Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.9
Journals
Sustainability
Special Issues
Sustainable Road Transport System Planning and Optimization
sustainability-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainable Road Transport System Planning and Optimization

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 19426

Special Issue Editors

Dr. Yusheng Ci

E-Mail Website
Guest Editor
School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China
Interests: sustainable transportation; traffic safety analysis and modelling; intelligent transportation systems; transportation systems network design and optimization; traffic control and operations
Dr. Lina Wu

E-Mail Website
Guest Editor
School of Automobile and Traffic Engineering, Heilongjiang Institute of Technology, Harbin 150050, China
Interests: vehicle fuel consumption and emission; traffic safety analysis; public transport planning and optimization; connected autonomous vehicles
Dr. Ming Wei

E-Mail Website
Guest Editor
School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China
Interests: travel behavior; big data; GIS-T; spatiotemporal analysis

Special Issue Information

Dear Colleagues,

Transportation systems are a basic, leading, and strategic industry and an important service industry in the national economy. They are an important support for the sustainable development of society as a whole. With the rapid development of emerging technologies such as big data, cloud computing, and artificial intelligence, the development of sustainable transportation systems has ushered in new development opportunities.

This Special Issue aims to gain insights into the sustainable development of road transport planning and optimization, vehicle fuel consumption and emission, traffic safety, and transportation resilience. We welcome high-quality papers that propose effective road transport planning initiatives and take an integrated approach to addressing road transport planning and optimization problems.

Consequently, the Guest Editor encourages submissions of state-of-the-art research articles on sustainable road transport system planning and optimization. Topics of interest include, but are not limited to, the following:

  • Data-driven transport system planning and optimization;
  • Integration of multi-modal transportation systems;
  • Public transport planning and optimization;
  • Shared mobility;
  • Mobility as a service;
  • Vehicle fuel consumption and emission modelling;
  • Traffic safety analysis and modelling;
  • Resilience in transportation systems.

Dr. Yusheng Ci
Dr. Lina Wu
Dr. Ming Wei
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

  • sustainable transportation
  • transport planning
  • public transport
  • fuel consumption and emission
  • spatiotemporal analysis
  • big data
  • traffic safety
  • resilience

Published Papers (12 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

21 pages, 66053 KiB  
Article
The Effect of the COVID-19 Pandemic on the Distribution of Traffic Accident Hotspots in New York City
by Hengyi Zhang, Yusheng Ci, Yikang Huang and Lina Wu
Sustainability 2024, 16(8), 3440; https://doi.org/10.3390/su16083440 - 19 Apr 2024
Viewed by 236
Abstract
The COVID-19 pandemic has had a substantial impact on the lives of city residents and has reshaped working patterns, with a concomitant impact on traffic accidents. We correlated data from multiple sources to explore the impact of residents’ mobility and residents’ travel behavior [...] Read more.
The COVID-19 pandemic has had a substantial impact on the lives of city residents and has reshaped working patterns, with a concomitant impact on traffic accidents. We correlated data from multiple sources to explore the impact of residents’ mobility and residents’ travel behavior on the spatiotemporal distribution characteristics of urban traffic accident hotspots and its internal mechanism under the impact of the pandemic and subsequent policy measures. The results showed that the pandemic and policy measures inhibited the mobility of residents, had a significant impact on working patterns, and changed the composition structure of the purpose of residents’ travel behavior, which substantially impacted the spatiotemporal distribution characteristics of urban traffic accident hotspots. The quantity of traffic accidents decreased significantly, and the spatial distribution characteristics of urban traffic accident hotspots changed substantially, with accident hotspots changing from the single-center spatial distribution before the pandemic to the multi-center spatial distribution during the pandemic; urban accident-prone areas changed from being mainly distributed in the central business district before the pandemic to being more widely distributed in public service areas during the pandemic. The results of this study may be helpful to better understand the spatiotemporal distribution characteristics of urban traffic accident hotspots and their intrinsic mechanism. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

24 pages, 4911 KiB  
Article
Blending Efficiency and Resilience in the Performance Assessment of Urban Intersections: A Novel Heuristic Informed by Literature Review
by Nazanin Zare, Elżbieta Macioszek, Anna Granà and Tullio Giuffrè
Sustainability 2024, 16(6), 2450; https://doi.org/10.3390/su16062450 - 15 Mar 2024
Viewed by 567
Abstract
Urban mobility underscores the vital importance of ensuring traffic efficiency on road segments, intersections, and transportation networks, especially in challenging circumstances. In this perspective, the essential approach to improving urban intersection efficiency should involve understanding critical factors for maintaining operational performance in the [...] Read more.
Urban mobility underscores the vital importance of ensuring traffic efficiency on road segments, intersections, and transportation networks, especially in challenging circumstances. In this perspective, the essential approach to improving urban intersection efficiency should involve understanding critical factors for maintaining operational performance in the face of disruptions such as storms. This paper, inspired by a systematic literature review, presents a novel heuristic for evaluating urban intersection efficiency, with resilience as its guiding principle. The methodological path was designed to address the fundamental question: How can urban intersections be designed and managed to ensure efficiency and resilience in the face of disruptions? Drawing inspiration from the Highway Capacity Manual procedure, the methodological approach encompasses both pre-storm and post-storm scenarios, comparing delay times at roundabouts and signalized intersections before and after a storm. The results reveal significant changes in delay times for traffic signals, although the choice between roundabouts and signalized intersections should be context-specific, considering factors like traffic conditions, resilience requirements, and associated trade-offs. By shedding light on the interplay between intersection design, control strategies, and urban resilience, this research provides valuable insights into integrating resilience considerations into intersection performance assessment and management strategies. It also underscores how particular intersection designs can impact efficiency and recovery, essential considerations when assessing whether a road or intersection project is resilient. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

20 pages, 2841 KiB  
Article
Assessing the Performance of Highway Safety Manual (HSM) Predictive Models for Brazilian Multilane Highways
by Olga Beatriz Barbosa Mendes, Ana Paula Camargo Larocca, Karla Rodrigues Silva and Ali Pirdavani
Sustainability 2023, 15(13), 10474; https://doi.org/10.3390/su151310474 - 03 Jul 2023
Cited by 2 | Viewed by 967
Abstract
This paper assesses the performance of Highway Safety Manual (HSM) predictive models when applied to Brazilian highways. The study evaluates five rural multilane highways and calculates calibration factors (Cx) of 2.62 for all types of crashes and 2.35 for Fatal or [...] Read more.
This paper assesses the performance of Highway Safety Manual (HSM) predictive models when applied to Brazilian highways. The study evaluates five rural multilane highways and calculates calibration factors (Cx) of 2.62 for all types of crashes and 2.35 for Fatal or Injury (FI) crashes. The Goodness of Fit measures show that models for all types of crashes perform better than FI crashes. Additionally, the paper assesses the application of the calibrated prediction model to the atypical year of 2020, in which the COVID-19 pandemic altered traffic patterns worldwide. The HSM method was applied to 2020 using the Cx obtained from the four previous years. Results show that for 2020, the observed counts were about 10% lower than the calibrated predictive model estimate of crash frequency for all types of crashes, while the calibrated prediction of FI crashes was very close to the observed counts. The findings of this study demonstrate the usefulness of HSM predictive models in identifying high-risk areas or situations and improving road safety, contributing to making investment decisions in infrastructure and road safety more sustainable. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

19 pages, 6760 KiB  
Article
Origin-Destination Traffic Survey—Case Study: Data Analyse for Bacau Municipality
by Oana Irimia, Mirela Panaite-Lehadus, Claudia Tomozei, Emilian Mosnegutu and Grzegorz Przydatek
Sustainability 2023, 15(6), 4975; https://doi.org/10.3390/su15064975 - 10 Mar 2023
Viewed by 1461
Abstract
In order to develop a transport model for the municipality of Bacau, it was necessary to collect data on the current mobility characteristics of people and goods. Traffic data were collected by means of using an origin-destination (O-D) survey. This survey was carried [...] Read more.
In order to develop a transport model for the municipality of Bacau, it was necessary to collect data on the current mobility characteristics of people and goods. Traffic data were collected by means of using an origin-destination (O-D) survey. This survey was carried out in the form of a manual traffic census arranged in stations at six points on the entrance sectors of the national roads in the city of Bacau. At the level of the municipality of Bacau, data from a sample of 3040 drivers were used for the origin-destination surveys. The respondents answered 11 questions. The article presents the results obtained from the six control points for seven questions that were considered relevant. The data obtained were initially used to identify, from a percentage and quantitative point of view, the type of traffic specific to the municipality of Bacau. The analysis of the data shows that the majority of vehicles, 78.9%, originate from Bacau County and that 87.2% of those interviewed have Bacau County as their destination. Most vehicles passing through the checkpoints were within the time intervals 7:30–8:30, i.e., 15.55%, and 16:30–17:30, i.e., 16.18%. The highest proportion of registered vehicles were from Romania, 97.99%. Additionally, 40.75% of the respondents were travelling for business purposes, and approximately the same share was found for the number of people in the vehicle; i.e., single occupant vehicles comprised 58.35% of the total vehicles surveyed. Passenger cars accounted for 67.66% of the vehicles. By using the OriginLab software, the aim was to create parallel graphs for each control point in order to identify certain correlations between the data obtained from the questionnaire. At the end of the article, a hierarchical cluster statistical analysis was carried out by using OriginLab, which identified a series of correlations between the analysed parameters. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

19 pages, 2169 KiB  
Article
Data-Driven Analysis of Fatal Urban Traffic Accident Characteristics and Safety Enhancement Research
by Xi Zhang, Shouming Qi, Ao Zheng, Ye Luo and Siqi Hao
Sustainability 2023, 15(4), 3259; https://doi.org/10.3390/su15043259 - 10 Feb 2023
Cited by 2 | Viewed by 1479
Abstract
The occurrence of fatal traffic accidents often causes serious casualties and property losses, endangering travel safety. This work uses the statistical data of fatal road traffic accidents in Shenzhen from 2018 to 2022 as the basis to determine the characteristic patterns and the [...] Read more.
The occurrence of fatal traffic accidents often causes serious casualties and property losses, endangering travel safety. This work uses the statistical data of fatal road traffic accidents in Shenzhen from 2018 to 2022 as the basis to determine the characteristic patterns and the main influencing factors of the occurrence of fatal road traffic accidents. The accident description data are also analyzed using the analysis method based on Term Frequency-Inverse Document Frequency (TF-IDF) data mining to obtain the characteristics of accident fields, objects, and types. Furthermore, this work conducts a kernel density analysis combined with spatial autocorrelation to determine the hotspot areas of accident occurrence and analyze their spatial aggregation effects. A principal component analysis is performed to calculate the factors related to the accident subjects. Results showed that weak safety awareness of motorists and irregular driving operations are the main factors for the occurrence of accidents. Finally, targeted safety management strategies are proposed based on the analysis results. In the current data era, the research results of this paper can be used for the prevention and emergency of accidents to formulate corresponding measures, and provide a theoretical basis for decision making. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

14 pages, 2365 KiB  
Article
Prediction Model of Car Ownership Based on Back Propagation Neural Network Optimized by Particle Swarm Optimization
by Hualei Zhang, Yuan Li and Lianghuan Yan
Sustainability 2023, 15(4), 2908; https://doi.org/10.3390/su15042908 - 06 Feb 2023
Cited by 2 | Viewed by 1264
Abstract
Aiming to address the problems of traditional BP neural networks, which include their slow convergence speed and low accuracy, a vehicle ownership prediction model based on a BP neural network with particle swarm optimization is proposed. The weights and thresholds of the BP [...] Read more.
Aiming to address the problems of traditional BP neural networks, which include their slow convergence speed and low accuracy, a vehicle ownership prediction model based on a BP neural network with particle swarm optimization is proposed. The weights and thresholds of the BP neural network are optimized by PSO to make the prediction results more accurate. Based on the current literature regarding BP neural networks’ ability to predict car ownership, a 9-10-1 BP neural network structure model is established. A traditional BP neural network and a PSO-optimized BP neural network are used to predict car ownership at the same time. In order to compare their prediction accuracy, a genetic algorithm (GA) and whale optimization algorithm (WOA) are additionally selected to optimize the BP neural network as a control group to predict car ownership. The data on China’s car ownership from 2005 to 2021 were collected as experimental data. The data from 2005 to 2016 were used as training data, and the remaining data were used as validation data for model prediction. The results show that the PSO-optimized neural network only undergoes three iterations of training, and the convergence accuracy reaches 1.41 × 10−8. The relative error between the predicted value of car ownership and the corresponding real value is between 0.023 and 0.083, and the decisive coefficient R2 is 0.96002, indicating that the neural network has better prediction ability and higher prediction accuracy for car ownership. The particle swarm optimization algorithm is used to optimize the weights and thresholds of the BP neural network, which solves the problems of the traditional BP neural network, including the ease with which it falls into the local minimum value and its slow convergence speed, and improves its prediction accuracy of car ownership. Compared with the results optimized by the genetic algorithm and whale optimization algorithm, the error of the BP neural network optimized by PSO is the smallest, and the prediction accuracy is the highest. Through the comparative analysis of training results, it can be seen that the PSO-BP prediction model has the best stability and accuracy. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

19 pages, 3920 KiB  
Article
An Improved Cellular Automata Traffic Flow Model Considering Driving Styles
by Tianjun Feng, Keyi Liu and Chunyan Liang
Sustainability 2023, 15(2), 952; https://doi.org/10.3390/su15020952 - 04 Jan 2023
Cited by 7 | Viewed by 1635
Abstract
An improved cellular automata model (CA model) considering driving styles is proposed to analyze traffic flow characteristics and study traffic congestion’s dissipation mechanism. The data were taken from a particular case in the Next Generation Simulation (NGSIM) program, which selected US-101 as the [...] Read more.
An improved cellular automata model (CA model) considering driving styles is proposed to analyze traffic flow characteristics and study traffic congestion’s dissipation mechanism. The data were taken from a particular case in the Next Generation Simulation (NGSIM) program, which selected US-101 as the survey location from 7:50 a.m.–8:05 a.m. to investigate vehicle trajectory information. Different driving styles and the differences in vehicle parameters (speed, acceleration, deceleration, etc.) were obtained using principal component analysis and the k-means clustering method. The selected model was proposed for improvement based on analyzing the existing CA models and combining them with the actual road conditions. Considerations of driving styles and two operation mechanisms (over-acceleration and speed adaptation) were introduced in the improved model. The result obtained after the traffic simulation shows that the improved CA model is effective, and the mutual transformation of different traffic flow phases can be simulated. In the improved CA model, dissipating traffic congestion effectively and balancing the overall flow of the road are realized to improve the traffic capacity up to around 115% compared to the NaSch model and meet the demand of all kinds of drivers expecting to drive at the safest distance, which provides a theoretical basis for relieving traffic congestion. The various driving styles in terms of safety, comfort, and effectiveness are performed differently in the improved CA model. An aggressive driving style contributes to increasing traffic capacity up to around 181% compared to a calm driving style, while the calm style contributes to maintaining traffic flow stability. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

15 pages, 8561 KiB  
Article
Research on Parking Space Status Recognition Method Based on Computer Vision
by Yongyi Li, Hongye Mao, Wei Yang, Shuang Guo and Xiaorui Zhang
Sustainability 2023, 15(1), 107; https://doi.org/10.3390/su15010107 - 21 Dec 2022
Cited by 1 | Viewed by 2449
Abstract
To improve the utilization rate of parking space resources and reduce the cost of installing and maintaining sensor recognition, this paper proposed an improved computer vision-based parking space status recognition method. The overall recognition accuracy was improved by graying the video, filtering smoothing [...] Read more.
To improve the utilization rate of parking space resources and reduce the cost of installing and maintaining sensor recognition, this paper proposed an improved computer vision-based parking space status recognition method. The overall recognition accuracy was improved by graying the video, filtering smoothing noise reduction, image enhancement pre-processing, introducing texture feature extraction method based on LBP operator, improving the background difference method, and then, we used a perceptual hash algorithm to calculate the Hamming distance between the background image and the hash string of the current frame of the video, excluding the influence of light and pedestrian on recognition accuracy. Finally, a parking space status recognition system is developed relied on the Python environment, and parking spaces are recognized in three environmental states: with direct light, without direct light, and in rain and snow. The overall average accuracy of the experimental results was 97.2%, which verifies the accuracy of the model. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

12 pages, 2435 KiB  
Article
Car-Following Model Optimization and Simulation Based on Cooperative Adaptive Cruise Control
by Cheng-Ju Song and Hong-Fei Jia
Sustainability 2022, 14(21), 14067; https://doi.org/10.3390/su142114067 - 28 Oct 2022
Viewed by 1289
Abstract
This study aims to improve the desired distance adaptability of the cooperative adaptive cruise control (CACC) during car-following. In this study, the characteristics of the desired distance in different traffic flow states were analyzed. The general functional form of the desired distance in [...] Read more.
This study aims to improve the desired distance adaptability of the cooperative adaptive cruise control (CACC) during car-following. In this study, the characteristics of the desired distance in different traffic flow states were analyzed. The general functional form of the desired distance in the car-following process was formulated. Then, a car-following platoon was constructed to compare the car-following effect of the platoon under different conditions, using the following speed and the lead vehicle disturbance, as the observed variable and the simulation condition, respectively. The car-following effect of the platoon under different parameters was also compared, based on the improved CACC model. The results show that the improved CACC model exhibited more advantages in car-following efficiency, it can better describe the state of the car-following queue under different traffic flow parameters and car-following behavior conditions, it has a strong anti-interference ability for the fluctuation of the car-following queue and is conducive to further improving the intelligent operation of car-following queue. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

28 pages, 5832 KiB  
Article
Research on Automatic Driving Trajectory Planning and Tracking Control Based on Improvement of the Artificial Potential Field Method
by Yongyi Li, Wei Yang, Xiaorui Zhang, Xi Kang and Mengfei Li
Sustainability 2022, 14(19), 12131; https://doi.org/10.3390/su141912131 - 25 Sep 2022
Cited by 12 | Viewed by 1865
Abstract
With the continuous increase in motor vehicle ownership in recent times, traditional transportation has been unable to meet people’s travel needs. Research on autonomous driving technology will help solve a series of problems associated with driving, such as traffic accidents, traffic congestion, energy [...] Read more.
With the continuous increase in motor vehicle ownership in recent times, traditional transportation has been unable to meet people’s travel needs. Research on autonomous driving technology will help solve a series of problems associated with driving, such as traffic accidents, traffic congestion, energy consumption, and environmental pollution. In this paper, an improved artificial potential field method is proposed to complete the planning of automatic driving trajectories by adding the distance adjustment factor, dynamic road repulsive field, velocity repulsive field, and acceleration repulsive field. The invasive weed algorithm is introduced to solve the defects associated with the traditional artificial potential field method. The prediction model—for which corresponding constraint variables were set and an optimal objective function was established to build up the MPC model controller to achieve the goal of trajectory tracking—was linearized and discretized from a vehicle dynamics model. Finally, co-simulation based on MATLAB and CarSim was used to verify the practicability of the model. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

14 pages, 3240 KiB  
Article
Analysis of the Characteristics of Real-World Emission Factors and VSP Distributions—A Case Study in Beijing
by Weinan He, Lei Duan, Zhuoyuan Zhang, Xu Zhao and Ying Cheng
Sustainability 2022, 14(18), 11512; https://doi.org/10.3390/su141811512 - 14 Sep 2022
Cited by 3 | Viewed by 1330
Abstract
Vehicle emissions intensity at a given travel speed is well known among the public since travel speed is the key parameter in both the traffic model and the emission model. Yet, several problems still remain in traditional approaches of measuring the emission intensity. [...] Read more.
Vehicle emissions intensity at a given travel speed is well known among the public since travel speed is the key parameter in both the traffic model and the emission model. Yet, several problems still remain in traditional approaches of measuring the emission intensity. To establish accurate and high-resolution emission factors, an established method of emission factors is proposed based on the real-time monitoring operation conditions data, which can reflect the effect of dynamic traffic changes on emissions. The speed-specific vehicle-specific power (VSP) distributions of different months, as well as those in different vehicles in Beijing were developed and compared. Statistical analyses such as Coefficient of Variation (CV) and Root Mean Square Error (RMSE) were used to quantify the differences in the VSP distribution. The results showed the significant correlation between the distribution of VSP, velocity, and operating patterns at time intervals within the annual range. Driving conditions in 2021 are more eco-friendly because of the improvement of digital development and driving habits. Furthermore, research on CO, HC, and NOx emission factor situations in different cycles revealed that the emission factors of NOx and HC are always underestimated in typical operating modes, while sometimes the emissions of CO are overvalued. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

20 pages, 5190 KiB  
Article
Optimization Method for Conventional Bus Stop Placement and the Bus Line Network Based on the Voronoi Diagram
by Fu Wang, Manqing Ye, Hongbin Zhu and Dengjun Gu
Sustainability 2022, 14(13), 7918; https://doi.org/10.3390/su14137918 - 29 Jun 2022
Cited by 11 | Viewed by 3314
Abstract
With the rapid development of the economy, the existing conventional bus transit system finds it difficult to meet people’s increasing travel needs. In addition, with the emergence and rapid development of urban rail transit, it is also necessary to integrate the existing conventional [...] Read more.
With the rapid development of the economy, the existing conventional bus transit system finds it difficult to meet people’s increasing travel needs. In addition, with the emergence and rapid development of urban rail transit, it is also necessary to integrate the existing conventional bus transit system with the rail transit system to realize the optimization of the whole public transport system. This study introduces the concept of the Voronoi diagram and uses it to divide the service area of bus stops. Taking the average walking time of regional passengers to the station as the main index, the convenience of passengers in the service area was evaluated, and a set of candidate station sites is established. Against the background of urban rail transit, a complete optimization model for a conventional bus station layout and line network was proposed. Finally, taking Wuhan East Lake High-tech Development Zone as an example, two optimization schemes for the public transport system were obtained. Compared with the status quo, the optimized scheme had obvious improvement effects on the repetition coefficient of bus lines, per capita transfer time, bus line network coverage and station service rate. This has been recognized by the local authorities, which proves the practicality and scientificity of the optimization method of this study. Full article
(This article belongs to the Special Issue Sustainable Road Transport System Planning and Optimization)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-12
Back to TopTop