Intercity Roads Research Articles

Factors Affecting Crash Severity on Two Major Intercity Roads in Western Sri Lanka: A Random Parameter Logit Approach

Although Sri Lanka has significant traffic-related fatalities and injuries, only a limited number of studies have focused on the road safety challenge. This study applies the random parameters logit model to police reported crash data to identify the factors contributing to the severity of crashes in Sri Lanka. We find that severe crashes are associated with roadways that are unlit, in rural areas and have traffic controls, dual purpose vehicles, heavy vehicles, head-on and hit pedestrian crashes, drivers who are unlicensed, and casualties who are older (65 years and older) and do not use safety equipment, while minor crashes are associated with rear-end crashes, and female or younger (aged 25 years or younger) casualties. Several engineering, enforcement, and education measures are recommended based on the risk factors identified.

The Sight Distance Planning for Road User Safety : A Case of Jalan Pasukan Sindangkasih-Majalengka

This study aims to provide practical and applicable solutions to improve road safety on the Troop-Sindangkasih Road section in Majalengka Regency, West Java, by analyzing road visibility using empirical data and the Bina Marga method. The primary data consisted of looking for a literature review on the classification of road classes based on their functions, calculation of visibility, while for secondary data collected about the location map of this study. The results show that visibility planning can be improved to improve traffic efficiency and reduce the risk of accidents. The research could also consider the influence of different vehicle types and weather conditions on visibility requirements to refine the standards set by the Geometric Planning Procedures for Intercity Roads. It is also hoped that this research will increase awareness of the importance of visibility planning for overall road safety to avoid accidents.

Expressways and policy choices of local governments

We examine how intercity road connection affects the policy choices of local governments, using the construction of China’s national expressway as a natural experiment. We show that peripheral counties reduced the level of spending and changed the spending composition since the expressway connection. They became less involved in spending competition, increased the effective tax rate on private firms, and slowed down the privatization of state-owned firms. These results are consistent with the view that mobile capital tends to relocate from peripheral areas to core regions with a lower trade cost. We further show that such changes in government policies contribute significantly to the output decline in these regions after the expressway connection.

Evaluating the performance of intercity road freight transport: Double-frontier parallel network cross-efficiency model

Performance assessment of Intercity Road Freight Transport (IRFT) involve a complex set of considerations to ensure the efficient transportation of goods between their origins and destinations. Notably, Data Envelopment Analysis (DEA) models are often the preferred approach for conducting assessment studies that involve multiple inputs and outputs. Even though the conventional Cross-Efficiency (CE) technique addresses the limitations of DEA in producing comparable results, it still fails to consider the evaluation of internal system operations. The use of Network CE leads to more realistic results in assessing problems. It addresses not only the limitations of the DEA model in producing comparable results but also considers the performance of internal operations and system efficiency. Incorporating CE into a Parallel Network System (PNS), which is known as CE-PNS, has also a significant drawback as it neglects both the optimistic and pessimistic viewpoints based on the efficient and anti-efficient frontiers simultaneously, and may therefore fail to provide a comprehensive analysis. The primary objective of this study is to propose a new double-frontier network CE that takes into account two perspectives simultaneously. Indeed, this study is the first to incorporate the concepts of CE and double-frontier DEA into a PNS to provide an effective tool for assessing Iranian IRFT. For this purpose, the Cross-Inefficiency (CIE) technique is first incorporated into the PNS, called CIE-PNS, which explores the relationship between system inefficiency and internal divisions. The CE-PNS and CIE-PNS may yield different results. Therefore, Double-Frontier CE for a PNS (DFCE-PNS) is derived by combining the efficiency results obtained from CE-PNS and CIE-PNS. This study also examines different inputs and outputs to assess the performance of Iranian IRFT. The results demonstrate that DFCE-PNS yields more comprehensive and reliable results.

A driver perspective-based investigation for lane line visibility of pavements on drivers’ lane utilization behaviors

There have been significant advances in vehicle safety and road construction in all over the world and driver misbehaviours are still shown as one of the most important reasons of traffic accidents. When the current traffic accidents are examined, the negative effect of lane line quality and level of visibility related on the accidents comes to the forefront in underdeveloped and developing countries. In this study, the effect of lane line visibility level on drivers' lane utilization was investigated in detail. For this aim, a total of 17 different points in Türkiye were selected and the lateral positions of the vehicles on the road surface at these points were determined with the help of the screen scaling technique. In order to determine the level of lane line quality for an expert group and driver perspective, a face-to-face survey was conducted. From the analysis results, the lane line quality was determined low in urban and intercity roads, and the average maximum evaluation score was determined as 4.7 and the lowest score was determined as 1.42 where the best line quality was 5. This result showed that the level of lane line quality had significant differences at different points. Although, it was observed that the lateral position distributions in the examined points fit the normal distribution, the distribution of both the right/left wheels and their gravity center skewed to the right or left and deviated from the ideal conditions on road surfaces. It showed that the vehicles do not center the lanes exactly, but usually move close to the right or left edge of the lane. This situation also clearly revealed that the lane utilization disciplines of drivers are quite weak with the effect of the low lane line quality on road surfaces.

Evaluation of intercity road passenger transportation using a novel double-frontier game-regret-cross-efficiency

The Cross-Efficiency (CE) method, based on Data Envelopment Analysis (DEA), is a commonly used approach to measure the efficiency of Decision-Making Units (DMUs). Various secondary goal models can yield different efficiency results. The recently developed Game CE (GCE) method aims to address this issue and achieve convergence efficiencies. However, the conventional GCE was developed under the unrealistic assumption that Decision Makers (DMs) are perfectly rational, as it relies on the arithmetic mean aggregation method. Additionally, the GCE evaluates DMUs based on efficient reference points, disregarding the pessimistic perspective. The study introduces a new aggregation method called Regret-Consensus Aggregation (RCA) that captures the subjective preferences of DMs. GCE-RCA scores are obtained by incorporating RCA into the GCE. A new method called Game Cross In-Efficiency (GCIE) with RCA (GCIE-RCA) has been developed to incorporate anti-efficient reference points into the evaluation process. A Double-Frontier GCE based on the RCA (DFGCE-RCA) is developed from two perspectives. The DFGCE-RCA is implemented to evaluate the performance of the Iranian Inter-City Road Passenger Transportation (IC-RPT) system based on six key performance indicators. DFGCE-RCA has several advantages in addition to those of GCE. Firstly, considering two perspectives provides more comprehensive results. Additionally, it can capture the subjective perspectives of DMs. Lastly; it enables the aggregation process to reach a consensus.

Mixed Traffic Behaviour in Heavy Flow: Two-Lane Road Insights

The current paper outlines a comprehensive methodology for modeling speed data on two-lane roads during periods of heavy traffic characterized by heterogeneous vehicle types. In such scenarios, the presence of diverse vehicle types causes a significant departure from the normal speed distribution model. This deviation becomes particularly pronounced during heavy traffic flows due to the frequent interactions among vehicles within the traffic stream. Consequently, there arises a necessity to develop a modeling approach specifically tailored to such flow conditions. Drawing upon empirical data collected from a major intercity road in India, this study uncovers a notable skewness in speed data under heavy traffic conditions. This skewness primarily stems from the formation of vehicle platoons within the traffic stream, exerting a substantial influence on their speed characteristics. By scrutinizing the distribution of this data, the study concludes that a logarithmic transformation effectively aligns with the assumption of normality. This assertion is supported by various goodness-of-fit metrics, affirming the suitability of the proposed modeling approach for capturing the intricacies of speed behavior in heterogeneous traffic environments.

Evolution and Driving Forces of Ecological Service Value in Anhui Based on Landsat Land Use and Land Cover Change

The main challenge in protecting ecosystems and improving the supply of ecosystem services is to quantify the ecological services value (ESV). However, the detailed spatiotemporal changes, sensitivity, spatial autocorrelation, and driving mechanisms of ESV are not clear in rapidly developing regions, particularly subsidence, floods, landslides, and the rapid urban development of Anhui province, China. In this paper, the ecological service value of Anhui Province in the past 30 years was calculated using the improved equivalent factor assessment method from satellite remote sensing such as Landsat. The spatiotemporal evolution characteristics of ESV were analyzed and the driving mechanism of ESV changes was studied using Geodetector. Finally, The GeoSOS-FLUS model was selected to predict the ecosystem service value until 2030 with three scenarios: business as usual (BAU), ecological protection (EP), and cultivated land protection (CLP). The main results were obtained: (1) the ESV in Anhui Province continued to decrease by 2.045 billion yuan (−6.03%) from 1990 to 2020. The top two contributors were the forest land, followed by water area. (2) The global Moran’s I of ESV at the landform subdivision, county, town, and grid scales in Anhui Province were −0.157, 0.321, 0.357 and 0.759, respectively. (3) The order of influence degree of driving factors was: precipitation (F4), distance to intercity road (F9), net primary productivity, NPP (F6), distance to urban road (F8), population (F13), temperature (F5), aspect (F3), distance to settlement (F11), slope (F2), elevation (F1), GDP (F14), distance to water (F12), distance to railway (F10), and soil erosion (F7). (4) In 2030, the simulated ESV under the three scenarios will decrease to varying degrees. Compared with 2020, the ESV of the three scenarios will decrease successively as follows: BAU (−1.358 billion yuan), EP (−0.248 billion yuan), and CLP (−1.139 billion yuan).

Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of electrocardiogram signals: the case of intercity roads

Objectives. This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. Methods. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22–67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). Results. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. Conclusions. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver’s state.

Impact of Illuminated Road Signs on Driver’s Perception

This study determined citizens’ perceptions and impact factors of illuminated road signs installed to ensure their visibility at night when the risk of traffic accidents is high. An ordered logit model was used to measure illuminated road signs’ impact on drivers’ perception based on the data from the citizens’ survey conducted by the Road Sign Center. According to the results, the internal (optical fiber) type variable had the highest impact, followed by the frequent fog variable and the complex road line variable. This study found that most citizens positively recognized road signs, preferred internal (optical fiber) types, and desired illuminated road signs that considered climate, environment, and road structure types. In Seoul, the importance and improvement of illuminated road signs at points where road structures are complex, such as city streets, were high. Additionally, the illuminated road sign recognition and road type variable were significant in Gyeonggi-do, which reflected the high number of citizens that commute to Seoul from Gyeonggi-do. Concerning local cities and counties and intercity roads highly affected by the climate, the impact was high at points with frequent fog. Fog affects the visibility distance, generates condensation on signs, and significantly degrades visibility. Therefore, an illuminated road sign installation method must be presented based on spatial analysis for regions vulnerable to climate, environment, and road location. Additionally, the road intersection point variable was significant in local cities and counties, which reflects the relatively lagged road infrastructure. Local cities and counties are financially poor and have numerous aged drivers; hence, central government support that considers these aspects is crucial.

Neue Grabepigramme aus Bilecik

This article is a continuation of the articles we published in the previous issues of Gephyra (23, 2022 and 24, 2022). The article analyses three inscriptions found in various villages of Bilecik. On the second artefact there is both an epigram (no. 2a) and a grave inscription in prose (no. 2b). Of these inscriptions, only the stele described in no. 3 is today in the Bilecik Museum. The other two inscriptions are probably still in the field. We read the first inscription from a photograph given to us by the museum authorities, but we did not see the inscription itself. We read the second inscription from a photograph given to us by a person in Bozüyük, but we did not see the stone itself either. The first inscription found in the village of Danışment in Yenipazar is a funerary epigram written for an old man named Antonius. It appears that one of his sons, Maximus, was a gerusiastes who ruled the gerusia. The second inscription found during the construction of the major intercity road in Bozüyük consists of two separate inscriptions carved on stone in different periods. Inscription A is a funerary epigram for a man named Gaius and his family. Inscription B was carved later and the Gaianus mentioned in the inscription is probably the grandson of the Gaius mentioned in inscription A. Inscription B is not an epigram, although it contains poetic words. Although the right half of the last epigram, no. 3, is missing, the inscription could be restored to a large extent. The grave owner, a farmer, probably died at the age of 70, leaving behind a young wife and three small children as orphans.

Assessing the Effect of COVID-19 on the Traffic Safety of Intercity and Major Intracity Roads in Saudi Arabia.

The coronavirus disease 2019 (COVID-19) pandemic led to rapid and unexpected changes across the world, particularly in road safety. Thus, this work assesses the impact of COVID-19 accompanied by government preventive policies on road safety in Saudi Arabia by investigating the crash frequency and crash rates. A 4-year crash dataset relating to 2018-2021 was collected, covering about 71,000km in total road length. It covers all intercity roads and some of the major intercity roads in Saudi Arabia with over 40,000 data logs of involved crashes. We considered three different time phases to observe road safety. These time phases were identified by the duration of government curfew measures against COVID-19 (before, during, and after). The crash frequency analysis showed that the curfew during COVID-19 significantly impacted the crash reduction. At a national level, the crash frequency decreased during 2020 and reached a 33.2% reduction compared to 2019 (the previous year), and it surprisingly continued decreasing in 2021 (the consequent year) to another 37.7% reduction although the government measures were lifted. Moreover, considering the traffic volume and road geometry, we analyzed crash rates for 36 selected segments, and the results showed a significant reduction in the crash rate before and after the COVID-19 pandemic. Additionally, a random effect negative binomial model was developed to quantify the impact of the COVID-19 pandemic. The results showed that the reduction in crashes was significant during and after COVID-19. Also, single roads (two-lane, two-way) were found to be more dangerous than other types of roads.

Stabilization of Aeolian Sand for Pavement Subbase Applications Using Alkali-Activated Fly Ash and Slag

Using local materials to construct building elements as well as transport road facilities, including highways, intercity roads, and roads, in remote areas is a top topic of scholarly research all over the world. The main reason for that is the fact that these kinds of materials not only ease the intensity of material transportation but are also cost-efficient. In desert areas, aeolian sand is a commonly used local material and it has been investigated in unbound and cement-stabilized pavement base/subbase applications. However, the production of cement is associated with a high carbon footprint, leading this research to seek alternative low-carbon binders. This research investigated the strength properties and the carbon footprint of fly ash (FA) and a ground-granulated blast-furnace slag (S)-based geopolymer-stabilized aeolian sand. Setting time, compressive strength, California bearing ratio (CBR), and temperature shrinkage measurements of the stabilized aeolian sand were carried out in this research. The maximum strength of the stabilized aeolian sand was found at the optimal ratio of Si/Al ratio of 2.5 and Na/Al ratio of 1.0. The compressive strength increased as the geopolymer stabilizer content increased. A stabilizer content ranging between 8% and 20% is recommended in practice. The carbon footprint of the geopolymer-stabilized aeolian sand was lower than that of cement-stabilized aeolian sand. This tendency became more evident in the samples with higher strength, indicating the effectiveness of geopolymer as an alternative green soil stabilizer to traditional Portland cement.

Deep Learning Inter-city Road Conditions in East Africa Focusing on Rwanda for Infrastructure Prioritization using Satellite Imagery and Mobile Data

Traditional survey methods for gathering information, such as questionnaires and field visits, have long been used in East Africa to evaluate road conditions and prioritize their development. These surveys are time-consuming, expensive, and vulnerable to human error. Road building and maintenance, on the other hand, has long experienced multiple challenges due to a lack of accountability and validation of conventional approaches to determining which areas to prioritize. With the digital revolution, a lot of data is generated daily such as call detail record (CDR), that is likely to contain useful proxy data for spatial mobility distribution across different routes. In this research we focus on satellite imagery data with applications in East Africa and Google Maps suggested inter-city roads to assess road conditions and provide an approach for infrastructure prioritization given mobility patterns between cities. With increased urban population, East African cities have been expanding in multiple directions affecting the overall distribution of residential areas and consequently likely to impact the mobility trends across cities. We introduce a novel approach for infrastructure prioritization using deep learning and big data analytics. We apply deep learning to satellite imagery, to assess road conditions by area and big data analytics to CDR data, to rank which ones could be prioritized for construction given mobility trends. Among deep learning models considered for roads condition classification, EfficientNet-B3 outperforms them and achieves accuracy of 99%.

Predicting of motor vehicle carbon emissions and spatio-temporal characteristic analysis in the Beijing-Tianjin-Hebei region.

In China, road traffic carbon emissions and their share in total carbon emissions have significantly increased. In the context of double carbon, the Beijing-Tianjin-Hebei region, the largest urban agglomeration in northern China, is receiving more and more attention. Due to the unbalanced development in Beijing-Tianjin-Hebei urban agglomeration, this thesis presents three computational models to calculate road traffic carbon emissions for large, medium-sized, and small cities and intercity traffic arteries based on the road network. The results show that in 2019, Beijing has the highest road carbon emissions reaching 19.91 milliont CO2 which is almost three times that of Shijiazhuang, the capital city of Hebei province. Dwellers' commuting usually results in an increase of 2.9%, 3.3%, and 4.5% on weekdays compared with weekends for Tianjin, Shijiazhuang, and Beijing, respectively. As for the intercity road, the daily traffic flow is about 1.92 million vehicles, leading to total carbon emissions of 22.97 milliont CO2. In addition, the reduction potential of carbon emissions in Beijing is evaluated. If the average road speed is increased to 0.9Vf (road design speed) during the morning rush hour in Beijing from 7 a.m. to 8 a.m., the road emission reduction could reach 57.85%.

ENVIRONMENTAL ASSESSMENT OF THE ROAD TRANSPORT IMPACT ON THE ENVIRONMENT

Environmental impact assessment of road transport is a serious problem that needs an immediate solution. Intensive development of road transport is associated with an increase in anthropogenic load on the environment in the form of exhaust gases containing more than 200 pollutants, waste generation, pollution of water bodies and soils. This problem concerns not only the environmental assessment of the state of cities and settlements, but also the assessment of the state of intercity roads, roads passing through natural areas and protected areas. This problem is especially acute in industrially saturated centers and large cities of Ukraine. In this regard, the issues of improving methods for assessing the impact of vehicles on the environment are being actualized in order to find reserves for reducing the ecological and economic damage to the biosphere. Environmental impact assessments carried out in accordance with state legislation are components of the environmental assessment system. The paper shows that when assessing the environmental impact of road transport, the full life cycle of a motor vehicle should be taken into account. Therefore, the work conducted a study of the life cycle of a car from mining to utilization of a motor vehicle and assessed its impact on the environment. Evaluation of production processes and products for the full life cycle of a car is very difficult, as it is associated with the collection of information about many production processes taking place, including outside the enterprise. It should be noted that the information obtained when assessing a vehicle for the full life cycle allows us to invent ways to improve the design of the car and technological processes of its production, as well as reduce the negative impact on the environment. Therefore, the work identified the main parameters and factors influencing the environment of road transport. Possible mathematical models of the impact of road transport on the environment, in particular on the hydrosphere, are considered.

Comparing Female and Male Pedestrians’ Relative Vulnerability Based on Crash Locations

While pedestrian fatalities represent 23% of all road crash fatalities in Iran, fatalities seem more common amongst female pedestrians than male pedestrians. This study investigated female pedestrian fatalities and contributing factors such as age, education, and visibility. Using Iran’s 2014 death registry data, a relative vulnerability ratio was estimated for different groups stratified by crash locations. Factors that increase the risk of fatal injuries for female pedestrians included: being under 15 years old or 41-64 years old; lacking formal education; being single; not receiving trauma care in time due to resting at home or long transfer time to a hospital; not wearing contrasting clothing in urban areas; and being involved in a crash on rural roads or at dusk/dawn on intercity roads.

Deep Learning-Based Traffic Behavior Analysis under Multiple Camera Environment

In a video surveillance system, tracking multiple moving objects using a single camera feed is having numerous challenges. A multi-camera system increases the output image quality in both overlapping and non-overlapping environment. Traffic behavior analysis is an intensified demand in a recent topic of research. Due to increasing traffic in intercity roads, interstate, and national highways. Automated traffic visual surveillance applications with the multi-camera are a topic of research in computer vision. This paper, present a multi-camera system study for the overlapping area of the road for traffic analysis in three sections. The second section represents the thorough literature survey on the multi-camera system. Here, the third section is our proposed system using a dual-camera experimental setup with their coordination. A deep neural network is used in the experiments for traffic behavior analysis. The emphasis of this paper is on the physical arrangement of the multi-camera system, calibration, and advantages- disadvantages. On a conclusion note, future development and advancement in traffic analysis using a multi-camera system is discussed.

საქართველოს საავტომობილო გზებზე სატრანსპორტო ნაკადების მახასიათებლები და მათი ფორმირების თავისებურებები

In recent years, Georgia's road network has developed significantly with the construction of the TRACECA Red Bridge-Sarpi Highway. The intra-regional intercity road network has also developed significantly. The paper presents the main characteristic dependences of the traffic flows obtained as a result of the research: flow speed VS (km/h), time TS (h) and distance LS (km) between vehicles in the flow, dependence of the values of the intervals on the traffic intensity NS (km/h). The results of the research will allow us to rationally solve specific current problems in the direction of transport logistics.

Insights for speed management among Iranian drivers: a social marketing formative research study.

Road traffic crashes are among the leading causes of death and disability in the world, particularly in low and middle-income countries. This study aimed at to conduct a social marketing formative research to inform the development of a campaign to manage driving speed on the intercity roads of Iran. To carry out the social marketing formative research, a qualitative and quantitative study were conducted. Also, a literature review of the speed management strategies was carried out and an analysis of traffic accident data and speeding violations was performed in selected provinces during 2019 and 2020. Based on the findings of the qualitative study, perceived sense of lack of speed control, poor monitoring system, and law enforcement are the main reasons drivers exceed the speed limit. They mostly suggest using punitive levers and more stringent law enforcement practices for speed management. Literature reviews also confirm that to successfully develop an effective speed management plan a set of measures should be implemented together, including road safety engineering, raising awareness, social marketing strategies, and finally strict law enforcement. The overriding findings of the formative research revealed that to persuade Iranian drivers to respect the speed limit, the messages of the campaign should focus on strict law enforcement in the selected corridors. In the minds of the Iranian audience, strict law enforcement is of paramount importance for a speed management strategy to work; hence it should be taken into consideration when tailoring the campaign messages. From the findings of the present study, it can be concluded that to manage speed on intercity routes in Iran, a social marketing campaign is needed to encourage compliance with speed limits.