Governance in niche development for a transition to a new mobility regime

Urban mobility is a difficult sustainability challenge; measures to reduce transport impacts produce only marginal reductions in overall energy use and CO2 emissions. Even fuel switch to electric vehicles and measures to manage traffic produce insufficient improvements. Seeking transport sustainability within the existing socio-technical regime involves policy approaches for dense cities to provide high-capacity, corridor-based public transport, expecting people to arrange their lives around such transport systems. Yet this socio-technical regime ill-fits modern mobility needs. The reluctance to use public transport stems much from this 150 year old regime configuration. The social-technical landscape has shifted significantly: travel patterns are increasingly dispersed in space and time – not funnelled into traditional corridor peak-hour movements. The key is not getting people to return to travel patterns of 100 years ago, but in a transition to a socio-technical transport regime that delivers sustainability compatible with the 21st century social-technical landscape. An opportunity may be emerging for socio-technical configurations in niche environments to effect transitions to alternate mobility futures. Autonomous vehicles are rapidly approaching market application. Since 2011, small autonomous pods have operated on segregated tracks at Heathrow Airport. In 2014 a similar system opened at the Suncheon Bay tourist area in South Korea. Since 2011 there have been public street trials of autonomous vehicles in the USA and in 2015 they became street legal in the UK. The Milton Keynes (MK) ‘Pathfinder’ project focuses on two-seat pods which do not need segregated tracks, but will run on cycleways and footpaths, mixing with cyclists and pedestrians. Trials will start in 2015, on short distance links from the railway station to destinations in Central Milton Keynes. This project forms part of the wider Milton Keynes Future Cities Programme and Open University-led MK:Smart project. This paper draws on these trials in MK to show through case study research how autonomous vehicles applications are moving beyond protected niches and, along with other developments, hold the potential to stimulate a major transition in public transport systems. The vehicles are small and each journey is individual to the passenger(s). Services do not run along corridor routes, like buses and trams, but are based on alternate rule-sets to the existing regime with individual journeys customised for each user. Such developments may therefore stimulate transition to totally different sorts of public transport systems and ultimately, socio-technical mobility regimes, by offering much more to users than any corridor system can provide. Rather than people adjusting their behaviour to bus routes, schedules and operating times, they travel directly, whenever they want, on services running 24/7. Thus these new regimes could be more compatible with lifestyle and economic trends that comprise 21st century socio-technical landscapes. As such, they provide credible alternatives to the private car, and so hold potential to deliver major sustainability gains. But such transitions face major challenges from entrenched actors within the existing regime. Taxis, minicabs and bus operators would be threatened. If the Uber cab app is being blocked by incumbent actors, they look likely to be powerful opponents of autonomous vehicle based cab services. However, MK provides an interesting innovation context where there are several overlapping smart transport niches in different stages of development. As well as autonomous pods, demand responsive minibuses are planned and inductive changed electric buses are in service. If these projects build links to each other (niche accumulation), demonstrate economic value and reproduced beyond their original experimental spaces (niche proliferation), there is potential for them to overcome incumbent resistance. In Milton Keynes, these processes could be getting close to reaching critical mass, opening up the possibility of moving closer to radical regime transitions

PMLR

We propose a neural information processing system obtained by re-purposing the function of a biological neural circuit model to govern simulated and real-world control tasks. Inspired by the structure of the nervous system of the soil-worm, C. elegans, we introduce ordinary neural circuits (ONCs), defined as the model of biological neural circuits reparameterized for the control of alternative tasks. We first demonstrate that ONCs realize networks with higher maximum flow compared to arbitrary wired networks. We then learn instances of ONCs to control a series of robotic tasks, including the autonomous parking of a real-world rover robot. For reconfiguration of the purpose of the neural circuit, we adopt a search-based optimization algorithm. Ordinary neural circuits perform on par and, in some cases, significantly surpass the performance of contemporary deep learning models. ONC networks are compact, 77% sparser than their counterpart neural controllers, and their neural dynamics are fully interpretable at the cell-level

Guided Frequency Loss for Image Restoration

Image Restoration has seen remarkable progress in recent years. Many generative models have been adapted to tackle the known restoration cases of images. However, the interest in benefiting from the frequency domain is not well explored despite its major factor in these particular cases of image synthesis. In this study, we propose the Guided Frequency Loss (GFL), which helps the model to learn in a balanced way the image's frequency content alongside the spatial content. It aggregates three major components that work in parallel to enhance learning efficiency; a Charbonnier component, a Laplacian Pyramid component, and a Gradual Frequency component. We tested GFL on the Super Resolution and the Denoising tasks. We used three different datasets and three different architectures for each of them. We found that the GFL loss improved the PSNR metric in most implemented experiments. Also, it improved the training of the Super Resolution models in both SwinIR and SRGAN. In addition, the utility of the GFL loss increased better on constrained data due to the less stochasticity in the high frequencies' components among samples

HopSkipJumpAttack: A Query-Efficient Decision-Based Attack

The goal of a decision-based adversarial attack on a trained model is to generate adversarial examples based solely on observing output labels returned by the targeted model. We develop HopSkipJumpAttack, a family of algorithms based on a novel estimate of the gradient direction using binary information at the decision boundary. The proposed family includes both untargeted and targeted attacks optimized for $\ell_2$ and $\ell_\infty$ similarity metrics respectively. Theoretical analysis is provided for the proposed algorithms and the gradient direction estimate. Experiments show HopSkipJumpAttack requires significantly fewer model queries than Boundary Attack. It also achieves competitive performance in attacking several widely-used defense mechanisms. (HopSkipJumpAttack was named Boundary Attack++ in a previous version of the preprint.

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin