Martin Ring, Jürgen Dürrwang, Florian Sommer, R. Kriesten
{"title":"Survey on vehicular attacks - building a vulnerability database","authors":"Martin Ring, Jürgen Dürrwang, Florian Sommer, R. Kriesten","doi":"10.1109/ICVES.2015.7396919","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396919","url":null,"abstract":"Modern cars are significantly linked to the outside world because of rising number of connections in the vehicle, connections between the vehicle and the exterior environment , e.g. diagnostics and flash interfaces or the numerous amounts of bus systems for data exchange. All these connections are potential security breaches. Previous papers and this research work show that there are a lot of security vulnerabilities in modern car connections. The aim of this paper is to merge the found vulnerabilities and the available results in literature, categorise them in the same way as in Information Technology (IT) and give an outlook on how most problems can be solved. This paper also aims to introduce an example database for automotive IT vulnerabilities.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124581545","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}
R. Hashimoto, R. Nomura, M. Kanbara, N. Ukita, Tetsushi Ikeda, Luis Yoichi Morales Saiki, Atsushi Watanabe, K. Shinozawa, N. Hagita
{"title":"Behavior representation of robotic wheelchairs with physiological indices for passenger comfort","authors":"R. Hashimoto, R. Nomura, M. Kanbara, N. Ukita, Tetsushi Ikeda, Luis Yoichi Morales Saiki, Atsushi Watanabe, K. Shinozawa, N. Hagita","doi":"10.1109/ICVES.2015.7396911","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396911","url":null,"abstract":"In this paper we propose a behavior representation system for robotic wheelchairs in which behavior information regarding the robotic wheelchair is provided to passengers to improve their sense of comfort; physiological indices are also used to measure passenger comfort. Many boarding-type robots (i.e., autonomous robots that carry passengers, such as autonomous vehicles, personal mobility robots, and robotic wheelchairs) have already been developed already. Most studies regarding this type of robot focus on safety control or efficient path planning but fail to consider passenger comfort. This paper describes how factors leading to passenger discomfort can be avoided by sharing behavior information. This study evaluates the validity of information sharing by estimating a stress level measured using heart rate and skin conductance as physiological indices. To investigate the relationship between different discomforting events and passengers' physiology indices, an experiment is conducted in which each passenger's physiology indices are measured while the autonomous robotic wheelchair is moving. For long-lasting stress events, the significant difference (p <; 0:01) in heart rate is shown by behavior representing of a robotic wheelchair with these indices. For strongly discomforting events, the significant difference (p <; 0:01) in skin response is also shown. These results show that the proposed system is effective for maintaining passenger comfort in robotic wheelchairs.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132391507","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}
Taishi Sawabe, M. Kanbara, N. Ukita, Tetsushi Ikeda, Luis Yoichi Morales Saiki, Atsushi Watanabe, N. Hagita
{"title":"Comfortable autonomous navigation based on collision prediction in blind occluded regions","authors":"Taishi Sawabe, M. Kanbara, N. Ukita, Tetsushi Ikeda, Luis Yoichi Morales Saiki, Atsushi Watanabe, N. Hagita","doi":"10.1109/ICVES.2015.7396897","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396897","url":null,"abstract":"This paper presents an approach for human passenger stress reduction while riding a personal mobility autonomous vehicle. The particular vehicle of interest is a robotic autonomous wheelchair which can provide mobility assistance in pedestrian paths. State of the art algorithms for autonomous vehicles mainly focus on collision free path planning and safe control for obstacle avoidance. This work studies comfort factors of the passenger while riding the vehicle. We propose a method for velocity control of the robotic wheelchair based on the concept of “behavior dependent observability” to reduce stress from the collision prediction in blind regions. Behavior dependent observability (BDO) is defined as the visible collision area against dynamic obstacles which is free from collision. By using BDO, the velocity of the robotic wheelchair is computed so that passengers feel comfortable. Experimental results based on physiological measurements (heart rate and galvanic skin response) show that the control of the robotic wheelchair using the behavior dependent observability decreases stressful situations for passengers.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122234383","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}
{"title":"Driving space detection by combining V-disparity and C-velocity","authors":"Houssem-Eddine Deghdache, S. Bouchafa","doi":"10.1109/ICVES.2015.7396921","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396921","url":null,"abstract":"This paper deals with road plane detection by image analysis in the context of automatic driver assistance systems. In this context, free navigable space detection is a very important step for any navigation and obstacle detection system. We propose a low-level combination of two main visual processes: stereovision and motion. We define a common representation that allows simple projections of stereo information to easy-interpretable features in a ”motion” space. We chose to combine two robust cumulative techniques: the stereo-based approach V-disparity and the motion-based approach C-velocity. The combination requires the definition of a common formalism. Results on synthetic image sequences and on KITTI database images reveal that our approach is more efficient than a higher level combination method. We show that it is possible, using no prior knowledge nor any calibration, to improve detection by a low cost method that exploits only image processing and a very simple stereo and motion combination.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129676831","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}
T. Speth, Igor Doric, H. Riedel, T. Brandmeier, U. Jumar
{"title":"Dynamic position calibration by road structure detection","authors":"T. Speth, Igor Doric, H. Riedel, T. Brandmeier, U. Jumar","doi":"10.1109/ICVES.2015.7396902","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396902","url":null,"abstract":"In this research study, the potential of landmarks for accuracy improvement in terms of satellite-based localization is analyzed. Advanced driver assistance systems (ADAS) and vehicle-to-vehicle (V2V) communication applications benefit from precise determination of position. Especially applications for cooperative car safety work best when the position determination is as accurate as possible. The novel approach is related to the differential GPS method, but without using a base station. Previously measured landmarks are used instead. To determine the potential of the approach, the level of increasing localization accuracy is evaluated. Moreover the distribution of naturally existing landmarks is analyzed using the recorded data of an endurance testing vehicle.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129318623","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}
{"title":"Rectification of 3D building models based on GPS signal collected by vehicle","authors":"L. Hsu, Yutaro Wada, Yanlei Gu, S. Kamijo","doi":"10.1109/ICVES.2015.7396907","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396907","url":null,"abstract":"For autonomous driving, both the estimation of the accurate ego position of vehicle and creation of the environment map such as Simultaneous localization and mapping (SLAM) technology are essential. In the SLAM technology, the 3D building model becomes an important aid to many positioning methods such as LiDAR and GPS positioning methods. To build accurate 3D building models, the accurate building footprint (the boundary of the building) is required. In this study, we propose an innovative method to correct the errors of building footprint on the 3D map by using GPS signal. In the urban canyon, GPS signal will be blocked by the buildings and only its reflection signal is received, which is well-known as non-line-of-sight (NLOS) reception. These reflections are potentially capable of indicating the correct position of the buildings. By using of a rough 3D building model, we apply it with a GPS ray-tracing method to track the simulated reflection path of the NLOS GPS. Theoretically, the length of observed reflection path, which is well-known as pseudorange measurement, and the length of simulated reflection path should be very similar. However, if the 3D map is not accurate, the difference between the observed pseudorange and simulated pseudorange will be detected. To utilize this fact, the proposed method is able to estimate the true position of the wall on the 3D map. The experiment results show that the proposed method successfully corrected the footprint of the rough 3D building model into about 1 meter accuracy. Importantly, the proposed method is capable of rectifying the building model only if several reflections GPS signals can be received from a same building.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131411562","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}
{"title":"Effects of errors in position- and navigation data on predictive vehicle operational strategy optimization","authors":"Jan Martin, Ulrich Vogele, C. Endisch","doi":"10.1109/ICVES.2015.7396916","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396916","url":null,"abstract":"Predictive operational strategies enable fuel savings by optimizing the powertrain operation of a vehicle taking lookahead data like velocity limits and slopes of the planned route into account. Gear changes, free-wheeling, speed and operational modes are optimized along that route to achieve minimal fuel consumption. However, these optimizations assume complete information on the route properties ahead. To evaluate the impact of look-ahead data quality on the predictive operational strategies of passenger vehicles, the fuel consumption of different optimized speed trajectories are simulated. The fuel consumption of a speed trajectory with perfect knowledge is then compared to the energy needs of different speed trajectories generated on the same route by optimization methods based on erroneous look-ahead data. In the tested scenarios, optimized velocity trajectories show in most of the cases same or better fuel consumption than constant, non-optimized speed profiles, even if they are based on erroneous map data. Errors in look-ahead data can be shown to have bigger effects on heavy vehicles.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114642786","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}
{"title":"Effect of skill development of haptic shared control in backward parking assist","authors":"S. Tada, T. Wada","doi":"10.1109/ICVES.2015.7396912","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396912","url":null,"abstract":"Advanced driver assistance systems (ADASs), such as parking assist, are widely used. ADASs have successfully reduced driver's workload. On the other hand, it is thought that it is important to improve the skill of the driver. The present study aims to establish a methodology for using an ADAS to achieve compatibility between decreasing the driver's workload and increasing the driver's skill. The present study focused on the assist system by haptic shared control (HSC) for backward parking maneuvers, which are considered to be a demanding task for novice drivers. The purpose of the present study was to investigate the effect of the HSC gain settings on the performance increase during and after the use of the system. First, we proposed a method to assist the driver's parking operation using the HSC. The proposed method displays torque around the steering wheel based on vehicle position feedback to reduce its error from the desired position, and steering angle feedback to reduce its error from the desired steering wheel angle, as determined by the preview driver model. Driving simulator experiments with various combinations of feedback gains demonstrated that skill improvements were achieved after and during the intervention when a higher gain is employed in the steering angle feedback term.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122878701","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}
Kazuhito Sato, Momoyo Ito, H. Madokoro, Sakura Kadowaki
{"title":"Driver body information analysis for distraction state detection","authors":"Kazuhito Sato, Momoyo Ito, H. Madokoro, Sakura Kadowaki","doi":"10.1109/ICVES.2015.7396886","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396886","url":null,"abstract":"For this study, we defined a \"concentration state\" when a driver performs only driving tasks, and a \"distraction state\" when a driver performs a driving task and a mental arithmetic task simultaneously. From results of these driving tests, we elucidate the characteristics of safety confirmation behaviors by near-misses according to differences between two driving conditions when approaching an intersection. Specifically, we examine the time-series variation of eye-gaze movements and face orientations before and after encountering a collision near-miss. From analyses conducted by dividing watching behaviors at the intersection approach and safety confirmation behaviors after a temporary stop, we extract behavioral patterns characterizing a \"distraction state,\" acquiring findings to support the construction of a model for predicting risky driving.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763902","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}
{"title":"Haptic interface of driver-assistance system based on safe driving evaluation","authors":"T. Hiraoka, Masafumi Hayakawa","doi":"10.1109/ICVES.2015.7396910","DOIUrl":"https://doi.org/10.1109/ICVES.2015.7396910","url":null,"abstract":"A previous study proposed a driver-assistance system (DAS) using a haptic interface to encourage drivers to prepare for spontaneous deceleration behavior against potential collision risk. Driving simulator experiments showed that drivers' reaction time were shortened while using the haptic DAS. However, there existed concerns regarding drivers' risk compensation behavior while using the system. Therefore, the present paper proposes an improved version of the aforementioned system. Experiments were performed to better understand the perception characteristics of seat protrusion haptic stimulus, and furthermore, new features such as a safe driving evaluation feedback were added in order to prevent drivers' risk compensation behavior. Results of driving simulator experiments indicated promising effects of the improved system in comparison to the previous system.","PeriodicalId":325462,"journal":{"name":"2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"42 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134579896","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}