Highlights Life stages associate with telework behavior in a complex way. Irrespective of gender and marital status, parents are less likely to telework compared to those without children. Regarding individuals without children, single individuals are more likely to telework than married ones, and males are more likely to telework than females. For individuals with children, the partnered parents are more likely to telework than the single parents, and females are more likely to telework than males.

Intermediate modes of transport, such as shared vehicles or ride sharing, are starting to increase their market share at the expense of traditional modes of car, public transport, and taxi. In the advent of autonomous vehicles, single occupancy shared vehicles are expected to substitute at least in part private conventional vehicle trips. The objective of this paper is to estimate the impact of shared autonomous vehicles on average trip duration and vehicle-km traveled in a large metropolitan area. A stated preference online survey was designed to gather data on the willingness to use shared autonomous vehicles. Then, commute trips and home-based other trips were generated microscopically for a synthetic population in the greater Munich metropolitan area. Individuals who traveled by auto were selected to switch from a conventional vehicle to a shared autonomous vehicle subject to their willingness to use them. The effect of shared autonomous vehicles on urban mobility was assessed through traffic simulations in MATSim with a varying autonomous taxi fleet size. The results indicated that the total traveled distance increased by up to 8% after autonomous fleets were introduced. Current travel demand can still be satisfied with an acceptable waiting time when 10 conventional vehicles are replaced with 4 shared autonomous vehicles.

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In this paper, the required models and methods to analyze and quantify the potential demand for urban air mobility (UAM) complementing public transport and possible impacts were defined and applied to the Munich Metropolitan region. An existing agent-based transport model of the study area were used and extended to cover socio-demographic changes up to the year 2030 and intermodal UAM services. An incremental logit model for UAM was derived to simulate demand for this new mode. An airport access model was developed as well. Three different UAM networks with different numbers of vertiports were defined. Sensitivity studies of ticket fare and structure, flying vehicle cruise speed, passenger process times at vertiports and different Urban Air Mobility networks sizes were performed. For the reference case, UAM accounts for a modal share of 0.5%. The absolute UAM demand is concentrated on very short routes; hence, UAM vehicle flight speed variation shows low UAM demand impacts. Kilometer-based fare, number of UAM vehicles per vertiport and passenger process times at vertiports show a significant impact on UAM demand.

Traditionally, integrated land-use/transportation models intend to represent all opportunities of travel and household location, maximize utilities and find an equilibrium in which no person or household could improve their satisfaction any further. Energy scarcity, higher transportation costs, and an increasing share of low-income households, on the other hand, demand special attention to represent constraints that households face, rather than opportunities for utility maximization. The integrated land-use model SILO explicitly represents various constraints, including the price of a dwelling, the travel time to work, and the monetary transportation budget. SILO ensures that no household makes choices that violate these constraints. Implementing such constraints helps SILO to generate more realistic results under scenarios that put current conditions under a stress test, such as a serious increase in transportation costs or severely increased congestion.

The project ILUMASS (Integrated Land-Use Modelling and Transportation System Simulation) aims at embedding a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating changes of land use, the resulting changes in transport demand, and the impacts of transport on the environment. The land-use component of ILUMASS will be based on the land-use parts of an existing urban simulation model, but is to be microscopic like the transport parts of ILUMASS. Microsimulation modules will include models of demographic development, household formation, firm lifecycles, residential and non-residential construction, labour mobility on the regional labour market and household mobility on the regional housing market. These modules will be closely linked with the models of daily activity patterns and travel and goods movements modelled in the transport parts of ILUMASS developed by other partners of the project team. The design of the land-use model takes into account that the collection of individual micro data (i.e. data which because of their micro location can be associated with individual buildings or small groups of buildings) or the retrieval of individual micro data from administrative registers for planning purposes is neither possible nor, for privacy reasons, desirable. The land-use model therefore works with synthetic micro data which can be retrieved from generally accessible aggregate data.

With the ongoing debates from Florida to California and throughout the country concerning the benefits of high-speed rail, there is a renewed interest in intercity mode choice modeling. The investments for improving long-distance travel are substantial and may have serious impacts on travel demand, the environment and the economy. As such, alternatives for improving longdistance travel require careful evaluation before decisions are made on the form and design of long-distance travel infrastructure. A new nested multinomial logit mode-choice model has been developed that is sensitive to travel costs, distance, transit station accessibility, service frequency, number of transfers and parking costs. On the auto side the model considers the modes drive-alone and shared-ride with 2, 3 and 4 or more passengers. The transit side models regional bus, rail and air as modal options. To explore the model sensitivities, scenarios on increased gasoline prices and improved bus service are described. After a short introduction, the state-of-the-art of mode choice modeling is reviewed. 44 Section 3 explains how total travel demand is generated, and section 4 describes the mode choice model developed in this paper. Section 5 describes the application to the North Carolina Statewide Transportation Model (NCSTM) and section 6 shows the scenario application. The paper ends with conclusions and future1. INTRODUCTION In the last few years, a new interest in mode choice analysis has risen due to the controversy regarding the implementation of high-speed rail in different parts of the U.S. Analysis tools, however, have not caught up with this new demand in transportation modeling. The vast majority of mode choice models developed over the last few decades have been implemented for urban models with a focus on short-distance travel, where modal availability is different from longdistance travel. The travel behavior in long-distance travel is quite different, too, as people tend to be more familiar with modal options for short-distance travel than for long-distance travel. In addition, the composition of travelers differs. While short-distance use of transit is dominated by commuters, long-distance transit modes (particularly rail and air) are heavily used for pleasure trips as well as by business travelers. Given the fact that long-distance travelers tend to stay longer at their destination, travel time tends to be a less dominant factor in mode choice than in short-distance travel. Investments for improving long-distance travel often are tremendous. Adding a lane to an existing highway or even building a new highway may cost millions of dollars, just as adding a new rail line or improving the speed on an existing rail line may be cost-intensive. Environmental impacts may be serious, as increased auto traffic or air travel may increase gaseous emissions and noise levels substantially. Finally, the economic impact may be significant as well. According to Krugman [1], more accessible regions are ceteris paribus economically more successfu...

Abstract:In this paper, we develop a synthetic population as the first step in implementing an integrated land use/transport model. The model is agent-based, where every household, person, dwelling, and job is treated as an individual object. Therefore, detailed socioeconomic and demographic attributes are required to support the model. The Iterative Proportional Updating (IPU) procedure is selected for the optimization phase. The original IPU algorithm has been improved to handle three geographical resolutions simultaneously with very little computational time. For the allocation phase, we use Monte Carlo sampling. We applied our approach to the greater Munich metropolitan area. Based on the available data in the control totals and microdata, we selected 47 attributes at the municipality level, 13 attributes at the county level, and 14 additional attributes at the borough level for the city of Munich. Attributes are aggregated at the household, dwelling, and person level. The algorithm is able to synthesize 4.5 million persons in 2.1 million households in less than 1.5 h. Directions regarding how to handle multiple geographical resolutions and how to balance the amount and order of attributes to avoid overfitting are presented.