An Overview of PIMMS (A Pricing and Investment Model for Multi-Modal Systems): An Areawide Urban Transport Policy Evaluation Model

The resurgence of interest in building better cities provides an opportunity to develop improved land use-transport models; models which are responsive to a wide variety of planning options, in contrast to current urban transport models which are only suitable for evaluating a limited number of major infrastructure options. A wide set of policy tools includes new infrastructure such as private tolled roads, light rail, bus priority systems; travel demand management through road pricing, area licensing and banning of cars in particular locations; and land use incentives/disincentives such as zoning for higher density activity, and more stringent environmental standards. To be responsive to a wide range of policy choices, it is desirable to develop models with a strong foundation in individual behaviour. This paper presents an overview of a project funded by the Australian Research Council. The aim is to develop a computer-based forecasting tool to give planners more flexibility in evaluating strategies designed to improve the performance of cities

Understanding temporal rhythms and travel behaviour at destinations: Potential ways to achieve more sustainable travel

This paper analyses the roles played by time in destination-based travel behaviour. It contrasts clock time's linear view of time with fragmented time, instantaneous time, fluid time and flow, time out and the multiple temporalities of tourism experiences. It explores temporal issues in a destination travel context, using qualitative techniques. Data were captured using diary photography, diary-interview method with tourists at a rural destination; their spatial and temporal patterns were captured using a purpose built smartphone app. The analysis revealed three temporal themes influencing travel behaviour: time fluidity; daily and place-related rhythms; and control of time. Three key messages emerge for future sustainable tourist destination-based travel systems. Given the strong desire for temporal fluidity, transport systems should evolve beyond clock-time regimes. Second, temporal forces favour personal modes of transport (car, walk, cycle), especially in rural areas where public transport cannot offer flexibility. Third, the car is personalised and perceived to optimise travel fluidity and speed, but is currently unsustainable. Imaginative initiatives, using new mobile media technology can offer new positive and proactive car travel, utilising spare public and private vehicle capacity. Research is needed to implement mechanisms for individualised space-time scheduling and collective vehicle use strategies. © 2013 Copyright Taylor and Francis Group, LLC

The Mobility and Accessibility Expectations of Seniors in an Aging Population

Populations of post-industrial nations are aging. With a growing number of people living well into their 80’s and maintaining active lives, the transportation system will have to start focussing more closely on understanding their mobility and accessibilty needs, so as to ensure that specific requirements of this large segment are not being ignored through the promotion of traditional ‘solutions’ and historical assumptions. This paper takes a close look at the evidence on the mobility needs and travel patterns of individuals over 64, distinguishing between the “young” elderly (aged 65 to 75 years) and the “old” elderly (over 75 years). This distinction is particularly useful in recognising the threshold of health change that impacts in a non-marginal way on mobility needs. This distinction also focuses transport planning and policy on a commitment to understanding the different needs of these subgroups of the population, identifying services and facilities that better cater for these groups. We review the evidence, in particular, on the mobility characteristics of the over 75 years age group, including how they secure support through migration and settlement patterns. We use the empirical evidence from a number of western nations to identify the role of conventional and specialised public transport as an alternative to the automobile in meeting mobility and accessibility needs

The Rational Locator: Why Travel Times Have Remained Stable

This paper evaluates household travel surveys for the Washington metropolitan region conducted in 1968 and 1988, and shows that commuting times remain stable or decline over the twenty year period despite an increase in average travel distance, after controlling for trip purpose and mode of travel. The average automobile work-to-home time of 32.5 minutes in both 1968 and 1988 is, moreover, very consistent with a 1957 survey showing an average time of 33.5 minutes in metropolitan Washington. Average trip speeds increased by more than 20 percent, countering the effect of increased travel distance. This change was observed during a period of rapid suburban growth in the region. With the changing distributional composition of trip origins and destinations, overall travel times have remained relatively constant. The hypothesis that jobs and housing mutually co-locate to optimize travel times is lent further support by these data. .

Trip Chaining as a Barrier to the Propensity to use Public Transport

Trip chaining is a growing phenomenon in travel and activity behaviour. Individuals increasingly seek out opportunities to minimise the amount of travel required as part of activity fulfilment, given the competing demands on time budgets and their valuation of travel time savings. This search for ways of fulfilling (more) activities with less travel input has produced a number of responses, one of which is trip chaining. A particularly important policy implication of trip chaining is the potential barrier it creates in attracting car users to switch to public transport. This paper seeks to improve our understanding of trip chaining as a barrier to public transport use. A series of discrete choice models are estimated to identify the role that socioeconomic and demographic characteristics of households have on the propensity to undertake trip chains of varying degrees of simplicity/complexity that involve use of the car or public transport with an embedded commuting or non-commuting primary purpose. Multinomial logit, nested logit and random parameter logit models are developed and contrasted to establish the gains in relaxing the strict conditions of the multinomial logit model

A Planning Template for Nonwork Travel and Transit Oriented Development, MTI Report 01-12

The Mineta Transportation Institute (MTI) at San José State University assigned a project team to design a planning template for transit-oriented development (TOD) that incorporates an understanding of nonwork travel, that is, trips for shopping, eating out, and engaging in recreational and cultural activities. Nonwork trips are growing in signifigance and now account for four of every five trips. At the same time, TOD has become a popular planning response to the impacts of metropolitan growth. Some planners believe that TOD will induce more pedestrian and transit trips and will reduce the average length and frequency of household auto travel. This effect is assumed to result from improved accessibility to employment and nonwork venues located in compact, mixed-use centers. Planning professionals in many MPOs also suggest that if multiple centers are linked by high quality transit, such as light or heavy rail, access is enabled to the broad range of nonwork activities. The project arrived at these essential findings: (1) Venues for nonwork activities are very numerous and geographically dispersed. 2) The spatial environment for nonwork activities is the result of growing prosperity, technical innovation, and a dynamic, competitive marketplace. (3) The consumer marketplace will provide many more places to go than mass transit can cost-effectively serve. (4) Current metropolitan planning methods and modeling tools focus on the work trip and do not adequately account for the complexity of nonwork trips and their linkage to work trips. These findings support the need for a new regional planning process to complement current methods. One recommended approach is that metropolitan communities establish a Nonwork Travel Improvement Planning Process using a multidisciplinary expert advisory group interacting with a core, Internet-enabled, professional transportation planning staff. An iterative interaction across varied but relevant skill sets could be achieved through a Backcasting Delphi process. The focus of the interaction would be on understanding the ramifications of consumer and retail industry behavior for TOD and other new transportation strategies, and then assessing the available strategies for cost-effectiveness in reducing the impacts of growth and automobility in a complex and uncertain metropolitan market

A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

Road transport accounted for 20% of global total greenhouse gas emissions in 2020, of which 30% come from road freight transport (RFT). Modeling the modern challenges in RFT requires the integration of different freight modeling improvements in, e.g., traffic, demand, and energy modeling. Recent developments in \u27Big Data\u27 (i.e., vast quantities of structured and unstructured data) can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes the state of the art in analyzing Big Data sources concerning RFT by identifying key challenges and the current knowledge gaps. Various challenges, including organizational, privacy, technical expertise, and legal challenges, hinder the access and utilization of Big Data for RFT applications. We note that the environment for sharing data is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify promising areas for future opportunities and research, including data collection and preparation, data analytics and utilization, and applications to support decision-making