Using recent results in mathematics, I point out that free energies and scale-dependent central charges away from criticality can be represented in compact form where modular invariance is manifest. The main example is the near-critical Ising model on a thermal torus, but the methods are not restricted to modular symmetry, and apply to automorphic symmetries more generally. One application is finite-size effects.

We present a novel metric for measuring relative connection between parts of a city using geotagged Twitter data as a proxy for co-occurrence of city residents. We find that socioeconomic similarity is a significant predictor of this connectivity metric, which we call "linkage strength": neighborhoods that are similar to one another in terms of residents' median income, education level, and (to a lesser extent) immigration history are more strongly connected in terms of the of people who spend time there, indicating some level of homophily in the way that individuals choose to move throughout a city's districts.

This paper presents a dynamic discrete choice model (DDCM) for daily activity-travel planning. A daily activity-travel pattern is constructed from a sequence of decisions of when, where, why, and how to travel. Individuals' preferences for activity-travel patterns are described by the sum of the utility of all travel and activity episodes in that pattern, but components of the utility functions, such as travel times, may be stochastic. In each decision stage, individuals act as if they maximized the expected utility of the remainder of the day. The DDCM-model presented allows for a detailed treatment of timing decision consistent with other choice dimensions, respects time-space constraints, and enables the inclusion of explicitly modeled uncertainties in, for example, travel time. In a case study, a model for daily planning of activity and travel on workdays is estimated whereby individuals can perform any number of trips that each is a combination of one of 1,240 locations, four modes, and six activities. Simulation results indicate that the model within sample accurately replicates timing decisions, trip lengths, and the distributions of the number of trips, tours, and trips per tour.

Assessing and predicting car type choices are important for policy analysis. Car type choice models are often based on aggregate alternatives. This is due to the fact that analysts typically do not observe choices at the detailed level that they are made. In this paper, we use registry data of all new car purchases in Sweden for two years where cars are observed by their brand, model and fuel type. However, the choices are made at a more detailed level. Hence, an aggregate (observed) alternative can correspond to several disaggregate (detailed) alternatives. We present an extensive empirical study analyzing estimation results, in-sample and out-of-sample fit as well as prediction performance of five model specifications. These models use different aggregation methods from the literature. We propose a specification of a two-level nested logit model that captures correlation between aggregate and disaggregate alternatives. The nest specific scale parameters are defined as parameterized exponential functions to keep the number of parameters reasonable. The results show that the in-sample and out-of-sample fit as well as the prediction performance differ. The best model accounts for the heterogeneity over disaggregate alternatives as well as the correlation between both disaggregate and aggregate alternatives. It outperforms the commonly used aggregation method of simply including a size measure.

It has been reported that platooning has the potential of saving fuel and increasing traffic throughput. We formulate a platoon coordination problem with soft time windows as a mixed-integer linear programming problem and solve it with exact solutions. The objective function consists of operation costs, schedule miss penalties and fuel costs. In the numerical example, a Swedish highway network model is used and the computation result shows that, for 21 vehicles, the total cost can be reduced by 3.5% when the optimal preferred arrival times are chosen. A random disturbance is then added to the optimal time windows and the optimal result shows great sensitivity with respect to the disturbance. When the mean of the disturbance becomes larger than 10 minutes, more than half of the platooning benefits will be lost. The study also analyzes the change of different cost compositions as disturbance increases.

The transport systems need improvement. Obvious problems are pollution and otheradverse environmental effects, congestion in the road network and partly also in therail network and in public transport. Moreover, system vulnerability to disturbances,i.e. system resilience is a growing issue of concern. In the EU as well as in Swedenthere is an outspoken interest for what potential opportunities the waterways mightoffer for improving the transport system. An often expressed solution is simply toshift cargo from the roads to the rail and seaborne modes of transport. The presentstudy addresses feasibility and assessment of such solutions. Initially it is illustratedhow the Swedish inland waterways could be used for regional freight transport.Values are identified that potentially can be realised into a benefit. For instance;increased accessibility, improved land use in urban areas, reduced load on road andrail networks, increased transport redundancy and decreased vulnerability, increasedsystem flexibility, energy efficiency and low noise. It also comes clear that nitrogenoxides and particle emissions from ships must decrease. Technological issues relatedto winter navigation and environment risk assessment need attention as do thedevelopment of the interface to road and rail modes of transport e.g. means ofreloading and the accessibility to quays and docks.The study shows on a well-developed framework for modelling logistics andperforming cost-benefit-analysis (CBA) although also showing great uncertaintiesand modelling weaknesses of aspects related to inland and urban waterways. I alsocome clear that assessment analysis focuses on effects from infrastructureinvestments and lack tools and methodology to assess the influence from measuresto lessen transport work, e.g. by short cuts, or to optimise the existing system, e.g.by regulatory incitements to modal shift.Finally, development opportunities are brought forward. It concerns improvementsin technology, operation and infrastructure, but also in logistic models and CBAtools, providing urban planners and the transport buyer with high quality decisionsupport.

When people state their willingness to pay for something, the amount usually differs from the behavior in a real purchase situation. The discrepancy between a hypothetical answer and the real act is called hypothetical bias. We investigated neural processes of hypothetical bias regarding monetary donations to public goods using fMRI with the hypothesis that amygdala codes for real costs. Real decisions activated amygdala more than hypothetical decisions. This was observed for both accepted and rejected proposals. The more the subjects accepted real donation proposals the greater was the activity in rostral anterior cingulate cortex-a region known to control amygdala but also neural processing of the cost-benefit difference. The presentation of a charitable donation goal evoked an insula activity that predicted the later decision to donate. In conclusion, we have identified the neural mechanisms underlying real donation behavior, compatible with theories on hypothetical bias. Our findings imply that the emotional system has an important role in real decision making as it signals what kind of immediate cost and reward an outcome is associated with.

Data sources using new technology such as the Geographical Positioning System are increasingly available. In many different applications, it is important to predict the average speed on all the links in a network. The purpose of this study is to estimate the link speed in a network using sparse GPS data set. Average speed is consistently estimated using Indirect Inference approach. in the end, the Monte Carlo evidence is provided to show that the results are consistent with parameter estimates.