Urban Transportation Environment Research Articles

Data science basis and influencing factors for the evaluation of environmental safety perception in Macau parishes

In the context of rapid urbanization, accurately identifying the visual factors that influence environmental safety perception is crucial for improving urban transportation environments and enhancing pedestrian safety. With the increase in urban population density and traffic flow, optimizing urban environmental design to elevate residents’ sense of safety has become a key issue in urban planning and management. However, the existing studies face numerous challenges in conducting large-scale quantitative analysis of environmental safety perception in complex scenarios, such as difficulties in data acquisition and limitations in analytical methods. This study addresses these challenges by applying image semantic segmentation and object detection techniques to extract key visual elements from street view images, combined with manual scoring and deep learning methods, to construct a road safety perception dataset. Using a LightGBM model and the SHAP interpretation framework, in this study, we identify the critical visual factors influencing environmental safety perception. An empirical study was conducted in Macau, a modern city where Eastern and Western cultures intersect, and tourism thrives. The findings reveal that: ① The overall environmental safety perception in the eight parishes and surrounding roads of Macau is relatively high, with significant regional differences in safety perception scores around Macau’s parish roads; ② The proportions of buildings, sidewalks, roads, and trees in images are the four primary factors influencing environmental safety perception; ③ The proportions and quantities of visual elements interact with each other, and their reasonable distribution helps form clear spatial visibility and creates conducive activity spaces, thereby enhancing the perception of environmental safety. Through empirical analysis, this study uncovers the mechanisms by which visual elements in urban street scenes affect environmental safety perception, providing scientific evidence for urban planning and transportation environment improvement. The research holds theoretical significance and offers practical references for urban design and management, demonstrating broad application value.

Joint Estimation of Ride-Hailing Services (RHS) Adoption and Frequency: Assessing Impacts of Built Environment on Work and Discretionary Trips

In recent years, ride-hailing services (RHS) (also known as on-demand ride services), such as Uber, Ola, Lyft, Didi, etc., have transformed the urban transportation environment. RHS promises to promote sustainable urban mobility as it combines the flexibility of personal vehicles and the shared nature of public transport. In developing countries like India, research on these emerging RHS is still in its infancy, and the role of the built environment (BE) in influencing RHS choice and usage has not been explored. The current study aims to do so, for the city of Kolkata, India which has the highest modal share of ride-hailing amongst million-plus cities in India. Revealed preference (RP) household surveys were conducted, and information on 841 ride-hailing user trips was collected and a semi-ordered bivariate probit model was developed to estimate RHS adoption and usage frequency simultaneously. Model results show that BE variables like destination accessibility, bus stop density, road density, and population density significantly influence the adoption of RHS and use frequency of RHS with varied intensity for work and discretionary trips. Users residing in neighbourhoods with higher accessibility and better public transit connectivity are the least likely to adopt RHS and are also likely to be infrequent users. On the other hand, individuals living in high-density neighbourhoods are more likely to adopt RHS. Also, with increasing distances between origin and destination, commuters tend to adopt and use RHS frequently.

Research on the urban green transportation development level evaluation based on the triangular pythagorean fuzzy multiple attribute decision making

With the acceleration of urbanization and the significant improvement of people’s living standards, the motorization of urban transportation in China has developed rapidly, and the number of urban motor vehicles has sharply increased. This has also caused a series of problems such as increasingly severe urban road traffic congestion, increased traffic energy consumption, and atmospheric environmental pollution. Unprecedented social and environmental pressures have put forward higher requirements for the development model of urban transportation. Against the backdrop of increasingly severe conflicts between urban transportation and resource environment in China, green transportation with the goal of “meeting maximum demand with minimum consumption” has gradually received widespread attention from the academic community. The urban green transportation development level evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy sets (TPFSs) and investigate the MADM problems under TPFSs. Based on the traditional geometric BM (GBM) operator and generalized weighted GBM (GWGBM) operator, some triangular Pythagorean fuzzy operators are proposed: triangular Pythagorean fuzzy generalized GBM (TPFGGBM) operator and triangular Pythagorean fuzzy generalized WGBM (TPFGWGBM) operator. Accordingly, we have took advantage of these operators to develop some approaches to work out the triangular Pythagorean fuzzy MADM. Ultimately, a practical example for urban green transportation development level evaluation is took advantage of to validate the developed approach, and an influence analysis of the parameter on the final results is been presented to attest its availability and validity.

Spatial–Temporal Analysis of Vehicle Routing Problem from Online Car-Hailing Trajectories

With the advent of the information age and rapid population growth, the urban transportation environment is deteriorating. Travel-route planning is a key issue in modern sustainable transportation systems. When conducting route planning, identifying the spatiotemporal disparities between planned routes and the routes chosen by actual drivers, as well as their underlying reasons, is an important method for optimizing route planning. In this study, we explore the spatial–temporal differences between planned routes and actual routes by studying the popular roads which are avoided by drivers (denoted as: PRAD) from car-hailing trajectories. By applying an improved Hidden Markov Model (HMM) map-matching algorithm to the original trajectories, we obtain the Origin-Destination (OD) matrix of vehicle travel and its corresponding actual routes, as well as the planned routes generated by the A* routing algorithm. We utilize the Jaccard index to quantify the similarity between actual and planned routes for the same OD pairs. The causes of PRADs are detected and further analyzed from the perspective of traffic conditions. By analyzing ride-hailing trajectories provided by DiDi, we examine the route behavior of drivers in Wuhan city on weekdays and weekends and discuss the relationship between traffic conditions and PRADs. The results indicate that the average accuracy of GNSS trajectory point-to-road map-matching reaches 88.83%, which is approximately 12% higher than the accuracy achieved by the HMM map-matching method proposed by Hu et al. Furthermore, the analysis of PRAD causes reveals that PRADs occurring on weekdays account for approximately 65% and are significantly associated with traffic congestion and accidents during that time. The findings of this study provide insights for future research on sustainable transportation systems and contribute to the development of improved route-planning strategies.

3D urban transport environment

The paper investigates issues related to the solution of problems in the development of public transport infrastructure in urban agglomerations. The opportunities of further development of the existing typical city public transport infrastructure have been studied. The conclusion about the possibility of reforming the existing typical urban public transport infrastructure is drawn. It is proposed to use the available airspace together with the ground and underground public transport as a direction for the development of urban public transport infrastructure. The formation of an urban transport 3D environment is studied. It is shown that the joint application of all three urban transport environments will significantly expand the potential of urban public transport infrastructure. The possibility of using ultralight aircraft as an air vehicle is considered. It is proposed to use new types of aircraft as air vehicles. The prototype of an aircraft based on cylindrical vane propellers under the code name “Cyclolet” is described. Its flight technical characteristics are given. The conclusion about the possibility of using an aircraft of the “Cyclolet” type on the basis of cylindrical vane propellers as an air vehicle in the organization of permanent public transportation in urban agglomerations in the Russian Federation and abroad is drawn.

Parameters and criteria the construction of the Beijing expressway for urban planning

The purpose of the study is to investigate parameters and criteria the construction of the Beijing expressway for urban planning. The main methods of the study were statistical methods of studying the economic situation, analogy and generalization of the received information. Results. The assessment presented the method and scale of the construction of expressways, the method of construction of auxiliary roads, the method of designing entrance and exit ramps, research on the choice of overpasses for interchanges, as well as the impact of the construction of expressways on the entire urban transport environment. As part of the development of Beijing's transport infrastructure, it is necessary to coordinate the development of Beijing-Tianjin-Hebei transport. It continuing the reasonable construction of expressways. In this article, we presented main measures to improve the ring road that development of transport infrastructure in Beijing, Tianjin and Hebei, and active implementation of information systems in traffic management.

Barriers to the adoption of the mobility-as-a-service concept: The case of Istanbul, a large emerging metropolis

Megatrends such as urbanization, digitalization, and decarbonization have created the necessity for new and creative approaches to the urban transportation system. As a solution to the problems of the increasingly digitalized urban transportation environment, “Mobility-as-a-Service” (MaaS) was proposed as a new sustainable transportation concept in Helsinki in 2014. With the use of the MaaS concept, residents of a large emerging metropolis, such as Istanbul, Turkey, can be offered a fast, efficient, environment-friendly, and inexpensive way of travel. However, despite the significant benefits of MaaS, there are several factors that can hinder the adoption of MaaS. This paper aims to analyze these barriers and their contextual relationships with each other using Total Interpretive Structural Modeling (TISM) and Matrix-based-Multiplication-Applied-to-a-Classification (MICMAC) methods. The case study has been conducted on an expert group to explore which significant barriers might be encountered during the adoption of a MaaS system in Istanbul. This study also addresses how these barriers should be overcome, and the MaaS concept should be adopted in Istanbul. The results showed that the most significant barrier to adopting the MaaS concept in Istanbul are Laws, Regulations, and Guidelines that primarily include the legal nature of this mobility service. The least important barriers are found to be Customer Acceptance and Labor Shortage. Therefore, the case study results provided a unique perspective for emerging countries in terms of barriers to successful MaaS implementations and revealed significant differences from the developed countries.

БИОНИЧЕСКИЕ ПОДХОДЫ К РАЗВИТИЮ ТРАНСПОРТНЫХ СИСТЕМ ГОРОДОВ

The modern city is an extremely complex, self-developing organism, trying to make its transport system more sustainable. This becomes even more urgent in a pandemic. Therefore, especially in the largest cities, it is necessary to implement a policy on the bionic development of transport systems and the use of natural approaches to regulating transport demand, increasing the attractiveness of route passenger transport and its design, developing means of individual mobility and non-motorized transport. It should be noted that the problems of the urban transport system are very multifaceted and complex, they require coordination of the efforts of the public and private sectors of the economy, which is very fragmented, with different and conflicting views and goals, reacts sharply to changes in the urban (transport) environment and should be built on the basis of bionic approaches, obvious and understandable, aimed at the sustainable development of the urban transport system and the city as a whole.

Capturing gender-age thresholds disparities in built environment factors affecting injurious traffic crashes

Rapid changes in the urban transportation environment amplify the impact of built environment factors on traffic collisions. Understanding the risk of potential harmful crashes for different populations as a result of changes in built environment thresholds is important for policy development and resource allocation. However, research on generic processes to effectively determine built environment threshold risks is lacking. Basing on extreme gradient boosting and SHapley Additive exPlanations, we establish a generic workflow for visualizing the risk thresholds for injurious traffic crashes for different genders and ages and built environment factors. The empirical results for the Wuhan metropolitan area (WMA) show that 1) thresholds for important population-specific variables require attention: bicycle speed for female children; street lighting for male children, female children, and female adults; and restaurant density for male children, female adults, and female seniors. 2) Threshold deviation shows the largest differences for the female children group. 3) Threshold risk maps show that high thresholds risk areas for male, adult, and child are located in the southeast of the WMA and those for females and elderly are located in the northwest. The generic workflow and empirical findings can help transportation planners develop specific practical strategies based on gender and age.

Ethical problems of practical interaction between strong artificial intelligence and humans in the urban transport environment and legal proceedings

The first 20 years of the XXI century are characterized by progressive development of science and technology, for instance, artificial intelligence. Smart devices, which are based on artificial intelligence, have penetrated all spheres of modern society from education and unmanned vehicles to medical and legal proceedings. In the article, the authors analyzed the key ethical aspects of creation a strong artificial intelligence. The analysis of the interaction between artificial intelligence humans using examples of the use of semi-autonomous Tesla cars in the urban transport environment and implementation in civil proceedings is carried out. In the paper, the authors pay special attention to the need to provision of a legal regulation of interaction between society and strong artificial intelligence. In addition, there are facts proving the need for special legal control over the activities of developers in terms of compliance with the basic ethical principles of creating artificial intelligence.

Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey

The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options.

Respiratory Disease Occupational Biomonitoring Collaborative Project (ROBoCoP): A longitudinal pilot study and implementation research in the Parisian transport company

The ROBoCoP project is launched within the EU COST Action CA16113 “CliniMARK” aiming to increase the number of clinically validated biomarkers and focused on chronic obstructive pulmonary disease (COPD) biomarker development and validation. ROBoCoP encompasses two consecutive studies consisting of a pilot study followed by a field study. The pilot study is a longitudinal exposure assessment and biomarker study aiming at: 1-understanding the suitability of the candidate biomarkers in surveying populations at risk such as workers exposed to COPD causing agents; 2-determining the best sampling plan with respect to the half-life of the candidate biomarkers; 3-implementing and validating the sampling procedures and analytical methods; 4-selecting the best suitable biomarkers to be measured in the field. Each study participant is surveyed every day during the 6–8 h work-shifts for two consecutive weeks. The field study has an implementation research designe that enabled us to demonstrate the applicability of the standardized protocol for biomarker measurements in occupational settings while also assessing the biomarkers’ validity. ROBoCoP will focus on particulate matter (PM) exposure measurements, exposure biomarkers and a series of effect biomarkers, including markers of lipoperoxidation: 8-isoprostane, malondialdehyd in exhaled breath condensate (EBC) and urine, potential markers of nitrosative stress: NO2−, NO3− and formate anion in EBC; markers of DNA oxidation: 8-hydroxy-2’deoxyguanosine in EBC and urine, marker of genotoxicity: micronuclei in buccal cells, and oxidative potential in exhaled air (OPEA). OPEA appears particularly promising as a clinical biomarker for detecting COPD, and will be tested independently and as part of a biomarker panel. COPD diagnosis will be performed by an experienced occupational physician according to international diagnostic standards and confirmed by a pulmonologist.This research will include approximatively 300 underground subway workers randomly selected from the personnel registry of a large Parisian transport company. Underground subways are suggested as the most PM polluted urban transport environment. We believe this occupational exposure is relevant for biomonitoring of workers and early detection of respiratory diseases.

Assessment of the Impact of Public Transport Accessibility on the Value of Urban Residential Real Estate

Currently, analysis of the impact of public transport on real estate and its value is widely demanded in the world. The analysis is used to plan investments in public transport and the efficiency of public transport networks. In Russia, such studies have been carried out mainly in the framework of the evaluation of specific properties, which does not make it possible to macroanalyze the urban public transport environment and compare them with each other. The aim of the work is to study the influence of the proximity of public transport infrastructure on the cost of urban residential real estate, to determine the average value of such an impact for Yekaterinburg. In this study, we intend to confirm the hypothesis about different influence of the proximity of a public transport stop on the cost of housing, taking into account the different set of attributes that characterize it. The calculations were carried out using the analysis of the supply of the real estate market, carried out with the method of multiple regression, simultaneously with the geo-positioning of real estate units on the map to calculate the distance of each object to the nearest public transport stop of a certain type. Based on the results of the calculations, a global tendency towards a higher cost of the properties that are close to tram stops or metro stations in Yekaterinburg is confirmed, and the share of the value of a property generated by the proximity of a public transport stop was calculated. The authors confirmed the hypothesis about varying sensitivity of residential real estate to the proximity of public transport stops. Newer homes have lower sensitivity to proximity to public transport stops than older ones. The obtained empirical evidence of the influence of public transport infrastructure on the value of residential real estate demonstrates the most significant contribution to the value of a real estate object, the proximity to the metro station in Yekaterinburg (3.0 – 12.0%). The tram infrastructure showed a slightly lower impact on the total cost of the facility (3.2 – 8.8%). The revealed interdependencies make it possible to apply the obtained data to forecasting the growth of the taxable base for property tax during the construction of new transport lines.

A Study on Impact of Sustainable Transportation Systems Indian Cities Using For EDAS Methods

India is undergoing economic change. Cities now have better quality of life, and they are now crucial hubs for human existence. The increase in urbanization of Indian cities was facilitated by this influx of people. Prosperity and changing lifestyles brought about by a booming economy made reliance on private vehicles essential. The total demand for travel has accelerated along with population expansion and increased car ownership, but the supply side has lagged behind demand and there are numerous external variables associated to transportation, such as accidents, congestion, pollution, inequality, etc. Promoting and promoting sustainability is important in the contemporary urban transportation environment, sustainable transportation policies. These policies' principal goal is to change people's travel habits, or, in other words, to alter the travel environment. However, many of these rules' ramifications are unclear or complicated. As a result, it is critical that decision-makers are informed of the effects of such policies before adopting and putting them into practice. Models of travel demand can be used in this situation to forecast future travel demand under various policy scenarios. In order to analyze sustainable transportation strategies, this study analyses the possibilities of travel demand models already in use in India. The study discovered that the trip-based, four-step aggregate method used in India as the standard model system was nsufficient for studying sustainable transportation policy. An analysis of an alternative strategy known as activity-based travel demand modeling revealed that it could manage such policies better than traditional models and was useful in selecting the best combination of policies for particular circumstances. Since India has not yet created an operational activity-based travel demand modeling system, the study concludes by proposing a conceptual framework for an integrated activity-based demand model based on the needs identified within the review's framework. In accordance with people's current activity-travel behavior, it can be utilized to create modified and verified applications for existing travel demand models. The final result is done by using the EDAS method. Delhi is highest Value and Agra is lowest value.

Hybrid operations of human driving vehicles and automated vehicles with data-driven agent-based simulation

Automated vehicles (AVs) receive tremendous attention and achieve rapid development. It is foreseeable that hybrid operations of human driving vehicles and automated vehicles in the urban transportation environment will be a long-standing state. To investigate the influence of AVs on the hybrid ride-hailing market, data-driven agent-based modeling and simulation (D2ABMS) for large-scale transportation networks is proposed, in which human drivers, automated vehicles, and passengers form three types of agents. D2ABMS goes beyond existing approaches by employing data-driven multi-objective deep learning to learn ride-sourcing drivers' offline/online behavior. E mbedding is used to represent the hidden attributes of different classes of drivers. Ride-sourcing data collected from the city of Hangzhou, China, are used to train and validate the drivers' decision-making model. Hybrid operations of human driving vehicles and automated vehicles with D2ABMS are comprehensively tested in various scenarios. The results show that a small proportion of automated vehicles in the hybrid ride-hailing market can significantly reduce the average waiting time of passengers. Besides, compared to the human driving scenario, the total exhaust emissions and vehicle kilometers traveled can be reduced by 12.3% in the AVs scenario. The proposed D2ABMS system has the potential to help transportation planners and ride-hailing platforms to assess their policies and operations management strategies in the era of shared mobility and automated vehicles.

The monitoring results of accessibility of the transport environment for people with disabilities living in the city of Rivne

This work is the result of research carried out by an initiative group in the city of Rivne to assess the accessibility of the transport environment for people with disabilities. It was monitored of the rights of people with disabilities to access transport services to study the accessibility of vehicles for such people. Monitoring was carried out by means of questionnaire method, conduct survey, registration (observation) and expert evaluation. The questionnaire was attended by 100 people, among them: disabled people with diseases of the musculoskeletal system (20 people); visually impaired people (28 people); hearing impaired people (22 people); parents of children with cerebral palsy and autism (30 people). The monitoring results are presented in the form of graphs, tables and diagrams. Based on the expert assessment, a summary table of indicators with recommended for evaluating the accessibility of transport system elements was obtained. A list of priority measures was proposed to create an accessible urban transport environment. The results of the monitoring are the basis for further investigation of the problem of transportation of people with disabilities.

Causal effects between bus revenue vehicle-kilometers and bus ridership

To create a sustainable urban transportation environment, transportation authorities often implement incentive strategies to attract new public transportation users. Various studies have shown that increasing bus revenue vehicle-kilometers (BK) is a key factor for increasing bus ridership (BR). In this situation, BK affects BR. However, an increase in BR may lead to an increase in BK. Then, BR affects BK. The existence and directions of causal effects between BK and BR are the research questions addressed in this study. Since 2007, the Taichung City Government has been adding and adjusting bus routes to build a dense bus network. In 2011, it implemented a free fare bus policy. BR grew from ca. 2 million per month in 2007 to 10 million per month in 2015. Moreover, BK increased by ca. 3 times during that same period. This provides an opportunity to understand the causal effects between BK and BR. Extended convergent cross mapping (ECCM) can be used to assess the causal relationship between two variables without modelling. We adopted this method to distinguish the influences of BK and BR. According to the results, increasing BK attracted more public transit passengers during the period 2007 to 2010. However, there was no effect of BR on BK. After implementation of free fare bus policy in 2011, increases in BK led to increases in BR and increases in BR drove incremental growth of BK. The result was a virtuous cycle of mutual influence between BK and BR. In conclusion, increasing BK, such as route length or number of scheduled runs, can promote the usage of public transportation. Moreover, authorities can implement free fare bus policy to attract potential users and force incremental growth of BK.

Dynamic Multimodal Freight Routing Using a Co-Simulation Optimization Approach

The complexity and dynamics of multimodal freight transportation networks make the optimum routing of freight demand a challenging task. Route decision-making in a dynamical and complex urban multimodal transportation environment aims to minimize a certain objective cost relying on the accurate prediction of the traffic network states and the estimation of the route costs that are not readily available. The purpose of this paper is to develop a methodology to be used by a central coordinator who generates individual routing decisions for shippers by minimizing overall cost, assuming that all participating shippers send their demands to this central coordinator. We propose, analyze, and evaluate a multimodal freight routing system with hard vehicle availability and capacity constraints based on a hierarchical Co-Simulation Optimization (COSMO) approach. The COSMO approach consists of a simulation layer that provides traffic state predictions and cost estimations to an upper optimization layer that incorporates a load balancing methodology to speed up the convergence of the optimization algorithm. A simulation test bed consisting of a road traffic simulation and a rail simulation model for the Los Angeles/Long Beach Ports regional area is developed and is used to demonstrate the efficiency of the proposed approach.

Evaluation system for the sustainable development of urban transportation and ecological environment based on SVM

Evaluation system for the sustainable development of urban transportation and ecological environment based on SVM

Taxi, Ride-Sourcing and Ride-Sharing Services – Background Note by the Secretariat

Traditional taxi services – together with other providers – constitute a crucial part of the urban transportation environment. Over the last 10 years the emergence of ride-sourcing and ride-sharing platforms put under competitive pressure the activity of traditional taxis. While these new services provide clear benefits to consumers, they largely operate outside of any regulatory framework, raising new questions for regulators and competition law enforcers. This note looks at the rules that apply to traditional taxis which might need reviewing in light of digitalisation. Technological developments have affected several aspects of the pre-booked and street-hailing segment, perhaps removing the need for some common regulations. Regulators have the opportunity to review existing rules, softening (or abolishing) those whose original justifications are not valid anymore. However, technological development may not solve some of the market failures affecting the sector. Thus, while some changes to the regulation of traditional taxis would help to establish a level playing field and increase competition in the market, some rules might need to be applied to new providers as well. Competition between traditional taxis and new services has also been at the top of National Competition Authorities’ (NCA) agenda. These have exerted a significant effort to enrich the discussion thorough their advocacy activity. A common point of view emerges from their work, as all the NCAs highlight the priority of recognising – and not banning – the new providers in order to increase competition in the market. The paper also analyses the role of new providers from a competition law enforcement perspective. Although competition law cases regarding ride-sourcing and ride-sharing services are very limited in number, growing volume of such services, their two-sided nature and issues related to big data pose potential challenges to competition authorities. This note discusses some of the issues NCAs might face in the future.