Road Layout Research Articles

Monocular Road Scene Bird’s Eye View Prediction via Big Kernel-Size Encoder and Spatial-Channel Transform Module

A detailed representation of the surrounding road scene is crucial for an autonomous driving system. yellow The camera-based Bird’s Eye View map has been a popular solution to present the surrounding information, due to its low cost and rich spatial context information. Most of the existing methods predict the BEV map based on the depth-estimation or the trivial homography method, which may cause the error propagation and the absence of content. To overcome these drawbacks, we propose a novel end-to-end framework that employs the front monocular image to predict the road layout and vehicle occupancy. In particular, to capture the long-range feature, we redesign a CNN encoder with a large kernel size to extract the image features. For reducing the big difference between the front image features and the top-down features, we propose a novel Spatial-Channel projection module to convert the front map into the top-down space. Additionally, concerning the correlation between front view and top-down view, we propose the Dual Cross-view Transformer module to refine the top-down view feature maps and strengthen the transformation. Extensive evaluations on the KITTI and Argoverse datasets present that the proposed model achieves the state-of-the-art results for both datasets. Furthermore, the proposed model runs in 37 FPS on a single GPU, demonstrating the generation of a real-time BEV map. The code will be published at https://github.com/raozhongyu/BEV_LKA.

Impact evaluation of different network planning concepts on traffic noise

The purpose of this paper is to study the impact of road structure on traffic noise from an urban network planning perspective, to provide solutions to control and prevent traffic noise at source. The process is divided into three parts. Firstly, the stochastic user equilibrium model for traffic flow allocation is improved to be more accurate. Secondly, a global traffic noise simulation method is proposed for the network based on the noise prediction model, and the noise data is visualized. Finally, a noise evaluation system is established to study the traffic noise evolution patterns under different road structures. The results show that with the increase of network density, the traffic noise value of the network decreases. The layout of one-way roads will reduce the regional traffic noise value. The impact of road grade adjustments on traffic noise is positively correlated with the rate of change in road capacity. The study can provide an effective basis for control traffic noise from the network planning stage.

Analysis of Physical and Mechanical Soil Properties Determined Using Interpretations of Dilatometric Test (DMT) and Cone Penetration Test (CPT) Methods

Road design is a complex, time-consuming, and very responsible process. To develop a high-quality and viable road project, it is very important to start with an accurate geological survey in order to define the best road layout. Moreover, the geotechnical characterisation of foundation soils and construction materials as well as the analysis and assessment of geotechnical works are mandatory. Laboratory and in situ investigations are complementary and should be carried out by defining a cost-effective investigation campaign. Most often, Dynamic Cone Penetrometer (DCP) or Cone (static) Penetration Test (CPT) are performed because they are economic and quick. In addition, it is also possible to perform the Marchetti Dilatometer Test (DMT). From the obtained test results, the data are interpreted by determining the properties of the soil layers. Although all probing methods are similar, each of them gives slightly different results. The aim of this study is to analyse and compare the results of the probing test, to determine the difference between the obtained data and to find out how the obtained results affect the development of constructive solutions from the safety and economic point of view.

The relevance of Manasara planning model in walled cities of India: An assessment review of Rajasthan

Whenever town planning of old towns is discussed, various planning models of the traditional towns that were planned in the Vedic times are always referred. To make these planning models a success, careful consideration was given to all the aspects associated with a town such as its size, scale, allocation of spaces for various activities based on their role, road layouts, and widths, building heights, assigning of housing sectors based on caste residing within the town and how all of these justified the means to achieve the same. At the same time, various walled cities and fortified towns of Rajasthan have always been studied while understanding newer planning models. This research aims to find a connection between the planning concepts that were given in the Manasara and the walled cities of Rajasthan in terms of their planning. To correspond to the local on-site conditions for these walled cities and determining the similarities and differences with the Manasara town models shall be an objective of this study with the conclusion of how much original character has been retained in their planning.

Exploring the Link between Street Layout Centrality and Walkability for Sustainable Tourism in Historical Urban Areas

Walkability is considered a vital component of the urban configuration; urban spaces should promote pedestrian walking, which is healthier and increases social sustainability by connecting people in urban spaces. This article aims to find the link between the street layout centrality values and the people’s walkability for sustainable tourism in historic areas. Moreover, it attempts to explore the linkage between the urban layout and visiting historical spaces in the urban layout. The approach to the research has two phases; the first is to find people density (the tourist density) in the historical areas, and the second is to measure the centrality values of the urban layout utilizing the spatial design network analysis tool (sDNA). The research found that the street network considerably impacts the final tourist distribution, mainly because of the betweenness centrality; consequently, spaces with low betweenness centrality values are less reachable by the tourists in the historical area, although it has a high closeness centrality. The research concluded that considering the street network is necessary concerning the tourists’ walkability since it affects their density in the urban layout.

Generating citywide street cross-sections using aerial LiDAR and detailed street plan

Precise information on spatial configurations of urban spaces, such as streets, is essential for investigating complex interrelationships between the quality of life, livability, and mobility. Street cross-sections can be central for such research as they depict the allocation of urban space by detailing the streetscape's layout and dimensions, including driveways, sidewalks, bikepaths, median strips, trees, adjoining buildings and open spaces, and shadows. However, creating an accurate description of the real world as a three-dimensional representation and translation into cross-sections is challenging due to the requirement of multiple data sources, such as road layouts with widths, height information, and, optionally, high-resolution aerial imagery. Without such datasets, the cross-section drawings are limited to manual measurements, which are difficult to extend to a city scale. This study aims to develop a method to automatically generate street cross-sections for the entire city of Berlin based on an aerial Lidar dataset and a city street plan. The study also includes shadows as a part of the sections and utilizes the Lidar dataset to generate solar radiation maps. Approximately 0.5 million cross-sections are generated with detailed information regarding the width and placement of the street elements. The details of the cross-sections are further processed to find generic street compositions, understand the influence of shadows on walkways and bikepaths, and calculate the enclosure.

A comparative evaluation of the safety performance of bus priority route configurations

One way to promote public transport use in cities lies in establishing bus priority routes (BPRs) on main traffic arterials, to reduce bus travel times. But, BPRs require infrastructure changes in road layouts, creating more complex traffic settings that may have safety implications. Previous research indicated that design features affect BPRs' safety, but findings regarding the impacts of various BPR configurations are scarce. In this study, we examined the safety performance of three BPR configurations: barrier-separated central, open centre-lane and curbside BPRs, in Israel. Multivariate regression models were fitted to identify design features affecting accident occurrences on urban arterials with BPRs, using a database on all BPRs in operation. The comparative evaluations showed that barrier-separated BPRs were characterised by lower accident rates on road sections but by substantially higher accident numbers at junctions, relative to other BPR types, and particularly when bus-overtaking was possible. Hence, the use of barrier-separated bus routes should be reduced and bus-overtaking settings should be avoided, when implementing BPRs. In the comparison of curbside and center-lane BPRs none of them demonstrated a superior safety performance: the centre-lane BPRs were safer on sections while at junctions both types had advantages for certain accident types, thus, both forms are applicable in future BPR designs.

Perencanaan Penerangan Jalan Umum Menggunakan Pembangkit Listrik Tenaga Surya Pada Jalan Ir. H. Nusyirwan Ismail, M.Si Di Kecamatan Samarinda Ulu, Kota Samarinda

This study discusses the Planning of Public Street Lighting Using a Solar Power Plant (PLTS) on Jalan Ir.H.Nusyirwan Ismail, M.Si in Samarinda District, Ulu Samarinda City. Jalan Nusyirwan Ismail has a road length of 5600 meters and a road width of 7 meters. Based on the road layout and calculations, the total number of poles used is 141 poles with a total of 282 light points used. In planning public street lights using solar power on the Nusyirwan Ismail street, the PJUTS used is the All In One PJUTS type, which has advantages in terms of economy, security, and better reliability than using conventional PJUTS.

Social and political foundations of the formation of urban planning and architecture of the cities of Ancient Russia

The subject of the study is the political and social aspect of the formation of town-planning scheme of ancient Russian cities. The object of the study is architecture, urban planning, street layout, urbanonims, social topography of cities such as Kiev, Novgorod, Vladimir, Ryazan. The author examines in detail the following aspects of the topic: the influence of the political situation on the architectural appearance of the city, the social and ethnic composition of the population of cities, the origin of ancient Russian urban toponyms. Particular attention is paid to architecture and urban planning as a source on social and political history, the process of evolution of urban development in the context of foreign policy relations, the influence of domestic political and social factors on it. The main conclusions of the study are that the following trends can be identified in the town-planning scheme of ancient Russian cities: chaotic development at the first stage of development and withdrawal to planning with the strengthening of political power, secondariness of streets in some cities of Ancient Russia, by means of urbanonims of ancient Novgorod, Vladimir and Kiev, it is possible to develop ideas about the social and ethnic composition of the city's population Ancient Russia, to trace the changes in its structure, in its political situation. A special contribution of the author to the study of the topic is the identification of a common architectural element between two religious buildings of different regions and different periods in the context of foreign policy contacts. This element is a promising portal in the Church of St. Paraskevi and in the church of Allenau in the village of Porechye, Kaliningrad region. The novelty of the research lies in the fact that urban planning and architecture of Ancient Russia can serve not only in the format of an art history discipline, but also as a visual illustration for political and social history. At the moment, the architecture and urban planning grid of ancient Russian cities is not considered as a serious source in research related to political power, international relations, and the history of social structures.

Regenerating the logistics industry through the Physical Internet Paradigm: A systematic literature review and future research orchestration

The operations of other businesses rely heavily on the logistics sector, making logistics the most crucial industry. There are multiple issues available in the existing logistics sector including the lack of logistics optimization and unsustainability operations. To deal with these issues, the concept of the Physical Internet (PI) has arisen. For this reason, the current study conducts a comprehensive literature review to determine how PI has emerged within the logistics sector to improve its condition. In this research, we present a comprehensive and in-depth analysis of the present situation of the PI in the logistics literature by conducting a systematic review of 114 publications published in 39 top journals on the topic between 2007 and 2022. This paper makes three significant contributions to the existing literature using such an analysis. To begin with, it provides an overarching context for the part played by the PIin the overall logistics industry. Second, it provides a road layout of the breadth and depth of the research on PI and the overall logistics, including the approaches taken by researchers, regions covered, sectors examined, and theoretical stances taken by those who have explored the topic thus far. Finally, it addresses the conclusions based on the different clusters discovered and the issues of existing logistics systems along with the moderators of influencing the PI and its outcomes. Given the rising significance of PI and channels for sustainability in the logistics sector, this is the first time that an effort has been made to investigate the function of the PI within the context of overall logistics performance. The paper identifies crucial gaps in research and brings to lightdifferent factors that have the potential to shed light on this essential subject. Furthermore, we argue that there is an immediate need to build new business models for enhanced adaptation and execution of the PI strategy, and we urge business managers, academics, and regulators to consider it. In addition, we advocate that professionals scrutinize ways in which the PI approach may be applied to the existing business structures.

Highly Efficient Traffic Planning for Autonomous Vehicles to Cross Intersections Without a Stop

Waiting in a long queue at traffic lights not only wastes valuable time but also pollutes the environment. With the advances in autonomous vehicles and 5G networks, the previous jamming scenarios at intersections may be turned into non-stop weaving traffic flows. Toward this vision, we propose a highly efficient traffic planning system, namely DASHX, which enables connected autonomous vehicles to cross multi-way intersections without a stop. Specifically, DASHX has a comprehensive model to represent intersections and vehicle status. It can constantly process large volumes of vehicle information, resolve scheduling conflicts, and generate optimal travel plans for all vehicles coming toward the intersection in real time. Unlike existing works that are limited to certain types of intersections and lack considerations of practicability, DASHX is universal for any type of 3D intersection and yields the near-maximum throughput while still ensuring riding comfort. To better evaluate the effectiveness of traffic scheduling systems in real-world scenarios, we developed a sophisticated open source 3D traffic simulation platform (DASHX-SIM) that can handle complicated 3D road layouts and simulate vehicles’ networking and decision-making processes. We have conducted extensive experiments, and the experimental results demonstrate the practicality, effectiveness, and efficiency of the DASHX system and the simulator.

A Practical Feeder Planning Model for Urban Distribution System

There is a significant gap between academic research and practical application for power distribution system planning (PDSP). For most of the existing PDSP models in academic research, cost is used as the objective function, and the most common constraints are power flow equality constraints, bus voltage or voltage drop limits, substation and feeder capacity limits, etc. Although various advanced models and methods have been proposed, they are rarely used in real distribution system companies. This paper proposes a new feeder planning model for the urban distribution network considering various practical requirements. According to field investigation, “supply electricity to loads using nearby power sources” is used as the objective, and it is analytically expressed by load moment. Block loads, practical street layout, meshed network configuration, connection mode of feeders, non-crossing requirement of feeders, power supply radius, etc., are all respected and embedded in the model. The proposed model is recast as a mixed integer linear programming (MILP) problem, and it can be solved by the state-of-art commercial solver. The effectiveness and validity of the proposed model are illustrated on a 9-block test system and a real 22-block district distribution system.

Using contextual data to predict risky driving events: A novel methodology from explainable artificial intelligence

Usage-based insurance has allowed insurers to dynamically tailor insurance premiums by understanding when and how safe policyholders drive. However, telematics information can also be used to understand the driving contexts experienced by the driver within each trip (e.g., road types, weather, traffic). Since different combinations of these conditions affect exposure to accidents, this understanding introduces predictive opportunities in driving risk assessment. This paper investigates the relationships between driving context combinations and risk using a naturalistic driving dataset of 77,859 km. In particular, XGBoost and Random Forests are used to determine the predictive significance of driving contexts for near-misses, speeding and distraction events. Moreover, the most important contextual factors in predicting these risky events are identified and ranked through Shapley Additive Explanations. The results show that the driving context has significant power in predicting driving risk. Speed limit, weather temperature, wind speed, traffic conditions and road slope appear in the top ten most relevant features for most risky events. Analysing contextual feature variations and their influence on risky events showed that low-speed limits increase the predicted frequency of speeding and phone unlocking events, whereas high-speed limits decrease harsh accelerations. Low temperatures decrease the expected frequency of harsh manoeuvres, and precipitations increase harsh acceleration, harsh braking, and distraction events. Furthermore, road slope, intersections and pavement quality are the most critical factors among road layout attributes. The methodology presented in this study aims to support road safety stakeholders and insurers by providing insights to study the contextual risk factors that influence road accident frequency and driving risk.

Impact of land consolidation on agricultural decarbonization: Estimation of changes in carbon dioxide emissions due to farm transport

Areas used for agriculture are a large source of carbon emissions, but there is great potential for reducing them. Land consolidation, through the comprehensive reorganization of the spatial arrangement of farms, can reduce emissions as a result of reducing fuel consumption. The subjects of this study are the veracity of this statement and the scope of variation in the potential reduction of carbon emissions. The analysis covered six land consolidation projects in Poland and Turkey, for several agricultural models that differ in the level of fuel consumption.Changes in agricultural road layout resulting from the implementation of land consolidation projects and changes in the number of farm plots and their spatial distribution were considered. The study considered several different levels and structures of fuel consumption on farms. The applied methodology is based on analysis of changes in distance to fields resulting from land consolidation projects, which are then expressed as changes in fuel consumption.The obtained emission reduction results for the studied land consolidation projects were diverse and range from 0.3 to 170 kg CO2/ha/year. The reduction in fuel consumption on farms at the level of individual villages reached a maximum of 32 %, while the average value of this reduction in the entire surveyed set was 12.5 %.The proposed approach increases the accuracy of existing methods for estimating the long-term balance of carbon emissions and carbon accumulation related to the implementation of land consolidation projects. The observed emission reduction values can be considered a significant economic and ecological effect because the effects of these projects persist for at least several decades.

Investigating pedestrian crossing route choice at mid-blocks without crossing facilities: The role of roadside environment

Due to the lack of instructions and regulations, pedestrian crossing areas and routes are usually uncertain at mid-blocks without crossing facilities, resulting in higher crossing risks. Using Unmanned Aerial Vehicle and roadside camera data, this study investigates pedestrian crossing behaviors at mid-blocks without crossing facilities by proposing metrics for characterizing pedestrian crossing routes, including entry point, crossing angle and trajectory shape. This study also contributes to the literature by investigating the role of roadside environment (i.e. pedestrian’s start–end Points of interest (POIs), distribution of curb cuts, roadside parking and bus stops) in explaining pedestrian route choice, which could help with the street layout design at such areas.The results emphasize the attractiveness effects of curb cuts on pedestrians’ choices of entry points. Moreover, crosswalk usage and choosing curb cut as the entry point could contribute to a larger crossing angle. In addition, pedestrians with direct opposite start–end POIs also have a higher inclination of crossing perpendicularly. Pedestrians alighting from roadside-parked cars are more likely to cross with larger angles and complex-curve trajectories. In contrast, crossings with bus stop as the start POI and end POI are related to smaller crossing angles. Finally, practical suggestions are also provided to help with the street layout design and the development of drivers warning facilities, further enhancing pedestrian crossing safety at mid-blocks without crossing facilities.

Intelligibility of Post-War Reconstruction in French Bombed Cities

In the aftermath of the WWII, many French cities faced a great need for reconstruction in response to the heavy destruction caused by the bombardments. Reconstruction plans were developed and implemented at relatively short notice in response to a critical and urgent situation. However, not all cities adopted the same approach: (a) some proposed and implemented a new layout; (b) others tried to recreate the old street layout but with some updates such as widening and alignment; and finally, (c) some have preferred to resort to more targeted interventions. The choice of approach was motivated by various factors associated with the level of destruction, the futuristic vision of the architect or urbanist in charge, or the historic value of the place destroyed. This article assesses the impact of these approaches on the urban tissue by measuring changes in the overall morphology and intelligibility of multiple city centres before and after the reconstruction based on their cadastral maps. Intelligibility is first measured as a configurational property of the street layout and then as a result of public participation in a navigation task using these maps and digital technology that records the speed of movement and trajectories. This allows a comparison between the original street layout and the new one, as well as across the different cities. Drawing on indicators of spatial cognition, this interdisciplinary research approach provides a means to measure and better understand the impact of the reconstruction on the intelligibility of urban environments.

Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal

Road traffic accidents (RTAs) are a problem with repercussions in several dimensions: social, economic, health, justice, and security. Data science plays an important role in its explanation and prediction. One of the main objectives of RTA data analysis is to identify the main factors associated with a RTA. The present study aims to contribute to the identification of the determinants for the type of RTA: collision, crash, or pedestrian running-over. These factors are essential for identifying specific countermeasures because there is a relevant relationship between the type of RTA and its severity. Daily RTA data from 2016 to 2019 in a district of Portugal were analyzed. A statistical multinomial logit model was fitted. The identified determinants for the type of RTA were geographical (municipality, location, and parking areas), meteorological (air temperature and weather), time of the day (hour, day of the week, and month), driver’s characteristics (gender and age), vehicle’s features (type and age) and road characteristics (road layout and type). The multinomial model results were compared with several machine learning algorithms, since the original data of the type of RTA are severely imbalanced. All models showed poor performance. However, when combining these models with ROSE for class balancing, their performance improved considerably, with the random forest algorithm showing the best performance.

Morphological and Fractal Characteristics of City Road Networks from Philippine Metropolitan Regions

City road networks evolve from the fundamental need to connect various locations and to subdivide available space, especially in large urban areas. No two cities are exactly the same, however, and the differences manifest themselves in the layout of roads across their geographical regions. In this work, the fractal dimensions of urban roads from the three major metropolitan regions of the Philippines were investigated, along with the distributions of dimensionless spatial metrics for characterizing roads and road-bounded blocks. The dimensionless metrics reveal the commonalities, particularly the road and block motifs found in the urban road network tapestry. On the other hand, the fractal dimensions hint at the difference in levels of urbanization of the various cities and municipalities, which are considered subject to geographical constraints. This research adds to the growing literature with a complexity perspective on urban systems by reporting on an archipelagic road network data set. From a practical perspective, this work is deemed to be a useful first step towards an even deeper quantitative analysis of these regional economic centers and its insights may be used for drafting effective policy measures for management and further development.

Exploring the Relationship between Urban Street Spatial Patterns and Street Vitality: A Case Study of Guiyang, China.

Understanding how street spatial patterns are related to street vitality is conducive to enhancing effective urban and street design. Such analysis is facilitated by big data technology as it enables more accurate methods. This study cites data from street view imagery (SVI) and points of interest (POI) to assess street vitality strength after the classification of street spatial and vitality types to explore the relationship between street spatial patterns and street vitality with a further discussion on the layout features of street vitality and its strength in various street spatial patterns. First, street spatial patterns are quantified based on SVI, which are further classified using principal component analysis and cluster analysis; POI data are then introduced to identify street vitality patterns and layout, and the strength of street vitality is evaluated using spatial overlay analysis. Finally, relevance analysis is explored to cast light on the relationship between street vitality layout and street spatial patterns by overlaying street spatial pattern, street vitality types, and street vitality strength in the grid cells. This paper takes the urban area of Guiyang, China, as an example and the analysis shows that a pattern is discovered in Guiyang regarding the layout of street vitality types and vitality strengths across different street spatial patterns; compact street spaces should be prioritized in designing street space renovation; and cultural leisure vitality is most adaptive to street spatial patterns. Based on big data and using grids to understand the intrinsic relationship between street spatial patterns and the type and strength of street vitality, this paper brings more options to urban street studies in terms of perspective and methodology.

Deep Learning with Attention Mechanisms for Road Weather Detection

There is great interest in automatically detecting road weather and understanding its impacts on the overall safety of the transport network. This can, for example, support road condition-based maintenance or even serve as detection systems that assist safe driving during adverse climate conditions. In computer vision, previous work has demonstrated the effectiveness of deep learning in predicting weather conditions from outdoor images. However, training deep learning models to accurately predict weather conditions using real-world road-facing images is difficult due to: (1) the simultaneous occurrence of multiple weather conditions; (2) imbalanced occurrence of weather conditions throughout the year; and (3) road idiosyncrasies, such as road layouts, illumination, and road objects, etc. In this paper, we explore the use of a focal loss function to force the learning process to focus on weather instances that are hard to learn with the objective of helping address data imbalances. In addition, we explore the attention mechanism for pixel-based dynamic weight adjustment to handle road idiosyncrasies using state-of-the-art vision transformer models. Experiments with a novel multi-label road weather dataset show that focal loss significantly increases the accuracy of computer vision approaches for imbalanced weather conditions. Furthermore, vision transformers outperform current state-of-the-art convolutional neural networks in predicting weather conditions with a validation accuracy of 92% and an F1-score of 81.22%, which is impressive considering the imbalanced nature of the dataset.