On the Challenges of Mobile Crowdsensing for Traffic Estimation

被引：8

作者：

Gil, Daniela Socas ^{[1
,2
]}

d'Orey, Pedro M. ^{[3
]}

Aguiar, Ana ^{[3
]}

机构：

[1] Univ Simon Bolivar, Caracas, Venezuela

[2] Univ Porto, Porto, Portugal

[3] Univ Porto, Inst Telecomunicacoes, Porto, Portugal

来源：

PROCEEDINGS OF THE 15TH ACM CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS (SENSYS'17) | 2017年

关键词：

Crowdsensing; traffic estimation;

D O I：

10.1145/3131672.3136958

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Traffic congestion adversely impacts our lives. Traffic estimation resorting to mobile (crowdsensing) probes is a challenging task. We present key challenges for accurate and real-time traffic estimation resorting to crowdsensing data, namely data sparsity, user trip diversity, population bias, data quality, among others. We propose solutions to address some of these issues and demonstrate the relevance of others through an exploratory data analysis.

引用

页数：2

共 50 条

[1] Traffic Condition Estimation Using Vehicular Crowdsensing Data
Shao, Lu
Wang, Cheng
Li, Zhong
Jiang, Changjun
2015 IEEE 34TH INTERNATIONAL PERFORMANCE COMPUTING AND COMMUNICATIONS CONFERENCE (IPCCC), 2015,
[2] CrowdPatrol: A Mobile Crowdsensing Framework for Traffic Violation Hotspot Patrolling
Jiang, Zhihan
Zhu, Hang
Zhou, Binbin
Lu, Chenhui
Sun, Mingfei
Ma, Xiaojuan
Fan, Xiaoliang
Wang, Cheng
Chen, Longbiao
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (03) : 1401 - 1416
[3] An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation
Rahman, Sawsan Abdul
Mourad, Azzam
El Barachi, May
IEEE ACCESS, 2019, 7 : 163323 - 163340
[4] RTS: road topology-based scheme for traffic condition estimation via vehicular crowdsensing
Shao, Lu
Wang, Cheng
Liu, Lu
Jiang, Changjun
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2017, 29 (03)
[5] Toward Efficient Mechanisms for Mobile Crowdsensing
Zhang, Xinglin
Yang, Zheng
Liu, Yunhao
Li, Jianqiang
Ming, Zhong
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017, 66 (02) : 1760 - 1771
[6] A Reference Architecture for Mobile Crowdsensing Platforms
Diniz, Herbertt B. M.
Silva, Emanoel C. G. F.
Nogueira, Thomas C. C.
Gama, Kiev
PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL 2 (ICEIS), 2016, : 600 - 607
[7] Maximum Profit Routing for Mobile Crowdsensing
Li, Zhiyao
Zhang, Jiale
Gao, Xiaofeng
Chen, Guihai
2022 21ST ACM/IEEE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN 2022), 2022, : 441 - 450
[8] QoS Assessment of Mobile Crowdsensing Services
Salvatore Distefano
Francesco Longo
Marco Scarpa
Journal of Grid Computing, 2015, 13 : 629 - 650
[9] In-network Collaborative Mobile Crowdsensing
Du, Yifan
2020 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS), 2020,
[10] QoS Assessment of Mobile Crowdsensing Services
Distefano, Salvatore
Longo, Francesco
Scarpa, Marco
JOURNAL OF GRID COMPUTING, 2015, 13 (04) : 629 - 650

← 1 2 3 4 5 →