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Article
Publication date: 11 July 2023

Yair Wiseman

Nowadays, transportation authorities in various countries are in tension as to whether to invest in railroads or roads. There are arguments for each side, and in the end, each…

Abstract

Purpose

Nowadays, transportation authorities in various countries are in tension as to whether to invest in railroads or roads. There are arguments for each side, and in the end, each transportation authority reaches a kind of balance between the investments. This study aims to anticipate how autonomous vehicles will influence this decision.

Design/methodology/approach

The roads' capacity in the era of autonomous vehicles is assessed and research has concluded that the anticipated increase in road capacity will encourage transportation authorities to invest much more in roads than in railroads.

Findings

The appearance of the autonomous vehicles will significantly change the balance in favor of the roads, because the roads' capacity will be increased substantially so the roads will be able to accommodate many more vehicles.

Research limitations/implications

Currently, autonomous vehicles are still very rare.

Practical implications

The impact of autonomous vehicles on the decision whether to build more roads is explained.

Originality/value

The study explained why the transportation authorities in the various countries will be more inclined to switch to road construction and why the transition to more roads and fewer railroads will likely be done gradually as more autonomous vehicles enter service.

Details

International Journal of Intelligent Unmanned Systems, vol. 12 no. 1
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 1 November 2023

Mahnoor Hasan and Fodil Fadli

There is lack of knowledge about how the existing streets need to be redesigned and the infrastructural changes that need to be made to adopt autonomous vehicles. The purpose of…

Abstract

Purpose

There is lack of knowledge about how the existing streets need to be redesigned and the infrastructural changes that need to be made to adopt autonomous vehicles. The purpose of this study is to investigate the infrastructure requirements of autonomous vehicles in terms of (1) lane widths, (2) parking spaces, (3) drop-off zones and (4) other facilities, followed by analyzing them and suggesting changes in the existing urban design of Msheireb Downtown Doha (MDD).

Design/methodology/approach

Mixed method of combining both qualitative (secondary research of analyzing the existing data about the urban design guidelines for an autonomous future, observations of the existing infrastructure) and quantitative methods (on-site measurements of pedestrian walkways and road lane widths) is used.

Findings

The outcome of the research consists of a series of major infrastructural changes with regard to lane widths, parking spaces, pick-up and drop-off zones and other facilities needed for the deployment of autonomous vehicles.

Practical implications

The results imply that Qatar can benefit by adopting the proposed urban design suggestions for the implementation of autonomous vehicles on the streets of MDD in particular, and smart cities of Qatar and the region in general.

Social implications

The proposed changes can work as a reference and serve as a possible setting for addressing Autonomous Vehicle preparations in emerging cities.

Originality/value

The proposed urban design changes can be adapted for an autonomous future in emerging cities.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 12 May 2023

İnci Sarıçiçek, Ahmet Yazıcı and Özge Aslan

This study aims to propose a novel method for the conflict detection and eradication of autonomous vehicles which has predetermined routes to establish multi pickup and delivery…

Abstract

Purpose

This study aims to propose a novel method for the conflict detection and eradication of autonomous vehicles which has predetermined routes to establish multi pickup and delivery tasks according to task priorities and vehicle capacity status on each pickup and delivery nodes in assembly cells in the automotive production.

Design/methodology/approach

In the designed system, the routing of autonomous vehicles (AVs) and scheduling of pickup and delivery tasks are established in production logistics. Gantt chart is created according to vehicle routes, and conflicts are detected using the proposed conflict-sweep algorithm. The proposed conflict-solving algorithm eliminates conflicts on intersections and roads by considering vehicle routes and task priorities.

Findings

In many production systems, there is a need to obtain flexible routes in each pickup delivery task group that changes during day, week, etc. Proposed system provides remarkable advantages in obtaining conflict-free routes for pre-scheduled multi transport tasks of vehicles by considering efficiency in production systems.

Originality/value

A novel method is proposed for the conflict detection and eradication of AVs. Proposed system eliminates conflicts on intersections and roads by considering pre-planned vehicle routes for a fleet of heterogeneous AVs. Unlike most of the other conflict-free algorithms, in which conflicts are solved between two points, proposed system also considers multi pickup and delivery points for AVs. This is pioneering paper that addresses conflict-free route planning with backhauls and scheduling of multi pickup and delivery tasks for AVs.

Details

Robotic Intelligence and Automation, vol. 43 no. 2
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 14 February 2022

Syama R. and Mala C.

This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways…

Abstract

Purpose

This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways incorporating current and historical information and contextual features. The interactions among the vehicles are modelled using long-short-term memory (LSTM).

Design/methodology/approach

Predicting the surrounding vehicles' behaviour is crucial in any Advanced Driver Assistance Systems (ADAS). To make a decision, any prediction models available in the literature consider the present and previous observations of the surrounding vehicles. These existing models failed to consider the contextual features such as traffic density that also affect the behaviour of the vehicles. To forecast the appropriate driving behaviour, a better context-aware learning method should be able to consider a distinct goal for each situation is more significant. Considering this, a deep learning-based model is proposed to predict the lane changing behaviours using past and current information of the vehicle and contextual features. The interactions among vehicles are modeled using an LSTM encoder-decoder. The different lane-changing behaviours of the vehicles are predicted and validated with the benchmarked data set NGSIM and the open data set Level 5.

Findings

The lane change behaviour prediction in ADAS is gaining popularity as it is crucial for safe travel in a mixed driving environment. This paper shows the prediction of maneuvers with a prediction window of 5 s using NGSIM and Level 5 data sets. The proposed method gives a prediction accuracy of 97% on average for all lane-change maneuvers for both the data sets.

Originality/value

This research presents a strategy for predicting autonomous vehicle behaviour based on contextual features. The paper focuses on deep learning techniques to assist the ADAS.

Details

International Journal of Pervasive Computing and Communications, vol. 19 no. 4
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 31 October 2023

Zhizhong Guo, Fei Liu, Yuze Shang, Zhe Li and Ping Qin

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance…

Abstract

Purpose

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

Design/methodology/approach

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

Findings

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

Originality/value

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

Open Access
Article
Publication date: 21 July 2023

Harry Edelman, Joel Stenroos, Jorge Peña Queralta, David Hästbacka, Jani Oksanen, Tomi Westerlund and Juha Röning

Connecting autonomous drones to ground operations and services is a prerequisite for the adoption of scalable and sustainable drone services in the built environment. Despite the…

Abstract

Purpose

Connecting autonomous drones to ground operations and services is a prerequisite for the adoption of scalable and sustainable drone services in the built environment. Despite the rapid advance in the field of autonomous drones, the development of ground infrastructure has received less attention. Contemporary airport design offers potential solutions for the infrastructure serving autonomous drone services. To that end, this paper aims to construct a framework for connecting air and ground operations for autonomous drone services. Furthermore, the paper defines the minimum facilities needed to support unmanned aerial vehicles for autonomous logistics and the collection of aerial data.

Design/methodology/approach

The paper reviews the state-of-the-art in airport design literature as the basis for analysing the guidelines of manned aviation applicable to the development of ground infrastructure for autonomous drone services. Socio-technical system analysis was used for identifying the service needs of drones.

Findings

The key findings are functional modularity based on the principles of airport design applies to micro-airports and modular service functions can be connected efficiently with an autonomous ground handling system in a sustainable manner addressing the concerns on maintenance, reliability and lifecycle.

Research limitations/implications

As the study was limited to the airport design literature findings, the evolution of solutions may provide features supporting deviating approaches. The role of autonomy and cloud-based service processes are quintessentially different from the conventional airport design and are likely to impact real-life solutions as the area of future research.

Practical implications

The findings of this study provided a framework for establishing the connection between the airside and the landside for the operations of autonomous aerial services. The lack of such framework and ground infrastructure has hindered the large-scale adoption and easy-to-use solutions for sustainable logistics and aerial data collection for decision-making in the built environment.

Social implications

The evolution of future autonomous aerial services should be accessible to all users, “democratising” the use of drones. The data collected by drones should comply with the privacy-preserving use of the data. The proposed ground infrastructure can contribute to offloading, storing and handling aerial data to support drone services’ acceptability.

Originality/value

To the best of the authors’ knowledge, the paper describes the first design framework for creating a design concept for a modular and autonomous micro-airport system for unmanned aviation based on the applied functions of full-size conventional airports.

Details

Facilities , vol. 41 no. 15/16
Type: Research Article
ISSN: 0263-2772

Keywords

Article
Publication date: 20 February 2024

I Gede Mahatma Yuda Bakti, Sik Sumaedi, Medi Yarmen, Marlina Pandin, Aris Yaman, Rahmi Kartika Jati and Mauludin Hidayat

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature…

Abstract

Purpose

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

Design/methodology/approach

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

Findings

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

Practical implications

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

Originality/value

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 12 December 2023

Mustafa Çimen, Damla Benli, Merve İbiş Bozyel and Mehmet Soysal

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation…

Abstract

Purpose

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

Design/methodology/approach

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

Findings

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

Originality/value

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 13 December 2021

Mati Ullah, Chunhui Zhao, Hamid Maqsood, Mahmood Ul Hassan and Muhammad Humayun

This paper aims to design an adaptive nonlinear strategy capable of timely detection and reconstruction of faults in the attitude’s sensors of an autonomous aerial vehicle with…

Abstract

Purpose

This paper aims to design an adaptive nonlinear strategy capable of timely detection and reconstruction of faults in the attitude’s sensors of an autonomous aerial vehicle with greater accuracy concerning other conventional approaches in the literature.

Design/methodology/approach

The proposed scheme integrates a baseline nonlinear controller with an improved radial basis function neural network (IRBFNN) to detect different kinds of anomalies and failures that may occur in the attitude’s sensors of an autonomous aerial vehicle. An integral sliding mode concept is used as auto-tune weight update law in the IRBFNN instead of conventional weight update laws to optimize its learning capability without computational complexities. The simulations results and stability analysis validate the promising contributions of the suggested methodology over the other conventional approaches.

Findings

The performance of the proposed control algorithm is compared with the conventional radial basis function neural network (RBFNN), multi-layer perceptron neural network (MLPNN) and high gain observer (HGO) for a quadrotor vehicle suffering from various kinds of faults, e.g. abrupt, incipient and intermittent. From the simulation results obtained, it is found that the proposed algorithm’s performance in faults detection and estimation is relatively better than the rest of the methodologies.

Practical implications

For the improvement in the stability and safety of an autonomous aerial vehicle during flight operations, quick identification and reconstruction of attitude’s sensor faults and failures always play a crucial role. Efficient fault detection and estimation scheme are considered indispensable for an error-free and safe flight mission of an autonomous aerial vehicle.

Originality/value

The proposed scheme introduces RBFNN techniques to detect and estimate the quadrotor attitude’s sensor faults and failures efficiently. An integral sliding mode effect is used as the network’s backpropagation law to automatically modify its learning parameters accordingly, thereby speeding up the learning capabilities as compared to the conventional neural network backpropagation laws. Compared with the other investigated techniques, the proposed strategy achieve remarkable results in the detection and estimation of various faults.

Details

International Journal of Intelligent Unmanned Systems, vol. 11 no. 2
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 24 August 2023

Mohammad Iranmanesh, Morteza Ghobakhloo, Behzad Foroughi, Mehrbakhsh Nilashi and Elaheh Yadegaridehkordi

This study aims to explore and ranks the factors that might determine attitudes and intentions toward using autonomous vehicles (AVs).

Abstract

Purpose

This study aims to explore and ranks the factors that might determine attitudes and intentions toward using autonomous vehicles (AVs).

Design/methodology/approach

The “technology acceptance model” (TAM) was extended by assessing the moderating influences of personal-related factors. Data were collected from 378 Vietnamese and analysed using a combination of “partial least squares” and the “adaptive neuro-fuzzy inference system” (ANFIS) technique.

Findings

The findings demonstrated the power of TAM in explaining the attitude and intention to use AVs. ANFIS enables ranking the importance of determinants and predicting the outcomes. Perceived ease of use and attitude were the most crucial drivers of attitude and intention to use AVs, respectively. Personal innovativeness negatively moderates the influence of perceived ease of use on attitude. Data privacy concerns moderate positively the impact of perceived usefulness on attitude. The moderating effect of price sensitivity was not supported.

Practical implications

These findings provide insights for policymakers and automobile companies' managers, designers and marketers on driving factors in making decisions to adopt AVs.

Originality/value

The study extends the AVs literature by illustrating the importance of personal-related factors, ranking the determinants of attitude and intention, illustrating the inter-relationships among AVs adoption factors and predicting individuals' attitudes and behaviours towards using AVs.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

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