Making Strides: State of the Practice of Pedestrian Forecasting in Regional Travel Models

Much has changed in the 30 years since non-motorized modes were first included in regional travel demand models. As interest in understanding behavioral influences on walking and policies requiring estimates of walking activity increase, it is important to consider how pedestrian travel is modeled at a regional level. This paper evaluates the state of the practice of modeling walk trips among the largest 48 metropolitan planning organizations (MPOs) and assesses changes made over the last 5 years. By reviewing model documentation and responses to a survey of MPO modelers, this paper summarizes current practices, describes six pedestrian modeling frameworks, and identifies trends. Three-quarters (75%) of large MPOs now model non-motorized travel, and over two-thirds (69%) of those MPOs distinguish walking from bicycling; these percentages are up from nearly two-thirds (63%) and one-half (47%), respectively, in 2012. This change corresponds with an increase in the deployment of activity-based models, which offer the opportunity to enhance pedestrian modeling techniques. The biggest barrier to more sophisticated models remains a lack of travel survey data on walking behavior, yet some MPOs are starting to overcome this challenge by oversampling potential active travelers. Decision-makers are becoming more interested in analyzing walking and using estimates of walking activity that are output from models for various planning applications. As the practice continues to mature, the near future will likely see smaller-scale measures of the pedestrian environment, more detailed zonal and network structures, and possibly even an operational model of pedestrian route choice

Linking land use and transportation : measuring the impact of neighborhood-scale spatial patterns on travel behavior

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2000.Includes bibliographical references (leaves 224-235).This dissertation aims to understand how changes in land use and transportation regulations at a local level could affect travel behavior such as trip-linking and mode choice. Studies indicate that the geographic distribution of jobs and population is far more crucial than population growth alone in creating dramatic changes in travel in individual locations. Land use initiatives represent a potentially effective tool for coping with the kinds of mobility patterns that North American cities face in the 1990s and in the coming century. As fine-grained data about land use and travel activity becomes available, it provides the opportunity to improve our understanding of the linkage between land use and transportation. Thus, we can now add a land use element to the models that have been used in the past in order to investigate travel behavior. We, therefore can extend, not only our knowledge of the land use/ transportation connection, but also the tools that have been used in the past to study their linkage. This study examines in detail the neighborhood characteristics that affect travel behavior. Neighborhood characteristics include land use, network and accessibility related characteristics which are quantified through the use of Geographical Information Systems (GIS). Ultimately, such measures could be used in conjunction with detailed surveys of travel behavior to specify, calibrate and use models of modal choice and trip type that are more sensitive to the fine-grain spatial structure of neighborhoods and transportation corridors in our metropolitan areas. Micro-level data for the Boston metro area, together with a 1991 activity survey of approximately 10,000 residents provide a rich empirical basis for experimenting with relevant neighborhood measures and for simulating the effects on travel behavior.by Sumeeta Srinivasan.Ph.D

Reducing travel by design: a micro analysis of new household location and the commute to work in Surrey.

Traffic volumes (and hence energy consumption) from the transport sector continue to rise, yet the potential fundamental role of urban planning in helping to reduce transport energy consumption remains to be poorly understood and hugely underplayed. Current urban planning practice, particularly in suburban areas, tends to increase traffic volumes by dispersing activities and hence facilitates private car travel rather than travel by public transport, walking or cycling. Public transport orientated development as an evolving practice tends to be focused very much on urban areas. This thesis seeks to understand the logic behind travel and suggests that urban planning can be applied more fully, at the strategic and local levels, to reduce energy consumption in car use (at least in the journey to work). The detailed analysis assesses the extent to which the design of the urban environment affects travel behaviour. The research hypothesis is that: "Journey to work travel behaviour generated by new residential development is dependent on a number of land use and socio-economic variables. The strength, significance and range of interaction vary spatially and over time." Within the analysis, the journey to work is used as the dependent variable, and is measured in terms of journey length and time, mode share and composite energy consumption. The independent variables considered include: Land use: resident population density, resident employment density, workplace population density, workplace employment density, resident population size, workplace population size, distance from urban centres and strategic transport networks, jobs-housing balance, resident classification (relative to the urban area), type of journey to work, neighbourhood streetscape design, public transport accessibility, and resident location (relative to the green belt). Socio-economic: household tenure, house type, house size, number of children, car availability, company car ownership, household income, house value, respondent sex, respondent age, marital status, occupation, qualification, attitude to travel, attitude to home and home location, reason for moving home and choosing new home location, relative levels of mobility, and dual income households. The methodological approach is to systematically examine the study hypothesis and a series of related research questions using data from the county of Surrey, UK. The empirical analysis is based on two new household occupier surveys carried out in 1998 and 2001, together with additional, complementary data taken from local authority datasets and the Census 2001. The thesis's particular originality is in providing: An examination of the complexity of the land use and transport interaction field, using energy consumption as the dependent variable and an estimation of the strength and significance of a wide range of land use and socio-economic variables - both previously researched and under researched variables A segmentation of respondents into different groups, such as stayers, inmovers and outmovers, showing the different manifestation of the land use and transport relationship for different groups within society A systematic tracking of the impact of time on the land use and transport relationship, with temporality and adaptation (including "co-location" effects) noted as critical features in travel behaviour, with the analysis controlling for potential attrition factors Analysis of a seldom-studied London fringe/suburban county such as Surrey - much previous work is concentrated on the city or other urban areas. The key findings and recommendations are that each land use, socio-economic and attitudinal variable, when considered on its own or even in small groupings, offers limited explanatory power in explaining travel behaviour. When a number of variables are brought together, including some variables not usually considered in the literature, the explanatory power of the modelling begins to work. Linear regression analysis shows that the land use and socio-economic variables, when considered together, explain 60% of the variation in energy consumption in 1998 and 54% in 2001 and for the stayers data only explain 65% of the variation in energy consumption in 1998 and 54% in 2001. Land use variables by themselves contribute approximately 10% of the variation in transport energy contribution hence a major part of the logic behind travel. In terms of temporal change from 1998-2001, although aggregate distance co-location might occur, aggregate energy consumption is likely to increase due to increased car dependency. Also, focusing on the aggregate trends also hides several detailed kurtosis effects: households located at higher densities, closer to major strategic centres, in areas with good public transport accessibility and strong jobs-housing balance are all likely to reduce their commuting travel distance. Other groups are likely to increase their composite transport energy consumption, for example, the higher income cohorts. Integration thus requires action across a wide range of fields. (Abstract shortened by UMI.)