Pub Date : 2021-06-07DOI: 10.5772/INTECHOPEN.97690
Prem Chand Jain
The objective of Intelligent transportation system (ITS) and related National highway traffic safety administration (NHTSA) is to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by the driver to take the decision. Vehicular communication is a part of Intelligent Transport System which provides an intelligent way of transport to avoid accidents. As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes important. Connected vehicles can be used for both infotainment and navigation for vehicle safety. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. C-V2X (Cellular-Vehicle-to-Everything) can provide better quality of service support, large coverage, and high data rate for moving vehicles. Device-to-device (D2D) communication in C-V2X provides high reliability and low latency. In 5G Rel.16 C-V2X will become an integral part of 5G cellular network providing higher capacity, coverage, etc. Today old aged/disabled person look for driving technology that is convenient and easy to use. V2X technology will offset some of the concerns about old aged/disabled driver’s abilities to respond quickly to challenge by driving environment as they no longer be required to handle most of the decisions.
{"title":"Trends in Next Generation Intelligent Transportation Systems","authors":"Prem Chand Jain","doi":"10.5772/INTECHOPEN.97690","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.97690","url":null,"abstract":"The objective of Intelligent transportation system (ITS) and related National highway traffic safety administration (NHTSA) is to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by the driver to take the decision. Vehicular communication is a part of Intelligent Transport System which provides an intelligent way of transport to avoid accidents. As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes important. Connected vehicles can be used for both infotainment and navigation for vehicle safety. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. C-V2X (Cellular-Vehicle-to-Everything) can provide better quality of service support, large coverage, and high data rate for moving vehicles. Device-to-device (D2D) communication in C-V2X provides high reliability and low latency. In 5G Rel.16 C-V2X will become an integral part of 5G cellular network providing higher capacity, coverage, etc. Today old aged/disabled person look for driving technology that is convenient and easy to use. V2X technology will offset some of the concerns about old aged/disabled driver’s abilities to respond quickly to challenge by driving environment as they no longer be required to handle most of the decisions.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126910505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-26DOI: 10.5772/INTECHOPEN.97108
M. Longo, W. Yaïci, F. Foiadelli
The trends of main interest on a global scale are those that can influence the development of humanity in the long term and are sometimes referred to as megatrends. The changes they bring with them can span several generations, profoundly changing society and, consequently, the competitive landscape of companies. The megatrends are numerous and each one involves the development of entire areas of activity. It is important to identify the megatrends of interest for strategic mobility planning and follow their developments, in order to consider them in the planning processes and correctly pilot investments. Megatrends are made possible and also influenced by the offer of new technologies, and lead to changes in cultural models. This chapter shows an era characterized by major technological innovations that are changing people’s ways of thinking and acting, with the establishment of new mobility models in order to meet new emerging needs.
{"title":"Future Mobility Advances and Trends","authors":"M. Longo, W. Yaïci, F. Foiadelli","doi":"10.5772/INTECHOPEN.97108","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.97108","url":null,"abstract":"The trends of main interest on a global scale are those that can influence the development of humanity in the long term and are sometimes referred to as megatrends. The changes they bring with them can span several generations, profoundly changing society and, consequently, the competitive landscape of companies. The megatrends are numerous and each one involves the development of entire areas of activity. It is important to identify the megatrends of interest for strategic mobility planning and follow their developments, in order to consider them in the planning processes and correctly pilot investments. Megatrends are made possible and also influenced by the offer of new technologies, and lead to changes in cultural models. This chapter shows an era characterized by major technological innovations that are changing people’s ways of thinking and acting, with the establishment of new mobility models in order to meet new emerging needs.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-24DOI: 10.5772/intechopen.95328
S. Easa, Yang Ma, A. Elshorbagy, A. Shaker, Songnian Li, S. Arkatkar
The three main elements of autonomous vehicles (AV) are orientation, visibility, and decision. This chapter presents an overview of the implementation of visibility-based technologies and methodologies. The chapter first presents two fundamental aspects that are necessary for understanding the main contents. The first aspect is highway geometric design as it relates to sight distance and highway alignment. The second aspect is mathematical basics, including coordinate transformation and visual space segmentation. Details on the Light Detection and Ranging (Lidar) system, which represents the ‘eye’ of the AV are presented. In particular, a new Lidar 3D mapping system, that can be operated on different platforms and modes for a new mapping scheme is described. The visibility methodologies include two types. Infrastructure visibility mainly addresses high-precision maps and sight obstacle detection. Traffic visibility (vehicles, pedestrians, and cyclists) addresses identification of critical positions and visibility estimation. Then, an overview of the decision element (path planning and intelligent car-following) for the movement of AV is presented. The chapter provides important information for researchers and therefore should help to advance road safety for autonomous vehicles.
{"title":"Visibility-Based Technologies and Methodologies for Autonomous Driving","authors":"S. Easa, Yang Ma, A. Elshorbagy, A. Shaker, Songnian Li, S. Arkatkar","doi":"10.5772/intechopen.95328","DOIUrl":"https://doi.org/10.5772/intechopen.95328","url":null,"abstract":"The three main elements of autonomous vehicles (AV) are orientation, visibility, and decision. This chapter presents an overview of the implementation of visibility-based technologies and methodologies. The chapter first presents two fundamental aspects that are necessary for understanding the main contents. The first aspect is highway geometric design as it relates to sight distance and highway alignment. The second aspect is mathematical basics, including coordinate transformation and visual space segmentation. Details on the Light Detection and Ranging (Lidar) system, which represents the ‘eye’ of the AV are presented. In particular, a new Lidar 3D mapping system, that can be operated on different platforms and modes for a new mapping scheme is described. The visibility methodologies include two types. Infrastructure visibility mainly addresses high-precision maps and sight obstacle detection. Traffic visibility (vehicles, pedestrians, and cyclists) addresses identification of critical positions and visibility estimation. Then, an overview of the decision element (path planning and intelligent car-following) for the movement of AV is presented. The chapter provides important information for researchers and therefore should help to advance road safety for autonomous vehicles.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123768886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-18DOI: 10.5772/intechopen.95060
D. Kotarski, P. Piljek, J. Kasać
Unmanned aerial vehicles (UAVs) have proven to be an advanced tool for a variety of applications in the civilian and military sectors. Different categories of UAVs are used in various missions and are also the subject of numerous researches. Due to their characteristics and potential in specific conditions, multirotor UAVs imposes itself as a solution for many tasks, including transport. This chapter presents a conceptual solution of autonomous cargo transportation where the primary research objective is the design of a heavy lift multirotor UAV system. The process of designing a multirotor UAV that can carry heavy lift cargo is quite challenging due to many parameters and constraints. Five selected series of electric propulsion systems are analyzed, with different multirotor configurations, and results are graphically displayed for payloads from 10 kg up to 100 kg.
{"title":"Design Considerations for Autonomous Cargo Transportation Multirotor UAVs","authors":"D. Kotarski, P. Piljek, J. Kasać","doi":"10.5772/intechopen.95060","DOIUrl":"https://doi.org/10.5772/intechopen.95060","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have proven to be an advanced tool for a variety of applications in the civilian and military sectors. Different categories of UAVs are used in various missions and are also the subject of numerous researches. Due to their characteristics and potential in specific conditions, multirotor UAVs imposes itself as a solution for many tasks, including transport. This chapter presents a conceptual solution of autonomous cargo transportation where the primary research objective is the design of a heavy lift multirotor UAV system. The process of designing a multirotor UAV that can carry heavy lift cargo is quite challenging due to many parameters and constraints. Five selected series of electric propulsion systems are analyzed, with different multirotor configurations, and results are graphically displayed for payloads from 10 kg up to 100 kg.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131619472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-17DOI: 10.5772/intechopen.95039
P. Turek, S. Grzywiński, W. Bużantowicz
The sensitivity of global navigation satellite systems to disruptions precludes their use in conditions of armed conflict with an opponent possessing comparable technical capabilities. In military unmanned aerial vehicles (UAVs) the aim is to obtain navigational data to determine the location and correction of flight routes by means of other types of navigational systems. To correct the position of an UAV relative to a given trajectory, the systems that associate reference terrain maps with image information can be used. Over the last dozen or so years, new, effective algorithms for matching digital images have been developed. The results of their performance effectiveness are based on images that are fragments taken from source files, and therefore their qualitatively identical counterparts exist in the reference images. However, the differences between the reference image stored in the memory of navigation system and the image recorded by the sensor can be significant. In this paper modern methods of image registration and matching to UAV position refinement are compared, and adaptation of available methods to the operating conditions of the UAV navigation system is discussed.
{"title":"Selected Issues and Constraints of Image Matching in Terrain-Aided Navigation: A Comparative Study","authors":"P. Turek, S. Grzywiński, W. Bużantowicz","doi":"10.5772/intechopen.95039","DOIUrl":"https://doi.org/10.5772/intechopen.95039","url":null,"abstract":"The sensitivity of global navigation satellite systems to disruptions precludes their use in conditions of armed conflict with an opponent possessing comparable technical capabilities. In military unmanned aerial vehicles (UAVs) the aim is to obtain navigational data to determine the location and correction of flight routes by means of other types of navigational systems. To correct the position of an UAV relative to a given trajectory, the systems that associate reference terrain maps with image information can be used. Over the last dozen or so years, new, effective algorithms for matching digital images have been developed. The results of their performance effectiveness are based on images that are fragments taken from source files, and therefore their qualitatively identical counterparts exist in the reference images. However, the differences between the reference image stored in the memory of navigation system and the image recorded by the sensor can be significant. In this paper modern methods of image registration and matching to UAV position refinement are compared, and adaptation of available methods to the operating conditions of the UAV navigation system is discussed.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127178542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.5772/INTECHOPEN.93856
C. Wolmar
There has been considerable hype about the expectations around driverless cars but tests and trials have shown that the concept is far more difficult to bring to fruition than expected. Since around 2010, there have been predictions of the imminent arrival of driverless cars. All these predictions have proved to be over optimistic and none of the goals have been achieved. Companies like Waymo, who are most advanced in the field, are beginning to admit that the task they faced is far more difficult than originally envidaged. This chapter will examine the obstacles to the achievement of the driverless car concept and assess whether the models of shared use driverless vehicle posited by the auto manufacturers and tech companies are realistic.
{"title":"The Long Journey of the Driverless Car","authors":"C. Wolmar","doi":"10.5772/INTECHOPEN.93856","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.93856","url":null,"abstract":"There has been considerable hype about the expectations around driverless cars but tests and trials have shown that the concept is far more difficult to bring to fruition than expected. Since around 2010, there have been predictions of the imminent arrival of driverless cars. All these predictions have proved to be over optimistic and none of the goals have been achieved. Companies like Waymo, who are most advanced in the field, are beginning to admit that the task they faced is far more difficult than originally envidaged. This chapter will examine the obstacles to the achievement of the driverless car concept and assess whether the models of shared use driverless vehicle posited by the auto manufacturers and tech companies are realistic.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123346582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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