Pub Date : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8964925
J. Raiyn
Intelligent transportation systems use three kinds of interactive cooperative communication to manage the urban road traffic. These are human to human communication (H2H), machine to human communication (M2H) and machine to machine communication (M2M). H2H communication is based mostly on human gestures involving the hands, face, eyes or other body parts. M2M communication is a hybrid system that is installed in autonomous vehicles (AVs) and responds to human gestures. It is found in three forms: vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X). In this paper, V2I communication will be studied to improve the internet communication of autonomous vehicles in 5G environment. V2I communication used to manage the platooning of vehicles on urban roads, which is a strategy for increasing road capacity. The performance of V2I communication is measured in terms of QoS parameters such as delay and interference. The interference analysis of wireless communications becomes increasingly difficult as the environment becomes increasingly complex This paper proposes an analytical model that integrate pathloss and cochannel interference, which are considered the most important factors contributing to the performance degradation of V2I communication. A discussion of the challenges of V2I communication and their impact on urban road management is presented. Improvements in V2I communication are intended to overcome the shortcomings of human divers by improving traffic flow, reducing accidents, and reducing social exclusion.
{"title":"Improving V2I Communication Technology Based on Interference Analysis for Wireless Networks","authors":"J. Raiyn","doi":"10.1109/ICCVE45908.2019.8964925","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964925","url":null,"abstract":"Intelligent transportation systems use three kinds of interactive cooperative communication to manage the urban road traffic. These are human to human communication (H2H), machine to human communication (M2H) and machine to machine communication (M2M). H2H communication is based mostly on human gestures involving the hands, face, eyes or other body parts. M2M communication is a hybrid system that is installed in autonomous vehicles (AVs) and responds to human gestures. It is found in three forms: vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X). In this paper, V2I communication will be studied to improve the internet communication of autonomous vehicles in 5G environment. V2I communication used to manage the platooning of vehicles on urban roads, which is a strategy for increasing road capacity. The performance of V2I communication is measured in terms of QoS parameters such as delay and interference. The interference analysis of wireless communications becomes increasingly difficult as the environment becomes increasingly complex This paper proposes an analytical model that integrate pathloss and cochannel interference, which are considered the most important factors contributing to the performance degradation of V2I communication. A discussion of the challenges of V2I communication and their impact on urban road management is presented. Improvements in V2I communication are intended to overcome the shortcomings of human divers by improving traffic flow, reducing accidents, and reducing social exclusion.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122365801","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8964843
E. Armengaud, O. Hegazy, B. Brandstätter, V. Ivanov, R. Tatschl, M. Gennaro, A. Sorniotti, J. Mierlo, C. Schernus
Electrification of road transport is a key challenge to reach the emission targets while enabling efficient mobility for persons and goods. Even though solutions already exist on the market, e-mobility is still a niche market. Main challenges for large scale deployment include higher maturity with respect to performance (e.g., range), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. In this context, the European Commission started different research programs in 2018 with a total volume of more than 50Mi€. Target of this paper is to present an overview of these programs and discuss how this portfolio will provide significant advances for e-mobility relying on European technologies.
{"title":"European Innovation for Next Generation Electrified Vehicles and Components","authors":"E. Armengaud, O. Hegazy, B. Brandstätter, V. Ivanov, R. Tatschl, M. Gennaro, A. Sorniotti, J. Mierlo, C. Schernus","doi":"10.1109/ICCVE45908.2019.8964843","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964843","url":null,"abstract":"Electrification of road transport is a key challenge to reach the emission targets while enabling efficient mobility for persons and goods. Even though solutions already exist on the market, e-mobility is still a niche market. Main challenges for large scale deployment include higher maturity with respect to performance (e.g., range), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. In this context, the European Commission started different research programs in 2018 with a total volume of more than 50Mi€. Target of this paper is to present an overview of these programs and discuss how this portfolio will provide significant advances for e-mobility relying on European technologies.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121857904","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965241
Yuki Mori, R. Ono, T. Mitani, K. Naito, T. Yamazato
This paper proposes a continuous identification scheme monitoring a driver's behavior and a detection scheme for an impostor. The proposed scheme uses Long Short-Term Memory (LSTM) to create a classifier of the driver's behavior according to acceleration data and classifies a driver. Additionally, it also detects an impostor according to statistical information of output from the classifier. Experimental results show that an acceleration sensor on a real vehicle is enough to classify 15 drivers according to real-time driver's behavior. Additionally, the proposed scheme can detect an impostor through the verification of real experimental data.
{"title":"Proposal for Identification Scheme of Driver and Impostor based on Acceleration Data","authors":"Yuki Mori, R. Ono, T. Mitani, K. Naito, T. Yamazato","doi":"10.1109/ICCVE45908.2019.8965241","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965241","url":null,"abstract":"This paper proposes a continuous identification scheme monitoring a driver's behavior and a detection scheme for an impostor. The proposed scheme uses Long Short-Term Memory (LSTM) to create a classifier of the driver's behavior according to acceleration data and classifies a driver. Additionally, it also detects an impostor according to statistical information of output from the classifier. Experimental results show that an acceleration sensor on a real vehicle is enough to classify 15 drivers according to real-time driver's behavior. Additionally, the proposed scheme can detect an impostor through the verification of real experimental data.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122049192","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8964994
F. Asadi, A. Anwar, J. Miles
This paper examines the long-term effect that connected and autonomous vehicles might have on urban, road-based, transport capacity. Using micro-simulation techniques, the authors produce estimates for the increase/decrease in congestion which might occur when fully autonomous vehicles are introduced to the roads. Despite the fact that these vehicles are likely to generate more road movements in future because of “empty-leg” journeys, the results suggest that overall congestion levels are more likely to be eased than aggravated by their ubiquitous presence.
{"title":"Investigating the Potential Transportation Impacts of Connected and Autonomous Vehicles","authors":"F. Asadi, A. Anwar, J. Miles","doi":"10.1109/ICCVE45908.2019.8964994","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8964994","url":null,"abstract":"This paper examines the long-term effect that connected and autonomous vehicles might have on urban, road-based, transport capacity. Using micro-simulation techniques, the authors produce estimates for the increase/decrease in congestion which might occur when fully autonomous vehicles are introduced to the roads. Despite the fact that these vehicles are likely to generate more road movements in future because of “empty-leg” journeys, the results suggest that overall congestion levels are more likely to be eased than aggravated by their ubiquitous presence.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130410877","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965224
Tobias Renzler, M. Stolz, D. Watzenig
An open question in platooning is the appropriate selection of the inter-vehicle distance: shorter distances reduce energy, but increase network demands, which have to be satisfied to guarantee safety. Even once determined appropriately, inter-vehicle distances need to adapt for varying traffic scenarios and heterogeneous platoons. Therefore, we introduce a new architecture that puts dynamic distances into effect and manages platoons in a decentralized way to maintain safety and robustness by considering network reliability, environmental, and vehicular constraints. Smooth trajectory planning allows energy efficient and comfortable adaptation of distances between vehicles. The presented architecture is tested using Omnet++ and SUMO in a highway entry and an emergency braking scenario.
{"title":"Decentralized Dynamic Platooning Architecture with V2V Communication Tested in Omnet++","authors":"Tobias Renzler, M. Stolz, D. Watzenig","doi":"10.1109/ICCVE45908.2019.8965224","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965224","url":null,"abstract":"An open question in platooning is the appropriate selection of the inter-vehicle distance: shorter distances reduce energy, but increase network demands, which have to be satisfied to guarantee safety. Even once determined appropriately, inter-vehicle distances need to adapt for varying traffic scenarios and heterogeneous platoons. Therefore, we introduce a new architecture that puts dynamic distances into effect and manages platoons in a decentralized way to maintain safety and robustness by considering network reliability, environmental, and vehicular constraints. Smooth trajectory planning allows energy efficient and comfortable adaptation of distances between vehicles. The presented architecture is tested using Omnet++ and SUMO in a highway entry and an emergency braking scenario.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126203521","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965236
Abhijit Vasili, Wilfrido Moreno
Smart cities and connected vehicles have witnessed rapid research and technological developments over the last two decades. Early research has indicated that together these technologies can significantly benefit public safety in particular post collision care. This paper reviews the literature relating three key aspects of public safety presented in relation to post collision care, which include first responders response time, crash vehicle communication time to the first responder and the ability of the first responder to focus on collisions where they are needed the most.
{"title":"Applications and Trends in Connected Vehicles: Debates and Conclusions","authors":"Abhijit Vasili, Wilfrido Moreno","doi":"10.1109/ICCVE45908.2019.8965236","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965236","url":null,"abstract":"Smart cities and connected vehicles have witnessed rapid research and technological developments over the last two decades. Early research has indicated that together these technologies can significantly benefit public safety in particular post collision care. This paper reviews the literature relating three key aspects of public safety presented in relation to post collision care, which include first responders response time, crash vehicle communication time to the first responder and the ability of the first responder to focus on collisions where they are needed the most.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115883744","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 : 2019-11-01DOI: 10.1109/iccve45908.2019.8965119
{"title":"[Copyright notice]","authors":"","doi":"10.1109/iccve45908.2019.8965119","DOIUrl":"https://doi.org/10.1109/iccve45908.2019.8965119","url":null,"abstract":"","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131917091","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965227
I. Viana, Husain Kanchwala, N. Aouf
This work considers the problem of cooperative optimal trajectory generation for autonomous driving. A distributed nonlinear model predictive control (NMPC) for each vehicle was employed to solve the cooperative path-planning problem. Cooperative behavior is introduced by broadcasting the planned trajectories of all connected automated vehicles (CAVs). The proposed method is evaluated by co-simulation in CarSim which emulates a high fidelity multi-body dynamics model of the vehicle. The results show the effectiveness of our approach for a cooperative overtaking scenario comprising two vehicles in a three-lane, one way road with obstacles.
{"title":"Cooperative Trajectory Planning for Autonomous Driving Using Nonlinear Model Predictive Control","authors":"I. Viana, Husain Kanchwala, N. Aouf","doi":"10.1109/ICCVE45908.2019.8965227","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965227","url":null,"abstract":"This work considers the problem of cooperative optimal trajectory generation for autonomous driving. A distributed nonlinear model predictive control (NMPC) for each vehicle was employed to solve the cooperative path-planning problem. Cooperative behavior is introduced by broadcasting the planned trajectories of all connected automated vehicles (CAVs). The proposed method is evaluated by co-simulation in CarSim which emulates a high fidelity multi-body dynamics model of the vehicle. The results show the effectiveness of our approach for a cooperative overtaking scenario comprising two vehicles in a three-lane, one way road with obstacles.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131172199","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965237
Arec L. Jamgochian, Mykel J. Kochenderfer
With the penetration of electric vehicles in local markets, vehicle-induced electricity demand can cause power grid instability. Collaborative smart charging can help stabilize grid demand and mitigate those issues. This paper formulates charge scheduling when connected vehicles constitute a large portion of instantaneous demand. Allowing coordinated charging to sway electricity price, we formulate a multi-objective stochastic optimization problem to minimize cost while maximizing charge in each car. We model stochastic base electricity demand using a Gaussian Mixture Model (GMM) and solve the certainty-equivalent stochastic optimization problem. We then implement a stochastic model predictive control (SMPC) algorithm and compare performance between a naive policy, a certainty-equivalent optimized policy, and SMPC on a dataset derived from California ISO-serviced demand.
{"title":"Stochastic Model Predictive Control for Scheduling Charging of Electric Vehicle Fleets with Market Power","authors":"Arec L. Jamgochian, Mykel J. Kochenderfer","doi":"10.1109/ICCVE45908.2019.8965237","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965237","url":null,"abstract":"With the penetration of electric vehicles in local markets, vehicle-induced electricity demand can cause power grid instability. Collaborative smart charging can help stabilize grid demand and mitigate those issues. This paper formulates charge scheduling when connected vehicles constitute a large portion of instantaneous demand. Allowing coordinated charging to sway electricity price, we formulate a multi-objective stochastic optimization problem to minimize cost while maximizing charge in each car. We model stochastic base electricity demand using a Gaussian Mixture Model (GMM) and solve the certainty-equivalent stochastic optimization problem. We then implement a stochastic model predictive control (SMPC) algorithm and compare performance between a naive policy, a certainty-equivalent optimized policy, and SMPC on a dataset derived from California ISO-serviced demand.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"40 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131608548","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 : 2019-11-01DOI: 10.1109/ICCVE45908.2019.8965210
Q. Lu, T. Tettamanti, Dániel Hörcher
In transportation modeling, after defining a road network and its origin-destination (OD) matrix, the next important question is how to assign traffic among OD-pairs. In our days, the technology of advanced traveler information systems (ATIS) makes it possible to realize the “user-optimal” solution. At the same time, with the advent of the Cooperative Intelligent Transport Systems (C-ITS) it is possible to solve the traffic assignment problem in “system-optimal” way. The difference in transportation performance between user-optimal and system-optimal principles is discussed in the paper. The main purpose of this research is to investigate what are the implications of the user and system optimal traffic assignment considering the autonomous vehicle fleets.
{"title":"Implications of user and system optimum based traffic control considering autonomous fleets","authors":"Q. Lu, T. Tettamanti, Dániel Hörcher","doi":"10.1109/ICCVE45908.2019.8965210","DOIUrl":"https://doi.org/10.1109/ICCVE45908.2019.8965210","url":null,"abstract":"In transportation modeling, after defining a road network and its origin-destination (OD) matrix, the next important question is how to assign traffic among OD-pairs. In our days, the technology of advanced traveler information systems (ATIS) makes it possible to realize the “user-optimal” solution. At the same time, with the advent of the Cooperative Intelligent Transport Systems (C-ITS) it is possible to solve the traffic assignment problem in “system-optimal” way. The difference in transportation performance between user-optimal and system-optimal principles is discussed in the paper. The main purpose of this research is to investigate what are the implications of the user and system optimal traffic assignment considering the autonomous vehicle fleets.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133732320","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：