Cited By
View all- Kato TFukumoto NSasaki CTagami ANakao A(2024)Challenges of CPS/IoT Network Architecture in 6G EraIEEE Access10.1109/ACCESS.2024.339536312(62804-62817)Online publication date: 2024
Smart traffic management with cyber-physical systems for scenic areas
Authors: 
Shuyi Wang, Yudong Zhang, Yi LiuAuthors Info & Claims
Article No.: 5, Pages 1 - 4
Abstract
This paper proposed a method to perform smart traffic management for scenic areas with cyber-physical system (CPS) by sharing information among tourists (the mobile phone application), the traffic information platform, and parking lots. Smart traffic management is suggested to be performed based on the interaction of information sharing and physical driving and parking. Taking Wuyuan scenic spots in Jiangxi province as an example, the AnyLogic simulation was used to simulate the cyber-physical system of traffic control and information sharing applying the Markov model. Simulation results show that the information flow can significantly shorten the waiting time of vehicles and improve the utilization rate of scenic areas. The method proposed in this paper may benefit to reduce traffic congestion and perform smart traffic management for scenic areas in busy seasons.
References
[1]
Jin C, Cheng J, Xu J, et al. Self-driving tourism induced carbon emission flows and its determinants in well-developed regions: A case study of Jiangsu Province, China[J]. Journal of Cleaner Production, 2018, 186(JUN.10):191--202.
[2]
Xinyue W, Wenliang Z, Xuejing L, et al. Spatial-temporal Evolution and Relationship Between Tourism Industrial Agglomeration and Efficiency in China's Coastal Provinces: An Analysis Based on 114 Cities with PVAR Model[J]. Journal of Ocean University of China (Social Sciences), 2019.
[3]
People's government of Wuyuan County. Government working report (2010-2019) (2020-4-15) [R/OL]. http://gk.jxwy.gov.cn/fzgh/gzjh/51808.htm.
[4]
Haiyan Z, Hongzhi G, Wanying L, et al. A Study on the Behavior of Holiday Tourists Coping with Congestion[A]. CICTP 2020: Advanced Transportation Technologies and Development-Enhancing Connections [C].2020.
[5]
Han Y, Zhang T, Wang M. Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage[J]. Transportation Research Part A: Policy and Practice, 2020, 134.
[6]
Malik S, Kim D H. Optimal Travel Route Recommendation Mechanism Based on Neural Networks and Particle Swarm Optimization for Efficient Tourism Using Tourist Vehicular Data [J]. Sustainability, 2019, 11.
[7]
Xiongbin W, Hongzhi G, Yan H. Tour Route Optimization Model Based on Tourist Experience under Multi-constraints[J]. Science Technology and Engineering, 2018.
[8]
Siyuan D, Chunxiang G, Maozhu J. Agent-based simulation on tourists' congestion control during peak travel period using Logit model[J]. Chaos, Solitons & Fractals, 2016,89: 187--194.
[9]
Mingming H, Rong Z, Peng G, et al. A Simulation Study of the Temporal and Spatial Distribution in Scenic Area Based on the Management Entropy[J]. Tourism science, 2018.
[10]
Liqiang Q, Yan S, Shanzhi C, et al. Modeling and Analysis of Safety Messages Propagation in Platoon-Based Vehicular Cyber-Physical Systems[J]. Wireless Communications & Mobile Computing, 2018, 2018:1--12.
[11]
Platzer, André. Cyber-Physical Systems: Overview[J]. 2018, 1):1--24.
[12]
Du J, Liu X, Rao L. Proactive Doppler Shift Compensation in Vehicular Cyber-Physical Systems[J]. IEEE/ACM Transactions on Networking, 2018:807--818.
[13]
Xin Z, Gangmin W. Optimization method of double objective traffic jam evacuation route in peak tourism period[J]. Journal of Yanshan University, 2018.
[14]
Song C, Guan W, Ma J. Potential travel cost saving in urban public-transport networks using smart phone guidance[J]. Plos One,2018,13(5): e0197181.
[15]
Ran B. Use of cell phone data in travel survey and transportation planning [J]. Urban Transport of China, 2013,11 (1) :72--81,32.
[16]
Manhong G. Research on traffic and parking problems in Wuyuan Scenic Area [D]. Jiangxi University of Finance and Economics,2018.
[17]
Gentile G, Florian M, Hamdouch Y, et al. The theory of transit assignment: Basic modelling frameworks [M]. Modelling Public Transport Passenger Flow sin the Era of Intelligent Transport Systems, Springer, Cham, 2016.
[18]
China National Tourism Administration. Guideline for Measurement of Carry Capacity of Scenic Area [S].2014.
[19]
Zaki J F, Alieldin A, Hussein S E, et al. Traffic congestion prediction based on Hidden Markov Models and contrast measure[J]. Ain Shams Engineering Journal
[20]
Xue Y, Luliang T, Kathleen S, et al. Automatic change detection in lane-level road networks using GPS trajectories[J]. International Journal of Geographical Information science, 2018, 32(3-4):601--621.
[21]
Cuiying S, Wei G, Jihui M. Bus Route Choice Model Considering Congestion Information Provided by Smartphone[J]. Journal of Transportation Systems Engineering and Information Technology,2019,19(6):237--248.
Index Terms
- Smart traffic management with cyber-physical systems for scenic areas
Recommendations
Modeling Automotive Cyber Physical Systems
DCABES '13: Proceedings of the 2013 12th International Symposium on Distributed Computing and Applications to Business, Engineering & ScienceAutomotive cyber physical systems (CPSs) involve interactions between software controllers, communication networks, and physical devices. These systems are among the most complex cyber physical systems being designed by humans. However, automotive cyber ...
Celer: A Smart Fleet Management System (Optimizing Traffic Flow in New York City)
SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2As society moves closer to fully autonomous vehicles, it must eventually make vehicles work together. This would reduce traffic jams, reduce cost of trips, reduce overall travel time, reduce the environmental impact, and reduce the number of casualties ...
Characteristics of Urban Road Non-recurrent Traffic Congestion Based on Floating Car Data
EITCE '20: Proceedings of the 2020 4th International Conference on Electronic Information Technology and Computer EngineeringNon-recurrent traffic congestion caused by traffic accidents is one of the most important factors that affect the operational efficiency of urban road networks. In this paper, the floating car data (FCD) and the traffic accident data in Wuhan were ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2020
44 pages
Copyright © 2020 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 November 2020
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Key R&D Program of China
- National Natural Science Foundation of China
Conference
SIGSPATIAL '20
Sponsor:
SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems
November 3, 2020
Washington, Seattle
Acceptance Rates
Overall Acceptance Rate 30 of 54 submissions, 56%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 73Total Downloads
- Downloads (Last 12 months)10
- Downloads (Last 6 weeks)2
Reflects downloads up to 12 Dec 2024
Other Metrics
Citations
Cited By
View all- Kato TFukumoto NSasaki CTagami ANakao A(2024)Challenges of CPS/IoT Network Architecture in 6G EraIEEE Access10.1109/ACCESS.2024.339536312(62804-62817)Online publication date: 2024
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in