Taking a look at small-scale pedestrians and occluded pedestrians

Small-scale pedestrian detection and occluded pedestrian detection are two challenging tasks. However, most state-of-the-art methods merely handle one single task each time, thus giving rise to relatively poor performance when the two tasks, in practice, are required simultaneously. In this paper, it is found that small-scale pedestrian detection and occluded pedestrian detection actually have a common problem, i.e., an inaccurate location problem. Therefore, solving this problem enables to improve the performance of both tasks. To this end, we pay more attention to the predicted bounding box with worse location precision and extract more contextual information around objects, where two modules (i.e., location bootstrap and semantic transition) are proposed. The location bootstrap is used to reweight regression loss, where the loss of the predicted bounding box far from the corresponding ground-truth is upweighted and the loss of the predicted bounding box near the corresponding ground-truth is downweighted. Additionally, the semantic transition adds more contextual information and relieves semantic inconsistency of the skip-layer fusion. Since the location bootstrap is not used at the test stage and the semantic transition is lightweight, the proposed method does not add many extra computational costs during inference. Experiments on the challenging CityPersons and Caltech datasets show that the proposed method outperforms the state-of-the-art methods on the small-scale pedestrians and occluded pedestrians (e.g., 5.20% and 4.73% improvements on the Caltech)

How do elderly pedestrians perceive hazards in the street? - An initial investigation towards development of a pedestrian simulation that incorporates reaction of various pedestrians to environments

In order to evaluate the accessibility of street and transport environments, such as railway stations, we are now developing a pedestrian simulation that incorporates elderly and disable pedestrians and their interaction with various environments including hazards on the street. For this development, it is necessary to understand how elderly and disabled pedestrians perceive hazards in the street and transport environments. Many elderly people suffer from some visual impairment. A study in the UK suggested 12% of people aged 65 or over have binocular acuity of 6/18 or less (Van der Pols et al, 2000). It should be noted that a quarter of the UK population will be aged 65 or over by 2031 (The Government Actuary's Department, 2004). Because of age-related changes of visual perception organs, elderly people suffer not only visual acuity problems but also other forms of visual disabilities, such as visual field loss and less contrast sensitivity. Lighting is considered to be an effective solution to let elderly and disable pedestrians perceive possible hazards in the street. Interestingly, British Standards for residential street lighting have not considered lighting needs of elderly pedestrians or pedestrians with visual disabilities (e.g. Fujiyama et al, 2005). In order to design street lighting that incorporates elderly and visually disabled pedestrians, it would be useful to understand how lighting improves the perception of hazards by elderly and disable pedestrians. The aim of this paper is to understand how elderly pedestrians perceive different hazards and to address issues to be investigated in future research. This paper focuses on fixation patterns of elderly pedestrians on different hazards in the street under different lighting conditions. Analysing fixation patterns helps us understand how pedestrians perceive environments or hazards (Fujiyama, 2006). This paper presents the initial results of our analysis of the eye tracker data of an ordinary elderly participant

BBN For Pedestrians

The simplest, `standard' model of Big Bang Nucleosynthesis (SBBN) assumes three light neutrinos (N_nu = 3) and no significant electron neutrino asymmetry, leaving only one adjustable parameter: the baryon to photon ratio eta. The primordial abundance of any one nuclide can, therefore, be used to measure the baryon abundance and the value derived from the observationally inferred primordial abundance of deuterium closely matches that from current, non-BBN data, primarily from the WMAP survey. However, using this same estimate there is a tension between the SBBN-predicted 4He and 7Li abundances and their current, observationally inferred primordial abundances, suggesting that N_nu may differ from the standard model value of three and/or that there may be a non-zero neutral lepton asymmetry (or, that systematic errors in the abundance determinations have been underestimated or overlooked). The differences are not large and the allowed ranges of the BBN parameters permitted by the data are quite small. Within these ranges, the BBN-predicted abundances of D, 3He, 4He, and 7Li are very smooth, monotonic functions of eta, N_nu, and the lepton asymmetry. It is possible to describe the dependencies of these abundances (or powers of them) upon the three parameters by simple, linear fits which, over their ranges of applicability, are accurate to a few percent or better. The fits presented here have not been maximized for their accuracy but, for their simplicity. To identify the ranges of applicability and relative accuracies, they are compared to detailed BBN calculations; their utility is illustrated with several examples. Given the tension within BBN, these fits should prove useful in facilitating studies of the viability of proposals for non-standard physics and cosmology, prior to undertaking detailed BBN calculations.Comment: Submitted to a Focus Issue on Neutrino Physics in New Journal of Physics (www.njp.org

User Equilibrium Route Assignment for Microscopic Pedestrian Simulation

For the simulation of pedestrians a method is introduced to find routing alternatives from any origin position to a given destination area in a given geometry composed of walking areas and obstacles. The method includes a parameter which sets a threshold for the approximate minimum size of obstacles to generate routing alternatives. The resulting data structure for navigation is constructed such that it does not introduce artifacts to the movement of simulated pedestrians and that locally pedestrians prefer to walk on the shortest path. The generated set of routes can be used with iterating static or dynamic assignment methods

Street crossing behavior in younger and older pedestrians: an eye- and head-tracking study

Background Crossing a street can be a very difficult task for older pedestrians. With increased age and potential cognitive decline, older people take the decision to cross a street primarily based on vehicles’ distance, and not on their speed. Furthermore, older pedestrians tend to overestimate their own walking speed, and could not adapt it according to the traffic conditions. Pedestrians’ behavior is often tested using virtual reality. Virtual reality presents the advantage of being safe, cost-effective, and allows using standardized test conditions. Methods This paper describes an observational study with older and younger adults. Street crossing behavior was investigated in 18 healthy, younger and 18 older subjects by using a virtual reality setting. The aim of the study was to measure behavioral data (such as eye and head movements) and to assess how the two age groups differ in terms of number of safe street crossings, virtual crashes, and missed street crossing opportunities. Street crossing behavior, eye and head movements, in older and younger subjects, were compared with non-parametric tests. Results The results showed that younger pedestrians behaved in a more secure manner while crossing a street, as compared to older people. The eye and head movements analysis revealed that older people looked more at the ground and less at the other side of the street to cross. Conclusions The less secure behavior in street crossing found in older pedestrians could be explained by their reduced cognitive and visual abilities, which, in turn, resulted in difficulties in the decision-making process, especially under time pressure. Decisions to cross a street are based on the distance of the oncoming cars, rather than their speed, for both groups. Older pedestrians look more at their feet, probably because of their need of more time to plan precise stepping movement and, in turn, pay less attention to the traffic. This might help to set up guidelines for improving senior pedestrians’ safety, in terms of speed limits, road design, and mixed physical-cognitive trainings

Fatally Injured Pedestrians and Bicyclists in the United States with High Blood Alcohol Concentrations

More than one-third of pedestrians and one-fifth of bicyclists killed in crashes in 2014 were impaired by alcohol, but scant attention has been paid to the problem. This omission contrasts starkly with the many successful policies that have reduced impaired driving, a new Institute study notes.The study looked at fatalities of passenger vehicle drivers, pedestrians and bicyclists 16 and older from 1982 to 2014. Using a federal database, IIHS researchers looked at the characteristics of those crashes and trends over time. They found that the percentage of fatally injured pedestrians and bicyclists 16 and older who were impaired has fallen over the decades, but not as dramatically as the percentage of impaired drivers

A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments

This paper reports on a data-driven, interaction-aware motion prediction approach for pedestrians in environments cluttered with static obstacles. When navigating in such workspaces shared with humans, robots need accurate motion predictions of the surrounding pedestrians. Human navigation behavior is mostly influenced by their surrounding pedestrians and by the static obstacles in their vicinity. In this paper we introduce a new model based on Long-Short Term Memory (LSTM) neural networks, which is able to learn human motion behavior from demonstrated data. To the best of our knowledge, this is the first approach using LSTMs, that incorporates both static obstacles and surrounding pedestrians for trajectory forecasting. As part of the model, we introduce a new way of encoding surrounding pedestrians based on a 1d-grid in polar angle space. We evaluate the benefit of interaction-aware motion prediction and the added value of incorporating static obstacles on both simulation and real-world datasets by comparing with state-of-the-art approaches. The results show, that our new approach outperforms the other approaches while being very computationally efficient and that taking into account static obstacles for motion predictions significantly improves the prediction accuracy, especially in cluttered environments.Comment: 8 pages, accepted for publication at the IEEE International Conference on Robotics and Automation (ICRA) 201