IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i10p8416-d1152892.html
   My bibliography  Save this article

The Impact of In-Vehicle Traffic Lights on Driving Characteristics in the Presence of Obstructed Line-of-Sight

Author

Listed:
  • Yunshun Zhang

    (Automobile Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
    Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan)

  • Qishuai Xie

    (Automobile Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Minglei Gao

    (Automobile Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Yuchen Guo

    (Automobile Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

Abstract

In-vehicle traffic lights (IVTLs) have been identified as a potential means of eco-driving. However, the extent to which they influence driving characteristics in the event of obstructed on-road traffic lights (ORTLs) has yet to be fully examined. Firstly, the situation of partially deployed IVTLs in both vehicles was analyzed to identify the factors that affect driving characteristics. Through the following distance model, relative vehicle speed, acceleration and deceleration, and following distance were recognized as the contributing factors. The evaluation indicators for driving characteristics were thereby further established. Then, a hardware-in-the-loop simulation platform was built using PreScan 8.5-MATLAB/Simulink R2018b joint simulation software and a Logitech G29 device. IVTLs were implemented using modules in the joint simulation software. Finally, under the scenarios of obstructed ORTLs and various deployment conditions of IVTLs, the original data were collected from 50 experimental subjects with simulated driving. The subjects included 25 males and 25 females, all of whom were non-professional drivers, with ages ranging from 20 to 40 years old. The conclusion was reached that IVTLs could improve driving comfort by approximately 10% in sunny weather ( p = 0.008 < 0.05, p = 0.023 < 0.05; p = 0.046 < 0.05, p = 0.001 < 0.05), driving maneuverability by approximately 30% in foggy weather ( p = 0.033 < 0.05), and driving safety by approximately 50% in the ORTLs obstructed by a truck scenario ( p = 0.019 < 0.05). In general, even if only one vehicle was equipped with IVTLs, certain gain effects on the driving characteristics of both vehicles could still be provided.

Suggested Citation

  • Yunshun Zhang & Qishuai Xie & Minglei Gao & Yuchen Guo, 2023. "The Impact of In-Vehicle Traffic Lights on Driving Characteristics in the Presence of Obstructed Line-of-Sight," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8416-:d:1152892
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/10/8416/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/10/8416/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Toledo, Galit & Shiftan, Yoram, 2016. "Can feedback from in-vehicle data recorders improve driver behavior and reduce fuel consumption?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 194-204.
    2. Gheorghe-Daniel Voinea & Cristian Cezar Postelnicu & Mihai Duguleana & Gheorghe-Leonte Mogan & Radu Socianu, 2020. "Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System," IJERPH, MDPI, vol. 17(19), pages 1-20, September.
    3. Guoqiang Zhang & Jun Chen & Jingya Zhao, 2017. "Safety Performance Evaluation of a Three-Leg Unsignalized Intersection Using Traffic Conflict Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-6, April.
    4. Lu, Huapu & Chen, Mingyu & Kuang, Wenbo, 2020. "The impacts of abnormal weather and natural disasters on transport and strategies for enhancing ability for disaster prevention and mitigation," Transport Policy, Elsevier, vol. 98(C), pages 2-9.
    5. Giuseppina Pappalardo & Salvatore Cafiso & Alessandro Di Graziano & Alessandro Severino, 2021. "Decision Tree Method to Analyze the Performance of Lane Support Systems," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Federico Orsini & Mariaelena Tagliabue & Giulia De Cet & Massimiliano Gastaldi & Riccardo Rossi, 2021. "Highway Deceleration Lane Safety: Effects of Real-Time Coaching Programs on Driving Behavior," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    2. Hoffmann, Christin & Thommes, Kirsten, 2024. "Can leaders motivate employees’ energy-efficient behavior with thoughtful communication?," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    3. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    4. Jian Gong & Junzhu Shang & Lei Li & Changjian Zhang & Jie He & Jinhang Ma, 2021. "A Comparative Study on Fuel Consumption Prediction Methods of Heavy-Duty Diesel Trucks Considering 21 Influencing Factors," Energies, MDPI, vol. 14(23), pages 1-18, December.
    5. Darko Babić & Dario Babić & Mario Fiolić & Arno Eichberger & Zoltan Ferenc Magosi, 2021. "A Comparison of Lane Marking Detection Quality and View Range between Daytime and Night-Time Conditions by Machine Vision," Energies, MDPI, vol. 14(15), pages 1-15, August.
    6. Cao, Jieyu & Chen, Junlan & Guo, Xiucheng & Wang, Ling, 2023. "Trajectory data-based severe conflict prediction for expressways under different traffic states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    7. Mujahid Ali & Dimas Bayu Endrayana Dharmowijoyo & Afonso R. G. de Azevedo & Roman Fediuk & Habil Ahmad & Bashir Salah, 2021. "Time-Use and Spatio-Temporal Variables Influence on Physical Activity Intensity, Physical and Social Health of Travelers," Sustainability, MDPI, vol. 13(21), pages 1-24, November.
    8. Javier Goikoetxea Gonzalez & Diego Casado-Mansilla & Diego López-de-Ipiña, 2020. "Analysis of Driver’s Reaction Behavior Using a Persuasion-Based IT Artefact," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    9. Yuan, Yali & Yang, Xiaobao & Zhang, Junyi & Song, Dongdong & Yue, Xianfei, 2024. "Adaptive behavior of intercity travelers within urban agglomeration in response to adverse weather: Accounting for multilayer unobserved heterogeneity," Transport Policy, Elsevier, vol. 153(C), pages 141-158.
    10. Jingyan Wu & Saini Yang & Feng Yang & Xihui Yin, 2021. "Road Weather Monitoring System Shows High Cost-Effectiveness in Mitigating Malfunction Losses," Sustainability, MDPI, vol. 13(22), pages 1-13, November.
    11. Sehyun Tak & Sari Kim & Hwapyeong Yu & Donghoun Lee, 2022. "Analysis of Relationship between Road Geometry and Automated Driving Safety for Automated Vehicle-Based Mobility Service," Sustainability, MDPI, vol. 14(4), pages 1-13, February.
    12. Guoqiang Zhang & Qiqi Zhou & Jun Chen, 2021. "Exploring Factors Impacting on the Lane Choice of Riders of Non-Motorized Vehicles at Exit Legs of Signalized At-Grade Intersections," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    13. Philipp Luz & Li Zhang & Jinyue Wang & Volker Schwieger, 2021. "Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security," Sustainability, MDPI, vol. 13(17), pages 1-18, August.
    14. Ma. Janice J. Gumasing & Frances Jeann Charlize S. Bermejo & Keisha Taranee C. Elpedes & Lady Fatima E. Gonzales & Aaron Chastine V. Villajin, 2023. "Antecedents of Waze Mobile Application Usage as a Solution for Sustainable Traffic Management among Gen Z," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    15. Chee Sun Lee & Peck Yeng Sharon Cheang & Massoud Moslehpour, 2022. "Predictive Analytics in Business Analytics: Decision Tree," Advances in Decision Sciences, Asia University, Taiwan, vol. 26(1), pages 1-30, March.
    16. Wan-Li Zhang & Chun-Ping Chang & Yang Xuan, 2022. "The impacts of climate change on bank performance: What’s the mediating role of natural disasters?," Economic Change and Restructuring, Springer, vol. 55(3), pages 1913-1952, August.
    17. Ghulam E Mustafa Abro & Saiful Azrin B. M. Zulkifli & Kundan Kumar & Najib El Ouanjli & Vijanth Sagayan Asirvadam & Mahmoud A. Mossa, 2023. "Comprehensive Review of Recent Advancements in Battery Technology, Propulsion, Power Interfaces, and Vehicle Network Systems for Intelligent Autonomous and Connected Electric Vehicles," Energies, MDPI, vol. 16(6), pages 1-31, March.
    18. Ran Tu & Junshi Xu & Tiezhu Li & Haibo Chen, 2022. "Effective and Acceptable Eco-Driving Guidance for Human-Driving Vehicles: A Review," IJERPH, MDPI, vol. 19(12), pages 1-14, June.
    19. Yichi Zhang & Xuan Dou & Hanping Zhao & Ying Xue & Jinfan Liang, 2023. "Safety Risk Assessment of Low-Volume Road Segments on the Tibetan Plateau Using UAV LiDAR Data," Sustainability, MDPI, vol. 15(14), pages 1-19, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8416-:d:1152892. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.