International Conference on Vehicle Technology and Intelligent Transport Systems最新文献

{"title":"Development of a Comprehensive Walking Path System in Hong Kong","authors":"L. Pun-Cheng","doi":"10.5220/0006785505010506","DOIUrl":"https://doi.org/10.5220/0006785505010506","url":null,"abstract":"Walkability has been defined as the extent to which the urban environment is pedestrian friendly. This article presents a case in Hong Kong of how to develop a walking path system to enable users to choose a pedestrian-friendly route. It is found that different details of land configuration can result in varying paths. Such differences can be significant in contributing not only to an accurate system, but also in convincing and stimulating people to walk more according to their own preference.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129505237","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":"Pictures of You, Pictures of Me - User Acceptance of Camera-technology in Intelligent Transport Systems","authors":"Teresa Brell, R. Philipsen, M. Ziefle","doi":"10.5220/0006700603710378","DOIUrl":"https://doi.org/10.5220/0006700603710378","url":null,"abstract":"The integration of connected and smart technology is a key factor of our future traffic system development. By integrating traffic participants into the technology development circle, possible trade-offs, obstacles and advances can be identified and further, an understanding of technology acceptance can be evolved. This paper will show, how camera-based technology in intelligent transport systems is evaluated from a user-centred perspective. The focus of this work lies on the identification and evaluation of perceived benefits and barriers, but also conditional and functional aspects are investigated as well as an overall acceptance picture. Results show, that the need for technology is not denied, but privacy concerns and a feeling of surveillance still re-","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123755763","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":"Intelligent Containers Network Concept","authors":"S. Jakovlev, A. Senulis, M. Kurmis, Darius Drungilas, Zydrunas Lukosius","doi":"10.5220/0006801305680574","DOIUrl":"https://doi.org/10.5220/0006801305680574","url":null,"abstract":"","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"39 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114124546","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":"Iterative Calibration of a Vehicle Camera using Traffic Signs Detected by a Convolutional Neural Network","authors":"A. Hanel, Uwe Stilla","doi":"10.5220/0006711201870195","DOIUrl":"https://doi.org/10.5220/0006711201870195","url":null,"abstract":"Intrinsic camera parameters are estimated during calibration typically using special reference patterns. Mechanical and thermal effects might cause the parameters to change over time, requiring iterative calibration. For vehicle cameras, reference information needed therefore has to be extracted from the scenario, as reference patterns are not available on public streets. In this contribution, a method for iterative camera calibration using scale references extracted from traffic signs is proposed. Traffic signs are detected in images recorded during driving using a convolutional neural network. Multiple detections are reduced by mean shift clustering, before the shape of each sign is fitted robustly with RANSAC. Unique image points along the shape contour together with the metric size of the traffic sign are included iteratively in the bundle adjustment performed for camera calibration. The neural network is trained and validated with over 50,000 images of traffic signs. The iterative calibration is tested with an image sequence of an urban scenario showing traffic signs. The results show that the estimated parameters vary in the first iterations, until they converge to stable values after several iterations. The standard deviations are comparable to the initial calibration with a reference pattern. 1 CALIBRATION OF CAMERAS FOR ADVANCED DRIVER ASSISTANCE SYSTEMS In recent years, an increasing number and capability (figure 1) of advanced driver assistance systems per vehicle can be observed (Shapiro, 2017), what is also reflected by the continuously growing sales of needed electronic control units in cars (AlixPartners, 2015). For capturing the scenario in and around the car for advanced driver assistance systems, different sensors are used (Dempsey, 2016). Ultrasonic sensors in the front and rear bumper can capture the close scenario in front and behind the car to avoid collisions during parking maneuvers. Radar sensors can be distinguished by their operating range. Cross traffic warnings can be realized with a short-range radar system with a range up to 30 m. A cruise control system adapting the speed of the ego-car dependent on preceding cars is used typically in highways scenarios, wherefore long-range radar systems with a range of more than 200 m are suitable. Pedestrian detection systems are typically used in urban scenarios with moderate speeds driven, requiring medium-range sensors like a LiDAR or a camera (Ors, 2017). During development of a new car model, costs are Figure 1: Traffic signs detected in images of a vehicle camera (field of view in blue) can be used to warn the driver against speed limits or other traffic regulations. These detections can be also used to iteratively calibrate the camera (Auto Body Professionals Club, 2017). an important design factor regarding customer acceptance. As the type of sensors installed in a car influences the total costs of advanced driver assistance systems, cameras with lower costs than for exa","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114574658","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":"Decision Support Dashboard for Traffic and Environment Analysis of a Smart City","authors":"Jorge Pereira, S. Sargento, J. Fernandes","doi":"10.5220/0006707603870394","DOIUrl":"https://doi.org/10.5220/0006707603870394","url":null,"abstract":"Porto city has an in-place infrastructure of fixed and moving sensors in more than 400 buses and roadside units, with both GPS and mobility sensors in moving elements, and with environmental sensors in fixed units. This infrastructure can provide valuable data that can extract information to better understand the city and, eventually, support actions to improve the city mobility, urban planning, and environment. Our system provides a full stack integration of the information into a city dashboard that displays and correlates the data generated from buses and fixed sensors, allowing different visualizations over the traffic and environment in the city, and decisions over the current status of the city. A good example relates bus speed variation with possible anomalies on the road or traffic jams. Visualizing such information and getting alarms on anomalies can be a valuable tool to a city manager when taking urban planning decisions to improve the","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117136099","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":"Towards an Automated Flying Drones Platform","authors":"B. Areias, Nuno Humberto, Lucas Guardalben, J. Fernandes, S. Sargento","doi":"10.5220/0006792405290536","DOIUrl":"https://doi.org/10.5220/0006792405290536","url":null,"abstract":"","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132123898","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":"When Should the Chicken Cross the Road? - Game Theory for Autonomous Vehicle - Human Interactions","authors":"Charles W. Fox, F. Camara, G. Markkula, R. Romano, R. Madigan, N. Merat","doi":"10.5220/0006765404310439","DOIUrl":"https://doi.org/10.5220/0006765404310439","url":null,"abstract":"Autonomous vehicle control is well understood for local- [15], good approximations exist such as particle �ltering, \u0000ization, mapping and planning in un-reactive environ- which make use of large compute power to draw samples \u0000ments, but the human factors of complex interactions near solutions. \u0000stood [16], and despite its exact solution being NP-hard \u0000with other road users are not yet developed. \u0000Route planning in non-interactive envi- \u0000ronments also has well known tractable solutions such as \u0000This po- \u0000the A-star algorithm. Given a route, localizing and con- \u0000sition paper presents an initial model for negotiation be- \u0000trol to follow that route then becomes a similar task to \u0000tween an autonomous vehicle and another vehicle at an \u0000that performed by the 1959 General Motors Firebird-III \u0000unsigned intersections or (equivalently) with a pedestrian \u0000self-driving car [1], which used electromagnetic sensing \u0000at an unsigned road-crossing (jaywalking), using discrete \u0000to follow a wire built into the road. \u0000Such path follow- \u0000sequential game theory. The model is intended as a ba- ing, using wires or SLAM, can then be augmented with \u0000sic framework for more realistic and data-driven future simple safety logic to stop the vehicle if any obstacle is \u0000extensions. The model shows that when only vehicle po- in its way, as detected by any range sensor. \u0000sition is used to signal intent, the optimal behaviors for open source systems for this level of `self-driving' are now \u0000both agents must include a non-zero probability of al- widely available [6]. \u0000lowing a collision to occur. \u0000In contrast, \u0000This suggests extensions to \u0000problems that these vehicles will face \u0000around interacting with other road users are much harder \u0000reduce this probability in future, such as other forms of \u0000both to formulate and solve. Autonomous vehicles do not \u0000signaling and control. Unlike most Game Theory appli- \u0000just have to deal with inanimate objects, sensors, and \u0000cations in Economics, active vehicle control requires real- \u0000maps. \u0000time selection from multiple equilibria with no history, \u0000They have to deal with other agents, currently \u0000human drivers and pedestrians and eventually other au- \u0000and we present and argue for a novel solution concept, \u0000meta-strategy convergence , suited to this task.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115274160","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":"Autonomous Vehicle Simulation Model to Assess Potential Collisions to Reduce Severity of Impacts","authors":"Alex Gilbert, D. Petrovic, K. Warwick, Vasilis Serghi","doi":"10.5220/0006663102430250","DOIUrl":"https://doi.org/10.5220/0006663102430250","url":null,"abstract":"Autonomous vehicle safety has received much attention in recent years. Autonomous vehicles will improve road safety by eliminating human errors. However, not all automotive collisions can be avoided. A strategy needs to be developed in the event when an autonomous vehicle encounters an unavoidable collision. Furthermore, the vehicle will need to take responsibility for the safety of its occupants, as well as any other individuals, who may be affected by the vehicle’s behaviour. This paper proposes a control system to assist an autonomous vehicle to make a decision to reduce the risks to occupants potentially involved in highway motorway collisions. Before any decision can be made, the potential collisions need to be assessed for their effects. A quick and numerical method for evaluation of impact of potential collisions was developed. Assessing the Kinetic Energy of the vehicles before and after collisions is proposed as a method to assess the severity of collisions. A simulation model developed calculates the kinetic energy values and recommends an autonomous vehicle the motorway lane to drive into to cause the least severe collision impact. Different scenarios are defined and used to test the simulation model. The results obtained are promising and in line with the decision made by the subject expert.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115489424","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":"Introducing Cellular Network Layer into SUMO for Simulating Vehicular Mobile Devices' Interactions in Urban Environment","authors":"Siim-Toomas Marran, Artjom Lind, Amnir Hadachi","doi":"10.5220/0006808305820589","DOIUrl":"https://doi.org/10.5220/0006808305820589","url":null,"abstract":"During the last decade researchers have been demonstrating the importance of mobile data or CDR data in depicting the human mobility patterns. However, this type of data is not easy to get access to from mobile operators. Besides, in order to make this type of data available and enable their usage for the scientific communities the process can face many constraints that can constitute obstacle. From this perspective, this paper introduces a way to produce realistic real-life mobility logs through the traffic simulation tool SUMO, which has been enhanced with a cellular network layer to mimic cellular networking behavior.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122602340","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":"Cellular Bandwidth Prediction for Highly Automated Driving - Evaluation of Machine Learning Approaches based on Real-World Data","authors":"Florian Jomrich, A. Herzberger, Tobias Meuser, Björn Richerzhagen, R. Steinmetz, Cornelius Wille","doi":"10.5220/0006692501210132","DOIUrl":"https://doi.org/10.5220/0006692501210132","url":null,"abstract":"To enable highly automated driving and the associated comfort services for the driver, vehicles require a reliable and constant cellular data connection. However, due to their mobility vehicles experience significant fluctuations in their connection quality in terms of bandwidth and availability. To maintain constantly high quality of service, these fluctuations need to be anticipated and predicted before they occur. To this end, different techniques such as connectivity maps and online throughput estimations exist. In this paper, we investigate the possibilities of a large-scale future deployment of such techniques by relying solely on lowcost hardware for network measurements. Therefore, we conducted a measurement campaign over three weeks in which more than 74,000 throughput estimates with correlated network quality parameters were obtained. Based on this data set—which we make publicly available to the community—we provide insights in the challenging task of network quality prediction for vehicular scenarios. More specifically, we analyse the potential of machine learning approaches for bandwidth prediction and assess their underlying assumptions.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114897456","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}