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Smart Cities
Special Issues
Connected and Cooperative Transportation Systems for the Future Society
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Connected and Cooperative Transportation Systems for the Future Society

A special issue of Smart Cities (ISSN 2624-6511). This special issue belongs to the section "Smart Transportation".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 14925

Special Issue Editors

Dr. Md Abdus Samad Kamal

E-Mail Website
Guest Editor
Gunma University, Japan
Interests: intelligent transportation system; cooperative traffic control; connected and automated transportation
Special Issues, Collections and Topics in MDPI journals
Dr. Jackeline Ríos-Torres

E-Mail Website
Guest Editor
Oak Ridge National Laboratory, Oak Ridge, USA
Interests: optimal control of transportation systems; intelligent transportation systems; traffic coordination systems; connected and automated vehicles; modeling and simulation of automotive systems
Dr. Susilawati

E-Mail Website
Guest Editor
Monash University Malaysia
Interests: intelligent transportation systems; connected and automated vehicles; transport modeling during disruption; transport network reliability; the dynamic bottleneck congestion model

Special Issue Information

Dear Colleagues,

We are dreaming of a future society that will provide a highly efficient, comfortable, economically-sound, and quality life to everyone by integrating cyber and physical spaces for sharing of cross-sectional knowledge for cooperation and economic advancements. Such a society will provide human-centered services and solve social and environmental problems. Transportation, as a key driver of social development, must play a critical role in realizing such an advanced society by providing the safest, most reliable, efficient, and environmentaly-friendly services to enable people having access to education, health, jobs, and goods. This Special Issue focuses on the most recent and relevant developments towards the realization of such multimodal cooperative future transportation systems.

The emergence of connectivity and automation is transforming road transportation and enabling unique opportunities to develop innovative controls for improving the operation of both individual vehicles and overall traffic. Both vehicles and users with high-speed wireless connectivity in various forms can help in enhancing the perception of the entire traffic network in a city. Introduction of automated vehicles will provide opportunities for cooperative management of the individual vehicles, traffic networks, and other modes of transportation and will allow the introduction of various services to maximize the benefits and overall comfort of the users. This Special Issue welcomes innovative research on new integrated transport services and cooperative management and control technologies in the context of intelligent transportation systems (ITS). In particular, this issue welcomes contributions in, but not limited to, the following relevant areas:

  • Smart city transportation network and services;
  • Cooperative automated vehicles;
  • Connected and automated transportation;
  • Cooperative and distributed traffic management;
  • Multimodal connected automated systems and IoT;
  • Applications of artificial intelligence for intelligent transportation systems;
  • Connectivity and automation in freight systems;
  • Ride sharing systems;
  • Multimodal transportation connectivity;
  • Cyber-physical systems and IoT for Transporation;
  • Mobility as a service.

Dr. Md Abdus Samad Kamal
Dr. Jackeline Ríos-Torres
Dr. Susilawati
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. Smart Cities 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 2000 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

  • Intelligent transportation systems
  • Connected-automated vehicles
  • Cooperative traffic management
  • IoT and smart mobility
  • Transport for Society 5.0
  • Multimodal transportation
  • Smart mobility services
  • Intelligent vehicles
  • Smart mobility for agriculture
  • Data science

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Published Papers (4 papers)

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Research

17 pages, 19679 KiB  
Article
Macroscopic Lane Change Model—A Flexible Event-Tree-Based Approach for the Prediction of Lane Change on Freeway Traffic
by Christina Ng, Susilawati Susilawati, Md Abdus Samad Kamal and Irene Chew Mei Leng
Smart Cities 2021, 4(2), 864-880; https://doi.org/10.3390/smartcities4020044 - 24 May 2021
Cited by 4 | Viewed by 2864
Abstract
Binary logistic regression has been used to estimate the probability of lane change (LC) in the Cell Transmission Model (CTM). These models remain rigid, as the flexibility to predict LC for different cell size configurations has not been accounted [...] Read more.
Binary logistic regression has been used to estimate the probability of lane change (LC) in the Cell Transmission Model (CTM). These models remain rigid, as the flexibility to predict LC for different cell size configurations has not been accounted for. This paper introduces a relaxation method to refine the conventional binary logistic LC model using an event-tree approach. The LC probability for increasing cell size and cell length was estimated by expanding the LC probability of a pre-defined model generated from different configurations of speed and density differences. The reliability of the proposed models has been validated with NGSIM trajectory data. The results showed that the models could accurately estimate the probability of LC with a slight difference between the actual LC and predicted LC (95% Confidence Interval). Furthermore, a comparison of prediction performance between the proposed model and the actual observations has verified the model’s prediction ability with an accuracy of 0.69 and Area Under Curve (AUC) value above 0.6. The proposed method was able to accommodate the presence of multiple LCs when cell size changes. This is worthwhile to explore the importance of such consequences in affecting the performance of LC prediction in the CTM model. Full article
(This article belongs to the Special Issue Connected and Cooperative Transportation Systems for the Future Society)
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20 pages, 3821 KiB  
Article
A Study of Spatiotemporal Distribution of Mobility-On-Demand in Generating Pick-Up/Drop-Offs Location Placement
by Ryan K. Gunawan and Susilawati
Smart Cities 2021, 4(2), 746-766; https://doi.org/10.3390/smartcities4020038 - 17 May 2021
Cited by 3 | Viewed by 3207
Abstract
The location placement of pick-up/drop-offs of ride hailing usually only considers spatial distribution within a certain area. Previous studies often mapped out the potential hotspots for pick-up/drop-offs, benefitting the ride-hailing company and not considering the passengers. Therefore, in this study, we incorporated the [...] Read more.
The location placement of pick-up/drop-offs of ride hailing usually only considers spatial distribution within a certain area. Previous studies often mapped out the potential hotspots for pick-up/drop-offs, benefitting the ride-hailing company and not considering the passengers. Therefore, in this study, we incorporated the spatiotemporal distribution of mobility-on-demand on generating pick-up/drop-off location placement using a genetic algorithm considering the walking distance and minimum demand data served within the radius. The data collected are analyzed through the clustering method, and the resulting cluster centers are fed into the location optimization algorithm. The genetic algorithm is used to optimize the location placement with the consideration of the user’s walking distance and demand. The algorithm is able to find an appropriate placement and determine reliable pick-up/drop-off stations within the study area based on observed spatiotemporal demand despite the difference in demand distribution through different time periods. Full article
(This article belongs to the Special Issue Connected and Cooperative Transportation Systems for the Future Society)
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11 pages, 567 KiB  
Article
Rider Perceptions of an On-Demand Microtransit Service in Salt Lake County, Utah
by Gregory S. Macfarlane, Christian Hunter, Austin Martinez and Elizabeth Smith
Smart Cities 2021, 4(2), 717-727; https://doi.org/10.3390/smartcities4020036 - 14 May 2021
Cited by 11 | Viewed by 2940
Abstract
On-demand microtransit services are frequently seen as an important tool in supporting first and last mile operations surrounding fixed route high frequency transit facilities, but questions remain surrounding who will use these novel services and for what purposes. In November 2019, the Utah [...] Read more.
On-demand microtransit services are frequently seen as an important tool in supporting first and last mile operations surrounding fixed route high frequency transit facilities, but questions remain surrounding who will use these novel services and for what purposes. In November 2019, the Utah Transit Authority launched an on-demand microtransit service in south Salt Lake County in partnership with a private mobility operator. This paper reports the results of an expressed preferences survey of 130 transit riders in the microtransit service area that was collected before and immediately after the service launched. There is not a clear relationship between current transit access mode and expressed willingness to use microtransit, although some responses from new riders indicate the novel service competes most directly with commercial transportation network company operations. The survey responses also reveal younger passengers express a more than expected willingness to use microtransit, middle-aged passengers a less than expected willingness, and older passengers neutral or no expressed opinion. The results suggest additional relationships between household size and transit use frequency, but further research is necessary. The effect of other user characteristics, including income and automobile availability, is less statistically clear and requires further research. Full article
(This article belongs to the Special Issue Connected and Cooperative Transportation Systems for the Future Society)
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16 pages, 1943 KiB  
Article
An Incentive Based Dynamic Ride-Sharing System for Smart Cities
by Abu Saleh Md Bakibillah, Yi Feng Paw, Md Abdus Samad Kamal, Susilawati Susilawati and Chee Pin Tan
Smart Cities 2021, 4(2), 532-547; https://doi.org/10.3390/smartcities4020028 - 22 Apr 2021
Cited by 10 | Viewed by 4144
Abstract
Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both [...] Read more.
Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both passengers and drivers) that incorporates travelers of similar routes and time schedules on short notice. The objective is to reduce the number of private vehicles on urban roads by utilizing the available seats properly. We develop a mobile-cloud architecture-based system that enables real-time ride-sharing. The effectiveness of the proposed system is evaluated through microscopic traffic simulation using Simulation of Urban Mobility (SUMO) considering the traffic flow behavior of a real smart city. Moreover, we develop a lab-scale experimental prototype in the form of Internet of Things (IoT) network. The simulation results show that the proposed system reduces fuel consumption, CO2 and CO emissions, and average waiting time of vehicles significantly, while increasing the vehicle’s average speed. Remarkably, it is found that only 2–10% ride-sharing can improve the overall traffic performance. Full article
(This article belongs to the Special Issue Connected and Cooperative Transportation Systems for the Future Society)
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