ADOPT: A system for Alerting Drivers to Occluded Pedestrian Traffic

Recent statistics reveal an alarming increase in accidents involving pedestrians (especially children) crossing the street. A common philosophy of existing pedestrian detection approaches is that this task should be undertaken by the moving cars themselves. In sharp departure from this philosophy, we propose to enlist the help of cars parked along the sidewalk to detect and protect crossing pedestrians. In support of this goal, we propose ADOPT: a system for Alerting Drivers to Occluded Pedestrian Traffic. ADOPT lays the theoretical foundations of a system that uses parked cars to: (1) detect the presence of a group of crossing pedestrians - a crossing cohort; (2) predict the time the last member of the cohort takes to clear the street; (3) send alert messages to those approaching cars that may reach the crossing area while pedestrians are still in the street; and, (4) show how approaching cars can adjust their speed, given several simultaneous crossing locations. Importantly, in ADOPT all communications occur over very short distances and at very low power. Our extensive simulations using SUMO-generated pedestrian and car traffic have shown the effectiveness of ADOPT in detecting and protecting crossing pedestrians

Child development and the aims of road safety education

Pedestrian accidents are one of the most prominent causes of premature injury, handicap and death in the modern world. In children, the problem is so severe that pedestrian accidents are widely regarded as the most serious of all health risks facing children in developed countries. Not surprisingly, educational measures have long been advocated as a means of teaching children how to cope with traffic and substantial resources have been devoted to their development and provision. Unfortunately, there seems to be a widespread view at the present time that education has not achieved as much as had been hoped and that there may even be quite strict limits to what can be achieved through education. This would, of course, shift the emphasis away from education altogether towards engineering or urban planning measures aimed at creating an intrinsically safer environment in which the need for education might be reduced or even eliminated. However, whilst engineering measures undoubtedly have a major role to play in the effort to reduce accidents, this outlook is both overly optimistic about the benefits of engineering and overly pessimistic about the limitations of education. At the same time, a fresh analysis is clearly required both of the aims and methods of contemporary road safety education. The present report is designed to provide such an analysis and to establish a framework within which further debate and research can take place

A Comprehensive Approach to WSN-Based ITS Applications: A Survey

In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

Effect on Speed Distribution due to Intrusive and Non-Intrusive Portable Speed Measurement Devices

Accurate traffic data are essential for supporting a multitude of transportation related decisions which affect transportation system operations, management, and planning. Advanced technology offers us various alternatives for accurately collecting traffic data. But accuracy of data is not just about the mechanical accuracy of the device, but it also about how people react when they see these devices installed either on roads or off roads. It is very important that the drivers should not get affected by the presence of these devices as these devices are not always to control the speeds but they are also installed to measure the true speed of the drivers. Such studies are the basis for important decisions, such as setting speed limits, timing traffic signals, placing traffic signs, and determining the effectiveness of the countermeasures. To evaluate the effectiveness on speed distribution due to the presence of various intrusive and non-intrusive portable speed measurement devices, automated traffic counters with pneumatic tubes, Smartsensor, Autoscope with camera trailer and Lidar gun were compared. Results showed that drivers did not react to pneumatic tubes and continued driving at the same speed; there was no significant difference in speeds at different locations while pneumatic tubes were installed. Drivers tend to react most by reducing their speeds when a Lidar gun was used, the Autoscope with camera trailer also effected driver behavior to a considerable amount. There was slight increase in speeds when the Smartsensor was installed. Similar driver behavior was observed when effect on the speeds of faster drivers was evaluated. For this analysis drivers driving above 85th percentile speeds were picked and tracked throughout the test site. Drivers reacted most to Lidar guns and then to the Autoscope with camera trailer. There was no significant difference in speeds when pneumatic tubes were installed

Effects of Emergency Vehicle Warning Lighting System Characteristics on Driver Perception and Behavior

Secondary crashes, including struck-by incidents are a leading cause of line-of-duty deaths among emergency responders, such as firefighters, law enforcement officers, and emergency medical service providers. The introduction of light emitting diode (LED) sources and advanced lighting control systems, provides a wide range of options for emergency lighting configurations. This study investigated the impact of lighting color, intensity, modulation, and flash rate on driver behavior while traversing a traffic incident scene at night. The impact of retroreflective chevron markings in combination with lighting configurations, as well as the measurement of “moth-to-flame” effects of emergency lighting on drivers was also investigated. The results indicate that higher intensity lights were judged consistently as more glaring, but were only rated as marginally more visible. This finding may suggest that dimming emergency lights at night could results in near equal visibility, but with significantly less glare. The rated visibility of the lights appears to be related to the perceived saturation of the color, while discomfort glare is related to the amount of short-wavelength spectral content. This suggest colors at the extreme ends of the light spectrum (red and blue) are more visible. However, the results indicate that blue lights, with their shorter wavelength are more glaring than red lights. Therefore, red may be a better choice for emergency vehicle lighting at night. The results also suggest that the presence of very highly reflective markings may decrease drivers’ ability to see first responders working adjacent to their vehicles. This is likely because the retro-reflective sheeting is compounding the emergency lighting visible to the drivers as well as the reflection of the driver’s headlights against the sheeting. Taking the study in its totality, it is likely that national standards are needed which specify the maximum intensities for emergency vehicle lighting at night. Further research is needed to identify these levels and likewise investigate the maximum luminance for retro-reflective sheeting

A System for the Generation of Synthetic Wide Area Aerial Surveillance Imagery

The development, benchmarking and validation of aerial Persistent Surveillance (PS) algorithms requires access to specialist Wide Area Aerial Surveillance (WAAS) datasets. Such datasets are difficult to obtain and are often extremely large both in spatial resolution and temporal duration. This paper outlines an approach to the simulation of complex urban environments and demonstrates the viability of using this approach for the generation of simulated sensor data, corresponding to the use of wide area imaging systems for surveillance and reconnaissance applications. This provides a cost-effective method to generate datasets for vehicle tracking algorithms and anomaly detection methods. The system fuses the Simulation of Urban Mobility (SUMO) traffic simulator with a MATLAB controller and an image generator to create scenes containing uninterrupted door-to-door journeys across large areas of the urban environment. This ‘pattern-of-life’ approach provides three-dimensional visual information with natural movement and traffic flows. This can then be used to provide simulated sensor measurements (e.g. visual band and infrared video imagery) and automatic access to ground-truth data for the evaluation of multi-target tracking systems

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Smart streetlights: a feasibility study

The world's cities are growing. The effects of population growth and urbanisation mean that more people are living in cities than ever before, a trend set to continue. This urbanisation poses problems for the future. With a growing population comes more strain on local resources, increased traffic and congestion, and environmental decline, including more pollution, loss of green spaces, and the formation of urban heat islands. Thankfully, many of these stressors can be alleviated with better management and procedures, particularly in the context of road infrastructure. For example, with better traffic data, signalling can be smoothed to reduce congestion, parking can be made easier, and streetlights can be dimmed in real time to match real-world road usage. However, obtaining this information on a citywide scale is prohibitively expensive due to the high costs of labour and materials associated with installing sensor hardware. This study investigated the viability of a streetlight-integrated sensor system to affordably obtain traffic and environmental information. This investigation was conducted in two stages: 1) the development of a hardware prototype, and 2) evaluation of an evolved prototype system. In Stage 1 of the study, the development of the prototype sensor system was conducted over three design iterations. These iterations involved, in iteration 1, the live deployment of the prototype system in an urban setting to select and evaluate sensors for environmental monitoring, and in iterations 2 and 3, deployments on roads with live and controlled traffic to develop and test sensors for remote traffic detection. In the final iteration, which involved controlled passes of over 600 vehicle, 600 pedestrian, and 400 cyclist passes, the developed system that comprised passive-infrared motion detectors, lidar, and thermal sensors, could detect and count traffic from a streetlight-integrated configuration with 99%, 84%, and 70% accuracy, respectively. With the finalised sensor system design, Stage 1 showed that traffic and environmental sensing from a streetlight-integrated configuration was feasible and effective using on-board processing with commercially available and inexpensive components. In Stage 2, financial and social assessments of the developed sensor system were conducted to evaluate its viability and value in a community. An evaluation tool for simulating streetlight installations was created to measure the effects of implementing the smart streetlight system. The evaluation showed that the on-demand traffic-adaptive dimming enabled by the smart streetlight system was able to reduce the electrical and maintenance costs of lighting installations. As a result, a 'smart' LED streetlight system was shown to outperform conventional always-on streetlight configurations in terms of financial value within a period of five to 12 years, depending on the installation's local traffic characteristics. A survey regarding the public acceptance of smart streetlight systems was also conducted and assessed the factors that influenced support of its applications. In particular, the Australia-wide survey investigated applications around road traffic improvement, streetlight dimming, and walkability, and quantified participants' support through willingness-to-pay assessments to enable each application. Community support of smart road applications was generally found to be positive and welcomed, especially in areas with a high dependence on personal road transport, and from participants adversely affected by spill light in their homes. Overall, the findings of this study indicate that our cities, and roads in particular, can and should be made smarter. The technology currently exists and is becoming more affordable to allow communities of all sizes to implement smart streetlight systems for the betterment of city services, resource management, and civilian health and wellbeing. The sooner that these technologies are embraced, the sooner they can be adapted to the specific needs of the community and environment for a more sustainable and innovative future