Hierarchical IPF: Generating a synthetic population for Switzerland

Agent-based microsimulation models for land use or transportation simulate the behavior of agents over time, although at different time scales and with different goals. For both kinds of models, the initial step is the definition of agents and their relationships. Synthesizing the population of agents often is the only solution, due to privacy and cost constraints. In this paper, we assume that the model simulates persons grouped into households, and a person/household population needs to be synthesized. However, the methodology presented here can be applied to other kinds of agent relationships as well, e.g. persons and jobs/workplaces or persons and activity chains. Generating a synthetic population requires (a) reweighting of an initial population, taken from census or other survey data, with respect to current constraints, and (b) choosing the households that belong to the generated population. The reweighting task can be performed using an Iterative Proportional Fitting (IPF) procedure; however, IPF cannot control for attributes at both person and household levels. A frequently applied pattern is to estimate household-level weights using IPF, so that they match the control totals for the households, and then, using these weights, to generate a population of households that best fits the person-level control totals. We propose an algorithm that estimates household-level weights that fit the control totals at both person and household levels. This eliminates the need to account for person-level control during the generation of synthetic households. The algorithm essentially performs a proportional fitting in the domains of both households and persons, and introduces an entropy-minimizing fitting step to switch between these two domains. We evaluate the performance of our algorithm by generating a synthetic population for Switzerland and checking it against the complete Swiss census.

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme --- a simple, but universal strategy requiring only local information --- and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.Comment: 4 figure

Surveying energy efficiency in housing and transport using a Priority Evaluator

This paper presents a survey combining a stated choice experiment and a priority evaluator. The survey addresses ways that people would invest in energy efficiency and differences between energy efficiency in housing and private transport. The survey sample consists of 500 homeowners (owner occupiers) owning at least one car and is divided in two parts: a paper and pen questionnaire with Stated Preference experiments followed by an Internet-based Priority Evaluator. Both choice experiments are personalized to present the candidates with meaningful choice sets. In the stated preference experiments, respondents are asked to choose between four alternatives as a reaction to hypothetically increasing fuel prices: insulating the house, buying a heat pump, buying a new, more efficient car and selling the car and switching to public transport. In the second part of the survey, the Priority Evaluator, respondents interactively optimize their CO2 output in an Internet application, selecting among long-term investments as well as short-term measures. Data collected in the survey will be processed using statistical models, such as multinomial logit models, to derive parameters for different efficiency measures used to predict long-term investment behavior of homeowners

Size Matters: The Use and Misuse of Statistical Significance in Discrete Choice Models in the Transportation Academic Literature

In this paper we review the academic transportation literature published between 2014 and 2018 to evaluate where the field stands regarding the use and misuse of statistical significance in empirical analysis, with a focus on discrete choice models. Our results show that 39% of studies explained model results exclusively based on the sign of the coefficient, 67% of studies did not distinguish statistical significance from economic, policy or scientific significance in their conclusions, and none of the reviewed studies considered the statistical power of the tests. Based on these results we put forth a set of recommendations aimed at shifting the focus away from statistical significance towards proper and comprehensive assessment of effect magnitudes and other policy relevant quantities.Comment: 14 pages, 1 table, 0 figure

Searching for the Rail Bonus

The inherent superiority of rail-based public transport options over bus-based alternatives, all other things being equal, has been stipulated in the literature and in the public policy discussion for some time. The exact strength of any such rail bonus is important to a public transport operator which has to consider the replacement of rail-based services by bus services. The public transport operator of the city of Dresden (DVB), while generally upgrading its services, has to consider this option, in particular where the continuing tram operation would require a costly rehabilitation of the tracks. The measurement of any such systematic preference for rail-based modes is difficult, as is requires either a before-and-after study of such a switch, controlled for the other relevant service attributes, e.g. frequency, speed, reliability, price, route, etc., or a study of a network, in which rail- and road-based modes offer comparable types of services, with bus services inparticular not restricted to feeder services to rail/tram lines. Both are rare for obvious reasons. A recent service change of the DVB offered the opportunity to look at the issue in detail. A series of surveys were undertaken for this purpose before and after: A one-day travel diary (including a household questionnaire)  A survey of the image of the services A between-mode stated preference exercise focusing on the choice between public transport and private motorised transport where public transport was provided by either bus or tram (7 choice situations) A within-mode stated preference exercise looking at the trade-offs between public transport modes, in particular levels of comfort, travel times and transfers (7 choice situations). The paper reports detailed results from this study addressing the differences in preferences between the waves (effects of familiarity with an alternative) from both separate and joint stated preference and stated preference/revealed preference models. The modelling so far indicates a consistent, but weak preference for the rail option through a higher value-of-time for rail usage, higher valuation of new rail vehicles in comparison to new busses, although they are partially balanced by a higher transfer penalty. &nbsp

Long distance mode choice and distributions of values of travel time savings in three European countries

The study presented in this paper uses Stated Preferences (SP) data on mode choice collected as part of a recent survey on long distance travel u n dertaken in three European countries. The purpose of this article is twofold. It aims at exploring the impacts of the choic e of mixing probability distri butions while accounting for unobserved taste heter ogeneity and it aims at focusing on the derived estimation of the distribu tions of values of travel time savings (VTTS). We compare eleven distributions, each having particular properties in terms of domain, location, scale, and shape. Due to the repetiti ve nature of the SP experiments, we estimate mixtures of Multinomial Logit (MNL) models for panel data. The results show that the mixing distributions differ from one country to another, suggesting existence of European disparities as it regards long - dista nce mode choice. The results also show that long - distance travellers pay a lot more attention to access and egress travel times to and from the main mode than to total travel time with the main mode