Transit to eternal youth: lifecycle and generational trends in Greater Montreal public transport mode share

Young people appear to be using public transit more than their predecessors, reversing twentieth century trends, but the importance of such findings depends on whether high transit use persists as these riders age. This paper examines whether transit mode share for commuting trips is increasing; socio-economic and geographic trends are also explored to attempt to determine whether these trends are likely to continue. The study uses repeated cross-sectional origin–destination surveys of Greater Montreal (1998, 2003 and 2008). Over 45,000 home-to-work and home-to-school trips are studied for each survey year. A general lifecycle pattern of decreasing transit share with age is apparent within cohorts until individuals reach their early 30s, followed by decades of stability. This pattern appears to hold in recent years, but with higher youth use rates, and it is argued that the higher use will continue as current younger cohorts mature. Suburbanization by those in their early 30s is evident and, along with household composition changes, appears to explain much of the final within-cohort mode share declines before equilibrium. Transit providers might see lasting ridership gains, as those currently in their early 30s and younger replace lower-use cohorts in the workforce, provided service provision keeps pace. Addressing the needs of young people, whose mode choices are comparatively unsettled, should be a priority for transit agencies to ensure higher transit usage in the future.     

Vehicle reidentification and travel time measurement on congested freeways

The paper presents an algorithm for matching individual vehicles measured at a freeway detector with the vehicles’ corresponding measurements taken earlier at another detector located upstream. Although this algorithm is potentially compatible with many vehicle detector technologies, the paper illustrates the method using existing dual-loop detectors to measure vehicle lengths. This detector technology has seen widespread deployment for velocity measurement. Since the detectors were not developed to measure vehicle length, these measurements can include significant errors. To overcome this problem, the algorithm exploits drivers’ tendencies to retain their positions within dense platoons. The otherwise complicated task of vehicle reidentification is carried out by matching these platoons rather than individual vehicles. Of course once a vehicle has been matched across neighboring detector stations, the difference in its arrival time at each station defines the vehicle’s travel time on the intervening segment.Findings from an application of the algorithm over a 1/3 mile long segment are presented herein and they indicate that a sufficient number of vehicles can be matched for the purpose of traffic surveillance. As such, the algorithm extracts travel time data without requiring the deployment of new detector technologies. In addition to the immediate impacts on traffic monitoring, the work provides a means to quantify the potential benefits of emerging detector technologies that promise to extract more detailed information from individual vehicles.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

A multiobjective land development optimization model: the case of New Castle County,Delaware

This paper develops a multiobjective optimization model to consider transportation impacts of the future development of land. The output of the model is the best location and type of land use that has minimal negative transportation effects and uses the maximum available public transportation infrastructure. It provides tools for both planners and transportation engineers and enables them to consider different scenarios of possible policies and land development. Since multiple objectives and their nonlinear structures are considered, the model is solved using mixed integer nonlinear programming. The final results are shown in both tabular and graphical format. The effectiveness of the model is applied to the northern part of New Castle County, Delaware. The results show that the model successfully finds the best locations for both residential and commercial land uses in order to meet several criteria discussed in the paper.     

Remoteness and accessibility in the vulnerability analysis of regional road networks

This paper considers the development of a method for network vulnerability analysis which considers the socio-economic impacts of network degradation and seeks to determine the most critical locations in the network. The method compares the levels of remoteness (or its inverse, accessibility) of localities within the study region, on the basis of the impacts of degradation of the road network on a recognised accessibility/remoteness index that can be applied to each and every location within the region. It thus extends the earlier work on accessibility-based vulnerability analysis which was limited to assessment of impacts on selected nodes in a network. The new method allows study of impacts on both specified locations (which do not have to be represented as network nodes) and the region as a whole. The accessibility/remoteness index is defined so that an accessibility surface can be calculated for the region, and the volume under this surface provides an overall measure of accessibility. Changes in the volume under different network states thus reflect the overall impacts. The method is applied to a rural region in south east Australia.     

The merits of accelerated depreciation for promoting investment in clean transport technologies: A simulation study in the Australian rail freight industry

This article ascertains the viability of promoting accelerated depreciation for newly acquired locomotives and other rolling stock as a means of encouraging technological investment in more efficient and environmentally friendly assets. The study uses a tax-adjusted asset replacement model to evaluate the merits of accelerated depreciation, and then compares the outcomes with alternative incentive schemes. It also examines what would occur if various schemes were used simultaneously.     

The cost saving potential of carsharing in a US context

Carsharing is a vehicle sharing service for those with occasional need of private transportation. Transportation planners are beginning to see great potential for carsharing in helping to create a more diversified and sustainable transport system. While it has grown quickly in the US in recent years, it is still far from the level where it can deliver significant aggregate benefits. A key element to the potential growth of carsharing is its ability to provide cost savings to those who adopt it in favor of vehicle ownership. This research seeks to quantify these potential cost savings. The costs of carsharing and vehicle ownership are compared based on actual vehicle usage patterns from a large survey of San Francisco Bay Area residents. The results of this analysis show that a significant minority of Bay Area households own a vehicle with a usage pattern that carsharing could accommodate at a lower cost. Further research is required to indentify how these cost savings translate to the adoption of carsharing.