Road Distance Research Articles

An Evaluation of Nutritional Security Impacts of Climate-Smart Adaptation Practices among Smallholder Farmers of Eastern Oromia, Ethiopia

Climate impact mitigation through improved agricultural practices is one means by which agricultural productivity increases to meet the growing food demands in the world. This study evaluated the impacts of climate-smart Practices on rural households’ nutrition security. The study used both primary and secondary data sources. Primary data was collected from sample respondents in the 2020/21 production year. Descriptive statistics and econometric models were employed for data analysis. Multinomial logit result indicated that the probability of adopting climate-smart agricultural practices is influenced by the education level of the head, extension contact, livestock holding, membership coop, market information, advice on land management, climate change information, farmers training, climate change perception, and weather road distance. The result from GPS estimation indicated that treatment level two the number of climate-smart practices increases household nutritional status by16%. Likewise, treatment level three and four of the number of climate-smart practices increases the household level nutritional status by 37% and 76% respectively over that of treatment level one of the climate-smart practices and is significant at a 1% statistical probability level. This study has found evidence that the adoption of climate-smart on the households’ nutrition security status. Therefore, the result of this study would be expected to significantly contribute as policy and strategic inputs for policymakers in designing rural livelihood improvement policies and to the beneficiary in enhancing their welfare and living standard.

Advanced algorithms for optimal meeting points in road networks

AbstractAn optimal meeting point query is used to determine a location in a spatial region to build a new facility that minimizes the sum of the (weighted) road distances from all clients. This problem has been studied in previous work with the assumption that all clients and facilities reside in Euclidean space or along road networks. However, due to the limitations of geographic information system technologies, it is difficult to return an exact geographic location to answer the optimal meeting point query based on a set of arbitrary coordinates. This issue results in various problems, such as positioning and measurement errors, in practical use. In this paper, it is aimed to identify the optimal meeting point in road networks for clients and facilities residing in non‐Euclidean spaces. Two efficient heuristic solutions are proposed based on approximate and adaptive query processing techniques by using randomized adaptive search and random direction search methods, respectively, to rapidly converge to the global optimum in the geographic coordinate system. Extensive experiments based on real datasets demonstrate that our proposed method achieves a 32.11% improvement over the state‐of‐the‐art approach.

Ultra-Long Transfers for Endovascular Thrombectomy-Mission Impossible?: The Australia-New Zealand Experience.

Endovascular thrombectomy (EVT) access in remote areas is limited. Preliminary data suggest that long distance transfers for EVT may be beneficial; however, the magnitude and best imaging strategy at the referring center remains uncertain. We hypothesized that patients transferred >300 miles would benefit from EVT, achieving rates of functional independence (modified Rankin Scale [mRS] score of 0-2) at 3 months similar to those patients treated at the comprehensive stroke center in the randomized EVT extended window trials and that the selection of patients with computed tomography perfusion (CTP) at the referring site would be associated with ordinal shift toward better outcomes on the mRS. This is a retrospective analysis of patients transferred from 31 referring hospitals >300 miles (measured by the most direct road distance) to 9 comprehensive stroke centers in Australia and New Zealand for EVT consideration (April 2016 through May 2021). There were 131 patients; the median age was 64 [53-74] years and the median baseline National Institutes of Health Stroke Scale score was 16 [12-22]. At baseline, 79 patients (60.3%) had noncontrast CT+CT angiography, 52 (39.7%) also had CTP. At the comprehensive stroke center, 114 (87%) patients underwent cerebral angiography, and 96 (73.3%) proceeded to EVT. At 3 months, 62 patients (48.4%) had an mRS score of 0 to 2 and 81 (63.3%) mRS score of 0 to 3. CTP selection at the referring site was not associated with better ordinal scores on the mRS at 3 months (mRS median of 2 [1-3] versus 3 [1-6] in the patients selected with noncontrast CT+CT angiography, P=0.1). Nevertheless, patients selected with CTP were less likely to have an mRS score of 5 to 6 (odds ratio 0.03 [0.01-0.19]; P<0.01). In selected patients transferred >300 miles, there was a benefit for EVT, with outcomes similar to those treated in the comprehensive stroke center in the EVT extended window trials. Remote hospital CTP selection was not associated with ordinal mRS improvement, but was associated with fewer very poor 3-month outcomes.

A Framework to Assess the Correlation between Transportation Infrastructure Access and Economics: Evidence from Iran

One of the most important impacts of access to transportation infrastructure is the economic and social well-being of residents. However, it is important to know, how much of an impact it has? Which of the access routes-road, rail, or air-has more impact? What methods can be used to assess this effect? Does this effect vary from country to country? This study attempts to provide a framework to examine the correlation between the access of a country’s cities (to various types of rail, air, and road transportation networks) and the economic and social parameters of its inhabitants. For this purpose, the connection of the city to the rail network was calculated by taking into account the distance in time between the city and the nearest station. A city’s road access is calculated by finding the average road distance of a city to other cities in that country. A city’s access to air traffic is calculated based on the weekly flights of that city’s airport (if that city has an airport). To evaluate the performance of the proposed framework, a case study is conducted in Iran. The results of the case study show that the access of cities to transportation networks strongly influences economic development and population size in Iran. Pearson’s correlation coefficients between transport infrastructure and economic growth and population size are 0.641 and 0.725, respectively. It was also found that among the transport networks, road transport is more correlated with economic development and unemployment rate of Iranian cities compared to other transport modes.

Near Real-Time Spatial and Temporal Distribution of Traffic Emissions in Bangkok Using Google Maps Application Program Interface

Traffic information from the distance matrix application program interface (API), which is a part of the Google Maps API service, was used to develop a near real-time traffic emissions inventory in Bangkok. The information provided includes distance and traveling time, which can be used to develop an Underwood traffic model for traffic volume estimation. The speed-dependent emission factors, road distance and traffic volume, which were estimated based on the distance matrix API, and fleet composition, were used to estimate carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOx) and particulate matter (PM) emissions from eight types of vehicles, including passenger cars, motorcycles, pick-ups, taxis, vans, buses, tuk-tuks and trucks. On the weekend, in Bangkok, the traffic released 190 tons/day of CO, 34 tons/day of HC, 55 tons/day of NOx and 3 tons/day of PM. The traffic emissions on a weekday in Bangkok were 209 tons/day of CO, 39 tons/day of HC, 61 tons/day of NOx and 4 tons/day of PM. The spatial and temporal distribution of traffic emissions demonstrate that the area of highest traffic emissions was the center of Bangkok. Therefore, the Google Map API service can be used to develop near real-time traffic emission inventories.

Research on spatiotemporal variation characteristics of soundscapes in a newly established suburban forest park

Passive acoustic monitoring has developed rapidly as a tool for ecological assessments, and the use of acoustic indices to assess biodiversity in urban forests promises to be a low-cost and efficient analytical approach. However, the accuracy of using acoustic indices to characterize biodiversity may be compromised by excessive human interference. The acoustic complexity index (ACI) and normalized difference soundscape index (NDSI) were chosen to determine their application value, and explore the spatiotemporal patterns of change in the soundscape of a newly established suburban forest park in China. To understand the influence of drivers such as different sound source types, road distance, and vegetation structure on the soundscape, the Eastern Suburb Forest Park was selected as the study area, and 55 recording points (200 m intervals, 5 × 11 grids) were set up using a systematic grid. Passive acoustic monitoring was performed for four consecutive days in each season, and the spatiotemporal variation of the soundscape was visualized based on indices interpolation. The results showed that when using ACI and NDSI to rapidly assess biodiversity in urban forest environments, attention needs to be paid to the implications of seasonal fluctuations on indices. The temporal variation of the soundscape was closely related to the natural rhythms and vocal activity intensity of organisms. Distance to a nearby main road, distance to water, and structural complexity of vegetation were key factors influencing spatial variation. The findings support the use of acoustic methods to assess the characteristics of soundscapes in human-built urban forests. Soundscape mapping visualizes hotspots and moments of ecoacoustic activity, and has great potential for development in the conservation and management of suburban forest soundscapes.

A Review on Landslide Susceptibility Mapping in Malaysia: Recent Trend and Approaches

The accelerating economic growth has assisted rapid urban development and expansion of construction sites into the landslide-vulnerable zones in Malaysia. Thus landslide susceptibility mapping has now become an important part of project designing work for landslide zone areas. There are several models that are used for susceptibility mapping, especially in the peninsular region. Every model has its own set of selected computing variables and characteristics to generate a map. To date, there is no single method applicable to assess and predict all landslides, as there are variations of geomorphological conditions set by the nature. This paper has reviewed recent research publications on landslide susceptibility mapping in Malaysia. Results show that there are 16 models that are being used to describe landslide risk mapping and among them, the Fuzzy model, Neural Network combined with Fuzzy logic, evidential belief function model, probability analysis (e.g. Weights-of-Evidence, and regression), and Support Vector Machine models are proved to be effective even in the areas with limited information. It is observed that most of the susceptible models use curvature, slope angles, distance from drainage, altitude, slope gradient, road distance, aspects as variable factors, and prolonged rainfall as the prime triggering factors. Furthermore, it is observed that the maximum number of research has been conducted in Cameron Highlands (28%) and Penang (20%), because of their high frequencies of landslide occurring and vulnerabilities. Sabah and Sarawak are covered by a negligible number of susceptibility research. Further, a comparison study between the selected models presents the limitations of each model and their benefits and some suggestions are also made based on the author's recommendations works.

Changes in retail food environments around schools over 12 years in Flanders, Belgium

Abstract Background Food environments influence food preferences, in particular among children. Besides their homes, children spend most of their time in and around the school. This study mapped changes in retail food environments around primary and secondary schools in Flanders between 2008 and 2020. In addition, associations between those indicators and children's weight status were assessed. Methods The food environment near primary and secondary schools was mapped using three spatial indicators: 1) The density of different types of food retailers within 1000m road distance from the school entrance, 2) the percentage of schools with at least one food retailer of a certain type within 1000m road distance from the entrance, and 3) the median walking distance from the school entrance to the nearest food retailer of a certain type. Associations between the density of convenience stores, as well as fast food outlets around the schools and the weight status of the schools’ children were assessed using generalized linear models adjusted for level of urbanization, socio-economic status of children at school level and sex. Results Food environments near schools in Flanders were found to be unhealthy, with a significant increase in fast-food outlets and convenience stores between 2008 and 2020. Food environments near schools with a higher proportion of children from a poor socio-economic background were found more unhealthy than those near schools with a lower proportion of such children, regardless of the urbanization level. A significant positive association was found between the density of fast food outlets as well as convenience stores around primary schools and the weight status of children aged &amp;lt;6 years and 6-12 years. Conclusions Food environments around schools in Flanders became more unhealthy over time and were associated with children's weight status. The government therefor has the responsibility to create healthy food environments near schools to protect children's health. Key messages • The food environment near schools became more unhealthy between 2008 and 2020. • The food environment near schools was associated with younger children's weight status.

Effects of computed distances, and other determinant factors on place of child delivery in Magadi Ward, Kenya

The choice of place of delivery is still debatable in most sub-Saharan African societies’ especially pastoral communities. The decision on whether to deliver at a health facility or at home varies across households. This study sought to evaluate the effects of computed distance, demographic and socio-economic factors on the place of child delivery in rural Magadi, Kenya. The integration of both spatial and statistical techniques was adopted. Distances (straight-line distance, road network distance to the nearest health facility and primary facility) were computed using tools in the Network Analyst toolbox. Computed distances of 246 sampled households together with demographic and socioeconomic factors were further analysed using univariate and multivariate logistic regression. The findings showed that calculated road network distance to the primary facility was a determinant of access and use of place of delivery both for the adjusted and the unadjusted odds. Women aged 20 years or below, having more children, secondary education or above and those who are unmarried are more likely to deliver at health facility. Receiving 1 or 2 childbirth services from a health facility, being aware of a private actor who set up the health facility and involvement of the spouse in the decision-making of place of birth are also linked to the use of health facility for child delivery. Deliveries at home were related to family monthly income level, family occupation, opinion on health facility location and being aged between 21 – 30 years. It was found that though computed road distance to the primary facility was the dominant factor, other variables such as level of education, parity, awareness of local actors, other childbirth services received prior to child delivery and marital status determined whether a woman would access and use health facilities for child delivery.

Non-linear effects of heterogeneous environmental regulations on industrial relocation: Do compliance costs work?

Reasonably designing environmental regulations for compliance-driven industrial relocation can avoid new pollution havens. The Cournot duopoly model simulates that the necessary condition for industrial relocation is differentiated market costs. Then, based on the province-industrial data of six Chinese pollution-intensive industries during 2005–2019, this study applies spatial Durbin model to explore the non-linear effects of heterogeneous environmental regulations on industrial relocation. Results shown that command-and-control environmental regulation manifests a U-shaped curve with local industrial relocation, with inverted U-shaped spillover effect radiating a road distance of 650 km, and both internal and external costs play the mediating roles; Market incentive environmental regulation has inverted U-shaped curves with industrial relocation in local and neighboring regions, it creates dual costs and works well in both short and long terms, which is the most potential regulatory tool to avoid pollution relocation accompanying industrial relocation; Voluntary environmental regulation exhibits inverted U-shaped relationships with industrial relocation in direct and spillover effects, and works through increased external cost rather than internal cost. Its spatial spillover radiates the longest 1250 km due to rapid spread of public opinions, but this effect takes more than 3 years to be effective.

Studying a matching method combining distance proximity and buffer constraints

Abstract In order to achieve fast matching of global navigation satellite system (GNSS) track data and vector road network data, a rough-to-fine matching method combining distance proximity and buffer constraints is studied. The GNSS track data is preprocessed: A rasterisation method is used to eliminate the low-quality track data and obtain the binary graph; then, the road centrelines are obtained by a skeleton extraction method; the thinning data is converted into line segments or closed lines starting from nodes by the boundary tracking method, which is stored in the vector form. Finally, the boundary tracking method is used to convert the thinning data into closed lines and store them in the vector form. A two-layer rough-to-fine matching strategy is applied: First, the changing state of the road arc is determined according to the rough matching strategy of road segment distance. Next, according to the buffer constraint criterion, a rectangular or circular buffer is selected to achieve precise matching of road network data. The results show that the proposed method has good matching effect, which is especially suitable for working with more GNSS track data.

Access to Alcohol Outlets From Home and Work in Sweden: Longitudinal Associations With Problem Drinking.

The association of proximity of alcohol outlets to the workplace with problem drinking has not been previously studied. We examined longitudinal associations of living and working in proximity to alcohol outlets with problem drinking. The data consisted of 13,306 employed respondents to the Swedish Longitudinal Occupational Survey of Health between 2012 and 2018. Road distances from the respondents' home and workplace to the nearest liquor outlet, beer outlet, and bar were calculated by Statistics Sweden. We used distance variables both as categorized, to indicate changes in distance, and as continuous variables. Self-reported problem drinking was assessed using modified Cut-Annoyed-Guilty-Eye (CAGE) questions. Binomial logistic regression with generalized estimating equation was used to examine the associations. A decrease (vs. remained unchanged) in the distance from home to a liquor outlet was associated with a higher likelihood of problem drinking (odds ratio = 1.21, 95% confidence interval [1.02, 1.45]). A protective association for problem drinking was observed when the distance from home to a beer outlet increased (vs. remained unchanged) (0.65 [0.44, 0.95]). A decrease (vs. remained unchanged) in the distance from work to a bar was also associated with a higher likelihood of problem drinking (1.37 [1.00, 1.88]). The likelihood of problem drinking was increased also per 1-km decrease in distance from home to liquor outlets (1.01 [1.00, 1.02]), risk estimates being higher for women than for men. Alcohol outlet proximity to the workplace could be an additional determinant of harmful alcohol consumption behavior. Reducing the number of on- and off-premise alcohol outlets could reduce the level of harmful alcohol consumption.

Does cycling to work benefit mental health? A natural experiment using linked administrative data.

ObjectivesWe spend an increasing part of our daily lives commuting. Observational studies have shown commuting by bicycle improves subjective well-being. This study uses a quasi-experimental approach and an objective measure of mental health taken from linked administrative data to ask “does cycling to work benefit mental health?” ApproachPrevious studies have tended to use cross-sectional survey data which have small sample sizes and self-reported health measures that are subject to reporting bias. The potential for unmeasured confounding and reverse causation also weakens any conclusions. Our study links the Scottish population census with NHS Prescribing Information System records for data on commuting in Edinburgh and Glasgow and mental health prescriptions, respectively. Although there are complexities in determining causal effects from observational data, we employ an instrumental variable approach to address this using road distance from home to nearest cycle path as an instrument. ResultsApproximately 400,000 people aged 16-74 living and working in the City of Edinburgh and Glasgow City council areas as at the 2011 census were included in our study. Of those, 1.85% of commuters in Glasgow and 4.8% of commuters in Edinburgh cycled to work. Amongst cyclists 9% had a prescription for mental health compared to 14% amongst non-cyclists. More than 50% of commutes in both cities are less than 5km. Using the instrumental variable in a bivariate probit model we estimate an average treatment effect of -16.1% (95% confidence interval: -15.1% to -17.1%) in mental health prescriptions amongst those who cycle to work compared to those who use other forms of transport. ConclusionThis work confirms the benefit of cycling to work for mental health and provides further evidence in support of the promotion of active travel to encourage commuters travelling shorter distances to shift to cycling to work.

IMPLEMENTATION OF THE SIMPLE MULTI-ATTRIBUTE RATING TECHNIQUE (SMART) METHOD FOR SUPPORT SELECTION OF COFFEE SHOP BUSINESS LOCATION

In choosing a business location, a computerized system is needed and can provide effective and accurate information about the business location. Many young entrepreneurs today are starting to try to manage and create a coffee shop business, so the competition in coffee shops is very high. The high competition in the coffee shop business makes it difficult for prospective tenants to determine the most appropriate location to establish a place of business according to their desired needs. In addition, the selection of business locations cannot be chosen arbitrarily because it can cause a shortage of visitors which results in the coffee shop being deserted. Therefore, choosing a strategic place using several criteria is needed to support business success. There are twelve criteria that will be used, the criteria are rental price, number of competitors, parking area, cleanliness, building area, supporting business, road distance, road access, population density, pedestrian traffic, population income, and the center of the crowd. This study aims to help prospective tenants who will open a place of business in the city of Bandar Lampung. The method used in this research is the Simple Multi Attribute Rating Technique (SMART). The SMART method is used because it is a multi-attribute decision-making method where the alternative consists of a set of criteria, with weights to determine how important one criterion is with another. The results obtained in this study are a decision support system for choosing a strategic coffee shop business location, making it easier for prospective tenants to choose the right business location for the development of a coffee shop business in Bandar Lampung.

Finding Second Hierarchy Points for Cooperative Multi-Vehicles Delivery Route with P-median and Voronoi Diagram in Various Driving Area

With the recent development of autonomous driving technology, various unmanned vehicles such as serving robots, mobile delivery robots, and drones have been developed. However, each robot has a different driving area, so it is necessary to find cooperative route for optimal unmanned delivery. In this paper, a cooperative scenario of an autonomous courier vehicle and five mobile delivery vehicles perform unmanned delivery tasks. The courier vehicle moves from a warehouse to the second hierarchy point, and drops off the five mobile delivery vehicles in order to transport goods to the doorstep of the destinations. We define the second hierarchy point by using the P-Median method and the Voronoi diagram method, and compare the results of each method using real map data. The points using P-Median are calculated based on the actual road distance and have shorter average moving distance than the Voronoi diagram method. The Voronoi diagram uses the Euclidian distance based on location information, which defines the second hierarchy point faster than the P-Median method. By comparing the results, we consider the Voronoi diagram method have capability in the cooperative multi-vehicle delivery route problem. The result of this paper have potential to be used in rough and remote areas where road information and infrastructure are lacking.

Estimated cost of transporting construction and demolition waste in Recife, Pernambuco, Brazil

The construction sector has grown significantly in the last decade, also expanding the environmental damage inherent to the activity, especially the production of solid waste, with an annual estimate of over 760,000 tons for the municipality of Recife. Proper disposal of construction and demolition waste (RCD) should be technically and economically feasible, where the collection and disposal process results in an additional cost for any building work, and transportation is a relevant stage of this, where its value is determined by variables such as distance, traffic and access road conditions. This study aims to analyze the variation in the cost of transportation of RCD in Recife, starting with a survey of the destination points on the CPRH page, delimiting three coverage areas, and calculating the minimum mean transport distances (DMT). and maximum in the demarcated regions, being observed the variations of the DMTs in each area, through the Tukey test. As a price reference, the SINAPI table was used, calculating the minimum and maximum costs for each area. Finally, a considerable variation in the minimum cost was observed in one of the areas, while no relevant disparities in the maximum price were detected.

The extent and magnitude of edge effects on woody vegetation in road‐bisected treed peatlands in boreal Alberta, Canada

AbstractTreed peatlands can exhibit dramatic shifts in woody plant cover when they are bisected by roads, a product of change in the flow of surface and subsurface water; however, the edge effects that roads have on overstory cover remain poorly understood. We examined how road and environmental conditions influence woody cover in treed fens in northeastern Alberta, Canada. We used generalized linear mixed models to explain variation in cover as measured using airborne laser scanning (ALS) data obtained for 48 road‐bisected fens. Over half of the study fens had &gt;10% differences in canopy cover between the upstream and downstream sides. Variation in cover was best explained by a complex interaction between road side, distance, and type, as well as distance to upland forest and open water, in both rich and poor treed fens. Substrate texture (fine vs. coarse) further explained cover in rich fens. Gravel roads appeared to have the most dramatic effect on cover adjacent to roads (0–20 m) in both fen types, with differences persisting beyond 100 m. In fens bisected by gravel and paved roads, differences in cover between road sides tended to be ameliorated within 200 m, except for unimproved roads where changes were more linear. This study demonstrates the complexity of landscape conditions under which roads built through peatlands can cause structural changes in woody cover and the usefulness of ALS data for studying this phenomenon.

Which Are the Best Site and Stand Conditions for Silver Fir (Abies alba Mill.) Located in the Carpathian Mountains?

Silver fir (Abies alba Mill.) is one of the most valuable and productive tree species across European mountains, that accomplish multiple economic, protective and ecologic functions. Alongside spruce (Picea abies (L.) Karst) and beech (Fagus sylvatica L.), silver fir is a characteristic species for the Romanian Carpathians. Although silver fir tree is recommended for the diversification of forests in order to increase the resistance to climate change, it is very sensitive to climatic excesses, especially those that proceed rapidly. Therefore, the aim of this study is to investigate both the environmental conditions and stand characteristics of fir from five mountain ranges of the Romanian Carpathians. The study is based on data recorded over a period of 10 years (1990–2000). As such, a total of 77,251 stands that occupy 211,954 hectares have been investigated in regard to silver fir behaviour. MATLAB scripts were used for analysing consistent data volumes as well as the impact of eight factors on the silver fir productivity (altitude, field aspect, field slope, soil type, participation percentage, road distance, structure and consistency). Our analysis has revealed that higher silver fir productivity is found at altitudes of up to 1200 m, on mid and upper slopes, on NW field aspects, on eutric cambisols and dystric cambisols, with a 10–20% participation in stand composition and in relatively-even aged stands with a full consistency. This study offers valuable insights for forest managers that require comprehensive information in adopting effective strategies to enhance forest resilience under climate change.

Influence of Short and Medium Distance Road Transport on the Acute Phase Proteins in Horses

Horse transport is a common practice and is usually associated as a cause of stress in animals, with consequences for their well-being. There are several of evidence that stress can increase an acute phase response. The aim of this study was to verify whether the road transport of horses over distances of 50 and 300 kilometers induces changes in the values of acute phase proteins. To do this, the serum SDS-PAGE was performed and the bands obtained were identified by mass spectrometry (MALDI-TOF). The blood samples were collected in tubes without anticoagulant to obtain the serum, and the evaluations occurred before the road transportation (T0), immediately after the journey (T1), six hours later (T2), and 24 hours (T3), 48 hours (T4), 72 hours (T5), 96 hours (T6), 120 hours (T7) and 144 hours (T8) after the end of the trip. All analyzes were performed using the Minitab 17 statistical package, and significance was considered when P<0.05. The APPs found through SDS-PAGE and properly identified were α2-macroglobulin, ceruloplasmin, transferrin, albumin, α1-antitrypsin, haptoglobin, apolipoprotein alpha 1, and α1-acid glycoprotein. No differences were observed in the concentration values between 50 and 300 km or between the moments after each route. The distances covered with the horses were not challenging enough to provoke an acute phase response reflected in changes in APPs.

Autonomous vehicle impact on improving road network vulnerability

PurposeThis study first presents a method to identify the parameters increasing road vulnerability on a macroscopic road network model. The second part exploresthe effect size difference of the analyzed attributes on network vulnerability through the implementation of different autonomous vehicles (AVs) penetrations and automation levels.MethodsThe road traffic network of Budapest, Hungary on PTV VISUM is studied by adopting a passenger car unit factor procedure to simulate the effect of AVs on road saturation. Five link parameters were used: length, distance from the centre, speed, number of lanes, and number of connectors. Network vulnerability was studied by simulating a combination of road elimination process with different passenger car unit values for AVs.ResultsThe analysis found the number of road lanes is the most significant parameter, affecting the link criticality; followed by road length and distance from the centre. The analysis of four AV scenarios with different AV penetration and level of automation showed huge effect differences ranging from 3.50% for a simple AV automation level with low AV percentage to as large to 28.53% for a fully automated fleet.ConclusionsAV implementation has proved efficient in reducing the amount of travel delays in the case of road failure. Finally, it was found that the number of lanes remained the most significant influencing parameter on travel delay. The main question is to discover the effect size difference of the analyzed attributes on network vulnerability through the implementation of different AVs penetrations and automation levels.