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24 pages, 7237 KiB

Open AccessArticle

Campus Shuttle Bus Route Optimization Using Machine Learning Predictive Analysis: A Case Study

by Rafidah Md Noor, Nadia Bella Gustiani Rasyidi, Tarak Nandy and Raenu Kolandaisamy

Sustainability 2021, 13(1), 225; https://doi.org/10.3390/su13010225 - 29 Dec 2020

Cited by 17 | Viewed by 6985

Public transportation is a vital service provided to enable a community to carry out daily activities. One of the mass transportations used in an area is a bus. Moreover, the smart transportation concept is an integrated application of technology and strategy in the [...] Read more.

Public transportation is a vital service provided to enable a community to carry out daily activities. One of the mass transportations used in an area is a bus. Moreover, the smart transportation concept is an integrated application of technology and strategy in the transportation system. Using smart idea is the key to the application of the Internet of Things. The ways to improve the management transportation system become a bottleneck for the traditional data analytics solution, one of the answers used in machine learning. This paper uses the Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithm for the best prediction of travel time with a lower error rate on a case study of a university shuttle bus. Apart from predicting the travel time, this study also considers the fuel cost and gas emission from transportation. The analysis of the experiment shows that the ANN outperformed the SVM. Furthermore, a recommender system is used to recommend suitable routes for the chosen scenario. The experiments extend the discussion with a range of future directions on the stipulated field of study. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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16 pages, 3632 KiB

Open AccessArticle

Travel Behavior of SME Employees in Their Work Commute in Emerging Cities: A Case Study in Dhaka City, Bangladesh

by Nuren Abedin, Md Mahmudur Rahman, Muhammad Ismail Hossain, Kenji Hisazumi and Ashir Ahmed

Sustainability 2020, 12(24), 10337; https://doi.org/10.3390/su122410337 - 10 Dec 2020

Cited by 3 | Viewed by 3481

Abstract

Corporate employees like to save the time they spend commuting to work. However, public transport in many emerging cities is not scheduled. Only big enterprises can afford scheduled staff buses. Rideshare services (e.g., Uber, Lyft, Pathao) can be a good alternative but are [...] Read more.

Corporate employees like to save the time they spend commuting to work. However, public transport in many emerging cities is not scheduled. Only big enterprises can afford scheduled staff buses. Rideshare services (e.g., Uber, Lyft, Pathao) can be a good alternative but are not affordable for every individual. This study aims to design a group rideshare service as a sustainable alternative for potential employees. For that purpose, it is important to know their commuting pattern. A survey was carried out on 314 employees of 20 Small and Medium Enterprises (SMEs) working in one office complex. This paper reports their current travel pattern in terms of distance, cost, time, and mode of transportations to measure their potentiality to use a group rideshare service uniquely designed for a work commute. This paper recommends that employees living within a distance of 2.5–15 km, currently using motorized vehicle for their work commute, who can spend $40 USD a month for work commute and agree to a mutually-determined commuting schedule are the most fitting potential users for an effective and financially sustainable rideshare service for the studied community. The same methodology can be used to obtain the potential ride share users to design a ride share model for other similar communities. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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24 pages, 3185 KiB

Open AccessArticle

Characterization of Public Transit Mobility Patterns of Different Economic Classes

by Priscila Santin, Fernanda R. Gubert, Mauro Fonseca, Anelise Munaretto and Thiago Henrique Silva

Sustainability 2020, 12(22), 9603; https://doi.org/10.3390/su12229603 - 18 Nov 2020

Cited by 2 | Viewed by 2512

Abstract

This paper analyzes public transit mobility of different economic classes of Curitiba, Brazil, exploring an official smart card dataset provided by the city. With the population divided into subsets corresponding to economic strata, we characterized vital spatial-temporal transit usage patterns, such as departure [...] Read more.

This paper analyzes public transit mobility of different economic classes of Curitiba, Brazil, exploring an official smart card dataset provided by the city. With the population divided into subsets corresponding to economic strata, we characterized vital spatial-temporal transit usage patterns, such as departure times and destinations reached by different economic classes. We also constructed a network representing the common origin and destination of public transit users, enabling discovering distinct patterns. Among the results, we observe that with the increase in wealth, the morning activity is postponed (on average for 2 h), and the spatial distribution of the trips becomes more localized compared with lower classes. We also show that our model captures fairly well realistic mobility patterns exploring a cheaper and larger-scale data source by comparing our results with a household travel survey from Curitiba. Understand how people in different economic classes appropriate urban spaces help to provide subsidies for, e.g., more sustainable economic development propositions. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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17 pages, 405 KiB

Open AccessArticle

How to Achieve a Continuous Increase in Public Transport Ridership?—A Case Study of Braunschweig and Tampere

by Christoph Schütze, Nina Schmidt, Heikki Liimatainen and Thomas Siefer

Sustainability 2020, 12(19), 8063; https://doi.org/10.3390/su12198063 - 30 Sep 2020

Cited by 8 | Viewed by 3778

Abstract

This manuscript is based on cooperation between the universities in Tampere, Finland, and Braunschweig, Germany. One of the main goals of the two institutes involved in research for public transport is a continuous increase in ridership. Therefore, the aim of this study is [...] Read more.

This manuscript is based on cooperation between the universities in Tampere, Finland, and Braunschweig, Germany. One of the main goals of the two institutes involved in research for public transport is a continuous increase in ridership. Therefore, the aim of this study is to (1) investigate the level of service attributes of public transport in Tampere and Braunschweig and evaluate their current state and (2) give advice to each city to further increase the ridership. At the beginning, the individual attributes and indicators for comparing public transport in both cities are presented and combined with theses from the literature. The attributes are divided into four chapters: “Level of Service”, “Pricing”, “Information and Marketing” and “Quality of travel”. In the following, the individual indicators, such as the travel speed (Level of Service) or information at stop (Information and Marketing) of the two study areas, are analysed and evaluated. Additionally, the public transport system in both investigated cities is expanded with new a tramway system (Tampere) or new tramway expansions (Braunschweig), which gives a lot of opportunities for improving the attractiveness of public transport. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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20 pages, 3845 KiB

Open AccessArticle

Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles

by Junpeng Cai, Dewang Chen, Shixiong Jiang and Weijing Pan

Sustainability 2020, 12(18), 7343; https://doi.org/10.3390/su12187343 - 8 Sep 2020

Cited by 7 | Viewed by 2515

Abstract

With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based [...] Read more.

With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based on the next destination of EV users’ trip, the strategy established a dynamic-area model to match charging stations with users’ travel demand intelligently. In the dynamic area, the Dijkstra algorithm is used to find the charging station with the shortest trip. Then, the area extension algorithm and the charging station attribution algorithm were developed to improve the robustness of the dynamic area. The two algorithms can automatically adjust the area size according to the number of charging stations in the dynamic area to reduce the number of nodes traversed by the Dijkstra algorithm. Finally, simulation examples were used to verify the effectiveness of the proposed model and algorithms. The results showed that the proposed intelligent charging guidance strategy can meet the travel demand of users. It is a promising technique in smart cities to find better travel trips with less travel distance and less computed time. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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19 pages, 1038 KiB

Open AccessArticle

How Does Operational Environment Influence Public Transport Effectiveness? Evidence from European Urban Bus Operators

by Georgios Georgiadis, Ioannis Politis and Panagiotis Papaioannou

Sustainability 2020, 12(12), 4919; https://doi.org/10.3390/su12124919 - 16 Jun 2020

Cited by 10 | Viewed by 2667

Abstract

Public transport systems’ effectiveness is a well-recognized pillar of their sustainability. In this study, we employed order-m efficiency estimators to investigate the effectiveness of 57 bus public transport operators that provide services in both large and medium sized European cities. Their effectiveness was [...] Read more.

Public transport systems’ effectiveness is a well-recognized pillar of their sustainability. In this study, we employed order-m efficiency estimators to investigate the effectiveness of 57 bus public transport operators that provide services in both large and medium sized European cities. Their effectiveness was simulated through a tailored production model and was evaluated against critical exogenous variables, which were mostly extracted from Eurostat database. Results showed that the effectiveness of the examined operators is generally satisfactory. Our research suggests that certain exogenous factors significantly affect operators’ effectiveness and thus create either advantageous or disadvantageous operational environments for maintaining public transport sustainability. Among these factors, household size, unemployment and car ownership rates were found to be unfavorable to bus public transport operations. Contrary to them, the presence of university students and metro systems in cities create a favorable operational environment for bus public transport effectiveness. These findings assist in the identification of sustainable development policies that would both contribute to public transport sustainability and to the fulfillment of wider community goals. Our findings also rationalize benchmarking exercises in the public transport industry, since they enable fair performance comparisons between systems that seek to incorporate successful management practices to improve their sustainability. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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17 pages, 2364 KiB

Open AccessArticle

Demand Responsive Transport Service of ‘Dead-End Villages’ in Interurban Traffic

by András Lakatos, János Tóth and Péter Mándoki

Sustainability 2020, 12(9), 3820; https://doi.org/10.3390/su12093820 - 7 May 2020

Cited by 16 | Viewed by 4373

Abstract

Providing a sustainable public transport service for areas with several small villages or hamlets is a challenge for the whole of Europe. To serve ‘dead-end villages’, vehicles must make a to-and-fro detour to each village, which requires considerable performance from the operator, and [...] Read more.

Providing a sustainable public transport service for areas with several small villages or hamlets is a challenge for the whole of Europe. To serve ‘dead-end villages’, vehicles must make a to-and-fro detour to each village, which requires considerable performance from the operator, and the service must also be ordered from the responsible bodies. The number of inhabitants in rural areas is constantly decreasing, and the remaining residents are aging. This process is due to the fact that economically active people in the country tend to move into towns offering jobs and public institutions instead of commuting to work. The performance requirement of serving low transport demand areas like ‘dead-end villages’ is high, while the number of passengers is very low. Furthermore, passengers are economically less active, and thus their transport must largely be subsidized. The present study hypothesizes that replacing traditional public transport with demand responsive transport (DRT) can make the service of rural areas with less public transport service and low demand sustainable. To prove this hypothesis, a generally applicable, innovative method of analysis based on performance–allocation is introduced, and the application of this method is illustrated by a case study conducted in northeastern Hungary. The number of ‘dead-end villages’ is high in the surveyed area; consequently, the results are impressive. The mathematical model applied here uses several parameters (e.g., population, traffic surveys, trip distance, operational costs), thus the analysis is highly complex. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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22 pages, 3943 KiB

Open AccessArticle

Analysis of the Passenger Flow Transfer Capacity of a Bus-Subway Transfer Hub in an Urban Multi-Mode Transportation Network

by Yuwei Yang, Jun Chen and Zexingjian Du

Sustainability 2020, 12(6), 2435; https://doi.org/10.3390/su12062435 - 20 Mar 2020

Cited by 6 | Viewed by 3354

Abstract

In the context of a rapid developing urban economy and the increasing number of motor vehicles, urban commuting transportation has witnessed a serious mismatch between the supply of and the demand for transportation network resources. In developing an urban multi-mode traffic network, using [...] Read more.

In the context of a rapid developing urban economy and the increasing number of motor vehicles, urban commuting transportation has witnessed a serious mismatch between the supply of and the demand for transportation network resources. In developing an urban multi-mode traffic network, using a urban traffic transfer hub to coordinate the transportation capabilities among different traffic networks is perceived to be highly effective for exploring the network transportation capacity of an entire transportation system, and improving travel efficiency and experiences for the public. Based on the super-network model, this paper develops a topological structure for a multi-mode traffic network, in which two typical combined travel modes are selected to establish the path impedance function for that network. Moreover, the multi-mode traffic allocation model and the solving algorithm are constructed in the research. The paper studies the impact of two types of factors related to the transfer capacity of passenger flows based on the regular traffic network of a bus-and-subway transfer hub using a sensitivity analysis of the transfer time and the associated penalty. The findings suggest that both changes in transfer walking time and the transfer penalty have no significant effect on the bus passenger flow. Full article

(This article belongs to the Special Issue Sustainable Public Transport System)

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