Pub Date : 2018-09-01DOI: 10.1109/ICVES.2018.8519495
S. S. Mateo, E. Perez-Moreno, F. Jiménez, J. Naranjo, Carlos Giovanny Perez Flores, Juan Antoazas Teruel
Merging is considered a complex maneuver to perform safely due to the high attention required by the driver, and the external variables that make up an unstructured environment. In spite of the great amount of ADAS technologies that are being developed, at present there are few systems that help to carry out this maneuver. However, thanks to the use of V2V inter-vehicular communications to propose a driver assistance system is possible, facilitating this maneuver on highways. Since a situation of merging requires a high cognitive load, in this study some variables to propose the design of an HMI interface that helps the driver to perform the maneuver securely, are evaluated. Through eye tracking system, driving tests will be carried out on a real vehicle, where several merging maneuvers will be performed on highways.
{"title":"Study of a driver assistance interface for merging situations on highways","authors":"S. S. Mateo, E. Perez-Moreno, F. Jiménez, J. Naranjo, Carlos Giovanny Perez Flores, Juan Antoazas Teruel","doi":"10.1109/ICVES.2018.8519495","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519495","url":null,"abstract":"Merging is considered a complex maneuver to perform safely due to the high attention required by the driver, and the external variables that make up an unstructured environment. In spite of the great amount of ADAS technologies that are being developed, at present there are few systems that help to carry out this maneuver. However, thanks to the use of V2V inter-vehicular communications to propose a driver assistance system is possible, facilitating this maneuver on highways. Since a situation of merging requires a high cognitive load, in this study some variables to propose the design of an HMI interface that helps the driver to perform the maneuver securely, are evaluated. Through eye tracking system, driving tests will be carried out on a real vehicle, where several merging maneuvers will be performed on highways.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115424435","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 : 2018-09-01DOI: 10.1109/icves.2018.8519498
{"title":"[Copyright notice]","authors":"","doi":"10.1109/icves.2018.8519498","DOIUrl":"https://doi.org/10.1109/icves.2018.8519498","url":null,"abstract":"","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126194752","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519513
Yearlor Patou, S. Obana, Suhua Tang
Pedestrian-to-vehicle communication, which delivers pedestrian position to vehicles to enable real-time estimation of pedestrian-vehicle distance even in the absence of line-of-sight path, has attracted much attention recently. This heavily relies on GPS, whose positioning performance, however, may be greatly degraded in urban canyons due to the influence of multipath error. In this paper, we first investigate the spatial correlation of multipath error. Then, we propose to estimate the multipath error at a pedestrian by (a) using a regression model and (b) Ieveraging the multipath errors at nearby points, which may be, e.g., provided by vehicles that happen to be there. Finally, the pseudo-ranges, corrected by removing the estimated multipath errors, are used to compute an accurate pedestrian position. The proposed method is evaluated with ray tracing simulation and 3D map. Compared with single point positioning without dealing with multipath error, the proposed method greatly reduces pedestrian positioning error by almost one order of magnitude, to 2.2m in the urban areas of Tokyo.
{"title":"Improvement of Pedestrian Positioning Precision by Using Spatial Correlation of Multipath Error","authors":"Yearlor Patou, S. Obana, Suhua Tang","doi":"10.1109/ICVES.2018.8519513","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519513","url":null,"abstract":"Pedestrian-to-vehicle communication, which delivers pedestrian position to vehicles to enable real-time estimation of pedestrian-vehicle distance even in the absence of line-of-sight path, has attracted much attention recently. This heavily relies on GPS, whose positioning performance, however, may be greatly degraded in urban canyons due to the influence of multipath error. In this paper, we first investigate the spatial correlation of multipath error. Then, we propose to estimate the multipath error at a pedestrian by (a) using a regression model and (b) Ieveraging the multipath errors at nearby points, which may be, e.g., provided by vehicles that happen to be there. Finally, the pseudo-ranges, corrected by removing the estimated multipath errors, are used to compute an accurate pedestrian position. The proposed method is evaluated with ray tracing simulation and 3D map. Compared with single point positioning without dealing with multipath error, the proposed method greatly reduces pedestrian positioning error by almost one order of magnitude, to 2.2m in the urban areas of Tokyo.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115044142","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519499
A. Bystrov, E. Hoare, Thuy-Yung Tran, N. Clarke, M. Gashinova, M. Cherniakov
In this paper, we compare the common remote sensing technologies in terms of their application for road surface classification. The presence of surface classification system in a vehicle will increase the safety of driving, especially in adverse weather conditions, as well as when driving offroad. The paper presents an overview of the application of optical, laser, ultrasonic, and microwave sensors for surface classification. From the analysis it follows that sensor data fusion allows obtaining more accurate and reliable results.
{"title":"Sensors for Automotive Remote Road Surface Classification","authors":"A. Bystrov, E. Hoare, Thuy-Yung Tran, N. Clarke, M. Gashinova, M. Cherniakov","doi":"10.1109/ICVES.2018.8519499","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519499","url":null,"abstract":"In this paper, we compare the common remote sensing technologies in terms of their application for road surface classification. The presence of surface classification system in a vehicle will increase the safety of driving, especially in adverse weather conditions, as well as when driving offroad. The paper presents an overview of the application of optical, laser, ultrasonic, and microwave sensors for surface classification. From the analysis it follows that sensor data fusion allows obtaining more accurate and reliable results.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128786099","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519598
Fabio Reway, W. Huber, Eduardo Parente Ribeiro
In order to correctly perceive its surroundings, advanced driver-assistance systems (ADAS) rely on the data quality of environment sensors, such as cameras, and on the data processing to distinguish multiple classes of traffic participants. Real test drives are important for their testing and validation, but certain test scenarios are difficult to be reproduced or automated, e.g., adverse weather conditions. Therefore, it is essential to bring this system to a controlled virtual environment so that it is possible to determine their correctness and performance under these circumstances before their release. For this reason, Hardware-in-the-Loop testing methods have been increasingly utilized in the industry, with which real hardware is connected to driving simulation software and deficiencies can be identified in a early development phase. This paper presents a test setup with a real automotive Camera-in-the-Loop and a testing method to evaluate a proprietary algorithm for multi-class object detection of an ADAS platform available on the market and validate the specifications described by its manufacturer.
{"title":"Test Methodology for Vision-Based ADAS Algorithms with an Automotive Camera-in-the-Loop","authors":"Fabio Reway, W. Huber, Eduardo Parente Ribeiro","doi":"10.1109/ICVES.2018.8519598","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519598","url":null,"abstract":"In order to correctly perceive its surroundings, advanced driver-assistance systems (ADAS) rely on the data quality of environment sensors, such as cameras, and on the data processing to distinguish multiple classes of traffic participants. Real test drives are important for their testing and validation, but certain test scenarios are difficult to be reproduced or automated, e.g., adverse weather conditions. Therefore, it is essential to bring this system to a controlled virtual environment so that it is possible to determine their correctness and performance under these circumstances before their release. For this reason, Hardware-in-the-Loop testing methods have been increasingly utilized in the industry, with which real hardware is connected to driving simulation software and deficiencies can be identified in a early development phase. This paper presents a test setup with a real automotive Camera-in-the-Loop and a testing method to evaluate a proprietary algorithm for multi-class object detection of an ADAS platform available on the market and validate the specifications described by its manufacturer.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128598037","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519500
Borja Monsalve, Enrique Puertas, Javier Fernández, N. Aliane
Naturalistic Driving Studies (NDS) register data in real driving situations, trying to extract conclusions about how real drivers behave in specific situations, and for this purpose unobtrusive devices are used. In this paper, we present our work analyzing brain activity using Muse, a wearable electroencephalography (EEG) brain band, and an ad-hoc Android smartphone application. Our study is focuses in a specific maneuver: the roundabouts, and in the comparison between the brainwaves produced in that handling and in a straight section. For this purpose we made the same route in different moments of the day and under different weather conditions, and we isolate a specific stretch of six roundabouts and a straight one. Then we compare the beta and gamma brainwaves obtained in this two different maneuvers, which occurs in normal brain alert consciousness, attention or concentration states.
{"title":"Using wearable devices in naturalistic driving to analyze brain activity in roundabout maneuvers","authors":"Borja Monsalve, Enrique Puertas, Javier Fernández, N. Aliane","doi":"10.1109/ICVES.2018.8519500","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519500","url":null,"abstract":"Naturalistic Driving Studies (NDS) register data in real driving situations, trying to extract conclusions about how real drivers behave in specific situations, and for this purpose unobtrusive devices are used. In this paper, we present our work analyzing brain activity using Muse, a wearable electroencephalography (EEG) brain band, and an ad-hoc Android smartphone application. Our study is focuses in a specific maneuver: the roundabouts, and in the comparison between the brainwaves produced in that handling and in a straight section. For this purpose we made the same route in different moments of the day and under different weather conditions, and we isolate a specific stretch of six roundabouts and a straight one. Then we compare the beta and gamma brainwaves obtained in this two different maneuvers, which occurs in normal brain alert consciousness, attention or concentration states.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128604176","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 : 2018-09-01DOI: 10.1109/icves.2018.8519592
{"title":"ICVES 2018 Committees","authors":"","doi":"10.1109/icves.2018.8519592","DOIUrl":"https://doi.org/10.1109/icves.2018.8519592","url":null,"abstract":"","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"12 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131505443","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519484
Ray Lattarulo, Daniel Hess, Jose A. Matute, Joshué Pérez
Automated driving is one of the major tendencies in last decades, and it is presented as a reliable option to improve comfort during driving, including disable and elder in society and increasing persons safety in roads. This last topic produces the question how is it possible to verify planning and control algorithms for a reliable commercial use of this technology. The question can be answered from two perspective: experimental or formal methods, where the formal one is selected as the most robust between both. Hence, the current work presents a case study verification in automated driving for lane change and double lane change maneuvers, using as basis a trace conformance method presented in [1]. The verification method is performed in Dynacar as a precise multibody simulator tuned for a commercial Renault Twizy vehicle.
{"title":"Towards conformant models of automated electric vehicles","authors":"Ray Lattarulo, Daniel Hess, Jose A. Matute, Joshué Pérez","doi":"10.1109/ICVES.2018.8519484","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519484","url":null,"abstract":"Automated driving is one of the major tendencies in last decades, and it is presented as a reliable option to improve comfort during driving, including disable and elder in society and increasing persons safety in roads. This last topic produces the question how is it possible to verify planning and control algorithms for a reliable commercial use of this technology. The question can be answered from two perspective: experimental or formal methods, where the formal one is selected as the most robust between both. Hence, the current work presents a case study verification in automated driving for lane change and double lane change maneuvers, using as basis a trace conformance method presented in [1]. The verification method is performed in Dynacar as a precise multibody simulator tuned for a commercial Renault Twizy vehicle.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126409309","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519506
Weilong Song, Bo Su, Guang-ming Xiong, Shengfei Li
Autonomous vehicles need to face human-driving vehicles with their uncertain intentions in dynamic urban environment. Thus it leads to a challenging decision-making problem. In this paper, we focus on solving this problem in lane driving situation including performing lane changing or lane keeping maneuvers. A general POMDP model is formulated to represent autonomous driving decision-making process, and several approximations are applied to reduce the complexity of solving POMDP model. Firstly, we proposed a maneuver-based decomposition method to represent the possible candidate policies using path and velocity profiles in policy generation process. Secondly, a deterministic machine learning model is built to recognize human-driven vehicles’ driving intentions. Then, a situation prediction model is proposed to calculate the possible future actions of other vehicles considering cooperative driving behaviors. Finally, we build a multi-objective reward function to evaluation each policy. In addition, we test our methods in realistic simulation software. The experimental results show that our algorithm could perform lane keeping or lane changing maneuvers successfully.
{"title":"Intention-aware Decision Making in Urban Lane Change Scenario for Autonomous Driving","authors":"Weilong Song, Bo Su, Guang-ming Xiong, Shengfei Li","doi":"10.1109/ICVES.2018.8519506","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519506","url":null,"abstract":"Autonomous vehicles need to face human-driving vehicles with their uncertain intentions in dynamic urban environment. Thus it leads to a challenging decision-making problem. In this paper, we focus on solving this problem in lane driving situation including performing lane changing or lane keeping maneuvers. A general POMDP model is formulated to represent autonomous driving decision-making process, and several approximations are applied to reduce the complexity of solving POMDP model. Firstly, we proposed a maneuver-based decomposition method to represent the possible candidate policies using path and velocity profiles in policy generation process. Secondly, a deterministic machine learning model is built to recognize human-driven vehicles’ driving intentions. Then, a situation prediction model is proposed to calculate the possible future actions of other vehicles considering cooperative driving behaviors. Finally, we build a multi-objective reward function to evaluation each policy. In addition, we test our methods in realistic simulation software. The experimental results show that our algorithm could perform lane keeping or lane changing maneuvers successfully.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951988","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519589
Mustafa Alberri, S. Hegazy, Mohamed Badra, Mohamed Nasr, Omar M. Shehata, E. I. Morgan
Autonomous systems have been considered a strong field of attraction to the research community in the last few decades. Accordingly, this paper proposes a design and implementation of a generalized Robot Operating System (ROS) based architecture applicable for multi-autonomous systems in heterogeneous environments. The architecture allows inter-robotic data exchange for Vehicle-to-Vehicle communication by integrating embedded systems into the architecture structure. Moreover, the proposed architecture is a hierarchical one composed of three layers connected through various communication protocols, and characterized by being affordable, powerful and expansible. The architecture has been tested on three different platforms; autonomous mobile robot, autonomous vehicle and autonomous quad-copter. Results of the conducted experiments showed stability and successful operation of the proposed architecture.
{"title":"Generic ROS-based Architecture for Heterogeneous Multi-Autonomous Systems Development","authors":"Mustafa Alberri, S. Hegazy, Mohamed Badra, Mohamed Nasr, Omar M. Shehata, E. I. Morgan","doi":"10.1109/ICVES.2018.8519589","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519589","url":null,"abstract":"Autonomous systems have been considered a strong field of attraction to the research community in the last few decades. Accordingly, this paper proposes a design and implementation of a generalized Robot Operating System (ROS) based architecture applicable for multi-autonomous systems in heterogeneous environments. The architecture allows inter-robotic data exchange for Vehicle-to-Vehicle communication by integrating embedded systems into the architecture structure. Moreover, the proposed architecture is a hierarchical one composed of three layers connected through various communication protocols, and characterized by being affordable, powerful and expansible. The architecture has been tested on three different platforms; autonomous mobile robot, autonomous vehicle and autonomous quad-copter. Results of the conducted experiments showed stability and successful operation of the proposed architecture.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133825713","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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