2019 IEEE Intelligent Transportation Systems Conference (ITSC)最新文献_第3页

Exploring Potential Travel Demand of Customized Bus Using Smartcard Data* 利用智能卡数据探索定制巴士的潜在出行需求*

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8916843

Rongge Guo, W. Guan, A. Huang, Wen-yi Zhang

引用次数: 10

Integrating the management and design of urban road network to alleviate tide traffic* 整合城市道路网络的管理与设计，缓解潮汐交通*

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917083

Guangmin Wang, Y. Q. Li, Meng Xu

{"title":"Integrating the management and design of urban road network to alleviate tide traffic*","authors":"Guangmin Wang, Y. Q. Li, Meng Xu","doi":"10.1109/ITSC.2019.8917083","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917083","url":null,"abstract":"During the morning and evening rush hour in big cities, roads present tide traffic feature, which not only worsens the traffic congestion but also wastes road resources. In this paper, we use the lane reversal to balance the asymmetric traffic flow distribution in the two directions of one road and lane addition to increase road supply. Moreover, we use the tradable credits scheme to manage the mobility. Thus, we integrate the lane reversal, lane addition and tradable credits scheme to alleviate the traffic congestion due to tide traffic, which is modeled into a mix-integer bilevel programming. In this model, the network authority decides the lane reversal scheme, lane addition scheme and credits charging scheme to minimize the total system travel time, while the travelers follow the user equilibrium (UE) to minimize their generalized travel cost. After proposing the algorithm for the model, the Sioux Falls network is adopted to illustrate the numerical experiments, which show that the integration of the management and design can obtain the better performance to alleviate tide traffic and traffic congestion.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"94 1","pages":"708-713"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79854619","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: 0

A Rear-end Collision Warning Algorithm based on Vehicular Communication* 基于车辆通信的追尾碰撞预警算法*

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917505

Dawei Cao, Zhiying Qin, R. Liu, Yang Yang, Dexing Zhong

引用次数: 0

Dynamical Interaction based Multi-objects Operation Simulation for Hub Airport APM System 基于动态交互的枢纽机场APM系统多目标运行仿真

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917321

Yue Cao, W. Shangguan, Xinhang Shang, Weizhi Qiu, Yu Du

引用次数: 2

Model Predictive Control Allocation of Systems with Different Dynamics 不同动态系统的模型预测控制分配

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917438

Moad Kissai, B. Monsuez, X. Mouton, D. Martinez, A. Tapus

引用次数: 6

A Feasibility Study on Upgrading the Static TLC Infrastructure to Adaptive TLC 静态TLC基础设施升级为自适应TLC的可行性研究

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8916836

Abhyudai Bisht, Khilan Ravani, Manish Chaturvedi, Naveen Kumar

{"title":"A Feasibility Study on Upgrading the Static TLC Infrastructure to Adaptive TLC","authors":"Abhyudai Bisht, Khilan Ravani, Manish Chaturvedi, Naveen Kumar","doi":"10.1109/ITSC.2019.8916836","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8916836","url":null,"abstract":"This paper evaluates the feasibility of upgrading the static traffic light control to a local adaptive traffic light control, for a road network carrying less-lane-disciplined, heterogeneous traffic. We analyze the performance of a few deep learning based object detection algorithms (e.g., SSD, RCNN), with respect to the computation requirements, and accuracy for computing the Passenger Car Unit (PCU) count, under heterogeneous traffic condition. We propose an algorithm for a local adaptive TLC, leveraging the existing infrastructure. This algorithm efficiently computes the phase duration, based on round-robin scheduling, considering real-time traffic information. Simulations are carried out to analyze the effect of varying error rates in PCU count on the performance of adaptive TLCs. Further, the performance of the proposed TLC is compared with the conventional static TLC and the recently proposed micro auction based adaptive TLC algorithms. The simulation results suggest that the proposed TLC algorithm can tolerate 20% error in the PCU count without degrading the performance. Also, this work demonstrates that the traffic information with the required accuracy can be processed in real time using the available platforms (e.g., Raspberry Pi). The proposed work establishes the feasibility of upgrading the existing static TLC to a local adaptive TLC with minimal infrastructure requirement.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"43 1","pages":"2563-2568"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82528704","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

An Integrated Approach to Probabilistic Vehicle Trajectory Prediction via Driver Characteristic and Intention Estimation 基于驾驶员特征和意图估计的概率车辆轨迹预测方法

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917039

Jinxin Liu, Yugong Luo, Hui Xiong, Tinghan Wang, Heye Huang, Zhihua Zhong

引用次数: 16

Comparing and Contrasting NEMA-based Virtual Phase-Link control with Max Pressure Control in Arterial Signal Systems 动脉信号系统中基于nema的虚拟相链控制与最大压力控制的比较

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917056

Qichao Wang, M. Abbas

{"title":"Comparing and Contrasting NEMA-based Virtual Phase-Link control with Max Pressure Control in Arterial Signal Systems","authors":"Qichao Wang, M. Abbas","doi":"10.1109/ITSC.2019.8917056","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917056","url":null,"abstract":"In this work, we compared two adaptive control systems: (1) a National Electrical Manufacturing Association (NEMA) based virtual phase-link macroscopic model and (2) a Max Pressure controller based model. The control variables of these models are the green splits. We contrasted the performance of these two models in controlling traffic signal systems in an experimental Vissim framework, and compared them with two other control strategies. It was found that the virtual phaselink method outperformed two control strategies and performed close, by not as good as, the Max Pressure control strategy. We found that the disadvantage of the virtual phase-link method stemmed from that fact that the cycle time was not fully used for some of the intersections. It was also found that the platoon created by the cyclic control schemes might slow down to allow vehicles to switch lanes. Compared to the Max Pressure control strategy, the virtual phase-link method can be implemented by any traffic controller that follows the NEMA standards. The real-time requirement of the virtual phase-link method is not as strict as the Max Pressure control strategy.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"299 1","pages":"1361-1366"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87532995","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: 1

Attention Neural Baby Talk: Captioning of Risk Factors while Driving 注意神经婴儿语:驾驶时危险因素的说明

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917187

Yuki Mori, Hiroshi Fukui, Tsubasa Hirakawa, Jo Nishiyama, Takayoshi Yamashita, H. Fujiyoshi

{"title":"Attention Neural Baby Talk: Captioning of Risk Factors while Driving","authors":"Yuki Mori, Hiroshi Fukui, Tsubasa Hirakawa, Jo Nishiyama, Takayoshi Yamashita, H. Fujiyoshi","doi":"10.1109/ITSC.2019.8917187","DOIUrl":"https://doi.org/10.1109/ITSC.2019.8917187","url":null,"abstract":"Driving has various risk factors, including the possibility of traffic accidents involving pedestrians and/or oncoming vehicles. A driver assistance system that can prevent traffic accidents must be able to get the driver ' s attention. A practical solution for attention attraction should involve caption generation from in-vehicle images. Although a number of approaches for caption generation with deep neural networks have been proposed, they are inadequate for the specific risk factors while driving. The reason is that conventional captioning methods focus on not these factors but the entirety of an image. To tackle this problem, we first created a dataset to attract attention, one that considers risk factors during driving. Furthermore, we propose an image captioning method for the assistance system. Our method is based on neural baby talk and introduces an attention mask focusing on risk factors in an image. The mask enables our model to generate captions on each factor. Experimental results with our created dataset show that our method can generate captions for ideal attention attraction.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"2 1","pages":"4317-4322"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87571896","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

Action and Object Interaction Recognition for Driver Activity Classification 面向驾驶员活动分类的动作与目标交互识别

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI: 10.1109/ITSC.2019.8917139

Patrick Weyers, David Schiebener, A. Kummert

引用次数: 15