Imitating Driver Behavior with Generative Adversarial Networks

The ability to accurately predict and simulate human driving behavior is critical for the development of intelligent transportation systems. Traditional modeling methods have employed simple parametric models and behavioral cloning. This paper adopts a method for overcoming the problem of cascading errors inherent in prior approaches, resulting in realistic behavior that is robust to trajectory perturbations. We extend Generative Adversarial Imitation Learning to the training of recurrent policies, and we demonstrate that our model outperforms rule-based controllers and maximum likelihood models in realistic highway simulations. Our model both reproduces emergent behavior of human drivers, such as lane change rate, while maintaining realistic control over long time horizons.Comment: 8 pages, 6 figure

Climate change, agriculture and Fairtrade: identifying the challenges and opportunities

This paper presents the findings of a study commissioned by the UK's Fairtrade Foundation on the implications of climate change for agricultural producers in Fairtrade value chains

Effective Tools for Supporting Struggling Teachers

When a district hires a teacher, the district has a responsibility to provide resources, dialogue, professional learning opportunities, and peer support to ensure that the teacher will be fully prepared to engage and inspire students in the classroom (Liesveld, 2005). When a teacher’s struggles are not related to instruction in the classroom, but are more about unacceptable behavior, the principal or supervisor might need to consider a level of corrective action that will help the teacher be successful both in and out of the classroom. Both new and experienced teachers need the tools to create engaging lessons, a grasp of the best teaching strategies common to all successful teachers, and the ability to understand what separates good teacher conduct from bad (Robinson, 2009). In this paper, we explore some practical tools designed to aid administrators as they manage and support teachers navigating the 21st century classroom

Next Steps & Closing

Discuss next steps for NTAS & PS&DS, action items, participant feedback, etc

MOToring along: The lives of cars seen through licensing and test data

For the past few years, the authors of this report have applied their expertise in transport studies, mathematical modelling, emissions analytics, statistics and geography to undertake innovative analysis of a dataset consisting of all registered light-duty vehicles in Great Britain and their annual mileages.Box 1 explains how this dataset has been created from two different sources to provide a unique information resource. It comprises a database of over 30 million vehicles in any given year. Statistical analysis of this database at the vehicle level allows for exploration of relationships between a large number of vehicle characteristics such as age, body type, changes in keepership, registered location and levels of vehicle usage – all of which was previously impossible. The dynamics of the car fleet can also be examined longitudinally,and monitored on an ongoing basis as the data comes on stream each year.In this report, we focus on analysis at the area level for one year: 2011. The data allows vehicles and their annual mileages to be attributed to the location of the registered keeper. When linked with other data about each local area such as the economic and demographic profiles, the availability of publictransport, collision rates and even the weather, it is possible to generate original insights about the distribution of cars, motorcycles, vans and other light duty vehicles, and about how the fleet and its usage varies across the country.In these uncertain times of changing vehicle purchasing patterns, possible shifts in attitudes to travel and in actual travel behaviour amongst younger generations, and the rapid growth in van traffic, this work has the potential to contribute to many policy and business objectives.In this report, we offer a selection of some of the topic areas we have investigated in our research to date. Whilst there is significant technical detail behind the generation of the MOT dataset and many of the additional variables that we have linked with it from sources such as the Census, we concentrate here on some key findings and why we believe these are novel and important. Technical details are saved for the final section of this report and in the further publications from the research team, which are detailed in the references section

Climate Variability and Change Impact on Crop Production: Evidence from Ghana

This paper explores the impact of climate variability and/or change on two major crop yields (cassava and maize) and cash crop (cocoa) in two districts in different agroecological zones - Atwima Mponua (Semi-Deciduous Forest Zone) and Ejura-Sekyeredumase (Transition Zone) of the Ashanti Region of Ghana. A comparative-case mixed-methods research design was adopted for the study, involving household survey questionnaires, focus group discussions (FGDs) and in-depth interviews with key informants to discuss farmers’ perceptions about changes in climate and impact on crop yields. Three hundred participants were involved in the study - 150 from each district. The study also used time series panel data approach to analyse the impact of climate variables (mean annual maximum and minimum temperatures; and total rainfall) on the three crops over the period 1992 - 2014.Farmers perceived changes in the weather patterns - mainly increasing temperature and erratic and low rainfall. Besides, farmers had observed invasion of weeds; and dryness of aquatic habitats (especially, during dry periods); and loss of major staples. The findings from the analysis of secondary data corroborate farmers’ perceptions about changes in climate and its negative impacts on cassava and maize yields for the past 20-30 years. However, qualitative feedback about impact of climate variables on cocoa yield conflicted with the findings of analysis of secondary data. The findings from this study can form a basis for policy makers to develop region specific adaptation policies to address climate change impacts on crops studied and extend it to other crops. Keywords: Climate variability and change; Vulnerability; Food crop; Cash crop. DOI: 10.7176/JEES/12-12-03 Publication date: December 31st 202

Probability of Physical Association of 104 Blended Companions to Kepler Objects of Interest Using Visible and Near-Infrared Adaptive Optics Photometry

We determine probabilities of physical association for stars in blended Kepler Objects of Interest (KOIs), and find that 14.5%_(-3.4%)^(+3.8%) of companions within ~ 4" are consistent with being physically unassociated with their primary. This produces a better understanding of potential false positives in the Kepler catalog and will guide models of planet formation in binary systems. Physical association is determined through two methods of calculating multi-band photometric parallax using visible and near-infrared adaptive optics observations of 84 KOI systems with 104 contaminating companions within ~ 4". We find no evidence that KOI companions with separations of less than 1" are more likely to be physically associated than KOI companions generally. We also reinterpret transit depths for 94 planet candidates, and calculate that 2.6% ± 0.4% of transits have R > 15R_⊕, which is consistent with prior modeling work

Robo-AO Kepler Survey IV: the effect of nearby stars on 3857 planetary candidate systems

We present the overall statistical results from the Robo-AO Kepler planetary candidate survey, comprising of 3857 high-angular resolution observations of planetary candidate systems with Robo-AO, an automated laser adaptive optics system. These observations reveal previously unknown nearby stars blended with the planetary candidate host star which alter the derived planetary radii or may be the source of an astrophysical false positive transit signal. In the first three papers in the survey, we detected 440 nearby stars around 3313 planetary candidate host stars. In this paper, we present observations of 532 planetary candidate host stars, detecting 94 companions around 88 stars; 84 of these companions have not previously been observed in high-resolution. We also report 50 more-widely-separated companions near 715 targets previously observed by Robo-AO. We derive corrected planetary radius estimates for the 814 planetary candidates in systems with a detected nearby star. If planetary candidates are equally likely to orbit the primary or secondary star, the radius estimates for planetary candidates in systems with likely bound nearby stars increase by a factor of 1.54, on average. We find that 35 previously-believed rocky planet candidates are likely not rocky due to the presence of nearby stars. From the combined data sets from the complete Robo-AO KOI survey, we find that 14.5\pm0.5% of planetary candidate hosts have a nearby star with 4", while 1.2% have two nearby stars and 0.08% have three. We find that 16% of Earth-sized, 13% of Neptune-sized, 14% of Saturn-sized, and 19% of Jupiter-sized planet candidates have detected nearby stars.Comment: Accepted to the Astronomical Journa

Robo-AO Kepler Survey V: The effect of physically associated stellar companions on planetary systems

The Kepler light curves used to detect thousands of planetary candidates are susceptible to dilution due to blending with previously unknown nearby stars. With the automated laser adaptive optics instrument, Robo-AO, we have observed 620 nearby stars around 3857 planetary candidates host stars. Many of the nearby stars, however, are not bound to the KOI. In this paper, we quantify the association probability between each KOI and detected nearby stars through several methods. Galactic stellar models and the observed stellar density are used to estimate the number and properties of unbound stars. We estimate the spectral type and distance to 145 KOIs with nearby stars using multi-band observations from Robo-AO and Keck-AO. We find most nearby stars within 1" of a Kepler planetary candidate are likely bound, in agreement with past studies. We use likely bound stars as well as the precise stellar parameters from the California Kepler Survey to search for correlations between stellar binarity and planetary properties. No significant difference between the binarity fraction of single and multiple planet systems is found, and planet hosting stars follow similar binarity trends as field stars, many of which likely host their own non-aligned planets. We find that hot Jupiters are ~4x more likely than other planets to reside in a binary star system. We correct the radius estimates of the planet candidates in characterized systems and find that for likely bound systems, the estimated planetary candidate radii will increase on average by a factor of 1.77, if either star is equally likely to host the planet. We find that the planetary radius gap is robust to the impact of dilution, and find an intriguing 95%-confidence discrepancy between the radius distribution of small planets in single and binary systems.Comment: 19 pages, 12 figures, submitted to AAS Journal