2019 IEEE Intelligent Transportation Systems Conference (ITSC)最新文献_第5页

Planning Ahead for EV: Total Travel Time Optimization for Electric Vehicles 电动汽车的提前规划:电动汽车总行程时间优化

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917335

Sven Schoenberg, F. Dressler

{"title":"Planning Ahead for EV: Total Travel Time Optimization for Electric Vehicles","authors":"Sven Schoenberg, F. Dressler","doi":"10.1109/ITSC.2019.8917335","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917335","url":null,"abstract":"Travelling long distances with electric vehicles is becoming more viable today. Nevertheless, recharging is still necessary on long trips. As of now, the charging infrastructure is not yet ubiquitous and can be very heterogeneous in terms of charging power. Thus, appropriate route planning is needed, which is still an open research problem. We present an approach to optimize the total travel time for electric vehicles by selecting charging stations and routes, respectively, between origin and destinaton and the charging stations. We also take the possibility into account that driving below the speed limit helps to save energy. In particular, we use a multi-criterion shortest-path search to find the best compromise between the fastest and most economic route. In our approach, we use a non-linear charging model that supports CC-CV and CP-CV charging protocols used for lithium-ion batteries. To achieve acceptable speed for the multi-criterion shortest-path search, we combine contraction hierarchies with precomputation of shortest-path trees. By exploiting the fact that most routes are queried between the known locations of the charging stations, we were able to accelerate these queries by about two orders of magnitude. We compare our proposed adaptive charging and routing strategy to other strategies often cited in the literature. Our results clearly show that we are able to achieve a lower total travel time.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"39 1","pages":"3068-3075"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88678256","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

Range-based Cooperative Localization with Nonlinear Observability Analysis 基于距离的非线性可观测性协同定位

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8916915

Brandon Araki, Igor Gilitschenski, Tatum Ogata, Alex Wallar, Wilko Schwarting, Zareen Choudhury, S. Karaman, D. Rus

{"title":"Range-based Cooperative Localization with Nonlinear Observability Analysis","authors":"Brandon Araki, Igor Gilitschenski, Tatum Ogata, Alex Wallar, Wilko Schwarting, Zareen Choudhury, S. Karaman, D. Rus","doi":"10.1109/ITSC.2019.8916915","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8916915","url":null,"abstract":"Accurate localization of other cars in scenarios such as intersection navigation, intention-aware planning, and guardian systems is a critical component of safety. Multi-robot cooperative localization (CL) provides a method to estimate the joint state of a network of cars by exchanging information between communicating agents. However, there are many challenges to implementing CL algorithms on physical systems, including network delays, unmodeled dynamics, and non-constant velocities. In this work, we present a novel experimental framework for range-based cooperative localization that enables the testing of CL algorithms in realistic conditions, and we perform experiments using up to five cars. For state estimation, we develop and compare a particle filter, an Unscented Kalman Filter, and an Extended Kalman Filter that are compatible with nonlinear dynamics and the asynchronous reception of messages. We also model the relative transform between two unicycle models and perform a nonlinear observability analysis on the system, giving us insight into the measurements required to estimate the system’s state. Our approach enables relative localization of multiple vehicles in the absence of any global reference frame or joint map, and we demonstrate the effectiveness of our system in real-world experiments. Our results show that the UKF is likely the best candidate to use for the CL task.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"148 1","pages":"1864-1870"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86654873","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: 3

Hierarchical Regional Control for Traffic Grid Signal Optimization 交通网格信号优化的层次区域控制

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917513

Lingzhou Shu, Jia Wu, Ziyan Li

{"title":"Hierarchical Regional Control for Traffic Grid Signal Optimization","authors":"Lingzhou Shu, Jia Wu, Ziyan Li","doi":"10.1109/ITSC.2019.8917513","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917513","url":null,"abstract":"Centralized traffic control in a large-scale grid is quite challenging due to the large search space of the policy. To deal with this problem, we propose a hierarchical regional control framework that can learn more quickly and efficiently, based on prior knowledge. Specifically, the traffic at intersections is controlled by local controller based on well-adjusted policies. The coordination of the local controllers is decided by a master controller that is trained by using reinforcement learning. The control of the whole grid is handled solely by learning a master policy. The master controller continuously observes the state of the traffic network and predicts the best possible traffic control strategy for the current state. In this way, the dimension of the action space is dramatically decreased, and it is much easier to explore the optimal policy. We verify our method by implementing a series of experiments in SUMO. The numerical experiments demonstrate that our method outperforms the traditional methods and the new control methods based on deep reinforcement learning in various typical scenarios. We also demonstrate that our method is easy to train and operates robustly.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"7 1","pages":"3547-3552"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91050271","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

Simulation-Based Methods for Validation of Automated Driving: A Model-Based Analysis and an Overview about Methods for Implementation 基于仿真的自动驾驶验证方法:基于模型的分析及实现方法概述

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917072

Stefan Jesenski, J. Stellet, Wolfgang Branz, Johann Marius Zöllner

引用次数: 8

Trajectory Planning for a Pseudo Omnidirectional Vehicle using Particle Swarm Optimization 基于粒子群算法的伪全向车辆轨迹规划

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917200

Philip Schörner, J. Doll, Maximilian Galm, Johann Marius Zöllner

引用次数: 1

Game theoretic decision making for autonomous vehicles’ merge manoeuvre in high traffic scenarios 大交通场景下自动驾驶车辆归并机动的博弈决策

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917314

M. Garzón, A. Spalanzani

引用次数: 18

Cyber-Physical-Social Motivated Collaborative Platoon Heads Selection for Intelligent and Connected Vehicles 基于网络-物理-社会动机的智能网联车辆协同排长选择

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917372

Siru Chen, Pengfei Zhu, W. Yan, Konglin Zhu, Lin Zhang

{"title":"Cyber-Physical-Social Motivated Collaborative Platoon Heads Selection for Intelligent and Connected Vehicles","authors":"Siru Chen, Pengfei Zhu, W. Yan, Konglin Zhu, Lin Zhang","doi":"10.1109/ITSC.2019.8917372","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917372","url":null,"abstract":"Vehicle platoon service is considered as a promising framework for Intelligent Transportation System (ITS) to reduce energy cost, and meanwhile enhance driving safety and comfortability. In platoon service, platoon head takes the crucial role for the quality of service. The secure and trustworthy platoon heads with good driving skills will provide a better service than untrusted ones. How to motivate secure platoon heads for the platoon service becomes an interesting problem. In this paper, we formulate the trust platoon heads selection as a platoon utility maximization (PUM) problem. Then we employ game-theoretical approach showing that the PUM game is a potential game, and thus exists a Nash Equilibrium. Furthermore, we propose a cyber-physical-social approach to motivate vehicles to become platoon heads and at the same time maximize the platoon utility by seeking for the Nash Equilibrium. The extensive evaluation results show that the proposed platoon heads selection approach effectively stimulate more trustworthy users to be platoon heads and gains up to 60% more platoon utility compared with baseline methods.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"1 1","pages":"1173-1177"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89723152","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

Ground Vehicle Monocular Visual Odometry 地面车辆单目视觉里程计

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917391

M. Sabry, Abdulla Al-Kaff, A. Hussein, Slim Abdennadher

引用次数: 4

Modeling Individuals' Largest Daily Trip Displacement using Extreme Value Theory 利用极值理论对个体最大日行程位移进行建模

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917413

Kaiqiang Xie, Lu Ma, Hui Xiong, Shasha Wu

引用次数: 0

A Generalized Stochastic Petri Net Model for Performance Analysis of Trackside Infrastructure in Railway Station Areas under Uncertainty * 不确定条件下铁路站区轨道旁基础设施性能分析的广义随机Petri网模型*

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917459

Malte Schmidt, N. Weik, Stephan Zieger, A. Schmeink, Nils Nießen

引用次数: 3