A Study on Recent Developments and Issues with Obstacle Detection Systems for Automated Vehicles

This paper reviews current developments and discusses some critical issues with obstacle detection systems for automated vehicles. The concept of autonomous driving is the driver towards future mobility. Obstacle detection systems play a crucial role in implementing and deploying autonomous driving on our roads and city streets. The current review looks at technology and existing systems for obstacle detection. Specifically, we look at the performance of LIDAR, RADAR, vision cameras, ultrasonic sensors, and IR and review their capabilities and behaviour in a number of different situations: during daytime, at night, in extreme weather conditions, in urban areas, in the presence of smooths surfaces, in situations where emergency service vehicles need to be detected and recognised, and in situations where potholes need to be observed and measured. It is suggested that combining different technologies for obstacle detection gives a more accurate representation of the driving environment. In particular, when looking at technological solutions for obstacle detection in extreme weather conditions (rain, snow, fog), and in some specific situations in urban areas (shadows, reflections, potholes, insufficient illumination), although already quite advanced, the current developments appear to be not sophisticated enough to guarantee 100% precision and accuracy, hence further valiant effort is needed

Frozen city: Analysing the disruption and resilience of urban activities during a heavy snowfall event using Google Popular Times

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establishments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure activities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field

Enhancing Road Infrastructure Monitoring: Integrating Drones for Weather-Aware Pothole Detection

The abstract outlines the research proposal focused on the utilization of Unmanned Aerial Vehicles (UAVs) for monitoring potholes in road infrastructure affected by various weather conditions. The study aims to investigate how different materials used to fill potholes, such as water, grass, sand, and snow-ice, are impacted by seasonal weather changes, ultimately affecting the performance of pavement structures. By integrating weather-aware monitoring techniques, the research seeks to enhance the rigidity and resilience of road surfaces, thereby contributing to more effective pavement management systems. The proposed methodology involves UAV image-based monitoring combined with advanced super-resolution algorithms to improve image refinement, particularly at high flight altitudes. Through case studies and experimental analysis, the study aims to assess the geometric precision of 3D models generated from aerial images, with a specific focus on road pavement distress monitoring. Overall, the research aims to address the challenges of traditional road failure detection methods by exploring cost-effective 3D detection techniques using UAV technology, thereby ensuring safer roadways for all users

Anti-collision systems in tunneling to improve effectiveness and safety in a system-quality approach: A review of the state of the art

Tunnelling and underground construction operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can lead to collisions between vehicles or between vehicles and pedestrians or structural elements, causing accidents and fatalities. To improve the OS&H conditions, it is important to investigate the possible introduction of innovative techniques and technologies to reduce the occurrences and consequences of shared spaces (spaces used by both vehicles and pedestrians). For this reason, research was conducted to investigate the possible use of different technologies of anti-collision systems in tunnelling operations. First, to achieve this goal, an extensive review of the literature was carried out in accordance with the PRISMA statement to select the current techniques and technologies used by general anti-collision systems in civil and mining construction sites. Then, the operating principles, the relative advantages and disadvantages, combinations, and costs were examined for each of these. Eight types of systems and many examples of applications of anti-collision systems in underground environments were identified as a result of the analysis of the literature. Generally, it was noted that the anti-collision techniques available have found limited application in the excavation sites of underground civil works up to the present day, though the improvement in terms of safety and efficiency would be considerable

Weather related pedestrians' slip risks and predicting sidewalk slipperiness

Wintertime slip injuries are a very common problem in Finland as well as in other countries where winter conditions are frequent. According to surveys, on average every third person in Finland slips each winter and more than 50,000 persons are injured needing medical attention. Slipping causes human suffering as well as significant financial costs due to medical expenses and sick leaves. On some of the most slippery days, the number of slipping injuries can be so high that the hospital emergency departments are crowded with patients requiring surgery. The severity of slipping injuries typically increases with age. In addition, the number of slips and slip related injuries are more common among women than men. Finland has set a goal to increase the share of sustainable transport modes, such as walking and cycling, in the future. The aim is to reduce greenhouse gas emissions from transport and improve public health. Walking and cycling are to be the primary means of transport, especially for short distances in dense urban areas. In addition, the aim is to improve traffic safety and to develop walking and cycling infrastructure. This dissertation presents in which weather situations slips occur more than usual. In addition, the work presents a meteorological tool to help predicting weather conditions that cause pedestrian sidewalk slipperiness. Weather has a significant role in pedestrian’s wintertime slips and resulting injuries. In this dissertation, it has been investigated what are the weather situations that increase the risk of slipping and what is the spatio-temporal distribution of slips. Special attention has been given to situations with clearly more slips than usual, i.e. so called peak days of slipping injuries. The results show that snow and ice significantly increase the risk of slipping, and that most of the wintertime slips occur when the temperature is near zero degrees or slightly below it. This dissertation presents a numerical model predicting slipperiness from the pedestrian’s point of view. The model is developed at the Finnish Meteorological Institute. The thesis presents the physical principles of the model and how the slipperiness classification is implemented. The model is a tool for meteorologists to supports the decision making when issuing warnings about slippery sidewalk conditions. In addition, the model benefits winter road maintenance personnel and also public with better sidewalk condition and issued warnings. Climate change will have a major impact on future winters, especially in the northern latitudes. The winter season is shortened and near zero temperatures are becoming more frequent also during mid-winter, meaning more slippery conditions during that period. It is expected that the slip period will become shorter but at the same time more intense.Talvikauden liukastumisonnettomuudet ovat hyvin yleinen ongelma Suomessa niin kuin myös muissa maissa, joissa talviolosuhteet ovat yleisiä. Kyselytutkimusten perusteella noin joka kolmas suomalainen liukastuu talvisin ja noin 50 000 liukastuu niin pahasti, että joutuu käymään sairaalassa tai ensiavussa liukastumisvammojen vuoksi. Liukastumista aiheutuu inhimillistä kärsimystä sekä merkittäviä taloudellisia kustannuksia niin sairaanhoitokulujen kuin sairauspoissaolojen kautta. Pahimpina päivinä liukastumisia saattaa tapahtua niin paljon, että sairaaloiden päivystykset ruuhkautuvat leikkausta tarvitsevista potilaista. Liukastumisvammojen vakavuus kasvaa yleensä iän myötä. Lisäksi liukastumisia ja niistä aiheutuvia vammoja sattuu enemmän naisille kuin miehille. Suomi on asettanut tavoitteeksi lisätä kestävien liikennemuotojen, kuten kävelyn ja pyöräilyn, kulkutapaosuutta tulevaisuudessa. Tavoitteena on liikenteestä aiheutuvia kasvihuonepäästöjen vähentäminen sekä kansanterveyden parantaminen. Kävely ja pyöräily halutaan saada ensisijaiseksi liikkumismuodoksi etenkin tiiviillä kaupunkiseudulla lyhyillä matkoilla. Lisäksi tavoitteena on parantaa liikenneturvallisuutta sekä kehittää kävely- ja pyöräilyinfrastruktuuria. Tämä väitöskirjatyö esittelee säätilanteita, joissa liukastumisia sattuu tavanomaista enemmän. Lisäksi työssä esitellään meteorologinen työkalu, joka auttaa jalankulkuliukkautta aiheuttavien säätilanteiden ennustamisessa. Säällä on merkittävä vaikutus jalankulkijoiden talvikauden liukastumismääriin. Tässä väitöskirjatyössä on tutkittu, mitkä säätekijät lisäävät liukastumisriskiä ja miten liukastumismäärät jakautuvat alueellisti ja ajallisesti. Erityishuomio on tilanteissa, joissa liukastumisia sattuu selvästi tavanomaista enemmän, eli ns. liukastumisten piikkipäivissä. Tulokset osoittavat, että lumi ja jää lisäävät selvästi liukastumisriskiä ja suurin osa talvikauden liukastumisista sattuu silloin, kun lämpötila on nollan vaiheilla tai vähän pakkasen puolella. Tässä väitöskirjatyössä esitellään Ilmatieteen laitoksella kehitetty numeerinen malli, joka ennustaa jalkakäytävien liukkautta. Työ esittelee mallin fysikaalisen toiminnan ja sen, miten liukkauden mallintaminen on toteutettu. Malli toimii päivystävien meteorologien apuvälineenä ja päätöksenteon tukena, kun annetaan varoituksia erittäin liukkaista jalkakäytävistä. Meteorologien lisäksi mallista hyötyvät myös kaupungin teiden talvikunnossapito sekä varoitusten kautta myös kansalaiset. Ilmastonmuutos tulee vaikuttamaan voimakkaasti tulevaisuuden talviin etenkin pohjoisilla leveyspiireillä. Talvikausi tulee lyhenemään ja nollan läheisiä lämpötiloja ennustetaan olevan tulevaisuudessa enemmän. Tämä tarkoittaa, että liukkautta esiintynee tulevaisuudessa enemmän myös keskitalvella. On odotettavissa, että liukastumiskausi tulee muuttumaan lyhyemmäksi mutta samalla intensiivisemmäksi

Weather related pedestrians' slip risks and predicting sidewalk slipperiness

Wintertime slip injuries are a very common problem in Finland as well as in other countries where winter conditions are frequent. According to surveys, on average every third person in Finland slips each winter and more than 50,000 persons are injured needing medical attention. Slipping causes human suffering as well as significant financial costs due to medical expenses and sick leaves. On some of the most slippery days, the number of slipping injuries can be so high that the hospital emergency departments are crowded with patients requiring surgery. The severity of slipping injuries typically increases with age. In addition, the number of slips and slip related injuries are more common among women than men. Finland has set a goal to increase the share of sustainable transport modes, such as walking and cycling, in the future. The aim is to reduce greenhouse gas emissions from transport and improve public health. Walking and cycling are to be the primary means of transport, especially for short distances in dense urban areas. In addition, the aim is to improve traffic safety and to develop walking and cycling infrastructure. This dissertation presents in which weather situations slips occur more than usual. In addition, the work presents a meteorological tool to help predicting weather conditions that cause pedestrian sidewalk slipperiness. Weather has a significant role in pedestrian’s wintertime slips and resulting injuries. In this dissertation, it has been investigated what are the weather situations that increase the risk of slipping and what is the spatio-temporal distribution of slips. Special attention has been given to situations with clearly more slips than usual, i.e. so called peak days of slipping injuries. The results show that snow and ice significantly increase the risk of slipping, and that most of the wintertime slips occur when the temperature is near zero degrees or slightly below it. This dissertation presents a numerical model predicting slipperiness from the pedestrian’s point of view. The model is developed at the Finnish Meteorological Institute. The thesis presents the physical principles of the model and how the slipperiness classification is implemented. The model is a tool for meteorologists to supports the decision making when issuing warnings about slippery sidewalk conditions. In addition, the model benefits winter road maintenance personnel and also public with better sidewalk condition and issued warnings. Climate change will have a major impact on future winters, especially in the northern latitudes. The winter season is shortened and near zero temperatures are becoming more frequent also during mid-winter, meaning more slippery conditions during that period. It is expected that the slip period will become shorter but at the same time more intense.Talvikauden liukastumisonnettomuudet ovat hyvin yleinen ongelma Suomessa niin kuin myös muissa maissa, joissa talviolosuhteet ovat yleisiä. Kyselytutkimusten perusteella noin joka kolmas suomalainen liukastuu talvisin ja noin 50 000 liukastuu niin pahasti, että joutuu käymään sairaalassa tai ensiavussa liukastumisvammojen vuoksi. Liukastumista aiheutuu inhimillistä kärsimystä sekä merkittäviä taloudellisia kustannuksia niin sairaanhoitokulujen kuin sairauspoissaolojen kautta. Pahimpina päivinä liukastumisia saattaa tapahtua niin paljon, että sairaaloiden päivystykset ruuhkautuvat leikkausta tarvitsevista potilaista. Liukastumisvammojen vakavuus kasvaa yleensä iän myötä. Lisäksi liukastumisia ja niistä aiheutuvia vammoja sattuu enemmän naisille kuin miehille. Suomi on asettanut tavoitteeksi lisätä kestävien liikennemuotojen, kuten kävelyn ja pyöräilyn, kulkutapaosuutta tulevaisuudessa. Tavoitteena on liikenteestä aiheutuvia kasvihuonepäästöjen vähentäminen sekä kansanterveyden parantaminen. Kävely ja pyöräily halutaan saada ensisijaiseksi liikkumismuodoksi etenkin tiiviillä kaupunkiseudulla lyhyillä matkoilla. Lisäksi tavoitteena on parantaa liikenneturvallisuutta sekä kehittää kävely- ja pyöräilyinfrastruktuuria. Tämä väitöskirjatyö esittelee säätilanteita, joissa liukastumisia sattuu tavanomaista enemmän. Lisäksi työssä esitellään meteorologinen työkalu, joka auttaa jalankulkuliukkautta aiheuttavien säätilanteiden ennustamisessa. Säällä on merkittävä vaikutus jalankulkijoiden talvikauden liukastumismääriin. Tässä väitöskirjatyössä on tutkittu, mitkä säätekijät lisäävät liukastumisriskiä ja miten liukastumismäärät jakautuvat alueellisti ja ajallisesti. Erityishuomio on tilanteissa, joissa liukastumisia sattuu selvästi tavanomaista enemmän, eli ns. liukastumisten piikkipäivissä. Tulokset osoittavat, että lumi ja jää lisäävät selvästi liukastumisriskiä ja suurin osa talvikauden liukastumisista sattuu silloin, kun lämpötila on nollan vaiheilla tai vähän pakkasen puolella. Tässä väitöskirjatyössä esitellään Ilmatieteen laitoksella kehitetty numeerinen malli, joka ennustaa jalkakäytävien liukkautta. Työ esittelee mallin fysikaalisen toiminnan ja sen, miten liukkauden mallintaminen on toteutettu. Malli toimii päivystävien meteorologien apuvälineenä ja päätöksenteon tukena, kun annetaan varoituksia erittäin liukkaista jalkakäytävistä. Meteorologien lisäksi mallista hyötyvät myös kaupungin teiden talvikunnossapito sekä varoitusten kautta myös kansalaiset. Ilmastonmuutos tulee vaikuttamaan voimakkaasti tulevaisuuden talviin etenkin pohjoisilla leveyspiireillä. Talvikausi tulee lyhenemään ja nollan läheisiä lämpötiloja ennustetaan olevan tulevaisuudessa enemmän. Tämä tarkoittaa, että liukkautta esiintynee tulevaisuudessa enemmän myös keskitalvella. On odotettavissa, että liukastumiskausi tulee muuttumaan lyhyemmäksi mutta samalla intensiivisemmäksi

Novel Environmental Features for Robust Multisensor Navigation

Many navigation techniques have now become so reliant on GNSS that there is no back up when there is limited or no signal reception. If there is interference, intentional or otherwise, with the signal, navigation could be lost or become misleading [1]. Other navigation techniques harness different technologies such as Wi-Fi [2], eLoran and inertial navigation. However, each of these techniques has its own limitations, such as coverage, degradation in urban areas or solution drift [3]. Therefore there is a need for new navigation and positioning techniques that may be integrated with GNSS to increase the reliability of the system as a whole. This paper presents the results of a feasibility study to identify a set of novel environmental features that could be used for navigation in the temporary absence of GNSS or degradation of the signal. By measuring these features during times of GNSS availability a map can be produced. This can be referred to during times of limited reception, a principle already used for some Wi-Fi positioning techniques [2]. Therefore a “measurable” can be defined as a feature either man-made or natural that is spatially distinct and has limited temporal variation. Possibilities considered include magnetic anomalies [4], light intensity and road signs. Firstly, a brainstorming exercise and a literature study were conducted to generate a list of possible environmental features that was assessed for the viability of each candidate. The features were ranked according to three criteria: practicality, precision and coverage. The definition of practicality for each measurable was that a suitable detector must be installable on a road vehicle, particularly an emergency vehicle, at a reasonable cost with minimal alterations to the vehicle. Precision was defined in terms of the spatial variation of the environmental feature and thus the accuracy with which position information might be derived from it. Coverage was assessed in terms of the availability of the feature over a range of different environments. Continuous coverage is not required because the new measurables may be used in combination and integrated with dead reckoning techniques, such as odometry and inertial navigation [3]. The outcome of the viability study was used to determine which features are to be experimentally tested. Magnetic anomalies, road texture and a dozen other environmental features were found to be worth investigation. Features which were discounted include wind speed and pulsars [5]. The initial experiment was carried out on foot in Central London. The same tests were repeated on two separate days, with a closed loop circuit walked three times on each occasion. This experiment used an Inertial Measurement Unit (IMU), comprising accelerometer and gyro triads, together with a barometer, three-axis magnetometer and GNSS receiver. The experiment was also recorded using a camcorder from the point of view of a pedestrian, enabling visual and audio features of the environment to be assessed. Magnetic anomalies were found to be a promising source of position information. Peaks in the magnetometer data were observed on all rounds at approximately the same positions. There were also similarities seen in the temperature profiles after correcting for the temporal variation of the background temperature. Another potential source of position information was found to be text-based signs. It is relatively simple to extract text from camera images and it is easily stored in a feature database. However, methods of dealing with identically-worded signs in close proximity will need to be developed. Sound levels were analysed in 10s intervals for the mean, minimum and maximum sound volume. There was no clear correlation observed between the different rounds of the experiment. Due to the pedestrian experimental results sound levels of the surroundings will not be used in further experimentation. An alternative area of enquiry for using sound (in the vehicular experiments) is using microphones to indirectly measure road texture based on the noise from the wheel contact with the road [6]. The paper will also present results of road vehicle experiments. Multiple circuits of the same routes will be compared. Different environments will be assessed including rural, dual carriageways, suburban and urban roads. Sensors to be used include the IMU and 3-axis magnetometer from the pedestrian experiment, a barometer, gas sensors, a microphone, an axle-mounted accelerometer, an ambient light sensor and a thermometer. These will be placed either on, inside or under the vehicle as determined by the individual needs of the sensors. The results will be used to determine which of these sensors could be potentially used for a multisensor integrated navigation system and also the environments in which they work optimally. Using the results of the three feasibility study phases (literature review, pedestrian and road experiment) the next project stage will be to produce a demonstration system that uses the most feasible features of the environment and creates a map database during times GNSS is present. This database will then be used for navigation in times of need. In the long term, it is envisaged that this technique will be implemented cooperatively, with a batch of vehicles collecting feature data and contributing it to a common shared database. / References [1] Thomas, M., et al., Global Navigation Space Systems: Reliance and Vulnerabilities, London, UK: Royal Academy of Engineering, 2011. [2] Jones, K., L. Liu, and F. Alizadeh-Shabdiz, “Improving Wireless Positioning with Look-ahead Map-Matching,” Proc. MobiQuitous 2007, Phildaelphia, PA, February 2008, pp. 1-8. [3] Groves, P.D., Principles of GNSS, Inertial, and Multisensor Intergrated Navigation Systems, Second Edition, Artech House, 2013. [4] Judd, T., and T. Vu, “Use of a New Pedometric Dead Reckoning Module in GPS Denied Environments,” Proc. IEEE/ION PLANS, Monterey, CA, May 2008, pp. 120?128. [5] Walter, D. J., "Feasibility study of novel environmental feature mapping to bridge GNSS outage," Young Navigator Conference, London, 2012. [6] Mircea, M., et al., “Strategic mapping of the ambient noise produced by road traffic, accordingly to European regulations,” Proc. IEEE International Conference on Automation, Quality and Testing, Robotics, Cluj Napoca, Romania, May 2008

Crowdsourcing geospatial data for Earth and human observations: a review

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors