SaferCross: Enhancing Pedestrian Safety Using Embedded Sensors of Smartphone

The number of pedestrian accidents continues to keep climbing. Distraction from smartphone is one of the biggest causes for pedestrian fatalities. In this paper, we develop SaferCross, a mobile system based on the embedded sensors of smartphone to improve pedestrian safety by preventing distraction from smartphone. SaferCross adopts a holistic approach by identifying and developing essential system components that are missing in existing systems and integrating the system components into a "fully-functioning" mobile system for pedestrian safety. Specifically, we create algorithms for improving the accuracy and energy efficiency of pedestrian positioning, effectiveness of phone activity detection, and real-time risk assessment. We demonstrate that SaferCross, through systematic integration of the developed algorithms, performs situation awareness effectively and provides a timely warning to the pedestrian based on the information obtained from smartphone sensors and Direct Wi-Fi-based peer-to-peer communication with approaching cars. Extensive experiments are conducted in a department parking lot for both component-level and integrated testing. The results demonstrate that the energy efficiency and positioning accuracy of SaferCross are improved by 52% and 72% on average compared with existing solutions with missing support for positioning accuracy and energy efficiency, and the phone-viewing event detection accuracy is over 90%. The integrated test results show that SaferCross alerts the pedestrian timely with an average error of 1.6sec in comparison with the ground truth data, which can be easily compensated by configuring the system to fire an alert message a couple of seconds early.Comment: Published in IEEE Access, 202

Trials with Microwave Detection of Vulnerable Road Users and Preliminary Empirical Modal Test. DRIVE Project V1031 Deliverable 11.

The general objective of the project is to provide a set of tools for the creation of traffic systems that enhance the safety and mobility of vulnerable road users (VRUs). This is being achieved in two ways: 1. By evaluating a number of RTI applications in signalling and junction control, in order to ascertain what benefits can be obtained for vulnerable road users by such local measures. 2. By developing a model of the traffic system that incorporates vulnerable road users as an integral part. The present workpackage, one of the last ones within the project, is intended to link the two strands together. The workpackage consists of two main parts: 1. Experiments with pedestrians and bicyclists. Two experiments were carried out, one in England (Bradford) and one in Sweden (Vijrjo), both applying microwave detectors for detection of pedestrians in a signalized intersection, but applying the detection in different ways. An observational study was carried out in Groningen (the Netherlands) to analyze bicycle/car interactions at an intersection with a cycle path. The aim of the experiment was to test the usefulness of a system giving car drivers warning in situations when a bicyclist approaches an intersection on a parallel bicycle path. 2. Reliability and validity testing of the submodels of the VRU-oriented traffic model WLCAN

Towards a Practical Pedestrian Distraction Detection Framework using Wearables

Pedestrian safety continues to be a significant concern in urban communities and pedestrian distraction is emerging as one of the main causes of grave and fatal accidents involving pedestrians. The advent of sophisticated mobile and wearable devices, equipped with high-precision on-board sensors capable of measuring fine-grained user movements and context, provides a tremendous opportunity for designing effective pedestrian safety systems and applications. Accurate and efficient recognition of pedestrian distractions in real-time given the memory, computation and communication limitations of these devices, however, remains the key technical challenge in the design of such systems. Earlier research efforts in pedestrian distraction detection using data available from mobile and wearable devices have primarily focused only on achieving high detection accuracy, resulting in designs that are either resource intensive and unsuitable for implementation on mainstream mobile devices, or computationally slow and not useful for real-time pedestrian safety applications, or require specialized hardware and less likely to be adopted by most users. In the quest for a pedestrian safety system that achieves a favorable balance between computational efficiency, detection accuracy, and energy consumption, this paper makes the following main contributions: (i) design of a novel complex activity recognition framework which employs motion data available from users' mobile and wearable devices and a lightweight frequency matching approach to accurately and efficiently recognize complex distraction related activities, and (ii) a comprehensive comparative evaluation of the proposed framework with well-known complex activity recognition techniques in the literature with the help of data collected from human subject pedestrians and prototype implementations on commercially-available mobile and wearable devices

Assessment of the Effectiveness of the Greek Implementation. VRU-TOO Deliverable 14

The work of VRU-TOO is targeted specifically at the application of ATT for reducing risk and improving comfort (e.g. minimisation of delay) for Vulnerable Road Users, namely pedestrians. To achieve this, the project operates at three levels. At the European level practical pilot implementations in three countries (U.K., Portugal and Greece) are linked with behavioural studies of the micro-level interaction of pedestrians and vehicles and the development of computer simulation models. At the National level, the appropriate Highway Authorities are consulted, according to their functions, for the pilot implementations and informed of the results. Finally, at the local level, the pilot project work is fitted into specfic local (municipality) policy contexts in all three pilot project sites. The present report focuses on the Elefsina pilot application in Greece and the relevant National and Local policy contexts are the following. At the National level, the ultimate responsibility for road safety and signal installations rests with the Ministry of Environment and Public Works. The Ministry is responsible for the adoption of standards and solutions for problems and also for a large number of actual installations, since local authorities lack the size and expertise to undertake such work on their own One of the project's aims is to provide information to the Ministry as to the suitability of the methods developed for aiding pedestrian movement, ultimately leading to a specification for its wider use. The Ministry is expecting to use the final results of the present study for possible modifications of its present standards for pedestrian controlled traffic signals. At the local level (Elefsina) the municipality has, in the past, pursued environmental improvements through pedestrianisation schemes in the city centre. At the same time it has developed a special traffic management policy, to solve a particularly serious problem of through traffic. A summary of the policy is contained in Appendix A and more details in a previous deliverable (Tillis, 1992). In the particular case of Elefsina pedestrian induced delay to through vehicular traffic, may form a key element in this policy ensuring at the same time, an incentive to divert to the existing bypass and enhancing pedestrian movement. The effectiveness of pedestrian detection techniques tested in the pilot, will provide valuable information on the future implementation of the policy. Thus, the Elefsina Pilot Project operates at the same time on three levels: It provides a basis, in combination with the other two pilot project sites, for comparing the effects of pedestrian detection on pedestrian safety and comfort at a European level. It provides information to the National authorities (Ministry of Environment and Public Works) for their standards setting, scheme design and implementation tasks. It fits into a comprehensive plan at the local level for effecting environmental improvements and enhancing pedestrian amenity and comfort at the same time. In addition, an investigation into the capabilities of pedestrian detectors to function as data collection devices, was performed. The data 'quality gap' betweenvehicular and pedestrian tr&c may be closed with the utilisation of microwave pedestrian detectors, providing a more solid foundation for the planning for total person movement through networks (vehicle occupants, public transport passengers, pedestrians). This the second deliverable issued for Elefsina and comprises of the main section which contains a description of the work undertaken, the results and a number of appendices serving as background material in support of the statements in the main text

A Pilot Study of Pedestrians with Visual Impairments Detecting Traffic Gaps and Surges Containing Hybrid Vehicles

The increasing number of hybrid and quiet internal combustion engine vehicles may impact the travel abilities of pedestrians who are blind. Pedestrians who rely on auditory cues for structuring their travel may face challenges in making crossing decisions in the presence of quiet vehicles. This article describes results of initial studies looking at the crossing decisions of pedestrians who are blind at an uncontrolled crossing (no traffic control) and a light controlled intersection. The presence of hybrid vehicles was a factor in each situation. At the uncontrolled crossing, Toyota hybrids were most difficult to detect but crossing decisions were made more often in small gaps ended by a Honda hybrid. These effects were seen only at speed under 20 mph. At the light controlled intersection, parallel surges of traffic were most difficult to detect when made up only of a Ford Escape hybrid. Results suggest that more controlled studies of vehicle characteristics impacting crossing decisions of pedestrians who are blind are warranted

Is the Pedestrian going to Cross? Answering by 2D Pose Estimation

Our recent work suggests that, thanks to nowadays powerful CNNs, image-based 2D pose estimation is a promising cue for determining pedestrian intentions such as crossing the road in the path of the ego-vehicle, stopping before entering the road, and starting to walk or bending towards the road. This statement is based on the results obtained on non-naturalistic sequences (Daimler dataset), i.e. in sequences choreographed specifically for performing the study. Fortunately, a new publicly available dataset (JAAD) has appeared recently to allow developing methods for detecting pedestrian intentions in naturalistic driving conditions; more specifically, for addressing the relevant question is the pedestrian going to cross? Accordingly, in this paper we use JAAD to assess the usefulness of 2D pose estimation for answering such a question. We combine CNN-based pedestrian detection, tracking and pose estimation to predict the crossing action from monocular images. Overall, the proposed pipeline provides new state-of-the-art results.Comment: This is a paper presented in IEEE Intelligent Vehicles Symposium (IEEE IV 2018