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Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments

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

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 31068

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Dr. Young-Ji Byon

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Guest Editor

Department of Civil Infrastructure and Environmental Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, UAE
Interests: Transportation engineering; autonomous vehicles; smart cities; GPS; GIS; airport systems; optimization; artificial intelligence
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Dr. Feng Chen

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Guest Editor

Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC, College of Transportation Engineering, Tongji University, Shanghai 1239, China
Interests: transportation safety, aviation meteorology; civil aviation safety; statistical modeling
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Meng Guo

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Guest Editor

The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China
Interests: innovative characterization methods of sustainable pavement materials; environmentally friendly pavement materials and structures; mechanistic modeling of fatigue cracking and durability of pavement materials; the mechanism of aging and recycling of asphaltic materials and its multiscale evaluation methods; emerging technologies and materials for pavement preservation and maintenance; life cycle assessment of transportation infrastructure
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With substantial impacts on crash reduction, time saving, and fuel economy, autonomous vehicles (AVs) have attracted much attention from the research community and industry. While AVs’ potential abilities to liberate us from dull driving, congestion, and potential crash risk have gained popularity, AVs influence on pavement infrastructure seems, to the best of our knowledge, to have received only limited attention. Given the rapid growth of AV technology, there is a pressing need to uncover its impact on the sustainability of traffic infrastructure. In addition, smart pavement technology, which will also influence infrastructure sustainability, has become the new concept and trend in the development of intelligent transportation. The topics of this Special Issue include, but are not limited to:

Durable pavement structure design for autonomous driving;
Smart road planning and design;
Transportation policies for infrastructure sustainability or smart roads;
Self-diagnosis or self-healing of pavement damage;
Energy harvesting pavement;
Sensor system based on smart roads;
Big data analysis based on smart roads;
Vehicle trajectory perception and prediction based on smart roads;
Life-cycle assessment of smart roads;
Finite element simulation of pavement service life under autonomous trucks;
Simulation models of mixed traffic flow (autonomous driving and manual driving);
Facility sustainability and optimal design under a mixed traffic environment;
Urban planning strategies for maintaining sustainability under a mixed traffic flow environment;
Environment friendly pavement materials and structures;
Aging and recycling of pavement materials.

Dr. Young-Ji Byon
Dr. Feng Chen
Prof. Meng Guo
Guest Editors

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Keywords

infrastructure sustainability
autonomous driving
smart road
durable pavement
transportation policies
traffic volume prediction
lateral distribution of wheel load
vehicle trajectory
pavement structure design
pavement self-healing
life-cycle assessment
pavement service life
environment friendly pavement

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Published Papers (11 papers)

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Research

13 pages, 4119 KiB

Open AccessArticle

Combination Layout of Traffic Signs and Markings of Expressway Tunnel Entrance Sections: A Driving Simulator Study

by Yong Fang, Jiayi Zhou, Hua Hu, Yanxi Hao, Dianliang Xiao and Shaojie Li

Sustainability 2022, 14(6), 3377; https://doi.org/10.3390/su14063377 - 14 Mar 2022

Cited by 10 | Viewed by 2155

Abstract

To determine a better combination of signs and markings on expressway tunnel entrance sections, three types of typical signs and markings were compared and tested according to five indicators: speed, lane lateral offset, lane change behavior, fixation behavior, and operating load, using a driving simulator. The results identified that the obvious no overtaking and speed limit signs, combined with a layer of thin red pavement, had the most influence on drivers’ speed, and they led to the highest fixation frequency of static facilities, the longest average distance from the completion point of the lane change to the entrance, and the longest average lane change distance, which could help drivers to pass through tunnel entrance sections more smoothly. The location of the static facilities should be between 3 s before the tunnel entrance and 3 s after entering the tunnel, as this is the area where a driver’s relative viewpoint changes. The improper combination of warning signs and deceleration measures will affect a driver’s judgment, causing negative effects, such as premature lane changes and an increased operating load. The research results can provide a design basis and reference for the combination setting of safety signs and markings on tunnel entrance sections. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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14 pages, 10928 KiB

Open AccessArticle

Identification of Moving Load Characteristic on Pavement Using F-P Cavity Fiber Optical Technology

by Cai Zhao, Zeying Bian, Hongduo Zhao, Lukuan Ma, Mu Guo, Kedi Peng and Erli Gao

Sustainability 2022, 14(4), 2398; https://doi.org/10.3390/su14042398 - 19 Feb 2022

Cited by 3 | Viewed by 1692

Abstract

The weigh-in-motion (WIM) system is a necessary piece of equipment for an intelligent road. It can provide real-time vehicle weight and lateral distribution data on wheel load to effectively support pavement structure design and service life analysis for autonomous driving. This paper proposed an enhanced weigh-in-motion sensors system using Fabry–Pérot (F-P) cavity fiber optical technology. Laboratory testing was performed to evaluate the feasibility of the proposed system and field application was conducted as well. The laboratory results show that the traffic loads could be obtained by measuring the center wavelength changes in the embedded F-P Cavity tunable filter. The laboratory results also show that the vehicle load and the number of vehicle axles can be estimated based on the system transfer function between the dynamic loading and the wavelength variation. The field application indicates that the weighting accuracy of the proposed system could reach 94.46% for moving vehicles, and the vehicle passing speed is the potentially relevant factor. The proposed system also has the ability to estimate the number of vehicle axles and the loading position, and the precision could reach 97.1% and 300 mm, respectively. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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11 pages, 1691 KiB

Open AccessArticle

Performance Assessment and Comparison of Two Piezoelectric Energy Harvesters Developed for Pavement Application: Case Study

by Chenchen Li, Shifu Liu, Hongduo Zhao and Yu Tian

Sustainability 2022, 14(2), 863; https://doi.org/10.3390/su14020863 - 13 Jan 2022

Cited by 4 | Viewed by 2072

Abstract

To advance the development of piezoelectric energy harvesters, this study designed and manufactured bridge-unit-based and pile-unit-based piezoelectric devices. An indoor material testing system and accelerated pavement test equipment were used to test the electrical performance, mechanical performance, and electromechanical coupling performance of the devices. The results showed that the elastic modulus of the pile structure device was relatively higher than that of the bridge structure device. However, the elastic modulus of the two devices should be improved to avoid attenuation in the service performance and fatigue life caused by the stiffness difference. Furthermore, the electromechanical conversion coefficients of the two devices were smaller than 10% and insensitive to the load magnitude and load frequency. Moreover, the two devices can harvest 3.4 mW and 2.6 mW under the wheel load simulated by the one-third scale model mobile load simulator, thus meeting the supply requirements of low-power sensors. The elastic modulus, electromechanical conversion coefficients, and electric performance of the pile structure device were more reliable than those of the bridge structure device, indicating a better application prospect in road engineering. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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17 pages, 4871 KiB

Open AccessArticle

The Compatibility between the Takeover Process in Conditional Automated Driving and the Current Geometric Design of the Deceleration Lane in Highway

by Cihe Chen, Zijian Lin, Shuguang Zhang, Feng Chen, Peiyan Chen and Lin Zhang

Sustainability 2021, 13(23), 13403; https://doi.org/10.3390/su132313403 - 3 Dec 2021

Cited by 2 | Viewed by 1745

Abstract

In recent years, the takeover process of conditional automated driving has attached a great deal of attention. However, most of the existing research has focused on the effects of human-machine interactions or driver-related features (e.g., non-driving-related tasks), while there is little knowledge about the compatibility between the takeover process and existing road geometric design. As there is a high possibility that drivers must take over the vehicle before they diverge from the mainline of the highway, this explanatory study aimed to examine the compatibility between the takeover process and the current deceleration lane geometric design. The distribution range of existing deceleration lanes’ lengths were obtained through a geo-based survey. Nine scenarios were recreated in the driving simulator which were designed with various deceleration lane lengths and driving modes (different takeover time budgets and manual driving as the baseline group). A total of 31 participants were recruited to take part in the experiment, their gaze behaviors were recorded simultaneously. Results showed that, compared with manual driving, both drivers’ horizontal and vertical gaze dispersion increased, while drivers adopted higher deceleration in the mainline and merged into the deceleration lane later under takeover conditions. Moreover, a longer deceleration lane could benefit vehicle control. However, its marginal effect was reduced with the increase of deceleration lane length. These findings can help automated vehicle manufacturers design dedicated takeover schemes for different deceleration lane lengths. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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29 pages, 2105 KiB

Open AccessArticle

Review on Lane Detection and Tracking Algorithms of Advanced Driver Assistance System

by Swapnil Waykole, Nirajan Shiwakoti and Peter Stasinopoulos

Sustainability 2021, 13(20), 11417; https://doi.org/10.3390/su132011417 - 15 Oct 2021

Cited by 23 | Viewed by 8096

Abstract

Autonomous vehicles and advanced driver assistance systems are predicted to provide higher safety and reduce fuel and energy consumption and road traffic emissions. Lane detection and tracking are the advanced key features of the advanced driver assistance system. Lane detection is the process of detecting white lines on the roads. Lane tracking is the process of assisting the vehicle to remain in the desired path, and it controls the motion model by using previously detected lane markers. There are limited studies in the literature that provide state-of-art findings in this area. This study reviews previous studies on lane detection and tracking algorithms by performing a comparative qualitative analysis of algorithms to identify gaps in knowledge. It also summarizes some of the key data sets used for testing algorithms and metrics used to evaluate the algorithms. It is found that complex road geometries such as clothoid roads are less investigated, with many studies focused on straight roads. The complexity of lane detection and tracking is compounded by the challenging weather conditions, vision (camera) quality, unclear line-markings and unpaved roads. Further, occlusion due to overtaking vehicles, high-speed and high illumination effects also pose a challenge. The majority of the studies have used custom based data sets for model testing. As this field continues to grow, especially with the development of fully autonomous vehicles in the near future, it is expected that in future, more reliable and robust lane detection and tracking algorithms will be developed and tested with real-time data sets. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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14 pages, 4767 KiB

Open AccessArticle

Research on the Anti-Reflective Cracking Performance of a Full-Depth Asphalt Pavement

by Fujin Hou, Tao Li, Xu Li, Yunliang Li and Meng Guo

Sustainability 2021, 13(17), 9499; https://doi.org/10.3390/su13179499 - 24 Aug 2021

Cited by 11 | Viewed by 2088

Abstract

In order to analyze the anti-reflective cracking performance of a full-depth asphalt pavement and study the propagation process of a reflection crack and its influencing factors, a mechanical model of pavement structural crack analysis was established based on the ABAQUS finite element software and the extended finite element method (XFEM). Based on two different loading modes of three-point bending and direct tension, the propagation process of a reflection crack is analyzed. The results show that the anti-reflective cracking performance of a full-depth asphalt pavement is better than that of a semi-rigid base pavement structure, and the loading mode II based on direct tension is more consistent with the propagation mechanism of pavement reflection cracks, while the loading mode II is more suitable for analyzing the anti-reflective cracking performance of the pavement structure. Appropriately reducing the elastic modulus of the stress-absorbing layer can significantly improve the anti-reflective cracking performance of the full-depth asphalt pavement. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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13 pages, 3178 KiB

Open AccessArticle

Using Molecular Dynamics Simulation to Analyze the Feasibility of Using Waste Cooking Oil as an Alternative Rejuvenator for Aged Asphalt

by Lin Li, Cheng Xin, Mingyang Guan and Meng Guo

Sustainability 2021, 13(8), 4373; https://doi.org/10.3390/su13084373 - 14 Apr 2021

Cited by 18 | Viewed by 2565

Abstract

The purpose of this study was to investigate the regeneration effect of waste cooking oil (WCO) on aged asphalt with molecular dynamics (MD) simulation, comparing it with a rejuvenator. Firstly, the molecular models of virgin and aged asphalt were established by blending the four components of asphalt (saturate, aromatic, resin, and asphaltenes). Then, different dosages of the rejuvenator and WCO (6, 9, and 12%) were included in the aged asphalt model for its regeneration. After that, MD simulations were utilized for researching the mechanical and cohesive properties of the recycled asphalt, including its density, viscosity, cohesive energy density (CED), shear modulus (G), bulk modulus (K), and elastic modulus (E). The results show that the density values of the asphalt models were relatively lower than the existing experimental results in the literature, which is mostly attributed to the fact that the heteroatoms of the asphalt molecules were not considered in the simulation. On the other hand, the WCO addition decreased the viscosity, the shear modulus (G), the bulk modulus (K), and the elastic modulus (E) of the aged asphalt, improving its CED. Moreover, the nature of the aged asphalt was gradually restored with increasing rejuvenator or WCO contents. Compared with the rejuvenator, the viscosity of the aged asphalt was more effectively restored through adding WCO, while the effect of the CED and the mechanical properties recovery of the aged asphalt was relatively low. This implies that WCO could restore partial mechanical properties of aging asphalt, which proves the possibility of using WCO as an asphalt rejuvenator. Additionally, the MD simulation played an important role in understanding the molecular interactions among the four components of asphalt and the rejuvenator, which will serve as a guideline to better design a WCO rejuvenator and optimize its content. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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16 pages, 4182 KiB

Open AccessArticle

Exploring the Impacts of Driving Environment on Crashes in Tunnel–Bridge–Tunnel Groups: An Eight-Zone Analytic Approach

by Zongyuan Sun, Shuo Liu, Jie Tang, Peng Wu and Boming Tang

Sustainability 2021, 13(4), 2272; https://doi.org/10.3390/su13042272 - 19 Feb 2021

Cited by 6 | Viewed by 1872

Abstract

Tunnel–bridge–tunnel groups (TBTGs) are emerging roads that often involve simple road alignments, but complex driving environments. Investigating crashes occurred in TBTGs is essential for revealing the driving environment–adaptability relationships for such roads. This study seeks to analyze the crash characteristics of component sections in TBTGs with different driving environments and compare the impact of differences in the key factor on the crashes. After TBTGs were defined through a proposed safety-critical distance metric determined via visual theory and actual crash analyses, an eight-zone analytical method considering road types and lighting was developed to probe into crashes in TBTGs. The results show that the proper safety-critical distances for bridge–tunnel and tunnel–tunnel groups are 150 and 500 m, respectively. In TBTGs, the crash rate in ordinary sections is higher than that in bridges and tunnels, particularly in the access zone. The first passed tunnel witnesses a higher proportion of crashes at the access zone and transition zone than the second tunnel. The influence of bridge and tunnel ratios on crashes is related to the ratio and type of bridges and tunnels. The findings presented herein can provide evidence-based guidance for the safety design and management of TBTGs. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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19 pages, 5287 KiB

Open AccessArticle

Preliminary Evaluation of Plasmix Compound from Plastics Packaging Waste for Reuse in Bituminous Pavements

by Clara Celauro, Rosalia Teresi, Francesco Graziano, Francesco Paolo La Mantia and Antonio Protopapa

Sustainability 2021, 13(4), 2258; https://doi.org/10.3390/su13042258 - 19 Feb 2021

Cited by 13 | Viewed by 2429

Abstract

Finding an appropriate technical solution for reusing waste plastics is crucial for creating a circular plastic economy. Although mechanical recycling is the best option for recycling post-consumer plastics, some heterogeneous mixed plastics cannot be recycled to produce secondary material due to their very low properties. In this case, alternative routes should be considered in order to limit their disposal as much as possible. Therefore, in order to solve the environmental problems in the landfills of plastic waste recycling, and to improve the mechanical performance of bitumen for road pavement, the reuse of these post-consumer plastic wastes are preliminarily evaluated for the modification of bitumen for road use. The field of polymers used so far and widely studied concerns virgin materials, or highly homogeneous materials, in case of recycled plastics. In this work, a highly heterogeneous mixed plastic—Plasmix—from the separate collection in Italy, is used as a bitumen modifier for road construction. The research focused on the dry (into the mixture) and wet (into the binder) addition of different content of the Plasmix compound, with the aim of assessing the feasibility of the modification itself. Results of the mechanical tests carried out prove an increase in performance and that there is a potential of the addition of the Plasmix compound both for binder and mixture modifications. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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13 pages, 544 KiB

Open AccessArticle

Optimization of International Roughness Index Model Parameters for Sustainable Runway

by Yu Tian, Shifu Liu, Le Liu and Peng Xiang

Sustainability 2021, 13(4), 2184; https://doi.org/10.3390/su13042184 - 18 Feb 2021

Cited by 10 | Viewed by 2654

Abstract

Pavement roughness is a critical airport pavement characteristic that has been linked to impacts such as safety and service life. A properly defined roughness evaluation method would reduce airport operational risk, prolong the life of aircraft landing gear, and optimize the decision-making process for pavement preservation, which together positively contribute to overall airport sustainability. In this study, we optimized the parameters of the International Roughness Index (IRI) model to resolve the current poor correlation between the IRI and aircraft vibration responses in order to adapt and extend the IRI’s use for airport runway roughness evaluation. We developed and validated a virtual prototype model based on ADAMS/Aircraft software for the Boeing 737–800 and then employed the model to predict the aircraft’s dynamic responses to runway pavement roughness. By developing a frequency response function for the standard 1/4 vehicle model, we obtained frequency response distribution curves for the IRI. Based on runway roughness data, we used fast Fourier transform to implement the frequency response distribution of the aircraft. We then utilized Particle Swarm Optimization to determine more appropriate IRI model parameters rather than modifying the model itself. Our case study results indicate that the correlation coefficient for the optimized IRI model and aircraft vibration response shows a qualitative leap from that of the original IRI model. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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14 pages, 4308 KiB

Open AccessArticle

Acoustic Emission Wave Velocity Attenuation of Concrete and Its Application in Crack Localization

by Dongxue Li, Kang Yang, Zhaoyi He, Hanlin Zhou and Jiaqi Li

Sustainability 2020, 12(18), 7405; https://doi.org/10.3390/su12187405 - 9 Sep 2020

Cited by 12 | Viewed by 2268

Abstract

The accurate localization of an acoustic emission (AE) source is a vital aspect of AE nondestructive testing technology. A model of wave velocity attenuation caused by the extension of transmission distance is established to analyze the attenuation of AE wave velocities in concrete and thus improve the acoustic source localization accuracy from the perspective of modified velocity. In combination with the exhaustive and region localization methods, a region exhaustive localization method is established based on the modified wave velocity. The results indicate that the smaller the water–cement ratio, the larger the reference wave velocity, and the spatially dependent attenuation of wave velocity increase. Moreover, the larger the aggregate particle size, the larger the reference wave velocity, and the greater the attenuation of wave velocity with distance. For a propagation distance of 1000 mm, the AE wave velocity attenuation exceeds 50% compared with the AE velocity. The optimized localization method reduces the number of nodes calculated, thus improving the method’s accuracy when used for localization. Full article

(This article belongs to the Special Issue Traffic Infrastructure Sustainability in Autonomous Driving and Smart Pavement Environments)

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