Road Type Research Articles

Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle

Electric vehicles (EVs) have gained importance in recent years, prompting the development of several control systems to improve their efficiency and performance. In this work, a quarter electric vehicle (QEV) was controlled using a conventional proportional integral derivative (PID) and fuzzy controller to examine and compare with the response of the adaptive neuro-fuzzy inference system (ANFIS) controller. The response of the ANFIS controller was evaluated using MATLAB/Simulink according to different parameters and compared with those of other controllers. In addition, the simulation was based on different driving conditions such as the acceleration and deceleration modes and the type of road: wet and dry. The simulations were carried out on a longitudinal electric vehicle model based on a brushless DC motor, including the Pacejka tire model. The results showed that the ANFIS controller outperformed the PID and fuzzy logic controllers, providing superior dynamic responsiveness and stability when the ANFIS controller smoothly followed the input speed and the longitudinal slip value reached 3%.

An Approach of Multi Criteria Decision Making in Analyzing Rural Road Safety in Nashik District

Abstract: Rural road safety evaluations play a significant role in the transportation industry, and most fatal accidents happen on these types of roads. Road Safety Analysis (RSA), a process to evaluate a road's safety criteria and support overall road management decision-making, ensures the avoidance of loss of life and property damage. The "Pradhan Mantri Gram Sadak Yojana," which is primarily utilized in rural areas, is the main emphasis of this. In order to identify the most vulnerable roadways and implement mitigation measures, roads must be prioritized depending on safety ratings. This document presents the results of a study conducted to rank the safety criteria of Pradhan Mantri Gram Sadak Yojana (PMGSY) roads, a particular category of rural roads. A questionnaire survey was used for the study's analysis, and three MCDM methods were used to examine the relationships and interactions between the various factors. The study's findings indicated that the based on input from PMGSY engineers and contractors. From the perspective of the engineers in the Nashik area, we can determine the safety impact factor that influences the safety assessment of the PMGSY route.

Analysis of a bus vertical dynamic performances – a comparison between linear and nonlinear suspension systems

This paper mainly focuses on the numerical calculation to determine the vertical evaluation indexes with all three types of typical harmonic, transient and random road excitations. The effects of linear and nonlinear suspension characteristics on the vertical evaluation indexes are fully understood systematically. The ride comfort, suspension working space, and road holding are analyzed for both two cases of linear and nonlinear suspension systems. The improvement of the vertical stability and road holding in the case of nonlinear suspension subjected under three different excitations could be characterized most meaningfully. The obtained results help to systematically get full understanding of the investigated problem nature. It also should guide interested readers in suspension design to improve the stability, safety, and ride comfort of buses.

Investigation of the Vehicle Driving Trajectory During Turning at Intersectional Roads Using Deep Learning Model

Two-thirds of vehicle accidents in Malaysia occurred at the straight type of roads, followed by intersection-type roads. Despite the deployment of traffic lights on the road, accidents still occur which are caused by illegal maneuvers, speeding or misjudgment of other’s actions. Hence, motivated by the lack of previous research regarding causes of accidents on intersectional roads, this study aims to observe the pattern of the vehicles’ speed and turning angle during the right turn after the traffic stop at the intersection road. To obtain these parameters, video samples of vehicles at two types of intersections were obtained and analyzed via YOLOV7 and DeepSORT. The two road intersections researched are four-legged intersection and three-legged intersection. 153 and 35 vehicle samples were collected from these types of road intersections, respectively. It was observed that 78 and 75 vehicles exit towards the nearest and furthest lanes at four-leg controlled crossings on divided roads. While, at a single-lane to a dual carriageway road intersection, 26 and 9 vehicles exit towards the nearest and furthest lanes, respectively. From the research, 16.52 - 17.53 km/h and 67.57°-73.33° are the most optimal turning speeds and angles respectively for vehicles at four-leg controlled crossings. Whereas 14.48 - 15.51 km/h and 144.77° - 154.403° are the most optimal turning speeds and angles respectively for vehicles at a single-lane to a dual carriageway road intersection.

From self-reports to observations: Unraveling digital billboard influence on drivers

The objective of this current study was to evaluate the impact of digital billboards (DBs) on self-reported and observed driving behavior, given their established association with distracted driving. This investigation focused on driver behavior in Iran using a dual-pronged approach. Initially, self-reported driving behavior was analyzed using a Driving Behavior Questionnaire (DBQ), which was completed online by 453 drivers. The factor analysis of the questionnaire data emphasized the significant role of DBs in generating driving errors, lapses, unintentional violations, and intentional violations. The DBQ questions exhibited a clear factor structure, demonstrating high factor loadings and satisfactory internal stability. The findings indicated that advertising signages notably influenced drivers' behavior, particularly in instances of neglecting the behavior of the leading vehicle's driver (Lapse), disregarding pedestrian crossings (Error), disregarding red lights (Intentional violation), and overtaking without considering traffic flow behind (Unintentional violation). Subsequently, participants engaged in an Instrumented Vehicle Study (IVS) to explore observed driver behavior when encountering DBs (899 samples). Four factors were identified as significantly influencing the likelihood of driver distraction: the driver's crash history, time of day, driver's age, and road type. A logistic regression analysis was conducted using the IVS data, revealing that drivers with prior crash experience approached DBs with 8.8 times more caution than those without such a history. Moreover, young adults were 8.25 times more susceptible to distraction from DBs compared to their older counterparts. Notably, the findings suggested that drivers were nearly four times more prone to distraction at night compared to daytime. Additionally, drivers were twice as likely to be distracted at intersections compared to other road types. The outcomes of this study can offer insights for policy interventions regarding the content and placement of DBs, aiming to minimize their impact on road safety while still enabling advertisers to target their intended audience.

Road infrastructure maintenance: Operative method for interventions’ ranking

Planned maintenance of transportation infrastructure is a milestone in maintaining the functionality and safety of road networks. This paper is part of this process and aims to propose an easily applicable and versatile operational methodology for prioritizing maintenance interventions generally scheduled on road networks of considerable extent. An operational methodology for ranking and prioritizing maintenance interventions is proposed; this method is applicable to road networks of such size that direct inspection of each situation is impossible. The core of the paper is the analytical description of this methodology, based on a weighted sum function of three blocks: i) Category − is a score related to the purpose of the intervention; ii) Asset − is a score due to the road on which the intervention is located (considering Average Daily Traffic, Accidentality, Social Cost, Road Type, Routes); iii) Typology − is a score related to the element on which the intervention is being carried out. After describing the parameters and the implementation procedure for each block, the calibration of the relative weights is described, and a sensitivity analysis is performed. In the case study, the proposed methodology is applied to the ANAS corporate network in Italy. This case study will highlight the usefulness, versatility, and operability of the methodology with GIS (Geographic Information System) tools for implementing thematic maps. A concluding section concerns the addition of a scoring block − Spatial Context − as an additional differentiating factor due to the spatial context of each road.

Sustainability of underground infrastructure – Part 1: Digitalisation-based carbon assessment and baseline for TBM tunnelling

Alongside the transition towards sustainable and renewable infrastructure and energy production, tunnelling projects that adopt tunnel boring machines (TBM) continue to increase in size and complexity. Life Cycle Assessment (LCA) methodologies have a significant impact on the Architecture, Engineering and Construction (AEC) industry, with a shift in focus to cost and carbon management across the infrastructure lifecycle through the use of digitalisation techniques and sustainability rating systems. This paper aims to develop a systematic framework to enhance the sustainability of underground infrastructure in the early design and construction stages, aiming for “build clever and efficiently”. This framework integrates digitalisation, carbon assessment standards, numerical modelling, and optimisation techniques to assess carbon emissions and establish benchmarks for construction products and processes. The approach uses parametric models to define tunnelling-related entities such as geological formations, TBM, and segments, designed with dimensional constraints that allow for adaptive modelling and interactions. Enabled by building information modelling (BIM) through parametric models enriched with domain properties, module-based carbon accounting is adopted to evaluate the footprint of material- and asset-level key emitters with functional units. Leveraging established databases, baselines for segmental lining designs and carbon reduction strategies are established. Through project-driven case studies, the correlations among geotechnical conditions, tunnel dimensions, and TBM operating parameters are developed to quantify TBM carbon emissions. A prototype programme demonstrates the framework's application on typical metro and road tunnels at different levels of details (LoD). This paper serves as a guideline for conducting embodied carbon assessments specifically tailored to TBM tunnelling, acknowledging the substantial contribution of the TBM construction process, which is controlled by geotechnical conditions.

Analysis of road traffic accidents and casualties associated with electric bikes and bicycles in Guangzhou, China: A retrospective descriptive analysis

IntroductionElectric bicycles (e-bikes) and bicycles in large Chinese cities have recently witnessed substantial growth in ridership. According to related accident trends, this study analyzed characteristics and spatial distribution in the period when e-bike-related accidents rapidly increased to propose priority measures to reduce accident casualties. MethodsFor e-bike- and bicycle-related accident data from the Guangzhou Public Security Traffic Management Integrated System, linear regression was used to examine the trends in the number of accidents and age-adjusted road traffic casualties from 2011 to 2021. Then, for the period when e-bike-related accidents rapidly increased, descriptive statistics were computed regarding rider characteristics, illegal behaviors, road types, collision objects and their accident liability. One-way analysis of variance (ANOVA) followed by Bonferroni's multiple comparison test. P < 0.05 was considered statistically significant. Finally, the density distribution of accidents was presented, and Moran's I (MI) was used for assessing spatial autocorrelation. Hotspots were identified based on an optimized hotspot analysis tool. ResultsBetween 2011 and 2021, the number of accidents and casualty rate (per 100,000 population) increased for e-bikes but decreased for bicycles. After 2018, e-bike-related accidents increased rapidly, and bicycle-related accidents plateaued. Accident hotspots were concentrated in central city areas and suburban areas close to the former. Three-quarters of accidents occurred in motorized vehicle lanes. Most occurred on roads without physically segregated nonmotorized vehicle lanes. More than three-fifths of the accidents involved motor vehicles with at least four wheels. The prevalence (per 100 people) of casualties among e-bike rider victims and cyclist victims accounted for 92.0 % and 96.5 %, respectively. A total of 71.6 % of e-bike-related accidents involved migrant workers. Riding in motorized vehicle lanes was the most common illegal behavior. ConclusionsAlthough e-bike-related and bicycle-related accidents presented similar characteristics, the sharp increase in e-bike-related accidents requires attention. To improve e-bike safety, governments should develop appropriate countermeasures to prevent riders from riding on motorways, such as improving road infrastructure, adjusting the driver's license system and addressing priority control areas.

Secure Aggregation for Privacy-preserving Federated Learning in Vehicular Networks

The automotive industry has been enhancing autonomous driving systems utilizing the computation and communication networks embedded in vehicles (e.g., cellular networks and sensors) and roadside units (e.g., radar and cameras). Robust security and privacy requirements are essential in Intelligent Transportation Systems (ITS). To satisfy these requirements, most developed autonomous driving systems (e.g., Waymo and Tesla) use machine learning. Machine learning models trained on sensitive raw data promise improvements in performance; however, they cannot provide privacy for sensitive raw data and users. Federated learning advances privacy-preserving distributed machine learning by aggregating the model parameter updates from individual devices in a secure manner. Security Credential Management System (SCMS) for Vehicle to Everything (V2X) communication provides a guarantee for authentication in a privacy-preserving manner and punishes misbehaving vehicles through misbehavior reporting. In this paper, we design a secure aggregation protocol for privacy-preserving federated learning for vehicular networks. Our protocol allows a server to verify vehicles in a secure manner and is used to aggregate each vehicle-provided global model update for federated learning. We prove our protocol for security in the honest-but-curious framework and detect active adversary attacks, as well as show that it provides trust in different domains (e.g., SCMS and outside the domain of SCMS) and in a privacy-preserving manner for vehicles using SCMS. We analyze the process of federated learning in each vehicle and server while communicating during driving on several types of roads (e.g., local, urban, and rural) using cellular networks (LTE and 5G).

Design Strategies to Improve Metro Transit Station Walking Environments: Five Stations in Chongqing, China

While transit-oriented development (TOD) has been widely adopted in urban design alongside the expansion of urban metro transit, the creation of pedestrian-friendly environments has often been overlooked during implementation. This has resulted in a lower walking advantage around metro transit stations. To address this issue and encourage walking and public transport use in metro transit station areas, this study undertook a quantitative comparative analysis of the pedestrian environment in five Chongqing metro transit station areas. The analysis focused on three key dimensions: “comprehensive evaluation”, “basic scale”, and “structural quality”. The comprehensive evaluation considered factors such as the pedestrian catchment area ratio, POI kernel density distribution, and crowd agglomeration. The basic scale dimension comprised floor area ratio, building density, pedestrian road density, and the quantity of station entrances and exits. Finally, structural quality factors included land use type mixing degree, POI function mixing degree, intersection connectivity, median street length, pedestrian route directness, and green view index. Based on these analyses, this study proposes a series of pedestrian environment design strategies including land use and transportation. The strategies for land use advocate for “developing compact and diverse land use”, “strengthening attraction of station center”, “positioning large projects on the edge”, “restricting private transportation capabilities”. The strategies for transportation consist of “increasing pedestrian road density”, “traffic calming organization”, “subdivision of road types”, and “three-dimensional pedestrian traffic system”. These strategies aim to create a more humanized and environmentally friendly pedestrian environment, proactively rise to the challenge of climate change, thereby cultivating sustainable urban development.

Evaluating the Landscape and Ecological Aspects of Urban Planning in Byblos: A Multi-Faceted Approach to Assessing Urban Forests

Byblos, designated as a UNESCO World Heritage site, stands as one of Lebanon’s most ancient urban centers, known for its expansive green spaces. However, ongoing urbanization threatens these valuable areas. This study uses a multi-faceted approach to evaluate the structure and landscape attributes of Byblos’ urban and peri-urban forests (UPFs). Landscape canopy cover, diversity indices, forest structure, and a silhouette perceptual test were assessed across 24 streets in the city center, residential zones, and areas with heavy vehicular traffic. Findings reveal that 28% of Byblos’ canopy cover is concentrated mostly in the northeastern region. Native tree species account for 30% of the total, and a notable variation in tree diversity exists among different land-use types (Shannon diversity index (H) was 1.02 for the city center, 1.35 for residential streets, and 0.64 for vehicular areas). Additionally, a normal J-shaped distribution of tree diameters was identified across all street types. This study highlights a correlation between tree silhouettes and visual preferences, with densely spreading canopies being favored. Residential trees demonstrate the highest structural diversity and varied blossoming seasons. This research represents the first investigation into the current state of urban forestry in Byblos and offers recommendations for sustainable management and planning strategies.

Mapping Road Surface Type of Kenya Using OpenStreetMap and High-resolution Google Satellite Imagery

Identifying road surface types (paved or unpaved) can ensure road vehicle safety, reduce energy consumption, and promote economic development. Existing studies identified road surface types by using sensors mounted on mobile devices and high-resolution satellite images that are not openly accessible, which makes it difficult to apply them to large-scale (e.g., national or regional) study areas. Addressing this issue, this study developed a dataset of road surface types (paved and unpaved) for the national road network of Kenya, containing 1,267,818 road segments classified as paved or unpaved. To accomplish this, this study proposes a method that integrates crowdsourced geographic data (OpenStreetMap) and Google satellite imagery to identify road surface types. The accuracy, recall, and F1 score of the method were all above 0.94, validating the effectiveness of the method. The data sources of the method are freely available, and the method may be applied to other countries and regions. The dataset developed based on the method can provide data support and decision support for local governments to improve road infrastructure.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road identification

Aiming at the problem that the current Anti-lock Braking System (ABS) control algorithm can not make full use of the ground friction to complete the braking when emergency braking on complex roads, an ABS sliding mode control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor regenerative braking and mechanical friction braking is designed. Based on the neural network control method, the road friction coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip ratio of different roads. The ABS sliding mode controler is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the symbol function in the traditional sliding mode control to weaken the chattering problem, and then the ABS controller is designed. The research results show that compared with the traditional ABS sliding mode controller, the designed ABS neural network sliding mode controller has the following advantages: 1. Through the identification of tire-road friction coefficient by neural network, the real-time performance and road adaptability of ABS controller are improved; 2. When the braking simulation is carried out at a given speed, the braking time is reduced by about 1.03 % and the braking distance is shortened by about 1.01%; 3. The identification of tire-road friction coefficient is realized, which weakens the chattering problem of traditional sliding mode control and improves the stability and robustness of ABS controller.

Urban heat load assessment in Zagreb, Croatia: a multi-scale analysis using mobile measurement and satellite imagery.

A limited number of meteorological stations and sparse data challenge microclimate assessment in urban areas. Therefore, it is necessary to complement these data with additional measurements to achieve a denser spatial coverage, enabling a detailed representation of the city's microclimatic features. In this study, conducted in Zagreb, Croatia, mobile air temperature measurements were utilized and compared with satellite-derived land surface temperature (LST). Here, air temperature measurements were carried out using bicycles and an instrument with a GPS receiver and temperature probe during a heat wave in June 2021, capturing the spatial pattern of air temperature to highlight the city's microclimate characteristics (i.e. urban heat load; UHL) in extremely hot weather conditions. Simultaneously, remotely sensed LST was retrieved from the Landsat-8 satellite. Air temperature measurements were compared to city-specific street type classification, while neighbourhood heat load characteristics were analysed based on local climate zones (LCZ) and LST. Results indicated significant thermal differences between surface types and urban forms and between street types and LCZs. Air temperatures reached up to 35 °C, while LST exceeded 40 °C. City parks, tree-lined streets and areas near blue infrastructure were 1.5-3 °C cooler than densely built areas. Temperature contrasts between LCZs in terms of median LST were more emphasised and reached 9 °C between some classes. These findings highlight the importance of preserving green areas to reduce UHL and enhance urban resilience. Here, exemplified by the city of Zagreb, it has been demonstrated that the use of multiple datasets allows a comprehensive understanding of temperature patterns and their implications for urban climate research.

Оптимизация конструктивных параметров рекуперативного дышла лесовозного автопоезда

The main advantages and peculiarities of the interaction of the links of a logging road train when moving during wood hauling along under-equipped logging roads are considered. Based on the analysis of the results of the research carried out by Russian and foreign authors, promising ways to improve the efficiency of logging trucks with trailers have been identified. The main disadvantages of the existing designs of the devices for coupling logging trucks with trailers have been presented. An improved design of the regenerative pneumohydraulic rod of the coupler of a road train has been proposed, which ensures a reduction in the maximum efforts during the dynamic interaction of the links, an increase in the road train reliability, the possibility of the power fluid energy recovery with its subsequent beneficial use, as well as the effect of self-pulling of the road train, improving its cross-country ability in the conditions of under-equipped logging roads. It has been revealed that the optimal internal diameter of 2 double-acting hydraulic cylinders connected in series with the free ends is within the range of 95 to 105 mm. With such a diameter, the recovered power reaches 4 kW, the average longitudinal acceleration of the trailer is in the range of 0.75 to 0.83 m/s2. The movement of a logging road train in the studied conditions at a speed of 20 to 60 km/h is accompanied by a change in the average recovered power from 1.8 to 11.3 kW and the average longitudinal acceleration of the trailer – from 0.2 to 1.4 m/s2. It has been determined that at average heights of support surface irregularities of 0.1 to 0.2 m, characteristic of typical under-equipped logging roads, the average recovered power is in the range of 2.2 to 4.1 kW and the average longitudinal acceleration of the trailer is in the range of 0.26 to 0.53 m/s2. The optimal stroke of the regenerative pneumohydraulic rod of the coupler of a road train is 0.55 m, the optimal rate of lengthening (or shortening) of the rod is 0.28 m/s. This ensures the average self-pulling speed of 0.22 m/s, the mean displacement of a logging road train of 0.11 m per one cycle of lengthening (or shortening) of the rod and the power recovered by the rod of 1.75 kW.

IJCM_246A: Estimating the prevalence of seat belt usage in motor cars: A descriptive cross-sectional study in Mangalore

Background: Every year 1.25 million people die of road traffic accidents. Several safety measures can be taken to prevent RTAs. The SDG 2030 set the target to halve the number of global death and injuries from road traffic accidents by the year 2020. The aim of this study is to estimate the prevalence of seat belt use and factors influencing it including driver characteristics, type of car and time of day and distractions while driving. Methodology: This Descriptive cross-sectional study was set on the major roads and intersections of Mangalore, recruiting the drivers and front-seat passengers in the motor cars at the time and site of observation. Results: A total of 6165 motor cars were observed. 15 (0.2%) of these cars had completely tinted car windows, therefore out of the total, 6150 motor cars could be properly observed. 70.91% (4361) of drivers were wearing seat belts. Seat belt usage among drivers was found to be higher on highways (76.6%) as compared to on residential and city roads (69.3%). In vicinity of traffic police, 76.5% of drivers were observed to be wearing seat belts in contrary only 67.8% of them were wearing seatbelts in the absence of traffic police. Prevalence of mobile phone use and other distractions amongst drivers was 2.1%. Out of 2646 adult front seat passengers observed, only 10.9% were wearing seat belts. Conclusion: Among drivers, type of motor car, traffic zone and type of road and presence of traffic police in vicinity are significantly associated factors with seatbelt usage. Among adult front seat passengers, type of motor car, traffic zone, type of road and presence of traffic police in vicinity are significantly associated. Among front seat child passengers, type of road and traffic zone are significantly associated with seat belt usage.

Unravelling route choices of large trucks using trajectory clustering and conditional Logit models

The mobility of sizable trucks is often limited by their large size. They thus may have additional requirements on road types, road widths, and the turning radius at the intersection when travelling. Therefore, this study explores the unique needs and preferences of large truck drivers’ route choice with a focus on trip and road network characteristics. GPS trajectory data from the central Kansai area of Japan with numerous ports and freight terminals are used. Trajectories are considered having the same origin (destination) if their starting (ending) coordinates are in the same 500 m × 500 m mesh. For the trajectories of the same pair of origin–destination (OD) meshes, several route clusters are obtained based on geographical configuration using a QuickBundles algorithm. Sampling techniques are employed to equalize the number of input points for each vehicle trajectory and the optimal number of clusters is determined automatically by our algorithm based on the Silhouette Coefficient. By taking the clusters as route choice options for an OD pair, a Conditional Logit Model is used to identify the factors that influence the route choice considering both vehicle- and trip-specific attributes. The results quantify the preference of trucks for wider roads and toll routes, as well as aversion to long distances and turns. Heterogeneity in route choice based on vehicle type, trip time (date), and trip purpose is also evident. The findings of this study can provide insights for freight road network design and optimization.

Potential effects of automated driving on vehicle travel demand: A comparison of three case cities

Automated vehicles (AVs) hold the potential to reduce road accidents, mitigate traffic congestion, and improve travel experience. However, the possible countervailing impacts from the changes in underserved populations' vehicle travel demand tend to be overlooked. To determine the vehicle travel demand changes that resulted from underserved populations aged between 6 and 80, this paper explores the latent effect of AVs on vehicle kilometers traveled (VKT) in a fully AV environment using person trip survey data from the cities of Sanya, Shijiazhuang, and Shenzhen in China. This paper uses the natural decline hypothesis of travel demand and proposes a regression model to investigate the difference among the cities' latent vehicle travel demand. Results show that the average VKT of the overall population in Sanya, Shijiazhuang, and Shenzhen increased by 33.4%, 47.0%, and 46.8%, respectively. The analysis of the regression model confirms that the current travel behavior of individuals can affect the degree of increase in their average VKT. Integrating AVs into public transport, increasing the acceptance of automated shared mobility options, transforming road space use type, and prototyping AV designs with various features and needs are potential methods to cope with the countervailing impacts. The total VKT of the overall population increased by approximately 10%–25% depending on the city. The conclusions of this paper provide informative insights into the evaluation of VKT for underserved populations and contribute to the deployment of AVs to address equity and inclusion issues.

Analysis of Road Safety Based on Road Type on National Roads in Bali Province

The Province of Bali is one of the most popular tourist destinations in Indonesia which accounts for 40% of tourist visits in Indonesia. Apart from being a tourist spot, Bali also often hosts various state events. As a destination that is often in the public and world spotlight, it is important for Bali to have safer road infrastructure. However, based on data in the field, there are still many accidents that occur on National Roads in Bali and even tend to increase. If this is not handled, the impact will also be a problem in various aspects. This research aims to analyze road safety based on the type of road using the accident rate and fatality rate method on National Road sections in Bali Province. Based on the results of data analysis, this research shows the results of data accident rate or the highest accident rate is 160 incidents per 1 million vehicles per year on the Kosamba – Angentelu Bali road section. For data analysis of fatality rate or death rate, the highest is 245 per 1 million vehicles per year on Jalan A.Yani (Amlapura) Bali. And the type of road that has the highest accident rate and fatality rate number is the 2/2 UD road type.

PERFORMANCES AND SELF-DECLARED OPINIONS ON HANDHELD MOBILE PHONE USE (DISTRACTION IN TRAFFIC) IN POLAND

This article presents the Motor Transport Institute’s research to set out road safety indicators of behaviors and opinions on one of the increasingly important road traffic problems. Two types of studies on the unsafe use of mobile phones and others on board devices (distraction) by road users in Poland between 2014 and 2023 are presented. Safety Performance Indicators (SPI) on handheld mobile phone use from roadside observations and declared opinions on talking, reading messages, checking social media/news, and listening to headphones while driving, cycling, and walking are presented. Overall, 306,240 passenger car drivers observed on all road types all week long in Poland showed a dropping trend (1.8%) between before the study in 2014 SPI 4.1% distracted drivers to SPI 2.3% after the study in 2022. More drivers used mobile phones on single carriageways both in built-up and outside built-up areas. On motorways outside built-up areas, where vehicles are speeding, drivers of passenger cars rarely talk on their handheld mobiles. Results from the first European Union (EU) Baseline project to collect road indicators produced a Key Performance Indicator of 3.8% distracted passenger car (all types of roads, all weekdays and weekend) from 44,011 observed in Poland in 2021. Results from the EU project E-Survey on Road Users’ Attitude, third edition (ESRA3), showed declared opinions of mobile use while driving, cycling, and walking down the street in Poland in 2023 compared to 2018 (ESRA2). A positive trend is seen among car drivers who declared lower use of handheld mobile phones than in 2018 (a drop of 11.2%). The survey showed Polish cyclist used more often headphones to listen to music, checked news and messages than cyclists in Europe in 2023. More by 10.1% pedestrians in Europe than in Poland declared checking social media/news, reading messages/emailing while walking down the street in 2023. This lower rate in Poland can be explained by pedestrian’s legal prohibition of mobile phone use while crossing the street since 2021. There is strong support for policy measures forbidding all drivers of motorized vehicles to use handheld mobile phone use while driving in all of Europe. Enforcement measures are twice as strong in Europe than in Poland. As the number of accidents and fatalities on distraction is unknown, calculating SPI during roadside observations and questionnaire surveys gives in-depth knowledge of the problem. The authors of the paper represent the Motor Transport Institute’s (MTI’s) research institution, which systematically analyzes trends in road safety in Poland during its own, national, and international projects.