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New Techniques to Promote Sustainable Mobility: Evaluation, Optimization and Behavioral Adaptation

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 20622

Special Issue Editors

Department of Architecture and Civil Engineering, Chalmers University of Technology, SE-412 96 Goteburg, Sweden
Interests: transportation electrification; shared mobility and connected vehicles
Special Issues, Collections and Topics in MDPI journals
College of Transportation Engineering, Tongji University, Shanghai 201804, China
Interests: road safety; driving behavior modeling; eco-driving; connected and autonomous vehicle; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden
Interests: machine learning
Faculty of Engineering, Computer Science and Psychology, Department of Human Factors, Ulm University, 89069 Ulm, Germany
Interests: transport emission control; traffic system optimization

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue of Sustainability on new techniques to promote sustainable mobility. The venue is a peer-reviewed open-access journal that publishes articles and communications in the interdisciplinary area of sustainability. For detailed information on the journal, we refer you to https://www.mdpi.com/journal/sustainability.

The commitment to reducing greenhouse gas (GHG) emissions for confining global climate change in the Paris Agreement and COP27 is driving urban managers and service providers worldwide to reduce emissions and energy consumption in the transport sector, which takes up around 30% of overall GHG emissions. In the past decades, the world has witnessed significant advances in transport electrification, connected automation, and shared mobility, which hold promising potential to facilitate transitions to sustainable mobility systems. Many techniques have already been implemented in reality. However, there are many theoretical, technical and practical issues that need to be addressed to put these new technologies or techniques to good use. To name a few, the emission and energy consumption of electric vehicles may be even larger than internal combustion engine vehicles if the electricity is mainly from thermal power in some regions and emissions in production/disposal are considered; shared mobility such as car-sharing and on-demand ride-hailing may result in more usage of passenger cars instead of public transits; the traffic safety in the mixed traffic with both connected and automated vehicle and human-driven vehicles may deteriorate due to divergent behavior between automated vehicles and human drivers.

Standing on the aforenoted backgrounds, the overall purpose of this Special Issue is to focus on: 1) evaluating the “real” impacts of implemented new transport systems (electric, connected and shared transport) based on emerging data resources, simulation and the combined way to identify key challenges and new issues; 2) novel approaches in terms of methodology frameworks, models, algorithms and case studies to optimize the new systems for improving efficiency, reducing emission and enhanced safety; and 3) diverse users’ behavior adaptation and response to new transport alternatives. These target at collective efforts from evaluation, optimization and user behavior to improve the sustainability of current transport systems, which contributes to climate actions.

We welcome systematic reviews, meta-analyses, conceptual proposals, data analysis, framework establishment, method and algorithm development, experimental investigation, empirical cases, intervention studies and other types of studies under the scope described before, including both logistics and passenger transport. No preference will be attached to results being null, mixed, negative or positive. If you are uncertain about whether your paper fits into the scope of this Special Issue, please contact the Guest Editors.

This Special Issue is open to any subject area related to electric, shared and connected mobility. The listed keywords suggest just a few topics, but any relevant studies are also welcomed. 

Dr. Kun Gao
Dr. Bo Yu
Dr. Yang Liu
Dr. Jieyu Fan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transportation electrification
  • connected and automated vehicles (CAV)
  • shared mobility
  • evaluating the impacts (environment and safety) of new transport technologies
  • impact assessment methods and framework based on new data resources
  • deep learning and machine learning for prediction, evaluation and analysis
  • big data analysis and solutions
  • optimization of the current practice of private electric cars and electric public transit
  • optimization of shared mobility systems
  • traffic management and strategies to reduce emission
  • eco-driving model and algorithms
  • environment-oriented traffic control leveraging CAV
  • driving behavior modeling and risk evaluation in ITS based on filed or experimental data
  • traffic safety management and human factors in ITS
  • travel choice behavior in ITS
  • subjective factors on modal shift to sustainable alternatives
  • efficient policy for promoting sustainable mobility

Published Papers (15 papers)

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18 pages, 2463 KiB  
Article
Assessing Knowledge Performance for the Fast-Track Delivery of Sustainable Mobility Solutions
by Maria Morfoulaki and Maria Chatziathanasiou
Sustainability 2024, 16(1), 39; https://doi.org/10.3390/su16010039 - 19 Dec 2023
Viewed by 536
Abstract
European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills the skills gaps and/or enables the acquisition of new ones related to [...] Read more.
European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills the skills gaps and/or enables the acquisition of new ones related to the planning and implementation of such solutions can empower local/regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at the project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents. Full article
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14 pages, 2208 KiB  
Article
Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic
by Jieyu Fan, Arsalan Najafi, Jokhio Sarang and Tian Li
Sustainability 2023, 15(22), 16118; https://doi.org/10.3390/su152216118 - 20 Nov 2023
Cited by 1 | Viewed by 932
Abstract
Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, [...] Read more.
Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NOx) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NOx emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NOx emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NOx emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic. Full article
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15 pages, 3030 KiB  
Article
Parking Generating Rate Prediction Method Based on Grey Correlation Analysis and SSA-GRNN
by Chao Zeng, Xu Zhou, Li Yu and Changxi Ma
Sustainability 2023, 15(17), 13016; https://doi.org/10.3390/su151713016 - 29 Aug 2023
Viewed by 742
Abstract
The parking generating rate model is commonly used in parking demand forecasting. However, the key indicators of the parking generating rate are generally difficult to determine, especially its future annual value. The parking generating rate is affected by many factors. In order to [...] Read more.
The parking generating rate model is commonly used in parking demand forecasting. However, the key indicators of the parking generating rate are generally difficult to determine, especially its future annual value. The parking generating rate is affected by many factors. In order to more accurately predict the urban parking generating rate, this paper establishes a parking generating rate prediction model based on grey correlation analysis and a generalized regression neural network (GRNN) optimized by a sparrow search algorithm (SSA). Gross domestic product (GDP), urban area, urban population, motor vehicle ownership, and land use type are selected as input variables of the GRNN via grey correlation analysis. The SSA is used to optimize network weights and thresholds, and a model based on the SSA to optimize the GRNN is constructed to predict the parking generating rate of different cities. The results show that, after SSA optimization, the maximum absolute error of the GRNN model in predicting the parking generating rate is reduced, and the prediction accuracy of the model is effectively improved. This model can provide technical support for solving urban parking problems. Full article
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20 pages, 4247 KiB  
Article
Multi-Objective Optimal Deployment of Road Traffic Monitoring Cameras: A Case Study in Wujiang, China
by Yiming Li, Zeyang Cheng, Xinpeng Yao, Zhiqiang Kong, Zijian Wang and Mengfei Liu
Sustainability 2023, 15(15), 12011; https://doi.org/10.3390/su151512011 - 04 Aug 2023
Viewed by 808
Abstract
This study presents a multi-objective optimal framework for deploying traffic monitoring cameras at road networks. Compared with previous studies that focused on addressing single traffic problem such as OD estimation, link flow observation, path flow reconstruction, and travel time estimation, this study aims [...] Read more.
This study presents a multi-objective optimal framework for deploying traffic monitoring cameras at road networks. Compared with previous studies that focused on addressing single traffic problem such as OD estimation, link flow observation, path flow reconstruction, and travel time estimation, this study aims to address a comprehensive traffic management problem, including crash prevention, traffic violation governance, and traffic efficiency improvement. First, a potential principle for selecting the location of traffic monitoring deployment is determined, taking into account the key signalized intersections, areas prone to traffic congestion, crash-prone spots, and areas prone to traffic violations. Then, a multi-objective optimal model is developed to minimize the ATFM (i.e., average traffic volume of each five minutes), TCF (i.e., traffic crash frequency), and TVF (i.e., traffic violation frequency) while adhering to cost constraints. Finally, RVEA and NSGA-II algorithms are used to solve the multi-objective optimal model, respectively, and a comprehensive metric is proposed to evaluate the deployment schemes. The case study results demonstrate that the solutions obtained by the RVEA algorithm outperform those of the NSGA-II algorithm, and the best traffic monitoring deployment rate is 62.79%, under cost constraints. In addition, the comparison using the FAHP method also illustrates that the RVEA scheme is superior to the NSGA-II scheme. The above research results could potentially be used to optimize the locations of traffic cameras in road networks, which help to improve traffic management. Full article
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22 pages, 6623 KiB  
Article
Towards Sustainable Safe Driving: A Multimodal Fusion Method for Risk Level Recognition in Distracted Driving Status
by Huiqin Chen, Hao Liu, Hailong Chen and Jing Huang
Sustainability 2023, 15(12), 9661; https://doi.org/10.3390/su15129661 - 16 Jun 2023
Cited by 2 | Viewed by 970
Abstract
Precise driving status recognition is a prerequisite for human–vehicle collaborative driving systems towards sustainable road safety. In this study, a simulated driving platform was built to capture multimodal information simultaneously, including vision-modal data representing driver behaviour and sensor-modal data representing vehicle motion. Multisource [...] Read more.
Precise driving status recognition is a prerequisite for human–vehicle collaborative driving systems towards sustainable road safety. In this study, a simulated driving platform was built to capture multimodal information simultaneously, including vision-modal data representing driver behaviour and sensor-modal data representing vehicle motion. Multisource data are used to quantify the risk of distracted driving status from four levels, safe driving, slight risk, moderate risk, and severe risk, rather than detecting action categories. A multimodal fusion method called vision-sensor fusion transformer (V-SFT) was proposed to incorporate the vision-modal of driver behaviour and sensor-modal data of vehicle motion. Feature concatenation was employed to aggregate representations of different modalities. Then, successive internal interactions were performed to consider the spatiotemporal dependency. Finally, the representations were clipped and mapped into four risk level label spaces. The proposed approach was evaluated under different modality inputs on the collected datasets and compared with some baseline methods. The results showed that V-SFT achieved the best performance with an recognition accuracy of 92.0%. It also indicates that fusing multimodal information effectively improves driving status understanding, and V-SFT extensibility is conducive to integrating more modal data. Full article
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19 pages, 11170 KiB  
Article
Spatial Distribution Characteristic and Type Classification of Rural Settlements: A Case Study of Weibei Plain, China
by Yaqiong Duan, Su Chen, Lingda Zhang, Dan Wang, Dongyang Liu and Quanhua Hou
Sustainability 2023, 15(11), 8736; https://doi.org/10.3390/su15118736 - 29 May 2023
Viewed by 1065
Abstract
The continuous development of urbanization in China has brought new opportunities to rural settlements but has also led to spatial problems such as disorderly layout and unbalanced morphological structures, and the sustainable development of the countryside faces great challenges. As the core spatial [...] Read more.
The continuous development of urbanization in China has brought new opportunities to rural settlements but has also led to spatial problems such as disorderly layout and unbalanced morphological structures, and the sustainable development of the countryside faces great challenges. As the core spatial carrier of rural settlements, scientific identification of their characteristics and delineation of their types is conducive to the subsequent spatial optimization of rural settlements to promote the coordinated and orderly development of rural areas. In recent years, several studies have explored the characteristics and classification of rural settlements based on single factor influences, but few studies have comprehensively considered them from a multidimensional perspective. To fill this gap, this paper takes the rural settlements in the Weibei Plain as the research object, uses the continuous spectral transect analysis method, combines the landscape security pattern analysis, establishes a multidimensional feature matrix model, quantitatively analyzes the spatial differentiation characteristics, and classifies the types. The key findings are as follows. (1) According to the analysis of landscape security patterns, it was divided into four types of rural settlements. The rural settlements with high and medium security patterns accounted for 86.79%, and the overall ecological adaptability was good. (2) In terms of spatial distribution, 80% of patches in the Weihe River transect are small and unevenly distributed under the influence of river runoff, gradually changing from dense to discrete; the fluctuation range of the 70% patch area is restricted by the terrain in the Hanyuan tableland transect is small and changes from discrete to dense. In terms of spatial morphology, 70% of the Weihe River transect was irregular and varied greatly. The morphology of the Hanyuan tableland transect tended to be similar, and the degree of fragmentation of the Hanyuan tableland transect was higher than that of the Weihe River transect. (3) The Weihe River transect was divided into six types of settlement space, the Hanyuan tableland transect was divided into seven types, and the characteristics of different settlement space types were quite different. The results can provide a scientific basis for the spatial planning, industrial guidance, and facility layout of rural settlements and have important significance for the rational formulation of spatial agglomeration guidance strategies and the promotion of sustainable rural development in China. Full article
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17 pages, 4231 KiB  
Article
Optimization Method of Transfer Streamlines in Integrated Passenger Hubs Based on 3D Spatial Perspective
by Zhaoguo Huang, Junlan Chen, Xiucheng Guo and Changxi Ma
Sustainability 2023, 15(10), 8296; https://doi.org/10.3390/su15108296 - 19 May 2023
Viewed by 817
Abstract
To optimize the functional space layout of various transportation modes of the integrated passenger transport hub, and improve the transfer efficiency and service quality of the hub, a quantitative analysis of the transfer flow lines of the integrated passenger hub is carried out. [...] Read more.
To optimize the functional space layout of various transportation modes of the integrated passenger transport hub, and improve the transfer efficiency and service quality of the hub, a quantitative analysis of the transfer flow lines of the integrated passenger hub is carried out. The research clarifies the layout factors of the functional areas of the “get on and drop off areas” for each mode of transportation, generates a candidate set of the placement of each functional area, and determines the priority ranking of the candidate sets and the transfer starting and end locations. Based on the analysis of passenger route selection factors, the basic transfer streamline network is generated. The basic network is distributed according to the improved shortest path allocation algorithm, and the relevant parameters are calculated to simplify the initial transfer streamline network, generate and compare the initial network plan of the transfer streamline. Take Wuxi Integrated Passenger Transport Hub as an example to verify: when the weight coefficient λ = 0.65 and the number of allocations n = 207, the optimal solution T = 2,738,027 s is obtained. As the calculation is based on the 15,000 passenger transfer flow at Wuxi Station, the optimized average transfer time per person is 3 min 2 s. Compared with the current average transfer time per person at Wuxi Station of 4.5 min, the optimization effect of this paper is significant. The initial network generation and comparison method of the transfer flow line enables the space layout of the transportation modes of the hub to be coordinated with the transfer flow line design, and solves the problem of the transfer flow line design when the hub building space layout is determined. The hub is designed to meet the requirements of functional space layout, passenger transfer needs and interchange efficiency at the initial stage of architectural design. Full article
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20 pages, 2907 KiB  
Article
Division and Analysis of Accident-Prone Areas near Highway Ramps Based on Spatial Autocorrelation
by Qing Ye, Yi Li, Wenzhe Shen and Zhaoze Xuan
Sustainability 2023, 15(10), 7942; https://doi.org/10.3390/su15107942 - 12 May 2023
Cited by 1 | Viewed by 2163
Abstract
This study focuses on identifying accident-prone areas and analyzing the factors contributing to the distribution of traffic accidents near highway ramps. A combined method of kernel density estimation, spatial autocorrelation analysis, and multivariate logistic regression analysis helped to identify accident hotspots. Through data [...] Read more.
This study focuses on identifying accident-prone areas and analyzing the factors contributing to the distribution of traffic accidents near highway ramps. A combined method of kernel density estimation, spatial autocorrelation analysis, and multivariate logistic regression analysis helped to identify accident hotspots. Through data collection and analysis, the clustering characteristics of traffic accidents in the diversion and merging areas were identified. Four levels of accident-prone areas were divided according to the accident rates. The factors influencing the spatial distribution of accidents were analyzed. The results showed that traffic accidents in the diversion area were concentrated near the exit, but the accidents in merging areas had a wider range of distribution. The analysis of this phenomenon was conducted using the multinomial logit model results. The important factors of different accident-prone areas were clarified. The temperature, the accident lane, weather conditions, and the time of day had significant impacts on the spatial distribution of traffic accidents. The study’s findings provide an important decision-making basis for highway accident prevention management. Full article
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31 pages, 6151 KiB  
Article
Micro-Mobility Sharing System Accident Case Analysis by Statistical Machine Learning Algorithms
by Hakan İnaç
Sustainability 2023, 15(3), 2097; https://doi.org/10.3390/su15032097 - 22 Jan 2023
Cited by 2 | Viewed by 1276
Abstract
This study aims to analyze the variables that affect the accidents experienced by e-scooter users and to estimate the probability of an accident during travel with an e-scooter vehicle. The data of e-scooter drivers, offered for use via rental application in 15 different [...] Read more.
This study aims to analyze the variables that affect the accidents experienced by e-scooter users and to estimate the probability of an accident during travel with an e-scooter vehicle. The data of e-scooter drivers, offered for use via rental application in 15 different cities of Turkey, were run in this study. The methodology of this study consists of testing the effects of the input parameters with the statistical analysis of the data, estimating the probability of an e-scooter accident with machine learning, and calculating the optimum values of the input parameters to minimize e-scooter accidents. By running SVM, RF, AB, kNN, and NN algorithms, four statuses (completed, injured, material damage, and nonapplicable) likely to be encountered by shared e-scooter drivers during the journey are estimated in this study. The F1 score values of the SVM, RF, kNN, AB, and NN algorithms were calculated as 0.821, 0.907, 0.839, 0.928, and 0.821, respectively. The AB algorithm showed the best performance with high accuracy. In addition, the highest consistency ratio in the ML algorithms belongs to the AB algorithm, which has a mean value of 0.930 and a standard deviation value of 0.178. As a result, the rental experience, distance, driving time, and driving speed for a female driver were calculated as 100, 10.44 km, 48.33 min, and 13.38 km/h, respectively, so that shared e-scooter drivers can complete their journey without any problems. The optimum values of the independent variables of the rental experience, distance, driving time, and driving speed for male drivers were computed as 120, 11.49 km, 52.20 min, and 17.28 km/h, respectively. Finally, this study generally provides a guide to authorized institutions so that customers who use shared and rentable micro-mobility e-scooter vehicles do not have problems during the travel process. Full article
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18 pages, 2940 KiB  
Article
Investigating the Factors Affecting Rider’s Decision on Overtaking Behavior: A Naturalistic Riding Research in China
by Cheng Wang, Liyang Wei, Kun Wang, Hongya Tang, Bo Yang and Mengfan Li
Sustainability 2022, 14(18), 11495; https://doi.org/10.3390/su141811495 - 14 Sep 2022
Cited by 3 | Viewed by 1395
Abstract
Overtaking behavior between non-motorized vehicles is one of the main characteristics of the cycling path, and unsafe overtaking behavior has a certain negative impact on riders’ safety. However, little is known about the factors affecting riders’ overtaking decisions. This study aimed to identify [...] Read more.
Overtaking behavior between non-motorized vehicles is one of the main characteristics of the cycling path, and unsafe overtaking behavior has a certain negative impact on riders’ safety. However, little is known about the factors affecting riders’ overtaking decisions. This study aimed to identify the influence of road facilities, types of non-motorized vehicles, and human factors on the characteristics of overtaking behavior on bicycle lanes. DJI drone-based naturalistic riding research was explored in China and a random parameter logit regression model was estimated to model the overtaking decisions of non-motorized vehicle riders. The results showed that gender, age, professional deliverer, type of lead non-motor vehicle, type of non-motorized vehicles, and width of cycling lane influence overtaking behavior significantly. The present study provides theoretical evidence to strengthen the safety design and evaluation of cycling lane infrastructure. Full article
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17 pages, 7038 KiB  
Article
An Improved Innovation Adaptive Kalman Filter for Integrated INS/GPS Navigation
by Bo Sun, Zhenwei Zhang, Dianju Qiao, Xiaotong Mu and Xiaochen Hu
Sustainability 2022, 14(18), 11230; https://doi.org/10.3390/su141811230 - 07 Sep 2022
Cited by 2 | Viewed by 1921
Abstract
The performance of transportation systems has been greatly improved by the rapid development of connected and autonomous vehicles, of which high precision and reliable positioning is a key technology. An improved innovation adaptive Kalman filter (IAKF) is proposed to solve the vulnerability of [...] Read more.
The performance of transportation systems has been greatly improved by the rapid development of connected and autonomous vehicles, of which high precision and reliable positioning is a key technology. An improved innovation adaptive Kalman filter (IAKF) is proposed to solve the vulnerability of Kalman filtering (KF) in challenging urban environments during integrated navigation. First, the algorithm uses the innovation to construct a chi-squared test to determine the abnormal measurement noise; on this basis, the update method of the measurement noise variance matrix is improved, and the measurement noise variance matrix is adaptively updated by the difference between the current innovation and the mean value of the innovation when the measurement data is abnormal so as to reflect the impact degree of the current abnormal measurement data, thus suppressing the filtering divergence and improving the positioning accuracy. The experimental results show that the proposed algorithm can well suppress the filtering divergence when the measurement data are disturbed. The results demonstrate that the algorithm in this paper has improved adaptiveness and stability and provides a novel idea for the development of an intelligent traffic positioning system. Full article
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25 pages, 3152 KiB  
Article
Research on Direct Yaw Moment Control of Electric Vehicles Based on Electrohydraulic Joint Action
by Lixia Zhang, Taofeng Yan, Fuquan Pan, Wuyi Ge and Wenjian Kong
Sustainability 2022, 14(17), 11072; https://doi.org/10.3390/su141711072 - 05 Sep 2022
Cited by 4 | Viewed by 1391
Abstract
To solve the problem of lateral instability of the vehicle caused by insufficient lateral force of the tires due to the insufficient torque provided by the motor to the tire when the vehicle turns sharply or avoids obstacles in an emergency, a layered [...] Read more.
To solve the problem of lateral instability of the vehicle caused by insufficient lateral force of the tires due to the insufficient torque provided by the motor to the tire when the vehicle turns sharply or avoids obstacles in an emergency, a layered control method is used to design a lateral stability control system. The upper decision layer selects the yaw rate and the sideslip angle of the center of mass as the control variables and uses the joint state deviation of the yaw rate and the sideslip angle of the center of mass and the rate of change of the deviation as the input of the sliding mode variable structure controller to calculate the additional yaw moment required to maintain vehicle stability. The lower torque distribution layer realizes the distribution of torque through the electro-hydraulic coordinated control method: the torque distribution rule based on real-time load transfer calculates the torque corresponding to the control wheel and generates the torque through the hub motor and transmits it to the wheel. When the torque output from the motor cannot provide sufficient torque for the vehicle, hydraulic braking is used as a compensating control, and the difference between the required yaw torque and the motor-generated yaw torque is used as the required torque for hydraulic control to calculate the wheel cylinder pressure required to brake the wheels. Based on the joint simulation model of MATLAB/Simulink and Carsim, the sine and double shift line working condition are selected for stability simulation experiments. From the simulation results, it can be seen that the yaw rate and sideslip angle of the center of mass of the vehicle with sliding mode control and electro-hydraulic coordinated control almost coincide with the ideal value curve, which are both smaller than the output parameters of the uncontrolled vehicle. From the perspective of the motor output torque, compared with pure motor control, the effect of electro-hydraulic coordinated control is better, and the hydraulic system can compensate for the braking torque in time and enhance the lateral stability of the vehicle. The designed control strategy can make the yaw rate and the sideslip angle of the center of mass of the vehicle follow the reference value better, which can effectively avoid the vehicle sideslip and instability and improve the vehicle yaw stability and driving safety. However, due to the limitations of experimental equipment, the proposed method could not be applied to the real vehicle test. The real vehicle test can better test the control effect of the proposed method. Full article
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24 pages, 2988 KiB  
Article
Arterial Coordination Control Optimization Based on AM–BAND–PBAND Model
by Min Li, Dijia Luo, Bilong Liu, Xilong Zhang, Zhen Liu and Mengshan Li
Sustainability 2022, 14(16), 10065; https://doi.org/10.3390/su141610065 - 14 Aug 2022
Cited by 5 | Viewed by 1413
Abstract
The green wave coordinated control model has evolved from the basic bandwidth maximization model to the multiweight approach to an asymmetrical multiband model and a general signal progression model with phase optimization to improve the operational efficiency of urban arterial roads and reduce [...] Read more.
The green wave coordinated control model has evolved from the basic bandwidth maximization model to the multiweight approach to an asymmetrical multiband model and a general signal progression model with phase optimization to improve the operational efficiency of urban arterial roads and reduce driving delays and the amount of exhaust gas generated by vehicles queuing at intersections. However, most of the existing green wave models of arterial roads are based on a single phase pattern and little consider the optimization of the combination of multiple phase patterns. Initial queue clearing time is also considered at the green wave progression line in the time–space diagram, which leads to a waste of green light time. This study proposes a coordination control optimization method based on an asymmetrical multiband model with phase optimization to address the abovementioned problem. This model optimizes four aspects in the time–distance diagram: phase pattern selection, phase sequence, offset, and queue clearing time. Numerical experiments were conducted using the VISSIM micro traffic simulation tool for intersections along Kunlunshan South Road in Qingdao, and the effect of green wave coordination was evaluated using hierarchical analysis and compared with the signal-timing schemes generated by the four models: the multiweight approach, the improved multiweight approach, an asymmetrical multiband model, and a general signal progression model with phase optimization. The results show that an asymmetrical multiband model with phase optimization obtains a total bandwidth of 314 s in both directions. In the outbound direction, average number of stops, average travel speed, average travel time, and average delay time improve by 16%, 7.9%, 17.9%, and 15.6%, respectively. In the inbound direction, they improve by 43.7%, 16.1%, 40.7%, and 36%, respectively. Polluting gas emissions and fuel consumption improve by 17.9%. The applicability of the optimization method under different traffic flow conditions is analyzed, and results indicate a clear control effect when the traffic volume is moderate and the turning vehicles on the feeder roads are few. This work can provide a reference for the optimization of subsequent arterial signal coordination and also has indirect significance for environmental protection to a certain extent. Full article
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17 pages, 3169 KiB  
Article
Spatio-Temporal Traffic Flow Prediction Based on Coordinated Attention
by Min Li, Mengshan Li, Bilong Liu, Jiang Liu, Zhen Liu and Dijia Luo
Sustainability 2022, 14(12), 7394; https://doi.org/10.3390/su14127394 - 16 Jun 2022
Cited by 5 | Viewed by 2109
Abstract
Traffic flow prediction can provide effective support for traffic management and control and plays an important role in the traffic system. Traffic flow has strong spatio-temporal characteristics, and existing traffic flow prediction models tend to extract long-term dependencies of traffic flow in the [...] Read more.
Traffic flow prediction can provide effective support for traffic management and control and plays an important role in the traffic system. Traffic flow has strong spatio-temporal characteristics, and existing traffic flow prediction models tend to extract long-term dependencies of traffic flow in the temporal and spatial dimensions individually, often ignoring the potential correlations existing between spatio-temporal information of traffic flow. In order to further improve the prediction accuracy, this paper proposes a coordinated attention-based spatio-temporal graph convolutional network (CVSTGCN) model for simultaneously and dynamically capturing the long-term dependencies existing between the spatio-temporal information of traffic flows. CVSTGCN is composed of a full convolutional network structure, which combines coordinate methods to specify the influence degrees of different feature information in different spatio-temporal dimensions, and the spatio-temporal information of different spatio-temporal dimensions by the graph convolutional network. In addition, the hard-swish activation function is introduced to replace the Rectified Linear Unit (ReLU) activation function in the prediction of traffic flow. Finally, evaluation experiments are conducted on two real datasets to demonstrate that the proposed model has the best prediction performance in both short-term and long-term forecasting. Full article
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21 pages, 1656 KiB  
Systematic Review
The Environmental Impacts of Automated Vehicles on Parking: A Systematic Review
by You Kong, Jihong Ou, Longfei Chen, Fengchun Yang and Bo Yu
Sustainability 2023, 15(20), 15033; https://doi.org/10.3390/su152015033 - 18 Oct 2023
Viewed by 1219
Abstract
Automated Vehicles (AVs) can drop off passengers at predetermined destinations and relocate to less expensive, remote parking facilities, which offers the potential to repurpose valuable urban land near activity centers for alternative uses beyond vehicle storage. While some researchers believe AVs are the [...] Read more.
Automated Vehicles (AVs) can drop off passengers at predetermined destinations and relocate to less expensive, remote parking facilities, which offers the potential to repurpose valuable urban land near activity centers for alternative uses beyond vehicle storage. While some researchers believe AVs are the core element to solving parking problems, relieving urban land use, and enabling low-emission travel, others contend that AVs could incentivize increased Vehicles Miles Traveled (VMT) and exacerbate congestion. To bridge these disparate perspectives, this study endeavors to elucidate the environmental ramifications of AVs on parking through a comprehensive literature review. Based on an initial sample of 299 retrieved papers, 52 studies were selected as the result of the selection criteria detailed in the paper. The selected papers were categorized into five gradual parts to answer the raised research questions. As a principal finding of this study, our research provides city planners, traffic operators, and scholars with full-picture insights and trustworthy guidance, emphasizing the pivotal role of AVs in deciphering the sustainable impact on the urban environment. Full article
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