow. Specifically, medium-dense gridiron networks are car-efficient in terms of travel costs and reliability at urban densities, when combined with high road and intersection capacities. Pedestrian networks ideally have higher intersection and road densities with lower capacities than car networks. Highly meshed networks improve overall travel cost efficiencies for all transport modes at various flow levels.

Destination choice models can be embedded in transport and land use models to understand travel and location choice behavior and to forecast scenarios. Utility-maximizing destination choice models can account for individual behavior and make them suitable for agent-based models, while processing destination capacities is also in line with agent-based modeling. This paper addresses the possibility and impact of introducing capacity constraints, their effect on choice behavior, and the feasibility of applying an approach like this in agent-based microsimulations with individual characteristics for each agent. Here, a comprehensive workplace choice model and its application in a large-scale simulation case study for Singapore are described; one technical and one methodological achievement are highlighted. Technical achievement benefits from recent computational advances; the workplace choice model is estimated with a comprehensive utility function on a large data set with 103 destinations. Reasonable model fit and robust parameters are achieved while obviating sampling techniques; resulting parameters are efficiently applied to the entire 5.4 million Singapore population and validated with survey data. For methodological innovation, capacity limitations are introduced at workplaces to avoid oversaturation. A robust optimization method based on shadow prices is proposed to accommodate capacity limitations at all workplaces during the choice model application defined above. The proposed method efficiently assigns commuters to unused workplaces while respecting individual commuter preferences. Validation of the simulation results, by comparing travel time distributions for commuting trips reported in travel diary data, shows that the model fits well with observed data.