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Emerging Technologies for Sustainable Intelligent Cooperative Vehicle-Infrastructure Transportation Systems

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 6858

Special Issue Editors


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Guest Editor
School of Transportation, Southeast University; Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China
Interests: big data analytics; intelligent transportation systems; intelligent cooperative vehicle-infrastructure systems
School of Transportation, Southeast University; Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China
Interests: intelligent transportation systems; big data analytics; freeway poractive control
Department of Civil and Environmental Engineering, University of Wisconsin–Madison, 1415 Engineering Dr, Madison, WI 53706, USA
Interests: connected and automated vehicle control; intelligent transportation system; traffic flow theory
Special Issues, Collections and Topics in MDPI journals
Department of Architecture and Civil Engineering; Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
Interests: connected and automated vehicles; motion planning; signalized intersection control; electric vehicle charging strategy

Special Issue Information

Dear Colleagues,

We are calling for papers for a Special Issue of the journal Sustainability on research into sustainable, intelligent, cooperative vehicle-infrastructure transportation applications, intelligent vehicle designs, and traffic analysis assisted by emerging technologies. The revolutionary development of sustainable transportation and vehicles brings great opportunities and challenges to improve the safety, throughput, and energy efficiency of transport systems. Effective design and analysis of smart vehicles and transportation systems depend on various technical, operational, and political factors, and require multi-disciplinary and novel techniques. Intelligent vehicles and transportation systems are mutually dependent. The expected dramatic change in intelligent vehicles and sustainable transportation systems is envisioned to happen in the near future. Therefore, new algorithms, sustainable system designs, and analysis tools have become a significant area of research, with emerging techniques. The overall objective of this Special Issue is to collect innovative contributions to the application of advanced techniques in sustainable, intelligent, cooperative vehicle-infrastructure transportation systems. Proposed papers for this Special Issue may cover a broad range of vehicle control, vehicle energy management, intelligent system design, modeling and analysis, connected and automated vehicle, transportation system proactive control, and artificial intelligence applications, as long as the focus is on emerging techniques for sustainable transportation systems.

Prof. Dr. Huachun Tan
Dr. Fan Ding
Dr. Yang Zhou
Dr. Jiaming Wu
Guest Editors

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Keywords

  • artificial intelligence applications on transportation systems
  • connected automated vehicle control algorithms
  • traffic operation and management assisted by emerging technologies
  • traffic safety analysis in an intelligent and connected traffic environment
  • traffic flow prediction, modeling, and analysis for emerging transportation systems
  • emerging sustainable transportation systems
  • intelligent cooperative vehicle-infrastructure transportation system design
  • vehicular energy management

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Published Papers (3 papers)

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Research

14 pages, 3075 KiB  
Article
Finding the Optimal Bus-Overtaking Rules for Bus Stops with Two Tandem Berths
by Lu Liu, Zhanglei Bian and Qinghui Nie
Sustainability 2022, 14(9), 5343; https://doi.org/10.3390/su14095343 - 28 Apr 2022
Cited by 3 | Viewed by 2212
Abstract
Overtaking rule is a key factor for the estimation of bus discharge flow and bus delay at stops. In general, there are four kinds of overtaking rules, namely no-overtaking, enter-overtaking, exit-overtaking and free-overtaking. This paper studies a two-berth tandem bus stop in a [...] Read more.
Overtaking rule is a key factor for the estimation of bus discharge flow and bus delay at stops. In general, there are four kinds of overtaking rules, namely no-overtaking, enter-overtaking, exit-overtaking and free-overtaking. This paper studies a two-berth tandem bus stop in a saturated state and proposes calculation models for the maximum bus discharge flow and average berth blocking time under different overtaking rules. Cellular automata simulation is applied to verify the model’s reliability. Then the influence of bus dwell time characteristics and overtaking rules are analyzed. Results show that overtaking has a positive impact on the maximum bus discharge flow and average berth blocking time to a certain extent. If only one overtaking behavior is allowed, the exit-overtaking rule is recommended. The study reveals that overtaking behavior plays an important role in bus service level and operational efficiency. Bus-overtaking rules are suggested to be changed with different bus flow states to obtain the optimal berth effectiveness. Full article
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19 pages, 1117 KiB  
Article
Radio Frequency Fingerprint-Based DSRC Intelligent Vehicle Networking Identification Mechanism in High Mobility Environment
by Tianshu Chen, Aiqun Hu and Yu Jiang
Sustainability 2022, 14(9), 5037; https://doi.org/10.3390/su14095037 - 22 Apr 2022
Cited by 4 | Viewed by 1958
Abstract
In recent years, Dedicated Short-Range Communication (DSRC) vehicle interconnection technology has achieved mature development and broad applications, which is the key Vehicle to Everything (V2X) technology to realize transport intelligence. However, the openness of wireless transmission and the mobility of wireless terminals cause [...] Read more.
In recent years, Dedicated Short-Range Communication (DSRC) vehicle interconnection technology has achieved mature development and broad applications, which is the key Vehicle to Everything (V2X) technology to realize transport intelligence. However, the openness of wireless transmission and the mobility of wireless terminals cause the identification mechanism of the DSRC system to face serious security threats. A radio frequency fingerprint (RFF)-based identification method can better resist the identity attack and spoofing by extracting the hardware characteristics formed by the differences of electronic components to authenticate different devices. Therefore, in this paper a novel RFF identification mechanism is proposed for IEEE 802.11p protocol-based DSRC intelligent vehicle networking devices suitable for a high mobility environment, in which the preamble field features of physical layer frames are extracted as device fingerprints, and the random forest algorithm and sequential detection method are used to distinguish and authenticate different devices. The experiment and simulation results demonstrate that the identification accuracy rates of the eight DSRC modules in the low-speed LOS and NLOS experimental states and up to 70 km/h high-speed simulations all exceed 99%, illustrating that this method has important application value in the field of identity authentication of V2X devices in high-speed scenarios. Full article
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21 pages, 1004 KiB  
Article
The Effects of Life Course Events on Car Ownership and Sustainable Mobility Tools Adoption Decisions: Results of an Error Component Random Parameter Logit Model
by Gaofeng Gu, Tao Feng, Chixing Zhong, Xiaoxi Cai and Jiang Li
Sustainability 2021, 13(12), 6816; https://doi.org/10.3390/su13126816 - 16 Jun 2021
Cited by 5 | Viewed by 1906
Abstract
Life course events can change household travel demand dramatically. Recent studies of car ownership have examined the impacts of life course events on the purchasing, replacing, and disposing of cars. However, with the increasing diversification of mobility tools, changing the fleet size is [...] Read more.
Life course events can change household travel demand dramatically. Recent studies of car ownership have examined the impacts of life course events on the purchasing, replacing, and disposing of cars. However, with the increasing diversification of mobility tools, changing the fleet size is not the only option to adapt to the change caused by life course events. People have various options with the development of sustainable mobility tools including electric car, electric bike, and car sharing. In order to determine the impacts of life course events on car ownership and the decision of mobility tool type, a stated choice experiment was conducted. The experiment also investigated how the attributes of mobility tools related to the acceptance of them. Based on existing literature, we identified the attributes of mobility tools and several life course events which are considered to be influential in car ownership decision and new types of mobility tools choice. The error component random parameter logit model was estimated. The heterogeneity across people on current car and specific mobility tools are considered. The results indicate people incline not to sell their current car when they choose an electric bike or shared car. Regarding the life course events, baby birth increases the probability to purchase an additional car, while it decreases the probability to purchase an electric bike or joining a car sharing scheme. Moreover, the estimation of error components implies that there is unobserved heterogeneity across respondents on the sustainable mobility tools choice and the decision on household’s current car. Full article
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