International Conference on Vehicle Technology and Intelligent Transport Systems最新文献_第4页

A Multi-Agent based Decision Framework for Sustainable Supplier Selection, Order Allocation and Routing Problem 基于多智能体的可持续供应商选择、订单分配和路由问题决策框架

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007833306210628

M. Drakaki, Hacer Güner Gören, P. Tzionas

{"title":"A Multi-Agent based Decision Framework for Sustainable Supplier Selection, Order Allocation and Routing Problem","authors":"M. Drakaki, Hacer Güner Gören, P. Tzionas","doi":"10.5220/0007833306210628","DOIUrl":"https://doi.org/10.5220/0007833306210628","url":null,"abstract":"Supply chain decisions should aim for sustainability, in order to meet the global market needs, as well as the Industry 4.0 requirements, therefore they should consider beyond economic and environmental, societal dimensions as well. The complexity in decision making increases, moreover, supply network relationships become important, including inter-relationships and those developed with the suppliers. Agent technology is compatible with Industry 4.0, whereas multi-agent systems (MAS) can provide decision support for supply chain management and model the relatationships and interactions between entities in the supply chain environment. Therefore, in this paper, a MAS-based framework is proposed to address sustainability focused decision making in supplier selection, order allocation and routing. Fuzzy Multi Criteria Decision Making (MCDM) approaches and multi-objective programming are used by the agents in the MAS in order to adress sustainability requirements. Futrhermore, developed agent services for the supply chain business processes are integrated with web services, in order to facilitate business process execution as web services.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132941842","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}

引用次数: 4

Using the CGAN Model Extend Encounter Targets Image Training Set 利用CGAN模型扩展遇见目标图像训练集

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007676803270332

Ruolan Zhang, M. Furusho

{"title":"Using the CGAN Model Extend Encounter Targets Image Training Set","authors":"Ruolan Zhang, M. Furusho","doi":"10.5220/0007676803270332","DOIUrl":"https://doi.org/10.5220/0007676803270332","url":null,"abstract":"A fully capable unmanned ship navigation requires full autonomous decision-making, large-scale decision model training data to answer for these conditions is essential. However, it is difficult to obtain enough scenes training data in a real sea navigation environment. In response to possible emergency situations even no shore-station support, this paper proposes a method using conditional generative adversarial networks (CGAN) to generate the most executable large-scale target ships image set, which can be used to training various sea conditions autonomous decision-making model. In practice, most of the current research on unmanned ships are based onshore remote control or monitoring. Nonetheless, in some extremely special circumstances, such as communication interruption, or if the ship cannot be guided or remotely controlled in real time on the shore, the unmanned ship must make an appropriate decision and form new plans according to the encounter targets and the whole current situation. The CGAN model is a novel means to generate the target ships to construct the whole encounter sea scenes situation. The generated targets training image set can be used to train decision models, and explore a new way to approach large-scale, fully autonomous navigation decisions.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124512381","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}

引用次数: 2

Expert Competitive Traffic Light Optimization with Evolutionary Algorithms 基于进化算法的专家竞争红绿灯优化

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007732701990210

Y. Semet, B. Berthelot, Thierry Glais, Christian Isbérie, Aurélien Varest

{"title":"Expert Competitive Traffic Light Optimization with Evolutionary Algorithms","authors":"Y. Semet, B. Berthelot, Thierry Glais, Christian Isbérie, Aurélien Varest","doi":"10.5220/0007732701990210","DOIUrl":"https://doi.org/10.5220/0007732701990210","url":null,"abstract":"We present a complete system to optimize traffic lights green phases and temporal offsets based on a combination of microscopic simulation and black box, evolutionary algorithms. We also report the outcome of an AI versus experts comparison workshop conducted with our algorithm and seasoned experts from a specialized traffic engineering office. Experimental results indicate that the proposed algorithmic scheme significantly outperforms expert efforts. Our system entails a memetic (genetic+gradient) calibration module to adapt the Origin/Destination (O/D) matrix to current traffic conditions, an inoculation procedure to incorporate existing traffic light programs, genetic multi-objective optimization capabilities and sound metrics. Experiments are conducted over several real world datasets of operational sizes from the Paris outskirts and various other French urban areas. Our experimental outcome is threefold. First, we report the success of the memetic calibration module in adjusting the simulator’s O/D matrix to a point with variation levels corresponding to recorded sensor data. Second, we confirm the ability of the system to obtain significant gains on that sound basis: gains ranging from 15% to 35% are consistently reached on both traffic jams reduction and pollutant emissions. Most importantly, we report the outcome of the comparison workshop: a formalized methodology followed by experts to manually optimize traffic lights, iterative experimental logs tracing the application of that methodology to two real world cases and comparable results obtained by the algorithm on the same cases. Results indicate that the AI module performs significantly better than experts in both speed and final solution quality.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125813701","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}

引用次数: 5

Traffic Monitoring using an Object Detection Framework with Limited Dataset 基于有限数据集的目标检测框架的交通监控

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007586802910296

V. Komašilovs, A. Zacepins, A. Kviesis, C. Estevez

{"title":"Traffic Monitoring using an Object Detection Framework with Limited Dataset","authors":"V. Komašilovs, A. Zacepins, A. Kviesis, C. Estevez","doi":"10.5220/0007586802910296","DOIUrl":"https://doi.org/10.5220/0007586802910296","url":null,"abstract":"Vehicle detection and tracking is one of the key components of the smart traffic concept. Modern city planning and development is not achievable without proper knowledge of existing traffic flows within the city. Surveillance video is an undervalued source of traffic information, which can be discovered by variety of information technology tools and solutions, including machine learning techniques. A solution for real-time vehicle traffic monitoring, tracking and counting is proposed in Jelgava city, Latvia. It uses object detection model for locating vehicles on the image from outdoor surveillance camera. Detected vehicles are passed to tracking module, which is responsible for building vehicle trajectory and its counting. This research compares two different model training approaches (uniform and diverse data sets) used for vehicle detection in variety of weather and day-time conditions. The system demonstrates good accuracy of given test cases (about 92% accuracy in average). In addition, results are compared to non-machine learning vehicle tracking approach, where notable vehicle detection accuracy increase is demonstrated on congested traffic. This research is fulfilled within the RETRACT (Enabling resilient urban transportation systems in smart cities) project.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129963027","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}

引用次数: 4

GCCNet: Global Context Constraint Network for Semantic Segmentation GCCNet:语义分割的全局上下文约束网络

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007705703800387

Hyunwoo Kim, Huaiyu Li, S. Kee

引用次数: 0

Vision based ADAS for Forward Vehicle Detection using Convolutional Neural Networks and Motion Tracking 基于卷积神经网络和运动跟踪的视觉ADAS车辆前向检测

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007626902970304

Chenxiao Lai, H. Lin, Wen-Lung Tai

{"title":"Vision based ADAS for Forward Vehicle Detection using Convolutional Neural Networks and Motion Tracking","authors":"Chenxiao Lai, H. Lin, Wen-Lung Tai","doi":"10.5220/0007626902970304","DOIUrl":"https://doi.org/10.5220/0007626902970304","url":null,"abstract":"With the rapid development of advanced driving assistance technologies, from the very beginning of parking assistance, lane departure warning, forward collision warning, to active distance control cruise, the active safety protection of vehicles has gained the popularity in recent years. However, there are several important issues in the image based forward collision warning systems. If the characteristics of vehicles are defined manually for detection, we need to consider various conditions to set the threshold to fit a variety of the environment change. Although the state-of-art machine learning methods can provide more accurate results then ever, the required computation cost is far much higher. In order to find a balance between these two approaches, we present a detection-tracking technique for forward collision warning. The motion tracking algorithm is built on top of the convolutional neural networks for vehicle detection. For all processed image frames, the ratio between detection and tracking is well adjusted to achieve a good performance with an accuracy/computation trade-off. Th experiments with real-time results are presented with a GPU computing platform.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125912551","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}

引用次数: 6

Towards Certification of Autonomous Driving: Systematic Test Case Generation for a Comprehensive but Economically-Feasible Assessment of Lane Keeping Assist Algorithms 走向自动驾驶认证:车道保持辅助算法全面且经济可行评估的系统测试用例生成

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007678603330342

Thomas Ponn, Dirk Fratzke, C. Gnandt, M. Lienkamp

{"title":"Towards Certification of Autonomous Driving: Systematic Test Case Generation for a Comprehensive but Economically-Feasible Assessment of Lane Keeping Assist Algorithms","authors":"Thomas Ponn, Dirk Fratzke, C. Gnandt, M. Lienkamp","doi":"10.5220/0007678603330342","DOIUrl":"https://doi.org/10.5220/0007678603330342","url":null,"abstract":"Automation of the driving task continues to progress rapidly. In addition to improving the algorithms, proof of their safety is still an unsolved problem. For an automated driving function that does not require permanent monitoring by the driver, a theoretically infinite number of possible traffic situations must be tested. One promising method to overcome this problem is the scenario-based approach. This approach shall enable an economic certification of automated driving functions with sufficient test space coverage. However, even with this approach, the selection of the scenarios to be tested is still problematic. The first step is to consider a driver assistance system in order to reduce complexity. For the Lane Keeping Assist System under consideration, this paper defines a methodology as well as the scenarios for a comprehensive yet economically-feasible certification. Economical-feasibility of the presented methodology is shown in the results by an approximation of the resulting simulation costs for executing the defined test cases.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114061081","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}

引用次数: 10

Development of 8х8 All-terrain Vehicle with Individual Wheel Drive 8х8单轮驱动全地形车辆的研制

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007765505560561

A. Belyaev, S. Manyanin, A. Tumasov, V. Makarov, V. Belyakov

引用次数: 8

CPD: Crowd-based Pothole Detection CPD:基于人群的坑洞检测

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007626700330042

Florian Wirthmüller, Jochen Hipp, K. Sattler, M. Reichert

{"title":"CPD: Crowd-based Pothole Detection","authors":"Florian Wirthmüller, Jochen Hipp, K. Sattler, M. Reichert","doi":"10.5220/0007626700330042","DOIUrl":"https://doi.org/10.5220/0007626700330042","url":null,"abstract":"Potholes and other damages of the road surface constitute a problem being as old as roads are. Still, potholes are widespread and affect the driving comfort of passengers as well as road safety. If one knew about the exact locations of potholes, it would be possible to repair them selectively or at least to warn drivers about them up to their repair. However, both scenarios require their detection and localization. For this purpose, we propose a crowd-based approach that enables as many of the vehicles already driving on our roads as possible to detect potholes and report them to a centralized back-end application. Whereas each single vehicle provides only limited and imprecise information, it is possible to determine these information more precisely when collecting them at a large scale. These more exact information may, for example, be used to warn following vehicles about potholes lying ahead to increase overall safety and comfort. In this work, this idea is examined and an offline executable version of the desired system is implemented. Additionally, the approach is evaluated with a large database of real-world sensor readings from a testing fleet and therefore its feasibility is proved. Our investigation shows that the suggested CPD approach is promising to bring customers a benefit by an improved driving comfort and higher road safety.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121486551","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}

引用次数: 4

Quantifying Impacts of Connected and Autonomous Vehicles on Traffic Operation using Micro-simulation in Dubai, UAE 阿联酋迪拜联网和自动驾驶汽车对交通运行的微观模拟量化影响

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-05-03 DOI: 10.5220/0007753905280535

A. Alozi, Khaled Hamad

{"title":"Quantifying Impacts of Connected and Autonomous Vehicles on Traffic Operation using Micro-simulation in Dubai, UAE","authors":"A. Alozi, Khaled Hamad","doi":"10.5220/0007753905280535","DOIUrl":"https://doi.org/10.5220/0007753905280535","url":null,"abstract":"Connected and Autonomous Vehicles (CAVs) will change the transportation system we know with their substantial impacts on the level of safety, traffic operation, fuel consumption, air emissions among other aspects. A large segment of the general public and decision makers are still sceptical of CAVs’ benefits and impacts. This study aims at quantifying the impacts of CAVs on traffic operation using micro-simulation of a 7-kilometer-freeway segment in Dubai, UAE. The simulation was run for different market penetration rates (MPRs) ranging from 0% (no CAVs) up to 100% (all CAVs), in 10% increment. Additionally, multiple scenarios under different traffic volumes were also modelled utilizing PTV VISSIM. To quantify the impacts of CAVs, three performance measures were collected, namely the average delay, average speed, and total travel time. The results showed that the highest impact of CAVs occurs in terms of delay, with a decreased average delay of up to 86%. The other performance measures also show improvement, with 42% speed increase and 25% travel time reduction. Moreover, CAVs show more significant changes at lower traffic volume conditions (off-peak hour).","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130586037","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}

引用次数: 5