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The paper aims to review current practices of road safety audits worldwide, investigate the perceptions of experts on highway work zone safety in the USA and issues of adopting work zone safety audits in the country, and propose a framework for developing guidelines for implementing work zone safety audits for safety improvements.

The paper was conducted by reviewing the existing literature of road safety audits and administering four‐week questionnaire surveys of experts on highway work zone safety in the USA.

Road safety audits have been successfully adopted worldwide to maximize safety of the roadway environment for highway users. The questionnaire surveys have clarified leading causes of work zone safety problems and effective countermeasures, types of projects suitable for auditing and audit frequencies, audit team composition and funding sources, audit tasks and tools, and project staff safety training audits. A similar procedure for road safety audits could be adopted for work zone safety audits with emphasis on mitigating work zone safety impacts.

Additional survey participants from the highway user group may add valuable insights into the use of highway work zone safety audits for safety improvements.

The paper findings would assist in preparing strategies and methodologies for developing the national highway work zone safety audit guidelines in the USA.

The work zone safety audit guidelines to be developed could help transportation practitioners effectively conduct work zone safety audits for safety improvements in the country.

This paper is a review of a number routing protocols in the internet of vehicles (IoV). IoV emphasizes information interaction among humans, vehicles and a roadside unit (RSU), within which routing is one of the most important steps in IoV network.

In this paper, the authors have summarized different research data on routing protocols in the IoV. Several routing protocols for IoV have been proposed in the literature. Their classification is made according to some criteria such as topology-based, position-based, transmission strategy and network structure. This paper focuses on the transmission strategy criteria. There exist three types of protocols that are based on this strategy: unicast protocol, broadcast protocols and multicast protocols. This later type is classified into two subclasses: geocast and cluster-based protocols. The taxonomy of the transmission strategy is presented in this study. We discuss the advantages and disadvantages of each type with a general comparison between the five types.

The authors can deduce that many challenges are encountered when designing routing protocols for IoV.

A simple and well-explained presentation of the functioning of the IoV is provided with a comparison among each categories of protocols is well presented along with the advantages and disadvantages of each type. The authors examined the main problems encountered during the design of IoV routing protocol, such as the quick change of topology, the frequent disconnection, the big volume of data to be processed and stored in the IoV, and the problem of network fragmentation. This work explores, compares existing routing protocols in IoV and provides a critical analysis. For that, the authors extract the challenges and propose future perspectives for each categories of protocols.

There are a number of individual and contextual variables that influence public opinion of the police but we know little about the public opinion regarding state law enforcement agencies. Prior studies involving municipal police and other criminal justice agencies indicate that the perceptions of procedural justice, or fair treatment, are important predictors of citizen satisfaction with police services. The purpose of this paper is to examine whether individuals who perceive procedurally just treatment during their contact with a state patrol officer improve the levels of satisfaction with the state patrol.

This paper presents the results of a public opinion study (n=846) regarding the Colorado State Patrol conducted in 2009. A subsample of 393 individuals who had contact with the state patrol and were further surveyed about their contact with the officer. Logistic regression models were used to examine individual- and contextual-level variables influence satisfaction with the state patrol and whether this relationship was mediated by the perceptions of procedural justice.

The authors found that individuals who perceive higher levels of procedural justice expressed higher satisfaction with the state patrol. Females, older respondents, and non-white respondents expressed greater satisfaction, as well as those who had voluntary contact or were not arrested. More importantly, procedural justice mediated the effect of involuntary contact and arrest on levels of satisfaction, and while non-white respondents were less likely to experience procedural justice, when levels of procedural justice are controlled for, they have higher levels of satisfaction.

The findings emphasize the significance of citizen perceptions of procedural justice during contacts with members of the state patrol. The current study contributes to our knowledge of procedural justice and citizen satisfaction with police encounters given previous research on citizen satisfaction with police focuses almost exclusively on local-level agencies, and research on procedural justice asks the respondents almost exclusively about the police in general.

Highway signage programs are important to the success of winery tourism industry. The purpose of this paper is to investigate the regulatory environment US wineries operate under in regards to highway signage programs. The goal then is to compare wine tourism-related highway signage programs in the USA and identify best practices for the programs.

Twenty-six programs from 13 US states are included in this study. Research collected both primary data (through interviews with 30 officials and representatives) and secondary data (from websites, government publications) to identify the costs, regulations and rules of each program.

A review of these programs shows that while there are many common elements in these programs, all are managed differently, have different operational and facility requirements for participation and vary in cost.

Highway signage programs related to winery tourism are best administered by a single state-wide governmental agency or foundations/trusts. Second, highway signage program should link with a separate certification program for the wineries which guarantees a certain minimum amount of local content. Winery owners and officials interviewed also emphasized the need for synergy among neighboring wineries to facilitate winery tourism.

Limited research has been conducted about the regulatory environment of signage programs that are specific to the wine industry in the USA. This study begins to address this gap in the literature by presenting an overview and best practices of 26 wine tourism-related highway signage programs from 13 different states across the USA.

This study aims to map out contractors' thoughts on construction-related environmental recovery as an excuse for deliberately carrying on unsustainable construction.

A typical highway construction project in China was investigated. Textual materials were collected through semistructured interviews. Content analysis was conducted to derive qualitative data from the textual materials.

The research findings reveal a trend of environmental recovery associated with construction activities. It is found that contractors utilize this trend to maintain unsustainable construction. Furthermore, the effects of environmental recovery equip local governments with a tolerance for environmental degradation, and the environmental tolerance allows contractors to continue unsustainable construction without being discovered.

This paper presents an environmental recovery-based perspective on unsustainable construction and sheds some light on the promotion of sustainable construction.

The advent of Industry 4.0 has engendered opportunities for a coalescence of digital technologies that collectively enable driverless vehicles to operate during the construction and use of a highway. Yet, hitherto scant research has been conducted to review these collective developments and/or sample construction practitioner opinion on them. This study aims to present a systematic review of extant literature on the application of driverless technologies in civil engineering and in particular, the highways infrastructure sector and offers insight into the limitations of associated barriers to full adoption, namely, current technological development processes, legal deficiencies and societal concerns. In so doing, this work presents a vignette of contemporary developments augmented by a critical analysis from practitioners’ perceptions.

A mixed philosophical methodological approach is adopted for this inductive research study. Interpretivism is used to critically analyse the literature and post-positivism to perform content analysis of the literature and synthesis of the discourse with practitioners. A total of 44 related papers published between 1998 and 2019 have been included in this study. Emergent themes identified from literature are then discussed in some further detail, namely, 1) automation and robotics; 2) case studies and simulations; and 3) safety and ergonomics). A focus group is then held with leading industrialists to discuss their experiences of advanced driverless technology applications in practice. Based upon a culmination of emergent evidence, a conceptual model of prevailing barriers is then developed to further elucidate upon the challenges facing the highways infrastructure sector.

Research into driverless technologies within the highways infrastructure sector has received relatively scant academic attention. Hitherto, most advancements made have stemmed from multidisciplinary teams consisting of engineering, information technology and social scientist researchers. There is insufficient supporting evidence of civil engineering and construction academics input into developments made – suggesting that prototype products often fail to adequately consider practical applications in the highways infrastructure sector at the design and use case stage. This view is substantiated by feedback from leading industry experts who participated in unstructured telephone interviews. Their feedback suggests that practical applications of products have been beset with problems, thus creating a perception that advanced technologies are largely “unusable” within the highways infrastructure sector and so are unsuitable for large-scale (and particularly bespoke) industrial applications.

This research critically synthesises the prevailing scientific discourse within extant literature on driverless technologies implemented but also garners practitioner feedback from leading UK industrialists on their applications in practice. Hitherto, this combined analysis approach has been rarely used in spite of it having significant advantages of tacit knowledge reflection on technologies used, where such can be used as a basis for further informed discourse and/or development. Moreover, this work culminates in a conceptual model that acts as a catalyst for future research investigations.

Safety research has focused on drivers, pedestrians and vehicles, with scarce attention given to highway traffic officers (HTOs). This paper develops a robust prediction model which enables highway safety authorities to predict exclusive incidents occurring on the highway such as incursions and environmental hazards, respond effectively to diverse safety risk incident scenarios and aid in timely safety precautions to minimise HTO incidents.

Using data from a highway incident database, a supervised machine learning method that employs three algorithms [namely Support Vector Machine (SVM), Random Forests (RF) and Naïve Bayes (NB)] was applied, and their performances were comparatively analysed. Three data balancing algorithms were also applied to handle the class imbalance challenge. A five-phase sequential method, which includes (1) data collection, (2) data pre-processing, (3) model selection, (4) data balancing and (5) model evaluation, was implemented.

The findings indicate that SVM with a polynomial kernel combined with the Synthetic Minority Over-sampling Technique (SMOTE) algorithm is the best model to predict the various incidents, and the Random Under-sampling (RU) algorithm was the most inefficient in improving model accuracy. Weather/visibility, age range and location were the most significant factors in predicting highway incidents.

This is the first study to develop a prediction model for HTOs and utilise an incident database solely dedicated to HTOs to forecast various incident outcomes in highway operations. The prediction model will provide evidence-based information to safety officers to train HTOs on impending risks predicted by the model thereby equipping workers with resilient shocks such as awareness, anticipation and flexibility.

Proper identification, allocation, and pricing of risks are critical to effective procurement and project delivery, particularly when contracts specify the intended performance instead of how the work is to be performed. This paper presents an overview of the sources of project risks when performance specifications are used for highway infrastructure procurement. The findings are based on a comprehensive literature review and interviews with subject-matter experts involved in developing performance specifications for highway infrastructure. The authors conclude that wider use of performance specifications in U.S. highway infrastructure construction requires a fundamental reassessment of risk allocation and pricing. Highway agencies and the contractors need to realign their respective organizational capabilities with the goal of using performance specifications as a facilitator of innovation, a goal that remains elusive after decades of applied research.

Proper identification, allocation, and pricing of risks are critical to effective procurement and project delivery, particularly when contracts specify the intended performance instead of how the work is to be performed. This paper presents an overview of the sources of project risks when performance specifications are used for highway infrastructure procurement. The findings are based on a comprehensive literature review and interviews with subject-matter experts involved in developing performance specifications for highway infrastructure. The authors conclude that wider use of performance specifications in U.S. highway infrastructure construction requires a fundamental reassessment of risk allocation and pricing. Highway agencies and the contractors need to realign their respective organizational capabilities with the goal of using performance specifications as a facilitator of innovation, a goal that remains elusive after decades of applied research.

Various approaches have emerged to assist practitioners in making more informed decisions in highway construction projects. However, industry practitioners are still using subjective ways to make decisions. Also, researchers have developed tools and techniques with similar objectives. Lack of information on what has been developed might lead to those issues. Therefore, this paper aims to review trends of evolution, pinpoint strengths and gaps in the literature and identifies potential future directions for decision-making research in highway construction projects.

A systematic review was conducted on published articles on decision-making in highway construction projects using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique.

The analysis of 101 articles revealed that existing decision-making research in highway construction projects targets improvements in four areas: feasibility, conceptual, detailed scope and detailed design. The four areas consist of sixteen subthemes that are detailed in this study. In addition, most research involved developing decision support tools and systems as well as decision-making models, techniques and frameworks. Lastly, several research areas have emerged, such as adding more decision criteria including those with uncertainties, expanding existing decision-making models into decision support systems, benchmarking decision criteria between different sample populations and exploring inter-and intra-relationships between decision criteria.

This paper provides an overview of existing research on decision-making in highway construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research. Finally, industry practitioners can use the findings to develop strategies for effective decision-making processes.

This study aims to investigate ground-related design deficiencies as potential avenues of avoidable cost overruns, discernible from the geotechnical practices of highway agencies in the Niger Delta region of Nigeria.

The study deploys an interpretivist qualitative methodology to provide a detailed descriptive analysis of the design-related geotechnical practices of highway agencies during the pre-contract phase of highway projects. Semi-structured interviews were conducted with in-house professionals, consultants and contractors affiliated with the three highway agencies in the Niger Delta and thematically analysed to identify significant deviations from geotechnical best practices.

The study outcome shows that during the pre-contract phase, a chain of design-related geotechnical shortcomings has plagued highway projects executed in the Niger Delta. This view of practice uncovered in this study demonstrates a culture of significant deviation from best practice recommendations, which could plausibly contribute to the history of significant project cost overruns recorded in the region.

The study qualitatively spotlights gaps in the practice of highway agencies and reinforces the need for a re-orientation of the attitude to risk management, to give geotechnical concerns a priority in the financial management of highway projects executed in the Niger Delta region of Nigeria.

The purpose of this paper is to accurately capture the risks which are caused by each road user in time.

The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.

The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.

This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

Given the significant amount of public infrastructure spending and the widely expressed concern about the declining quality of the American public infrastructure system, research about the effectiveness of public infrastructure investment is especially timely and crucial. The study extends public service production theory and public choice theory to the public infrastructure field, and develops a realistic and full theoretical model of public highway production by taking state highway efficiency differences into account. The panel fixed-effects method is used to examine the effects of state highway finance on state highway infrastructure quality. This study finds that state highway maintenance spending plays a crucial role in improving state road and bridge quality. Moreover, highway efficiency elements matter for state highway infrastructure quality.

Highway projects in India have a history of cost overruns and delay in project delivery, thus incurring huge losses to public funds. The study aimed to measure the extent of influence of various constraints on the overall success of highway projects (e.g. National highway project, state highway projects and major district roads). Based on the literature, various factors were grouped under three categories (a) Project Constraints, (b) Project Governance Constraints and (c) Stakeholder Induced Constraints.

A quantitative approach was adopted. A questionnaire-based survey was conducted with 435 respondents from the field of highway projects with a minimum experience of 1 year as Project Manager. The data was analyzed by partial least squares structural equation modeling technique.

It was identified that the impact of project constraints (ES = 0.313) on project success is more than that of project governance constraints (ES = 0.231) and stakeholder induced constraints. Additionally, it was found that project governance constraints have a strong impact on project constraints (ES = 0.535) and stakeholder induced constraints (ES = 0.403).

The study presented in this paper is first of its kind to measure and articulate the impact of project governance constraint, project constraint and stakeholder induced constraints on project success.

Public-private partnership (PPP) highway projects in India are undertaken at both state and national levels, such that differences exist in how the procuring authorities manage project risk during the development and construction phase under different institutional frameworks. This study assesses the performance implication of the different administrative positionings of the procuring authority.

A data set of 516 PPP highway projects implemented in India formed the basis of this study. Means comparison, ordinary least squares (OLS) regression and seemingly unrelated regression were used to assess the impact of procuring authority on schedule performance.

The findings suggest that the state and the national highway projects were no different in achieving financial closure. However, the administrative positioning of the procuring authorities had a significant impact on other schedule performance variables. The construction of the state highway projects started quickly after the financial closure compared to the national highway projects. Moreover, the state highway projects were not only planned to be implemented at a faster rate but they were actually implemented at a faster rate and had a lower time overrun.

Procuring authorities under the state governments, being closer to the project, are better placed to manage project risk than those under the national government.

The administrative distance of the procuring authority from the PPP project and its implication on performance has never been studied.

Transportation infrastructure projects are inevitably delayed due to delays in the completion of underground utility relocation. Unfamiliar location, difficulty in utility identification and use of ineffective coordination practices hamper timely completion of utility relocation works. This paper aims to develop integrated road information modeling (RIM) and geographic information system (GIS) models to assist early identification of utilities and effective coordination during utility relocation in infrastructure projects.

An ethnographic action-based case study research methodology was adopted in this paper. Two ongoing infrastructure projects with significant utility relocation delays are chosen as case studies and integrated RIM-GIS models are developed to assist utility relocation. To verify the applications of developed RIM-GIS models, a focus group discussion was conducted with 10 field experts from the considered case studies.

The application of the developed RIM-GIS models enabled 3D visualization of existing underground utilities and enabled identification of utility conflicts before the start of the construction. They also enabled facilitating coordination and reduce utility relocation delays. The evaluation of the developed models shows that the RIM-GIS model approach enabled early planning and coordination and facilitates effective management of utility relocations.

The current practices of using CAD and GIS for utility relocations are inadequate due to the difficulties in characterizing utilities and ineffective coordination practices. The proposed RIM-GIS approach can be adopted as a suitable alternative for effective management of utility relocations.

Several studies have contributed toward integrating BIM and GIS for the analysis of highway and utility infrastructure projects. Efforts on integrating RIM and GIS for the support and management of utility relocations in highway and utility infrastructure projects remain unexplored.

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).

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.

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.

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.

Involvement of lenders for PPP highway projects in India starts after the bid award. The post-award development phase of Toll and Annuity PPPs differ significantly in terms of potential risk assumed by lenders. This study aims to assess the impact of the transparency law on the post-award development phase of Toll and Annuity PPPs.

A unique dataset of 469 PPP highway projects implemented in India was used to conduct this empirical study. An OLS regression model was developed to assess the impact of the transparency law on the post-award development phase.

Enacting the transparency law increased the duration of the post-award development phase of Toll projects; however, its impact on Annuity projects was not significant. Moreover, Toll and Annuity projects with a longer post-award development phase had a shorter construction phase. The post-award development phase of the Toll projects was relatively more sensitive to technical, economic and location-specific variables than Annuity projects. Length of road stretch, duration of the concession period and individual income of end-users significantly impacted the duration of this phase of Toll projects.

Transparency law can improve risk mitigation of Toll projects during the post-award development phase.

The impact of transparency law on PPP projects has never been assessed. This study assesses its impact on the two forms of PPPs. It also highlights the determinants of this phase and how they differ for the two forms of PPPs.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

The purpose of this paper is to analyze walking activity and recent efforts at augmenting walkability conditions in the cities of Macau, Lisbon and Las Vegas.

The methodology consisted mostly of in-loco observations, pedestrian counts and extensive reviews of the literature, city plans and regulations.

The findings include the need to properly design, maintain and retrofit pedestrian facilities, while reducing safety conflicts among street users as well as the establishment and the nurturing of a culture of walking.

A fivefold international walkability research agenda with implications for other cities around the world is established: the value and the need for comparative studies and best practices; the need for urban design interventions; the cultivation of attractiveness and aesthetics; the implementation of safety, construction and maintenance criteria; and responsible funding programs.

This paper has twofold implications for stakeholders with direct responsibilities in the design, planning, building and maintenance of streets and public spaces, and for those who simply use those places at their own discretion.

A succinct set of recommendations include the need to augment endogeneity, the need to make cities for people and not for automobiles and commitment to resolving pedestrian safety concerns.

This paper discusses the factors affecting street vibrancy from both a stakeholder’s and a user’s perspective. The fundamental and inalienable right to walk is analyzed using the WPPFUS framework (walking levels, purposes, primacy of walking, facilities, unique features and safety concerns).

Public opinion regarding the police is generally positive, although there are number of individual and contextual variables that affect these views. Yet research examining public perceptions regarding state law enforcement agencies (particularly state patrols) is rare.

The paper utilizes a representative state‐wide sample of state residents and examine their perceptions of the Colorado State Patrol (CSP).

The paper finds positive views of the CSP overall and place particular emphasis on how individual, contextual, and contact‐related variables affect opinions.

The study focusses on one state patrol and is not generalizable to all state patrols and to other forms of state law enforcement.

The paper fills a void in the research on public opinion regarding state law enforcement and discuss similarities and differences in how they are viewed when compared to municipal agencies.

The purpose of this paper is to develop an approach to urban environment management through analysis of “urban emptiness” based on user-generated big data.

The research design is based on creating a theoretical model of urban emptiness as a multilayer phenomenon in the city space and then developing an applied approach to map its different types through user-generated and open big data from multiple online sources.

The paper provides a definition and a theoretical model of “urban emptiness” as a multilayer phenomenon integrated into the complexity of the city system and as a resource for sustainable urban development. The paper presents a methodological approach to analyse urban emptiness based on spontaneous user-generated geolocated open data emerging online. This approach is applied to the Russian city of St Petersburg with a demonstration of the data set formation based on multiple sources and an interpretation of the preliminary results.

The paper focuses on the under-researched phenomenon of urban emptiness, which leads to a certain speculation of propositions and lack of generalisability of the results. Therefore, the researchers are encouraged to further test the proposed propositions.

The paper describes urban emptiness as a resource in urban development and gives recommendations on how to account for it in sustainable urban environment management, in particular, in limiting urban sprawl.

This paper consolidates data-driven methods to create an integrated approach to urban environment management from an original standpoint – analysis of urban emptiness.

This study aims to consider active vision in low-visibility environments to reveal the factors of optical properties which affect visibility and to explore a method of obtaining different depths of fields by multimode imaging.Bad weather affects the driver’s visual range tremendously and thus has a serious impact on transport safety.

A new mechanism and a core algorithm for obtaining an excellent large field-depth image which can be used to aid safe driving is designed and implemented. In this mechanism, atmospheric extinction principle and field expansion system are researched as the basis, followed by image registration and fusion algorithm for the Infrared Extended Depth of Field (IR-EDOF) sensor.

The experimental results show that the idea we propose can work well to expand the field depth in a low-visibility road environment as a new aided safety-driving sensor.

The paper presents a new kind of active optical extension, as well as enhanced driving aids, which is an effective solution to the problem of weakening of visual ability. It is a practical engineering sensor scheme for safety driving in low-visibility road environments.

Hiring, selecting or assessing plant operatives' proficiency in the UK construction industry is an increasingly difficult task. A number of plant operator certification schemes are available to practitioners and each scheme trains to a myriad of bespoke standards. Consequently, the decision to employ a candidate often rests upon the employer's intuition and judgement and creates an unnecessary dilemma. To address this aforementioned problem, findings of research work that modelled plant operators' maintenance proficiency is presented. A UK nationwide survey was conducted to elicit plant professional opinion on what ‘training and educational’ (T&E) attributes constitute ‘good’ operator proficiency. The data was then arranged into three categories of operator maintenance proficiency: good, average and poor Multivariate Discriminant Analysis (MDA) was used on 75 percent of a simulated data set. The model utilised five T&E attributes, namely: duration of training provided, operator holder of alternative training card (not Certificate of Training Achievement (CTA) or Scottish/National Vocational Qualifications (S/NVQ)), operator's oral communication skills, operator's planning skills and operator's mechanical knowledge. Performance analysis revealed that model classification accuracy was 89.10 percent. The remaining 25 percent hold out sample was then modelled for validation purposes using the derived MDA model. Accuracy of the sub‐sample model was high at 77.60 percent whilst a paired sample T‐tests for the 75 percent and 25 percent sample data established that there was no significant statistical difference between actual and predicted classifications. Future work is proposed that aims to model other factors that influence operator maintenance proficiency; namely, work situational, motivational management and personal factors.

To address the issues of low localization and mapping accuracy, as well as map ghosting and drift, in indoor degraded environments using light detection and ranging-simultaneous localization and mapping (LiDAR SLAM), a real-time localization and mapping system integrating filtering and graph optimization theory is proposed. By incorporating filtering algorithms, the system effectively reduces localization errors and environmental noise. In addition, leveraging graph optimization theory, it optimizes the poses and positions throughout the SLAM process, further enhancing map accuracy and consistency. The purpose of this study resolves common problems such as map ghosting and drift, thereby achieving more precise real-time localization and mapping results.

The system consists of three main components: point cloud data preprocessing, tightly coupled inertial odometry based on filtering and backend pose graph optimization. First, point cloud data preprocessing uses the random sample consensus algorithm to segment the ground and extract ground model parameters, which are then used to construct ground constraint factors in backend optimization. Second, the frontend tightly coupled inertial odometry uses iterative error-state Kalman filtering, where the LiDAR odometry serves as observations and the inertial measurement unit preintegration results as predictions. By constructing a joint function, filtering fusion yields a more accurate LiDAR-inertial odometry. Finally, the backend incorporates graph optimization theory, introducing loop closure factors, ground constraint factors and odometry factors from frame-to-frame matching as constraints. This forms a factor graph that optimizes the map’s poses. The loop closure factor uses an improved scan-text-based loop closure detection algorithm for position recognition, reducing the rate of environmental misidentification.

A SLAM system integrating filtering and graph optimization technique has been proposed, demonstrating improvements of 35.3%, 37.6% and 40.8% in localization and mapping accuracy compared to ALOAM, lightweight and ground optimized lidar odometry and mapping and LiDAR inertial odometry via smoothing and mapping, respectively. The system exhibits enhanced robustness in challenging environments.

This study introduces a frontend laser-inertial odometry tightly coupled filtering method and a backend graph optimization method improved by loop closure detection. This approach demonstrates superior robustness in indoor localization and mapping accuracy.

This study seeks to focus on factors characterizing a pool of hyper‐growth firms, trying to gather insights on how the hyper‐growth firms achieve hyper‐growth.

A theoretical framework is proposed, borrowing well established approaches from strategic management and entrepreneurship. Subsequently, some explorative case studies are described and help in understanding how much of a firm's hyper‐growth can be explained by the resource endowment and entrepreneurial orientation (EO). A revised framework and some propositions are eventually suggested.

Hyper‐growth seems mainly explainable by extraordinary business opportunities and extraordinary access to resources (especially knowledge‐based). Entrepreneurship appears much more as a moderating variable, rather than an explanatory variable per se of hyper‐growth.

Although the case study approach is robustly motivated as a research step that can contribute to the process of theory building, the findings are not statistically generalizable.

It has long been argued that policy makers and governments, especially in Europe, should concentrate their efforts on those industries and environments where rapid growth firms are likely to be found. The paper offers a practical example on a suitable environment to facilitate such growth, where practices like mergers and acquisitions in foreign countries as well as venture capital and private equity financing play a role.

No research has been performed so far on the explicit link between resources, EO and hyper‐growth. Moreover, the research suggests a possible reconciliation of resource‐based view (RBV) and EO frameworks in explaining such a pattern.

Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.

First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.

The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.

Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.

In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.

The aim of this study was to determine the bona fide occupational requirements of general duty police work, and use this information to re‐validate a physical abilities test used in the police recruit selection process. A systematic random sample (n = 267) of general duty police officers completed two questionnaires: one concerning “average” duties, and one concerning the most physically demanding critical incident occurring in the 12 months prior. Of those completing the surveys, observational data were collected on every second officer, resulting in observational data collected for 121 officers, involving the recording of all physical activities and movement patterns observed throughout a ten hour shift. Data collected suggest there is a core of bona fide occupational requirements for general duty police work – walking, climbing stairs, manipulating objects, twisting/turning, pulling/pushing, running, bending, squatting and kneeling, and lifting and carrying. Many of these are involved in physical control of suspects, and can be tested using a well designed physical abilities test that simulates getting to the problem, controlling the problem, and removing the problem.

Information and communication technologies (ICTs) have featured strongly in all the recent national foresight studies. This paper documents some of the common trends that emerge from a comparison of these different studies and attempts to draw some strategic conclusions. The first section charts their relative importance. The main trends identified in the national foresight studies are then discussed by main technological areas in turn: software, components and peripherals, advanced telecommunications and telematics applications. Finally, the third part of the paper, strong interactions that ICTs have with other technological disciplines is considered, especially in relation to new materials, nanostructures and bioinformatics.

In the UK healthcare sector, funding and provision of public care facilities has been primarily the responsibility of government through the National Health Service (NHS). After decades of under-investment and consequent effects on the quality of care, new procurement routes are currently being used to improve the standards of facilities to meet the requirements of modern care services. This paper critically reviews these new procurement routes in terms of concepts and suitable areas of application, and examines how the principal procurement methods have evolved into the forms used for UK healthcare facilities. The paper outlines recommendations for further research in assessing the suitability or otherwise of these new procurement methods, both for construction projects generally and specifically for healthcare facilities.

Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to poor interpretability. These have exacerbated user distrust and further forestalled their widespread deployment in practical usage. This paper aims to develop explainable DL models for autonomous driving by jointly predicting potential driving actions with corresponding explanations. The explainable DL models can not only boost user trust in autonomy but also serve as a diagnostic approach to identify any model deficiencies or limitations during the system development phase.

This paper proposes an explainable end-to-end autonomous driving system based on “Transformer,” a state-of-the-art self-attention (SA) based model. The model maps visual features from images collected by onboard cameras to guide potential driving actions with corresponding explanations, and aims to achieve soft attention over the image’s global features.

The results demonstrate the efficacy of the proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with much lower computational cost on a public data set (BDD-OIA). From the ablation studies, the proposed SA module also outperforms other attention mechanisms in feature fusion and can generate meaningful representations for downstream prediction.

In the contexts of situational awareness and driver assistance, the proposed model can perform as a driving alarm system for both human-driven vehicles and autonomous vehicles because it is capable of quickly understanding/characterizing the environment and identifying any infeasible driving actions. In addition, the extra explanation head of the proposed model provides an extra channel for sanity checks to guarantee that the model learns the ideal causal relationships. This provision is critical in the development of autonomous systems.

Delays in utility shifting during road construction have broad ramifications. These delays not only lengthen the project's timeline but also raise expenses and cause problems with resource allocation. Thus, this study investigates the influence of delay in utility shifting for extension of time claims in road construction projects (RCPs) in Sri Lanka.

The study used a quantitative approach with three rounds of Delphi surveys to gather empirical data. Further, the probability impact assessment was used to carefully analyse the data and appraise the information gathered.

The findings initially revealed 33 causes of delays in utility shifting for extension of time claims in RCPs in Sri Lanka. Ultimately, 11 severe causes were identified based on their high probability and impact, concluding with 45 strategies that were assigned to overcoming those most severe causes of delay.

This study will contribute to the industry and theory by providing solutions to handle utility-shifting delays with the linkage of preventing time extension claims for RCPs in Sri Lanka. Further, there is a dearth of literature in the research area, both locally and globally. Thus, the findings of this research will provide a benchmark for further detailed studies in other countries as well.

As the technology evolves, the ways in which supply chain is coordinated improve. During a careful study on the intelligent wireless web (IWW) and its services for future applications, its great potentials for the implementation of a mobile real‐time system for supply chain coordination were realized. This paper seeks to introduce a development process for the IWW. In addition, it aims to explain the concept of mobile real‐time supply chain coordination, and propose and describe a practical model for this subject matter based on the most recent technologies including the IWW and agents.

Objectives were achieved through a thorough study on the IWW, agent technology, and the ways of applying them for mobile real‐time coordination in supply processes. As a method to conduct the research, first, the paper made out what the IWW services are and how one may develop them. Since mobile real‐time coordination is an absolutely innovative concept, the study prepared a comprehensive understanding of it and then, a practical framework was sketched and explained to implement the suggested system. The approach to this topic was a realistic one and an attempt was made to include all the prerequisites and details for the intended system.

In the course of the work, it was found that the IWW and other corresponding technologies have the greatest potentials ever available for the realization of a mobile real‐time supply chain coordination system and most of the chapters illustrate the claim.

Mobile real‐time coordination and its use in supply chains is something new. The development process for IWW proposed here is totally practicable and no other implementation scenario for the application of the IWW in mobile real‐time coordination has been suggested yet.

The purpose of this paper is to explore use of the Theory of Constraints (TOC) approach in addressing traffic congestion as the main impediment to improving utility of the land transportation systems. The observed element is a motorway segment with regulated access.

As the literature addressing this topic is rare or nonexistent, this study employs exploratory design, developing tentative theory through the generation of new ideas and assumptions forming grounded picture as a base for further investigation.

The study concludes that the most binding constraint is broken in the third out of the TOC’ five steps and that the improvement in the given segment of the land transportation system is possible to be achieved using this framework.

Although the merits of use of TOC have been considered in other than just production-planning environments, its application in land transportation systems has never been examined. This study presents one of the rare, if not the only attempt to make use of this unique theory that is systematised in the systems management paradigm within the realm of land transportation systems.

In 1742, the French chemist Melouin presented a paper to the French Royal Academy in which he described how a zinc coating could be applied to iron by dipping it into molten zinc. The first patents covering the ‘galvanizing’ process were taken out in France and England during the 1830's; the name being taken from that of the Italian physiologist Luigi Galvani who observed that electric current could be generated when dissimilar metals are brought into contact.

The global construction industry has a history of poor project success, with evident and frequent overruns in cost and schedule. This industry is a highly interconnected and complex system in which the components, i.e. suppliers, contractors, end-users, and stakeholders, are delicately linked to each other, the community, and the environment. Therefore, defining and measuring project success can be challenging for sponsors, contractors, and the public. To address this issue, this study develops and analyzes a more comprehensive set of success criteria for medium and large construction projects.

After reviewing the existing literature, this study identified 19 success criteria for medium and large construction projects, which were categorized into five groups. The fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) method was used to gain further insight into the interrelationships between these categories and explain the cause-and-effect relationships among them. Next, this study applied the modified logarithmic least squares method to determine the importance weight of these criteria using the fuzzy analytic hierarchy process.

28 project managers working in the construction industries in Australia and New Zealand participated in this study. Results suggest that “project efficiency” and “impacts on the project team” are cause criteria that affect “business success,” “impacts on stakeholders,” and “impacts on end-users.” Effective risk management emerged as the most crucial criterion in project efficiency, while customer satisfaction and return on investment are top criteria in “impacts on end-users” and “business success.”

Although numerous studies have been conducted on project success criteria, multicriteria analyses of success criteria are rare. This paper presents a comprehensive set of success criteria tailored to medium and large construction projects. The aim is to analyze their interrelationships and prioritize them thoroughly, which will aid practitioners in focusing on the most important criteria for achieving higher success rates.

Building information modelling (BIM) implementation is a major change management task, involving diversity of risk areas. The identification of the challenges and barriers is therefore an imperative precondition of this change process. This paper aims to diagnose UK's construction industry to develop a clear understanding about BIM adoption and to form an imperative step of consolidating collective movements towards wider BIM implementation and to provide strategies and recommendations for the UK construction industry for BIM implementation.

Through comprehensive literature review, the paper initially establishes BIM maturity concept, which paves the way for the analysis via qualitative and quantitative methods: interviews are carried out with high profile organisations in Finland to gauge the best practice before combining the results with the analysis of survey questionnaire amongst the major contractors in the UK.

The results are established in the form of the initial phase of a sound BIM implementation guidance at strategic and operational levels. The findings suggest three structured patterns to systematically tackle technology, process and people issues in BIM implementation. These are organisational culture, education and training, and information management. The outcome is expressed as a roadmap for the implementation of BIM in the UK entailing issues that require consideration for organisations to progress on the BIM maturity ladder.

It paves a solid foundation for organisations to make informed decisions in BIM adaptation within the overall organisation structure.

This research consolidates collective movements towards wider implementation of BIM in the UK and forms a base for developing a sound BIM strategy and guidance.

Firms compete using a variety of strategies. Typically they aim to provide something different, to be better, or simply cheaper. In the construction industry, the performance characteristics, quality and cost of the final delivered project will be the outcome of the interplay of capabilities of all the firms involved in the project. Consequently, in order to improve competitiveness, firms must pay attention to not only their own competitive advantage but to those of the firms, both up-stream and down-stream, on whom they depend in delivering their projects. For foreign constructors in China, those competitive considerations will be informed by circumstances different from home. How then do foreign constructors adapt themselves to the problem of sourcing competitively when located within a China-based supply chain? The paper aims to discuss these issues.

In this study 60 foreign enterprises operating within the Chinese construction sector were investigated by using a comparative case study approach.

Four generic procurement strategies were identified. First, firms adapt themselves in the search for optimal supply sources by replicating home-based suppliers, controlling local suppliers, or by remaining agile and non-aligned. Second, firms develop niche supply monopolies through market dominance, uniquely differentiated offerings, or by integration with down-stream providers. Third, firms find opportunities to bring in off-shore technology intensive procurements, where that technology is either protected, improved upon, or sold. Finally, firms also seek to transit to China as a procurement base in order to reduce local supply cost, service world-wide operations, or as part of a total strategy of China relocation.

The identification of this rich range of procurement approaches will be of interest to internationalization strategists, as well as to industry practitioners looking to find appropriate business models for off-shore operations.

In build-operate-transfer (BOT) transportation projects, design and construction phases are critical in terms of their effect on time and cost overruns. The purpose of this paper is to identify the role of risk factors affecting these phases and their significance level for BOT transportation projects.

Design and construction risks were determined and then validated by focus group discussions. Afterwards, an illustrated case study was presented to better understand the effects of determined risks in a BOT mega transportation project. As the last step of the study, the fuzzy analytical hierarchy process method was used to prioritize risk factors.

The prominent risk factors were found out as occupational accidents, integration between design and construction phases and excessive design variations.

Different kinds of BOT transportation projects in different countries might be executed very differently considering specific social, political, economic and other factors. However, the results of the study are important in terms of the specific lessons learned from the case study that can be used as a foundation for developing possible risk mitigation measures.

Though the risk management of BOT projects has been investigated frequently in the literature, there is a knowledge gap in the quantitative evaluation of risk significance specific to design and construction risks. The prioritization of determined risks with an associated case from a mega transportation project will contribute to the BOT project practitioners about possible challenges in design and construction phases in BOT mega transportation projects.

The purpose of this study is to identify building contractors’ views as to the need for, impact of and barriers to the use of project bank accounts (PBAs) in the UK construction industry.

A cross-sectional research study was carried out by the use of questionnaires to collect quantitative data. The population for the research was of construction professionals working as full-time employees for either main (Tier 1) or specialist contractors (Tiers 2-4).

Contractors consider PBAs as an effective initiative to encourage fair payment. There is uncertainty, however, as to whether PBAs will result in project cost savings. Head contractor resistance is perceived to be the biggest barrier to the use of PBAs. Adoption of PBAs in private-sector construction projects is likely to be slow.

The relative infancy of PBA usage in the construction industry means that responses are largely based on awareness as opposed to experience. Nevertheless, survey data represent a snapshot of contractors’ perceptions with respect to PBAs, which may be used as a benchmark against which to compare future studies to monitor how contractors’ views and expectations have changed with time.

The survey results will be of particular interest to those international jurisdictions who are considering, or who have already embarked on, the path of trialling and/or using PBAs in the public sector.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The objective of this paper is to explore the progress of current reforms to government in the English regions through administrative decentralisation aimed at delivering economic growth and greater accountability.

In addition to government documents the paper is informed by the views of a range of public and non‐governmental bodies on key aspects of the reforms, including the preparation of integrated regional strategies, accountability arrangements and institutional capacity.

While holding out the prospect of a more effective approach to regional policy making and delivery, implementation of the reforms carries risks for the delivery of key government policies. There is little evidence that they will assist in reversing disparities in economic growth rates between the English regions or tackle England's ingrained tradition of centralisation. There are also concerns that the prominence given to economic considerations is incompatible with delivering sustainable development.

Greater attention needs to be given to the coordination of national policies with a regional dimension and to the sub‐national institutional capacity required to both prepare and deliver integrated regional strategies.

Drawing on empirical evidence this paper offers insights into the administrative and policy tensions associated with ongoing reforms to sub‐national government in England.

The intention of this paper is to examine the perceptions of existing office occupiers in an effort to determine whether current property provision is meeting need and also to aid understanding of potential future requirements. The data which support the paper were gathered as part of a comprehensive study of the Birmingham office market undertaken by the authors. The objective of that study was to gain a better understanding and appreciation of occupier needs and preferences in terms of the type and location of commercial office accommodation. The study also included an analysis of occupiers’ responses to determine future demands and trends for such accommodation.

The authors will give an overview of the railway market, with a focus on Morocco, before seeing the challenges to face, before listing some benefits of rail links in terms of development, ecology, security, space management, etc. The authors will then give an overview of the development of BIM, its benefits, risks and issues. The purpose of this paper is to verify that the BIM can provide the railway with the tools to face some of its challenges and improve its productivity.

This paper is part of our research project on the integration of BIM in railway, which is the result of a partnership between Colas Rail Maroc and the ENSAK of the Ibn Tofail University of Kenitra. The objective of this paper is mainly to confirm that the integration of BIM with the railway, through a theoretical and practical study, can have positive impacts. To do this, our methodology consists in studying briefly the development of the railway, the need to improve the budgets and schedules of the projects, to increase the productivity, before showing the advantages of the BIM in the sector of the Architecture, Engineering and Construction (AEC). The study of feedback from railway projects (chosen for their date of completion – beyond 2014, their size, their geographical situation in several countries and for the availability of literature in a new field) will confirm the initial hypotheses. Among the projects studied will be a project that has been the subject of an article written by the authors of this paper. In the discussion of the results, the authors will focus on the benefits, risks and limitations of integrating BIM into the railway. In conclusion, the authors are laying the groundwork for future research in the field.

The cases study discussed in this paper and previous research confirms the hypotheses of the literature. The integration of BIM into railway projects can have several advantages: collaboration, time saving, cost optimization, prevention of conflicts between networks, construction before construction, optimization of facility management, improvement of the quality of works, prefabrication. They also allowed us to illustrate the risks (status and appropriation of the BIM model, lack of standardization of versions or software and lack of understanding of the basics of schedules and specifications) and limitations (lack of feedback, lack of adaptability and convergence of tools). These experiences have also shown that the use of BIM is not just a technological transition, but a revolution in the project management process, which requires several key success factors (participation of all, commitment, change management and adoption of the collaborative approach). Visualization, collaboration and conflict elimination are the three main chapters where the benefits of BIM can be organized. In fact, there is a lot of intersection between these chapters, but they have been chosen as the main ideas around which all the benefits can be better understood. Visualization primarily addresses the benefits to an individual and improving one’s personal understanding as a result of using BIM. The collaboration refers to the cooperative action of several team members, which is encouraged and facilitated by BIM. Conflict elimination mainly concerns project-related benefits, such as conflict reduction, waste, risks, costs and time. For railway infrastructure projects, the main purpose of using BIM is to improve the design integration process, internal project team communication and collision detection to eliminate risk of rehabilitation.

The application of the BIM process in railway infrastructure requires constant improvement. This concerns the development of libraries and the models available to all users in order to encourage the development of this methodology and, consequently, its use of information throughout the life cycle of an infrastructure work.

The case study of real projects incorporating BIM confirms the results of the literature review. The benefits of integrating BIM into rail projects are multiple and proven: cost control, decision support, avoids extra work due to design errors, improves detection of interface problems, improves planning of vision, help with prefabrication and facility management, etc. Finally, the BIM process is able to overcome delays in procedures slowing the development of the construction industry in many countries, especially in Morocco, because of the slowness of design (or downright bad design).

The integration of BIM into rail is becoming a global trend. This integration requires government decisions and a maturation of technology and tools. The authorities of some developed countries studied (Sweden, UK, France, Germany) in the railways, at different stages of implementation, are adopting BIM in the process of setting up new railway projects. This political impulse is still behind in southern countries, such as Morocco. The trend and the data collected indicate an adoption between 2020 and 2030 of BIM in all/some AEC projects in developed countries. This will have an impact on other countries that will soon be doing the same, especially in the railway sector to adopt the BIM.

As part of the realization of this paper, we proceeded to the implementation of an electrical substation as part of the project to build 40 electric traction substations built by Colas Rail on behalf of ONCF.

Until April 1995, Mark Springthorpe worked for Nottinghamshire County Council and was the Project Manager responsible for the implementation of County Contact, an electronic public information system which represents the largest commitment made by a single UK publicly funded organisation for a customer‐facing, interactive kiosk system. This article describes the experiences gained during this period and examines some of Nottinghamshire's plans for the future. Having spent time at Interactive Software Products Ltd, Mark now works for ITnet where he is the Senior Consultant for Local Government.