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The impact of Automated Vehicles (AVs) on urban geography has been widely speculated, though there is little quantitative evidence in the literature to establish the magnitude of such effects. To quantify the impact of the greater precision of automated driving on the spatial efficiency of off-street parking facilities, we develop a mixed integer nonlinear model (solved via a branch-and-cut approach) and present comparisons against industry-standard requirements for human-driving operation. We demonstrate that gains on the order of 40-50% in spatial efficiency (parking spaces per unit area) are in principle achievable while ensuring that each parked vehicle is independently accessible. We further show that the large majority of these efficiency gains can be obtained under current automotive engineering practice in which only the front two wheels pivot. There is a need for standardized methods that take the parking supply of a city as an input and calculate both the aggregate (citywide) efficiency impacts of automated driving and the spatial distribution of the effects. This study is intended as an initial step towards this objective., 1. Introduction Automation technologies for automobiles and other road vehicles are becoming increasingly available commercially, with further advances anticipated in coming years in both fundamental technology and its manifestation as [...]

This study is the first to quantify throughput (saturation flow) of noncooperative automated vehicles when performing turning maneuvers, which are critical bottlenecks in arterial road networks. We first develop a constrained optimization problem based on AVs' kinematic behavior during a protected signal phase which considers both ABS-enabled and wheels-locked braking, as well as avoiding encroaching into oncoming traffic or past the edge-of-receiving-lane. We analyze noncooperative ('defensive') behavior, in keeping with the Assured Clear Distance Ahead legal standard to which human drivers are held and AVs will likely also be for the foreseeable future. We demonstrate that, under plausible behavioral parameters, AVs appear likely to have positive impacts on throughput of turning traffic streams at intersections, in the range of +0.2% (under the most conservative circumstances) to +43% for a typical turning maneuver. We demonstrate that the primary mechanism of impact of turning radius is its effect on speed, which is likely to be constrained by passenger comfort. We show heterogeneous per-lane throughput in the case of 'double turn lanes.' Finally, we demonstrate limited sensitivity to crash-risk criterion, with a 4% difference arising from a change from 1 in 10,000 to 1 in 100,000,000. The paper concludes with a brief discussion of policy implications and future research needs., 1. Introduction Within the functional lifetime of much of today's road infrastructure, vehicle automation is expected to impact a range of important aspects of the transportation system, including traffic operations [...]

The UK is one of many high-income countries to experience a decline in driving license acquisition among young adults in the 2000s. This paper draws on newly available nationally representative microdata that captures the progress of individual drivers through the UK driving license acquisition process, to establish socio-demographic correlates. Using the 2016 and 2017 editions of England's National Travel Survey data, a series of binary logit models were employed to identify factors associated with progression through the various phases of the UK's driving license acquisition process. Factors that are associated with (1) the frequency of taking the driving license tests, (2) the number of times having failed the theory and driving tests are then identified. The socio-demographic explanators considered were each found to be associated with driving license holding in intuitive ways that are consistent with prior literature. However, relatively few factors are significantly associated with progress through the steps of the license acquisition process, and the goodness-of-fit for progress through these intermediate phases are generally lower (indicating that other unobservable idiosyncratic personal or contextual characteristics are dominant in these processes). A consistent theme is the strong relationship with labor market participation. Links between income and the intermediate phases, however, were generally weaker. Age is negatively associated with progress through the early phases when respondents are applying for provisional license and taking theory test, but this relationship turns positive in later stages of the acquisition process. To the authors' knowledge, this study is the first opportunity to evaluate this novel data resource covering the UK's driving license acquisition process. This is an important research direction to help policymakers understand young adults' delay in acquiring licenses, particularly the extent to which there may be structural inequalities. The main finding is that socio-demographic factors appear to be relatively poor predictors, with employment status the strongest single correlate of the variables that were tested. This paper is concluded with suggestions for designers of household travel surveys in regions where youth license-acquisition is of increasing focus, as well as a brief discussion of future research needs. [ABSTRACT FROM AUTHOR]

This study draws on respondents from Greater London within the 2016/17 wave (n = 2640) of Britain's Annual Survey of carsharing users, which we enrich with external data from the 2011 England and Wales Census and small-area income estimates. Focusing on round-trip carsharing users, we present multivariate analyses of frequency-of-usage of carsharing vehicles and impacts on annual vehicle miles traveled (VMT). Published attribute effects from other geographic and contextual circumstances are compiled and compared (where direct comparison is possible) with the specific attribute effects that we report in this paper. We demonstrate a statistically significant link between customer satisfaction with proximity of carsharing vehicles and VMT impacts. Car ownership (both current, and changes upon joining a carsharing service) is shown to have intuitive structural impacts. We find that frequent usage is associated ceteris paribus with increasing VMT after joining a carsharing service, and that subscribing to multiple types of carsharing is associated with frequent carsharing usage and a reduction in VMT. Interestingly, we did not find any significant effect of household income on either frequency-of-usage or VMT impacts. [ABSTRACT FROM AUTHOR]

Postcolonial African Writers: A Bio-Bibliographical Critical Sourcebook. Ed. by Pushpa Naidu Parekh and Siga Fatima Jagne. Westport, Conn.: Greenwood Pr., 1998.525p. acid free $85 (ISBN 0-313-29056-3). This Sourcebook's foreword, by [...]