Transport and Older People: Integrating Transport Planning Tools with User Needs

This study was funded through a pump-priming grant from the Strategic Promotion of Ageing Research Capacity (SPARC) programme. The purpose of the project was to bring together transport and public health research in order to demonstrate how the involvement of older people can help improve tools for transport planning. The study was unique in that it brought together public health and transport planning and engineering with older people to consider how services can be more responsive to older people’s transport needs. The project had five research objectives: 1. To investigate how accessibility problems impact on older people’s independence 2. To determine the extent to which currently available data sources and modelling tools reflect older people’s stated accessibility needs 3. To understand how the gap between expected and perceived accessibility problems varies across different categories of older people 4. To pilot techniques that could be applied to provide a more robust measure of accessibility for older people. 5. To build new research capacity across disciplines to develop a national focus on the interactions between ageing and transport planning. The methods were determined on the basis of ‘appropriate tools with maximum output’. Focus group interviews were selected as a useful tool for reaching a large number of older people within a limited time span, for providing an arena for discussion and debate about a topical subject and for generating ideas for improving transport planning. Following the interviews accompanied walks were undertaken with older people in a range of road environments and traffic situations. The purpose of these walks was to observe and explore the way older people interact with their environment. Data from the focus group interviews and the observations were compared with the outputs from an accessibility planning tool used by local authorities to plan accessible and acceptable transport routes (Accession™). The purpose of this exercise was to investigate whether or not such tools are able to take into account the varying needs of older people. The study was undertaken over eight months. Eighty one older people living in the Leeds district took part in the focus groups. They covered a broad range of mobility levels and used a variety of transport types, as such a reasonably rounded perspective on the issues concerned was offered. In addition six walks were undertaken with older people in their community

Getting Around When You’re Just Getting By: The Travel Behavior and Transportation Expenditures of Low-Income Adults, MTI Report 10-02

How much do people with limited resources pay for cars, public transit, and other means of travel? How does their transportation behavior change during periods of falling employment and rising fuel prices? This research uses in-depth interviews with 73 adults to examine how rising transportation costs impact low-income families. The interviews examine four general areas of interest: travel behavior and transportation spending patterns; the costs and benefits of alternative modes of travel; cost management strategies; and opinions about the effect of changing transportation prices on travel behavior. Key findings include: Most low-income household are concerned about their transportation costs. Low-income individuals actively and strategically manage their household resources in order to survive on very limited means and to respond to changes in income or transportation costs. In making mode-choice decisions, low-income travelers—like higher-income travelers—carefully evaluate the costs of travel (time and out-of-pocket expenses) against the benefits of each of the modes. Some low-income individuals in our sample were willing to endure higher transportation expenditures—such as the costs of auto ownership or congestion tolls—if they believed that they currently benefit or would potentially benefit from these increased expenses. Although low-income households find ways to cover their transportation expenditures, many of these strategies had negative effects on households. The report concludes with recommendations on how to increase transportation affordability, minimize the impact that new transportation taxes or fees have on low-income people, and develop new research and data collection to support the previous two efforts

The Hypervelocity Star SDSS J090745.0+024507 is a Short-Period Variable

We present high-precision photometry of the hypervelocity star SDSS J090745.0+024507 (HVS), which has a Galactic rest-frame radial velocity of v=709 km/s, and so has likely been ejected from the supermassive black hole in the Galactic center. Our data were obtained on two nights using the MMT 6.5m telescope, and is supplemented by lower precision photometry obtained on four nights using the FLWO 1.2m telescope. The high-precision photometry indicates that the HVS is a short-period, low-amplitude variable, with period P=0.2-2 days and amplitude A = 2-10%. Together with the known effective temperature of T_eff ~ 10,500 K (spectral type B9), this variability implies that the HVS is a member of the class of slowly pulsating B-type main sequence stars, thus resolving the previously-reported two-fold degeneracy in the luminosity and distance of the star. The HVS has a heliocentric distance of 71 kpc, and an age of ~0.35 Gyr. The time of ejection from the center of the Galaxy is < 100 Myr, and thus the existence of the OS constitutes observational evidence of a population of young stars in the proximity of the central supermassive black hole ~0.1 Gyr ago. It is possible that the HVS was a member of a binary that was tidally disrupted by the central black hole; we discuss constraints on the properties of the companion's orbit.Comment: ApJL, submitted, 4 pages, 4 figure

Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation

Traffic speed data imputation is a fundamental challenge for data-driven transport analysis. In recent years, with the ubiquity of GPS-enabled devices and the widespread use of crowdsourcing alternatives for the collection of traffic data, transportation professionals increasingly look to such user-generated data for many analysis, planning, and decision support applications. However, due to the mechanics of the data collection process, crowdsourced traffic data such as probe-vehicle data is highly prone to missing observations, making accurate imputation crucial for the success of any application that makes use of that type of data. In this article, we propose the use of multi-output Gaussian processes (GPs) to model the complex spatial and temporal patterns in crowdsourced traffic data. While the Bayesian nonparametric formalism of GPs allows us to model observation uncertainty, the multi-output extension based on convolution processes effectively enables us to capture complex spatial dependencies between nearby road segments. Using 6 months of crowdsourced traffic speed data or "probe vehicle data" for several locations in Copenhagen, the proposed approach is empirically shown to significantly outperform popular state-of-the-art imputation methods.Comment: 10 pages, IEEE Transactions on Intelligent Transportation Systems, 201

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Analyzing travel time reliability of a bus route in a limited data set scenario: A case study

In this information era commuters prefer to know a reliable travel time to plan ahead of their journey using both public and private modes. In this direction reliability analysis using the location data of the buses is conducted in two folds in the current work; (i) Reliability analysis of a public transit service at route level, and (ii) Travel time reliability analysis of a route utilizing the location data of the buses. The reliability parameters assessed for public transit service are headway, passenger waiting time, travel speed, and travel time as per the Service Level Benchmarks for Urban Transport by the National Urban Transport Policy, Government of India. And travel time reliability parameters such as Buffer Time Index, Travel Time Index, and Planning Time Index are assessed as per Federal Highway Administration, Department of Transportation, U S. The study is conducted in Tumakuru city, India for a significant bus route in a limited data sources scenario. The results suggest that (i) the Level of Service of the public transit service needs improvement. (ii)around 30% excess of average travel time is needed as buffer time. (iii) more than double the amount of free flow travel time must be planned during peak hours and in the worst case. In the future, the analysis conducted for the route can be extended for citywide performance analysis in both folds. Also, the same method can be applied to cities with similar demographics and traffic-related infrastructure.Comment: 10 pages, 7 figures, 6 table