Path planning is a critical part for improving the driving safety and driver comfort of autonomous vehicles (AVs), especially in complex maneuvering conditions. In addition, different drivers have ...different preferences for AVs, thus, how to provide personalized trajectories for different drivers is a vital issue for AVs. The collision-free path planning problem in conditions with large road curvatures is investigated in this paper, with the consideration of environmental safety constraints, drivers' comfort, vehicle actuator constraints, etc. Firstly, a Driver-Vehicle-Road (DVR) system is established based on the combination of the kinematic vehicle model and the two-point visual preview driver model, such that the driver's individual handling characteristics can be considered in the controller. The kinematic vehicle model is modified to have the similar understeering characteristics with those of the nonlinear full car models, and then the proposed DVR system can satisfy different groups of drivers and cars. Secondly, for environmental constraints, a new artificial potential field (APF) method is proposed, which can form a banana-shaped 3-D dangerous imaginary mountain and a lane boundary cliff suitable for arbitrary curvature roads to generate a collision-free evasive path. Finally, the Linear-Time-Varying (LTV) model predictive control (MPC) method is adopted to design the path planner. The CarSim-Simulink joint simulation illustrates that with the proposed planner, the host vehicle is capable of avoiding obstacles with a safer and more comfortable maneuver on large curvature roads. And the proposed path planner can provide individually safe trajectories for different drivers with good maneuverability.
Abstract
Road preservation is a road handling activity starting from prevention, maintenance and repairs needed to maintain road conditions to function optimally to serve traffic. Preservation ...activities include routine maintenance work, rehabilitation, reconstruction, and widening to standards. The purpose of this study is to evaluate the indicators used in the implementation of road preservation activities based on the level of importance and satisfaction of the perceptions of stakeholders involved in road conservation activities in the West Nusa Tenggara National Road Implementation Agency. The indicators used in this study are structural indicators and functional indicators. The hole parameter in the structural indicator is an important parameter in the implementation in the implementation of preservation activities in the West Nusa Tenggara National Road Implementation Center with the satisfaction level in handling of very satisfied.
Road intersection data have been used across a range of geospatial analyses. However, many datasets dating from before the advent of GIS are only available as historical printed maps. To be analyzed ...by GIS software, they need to be scanned and transformed into a usable (vector-based) format. Because the number of scanned historical maps is voluminous, automated methods of digitization and transformation are needed. Frequently, these processes are based on computer vision algorithms. However, the key challenges to this are (1) the low conversion accuracy for low quality and visually complex maps, and (2) the selection of optimal parameters. In this paper, we used a region-based deep convolutional neural network-based framework (RCNN) for object detection, in order to automatically identify road intersections in historical maps of several cities in the United States of America. We found that the RCNN approach is more accurate than traditional computer vision algorithms for double-line cartographic representation of the roads, though its accuracy does not surpass all traditional methods used for single-line symbols. The results suggest that the number of errors in the outputs is sensitive to complexity and blurriness of the maps, and to the number of distinct red-green-blue (RGB) combinations within them.
Achieving remote and rural road safety is a global challenge, exacerbated in Australia and New Zealand by expansive geographical variations and inconsistent population density. Consequently, there ...exists a rural-urban differential in road crash involvement in Australasia. New vehicle technologies are expected to minimise road trauma globally by performing optimally on high quality roads with predictable infrastructure. Anecdotally, however, Australasia’s regional and remote areas do not fit this profile. The aim of this study was to determine if new vehicle technologies are likely to reduce road trauma, particularly in regional and remote Australia and New Zealand. An extensive review was performed using publicly available data. Road trauma in regional and remote Australasia was found to be double that of urban regions, despite the population being approximately one third of that in urban areas. Fatalities in 100 km/h + speed zones were overrepresented, suggestive of poor speed limit settings. Despite new vehicle ownership in regional and remote Australasia being comparable to major cities, road infrastructure supportive of new vehicle technologies appear lacking, with only 1.3–42% of all Australian roads, and 67% of all New Zealand roads being fully sealed. With road quality in regional and remote areas being poorly mapped, the benefits of Advanced Driver-Assistance Systems (ADAS) technologies cannot be realised despite the fact new vehicles with these technologies are penetrating the fleet. Investments should be made into sealing and separating roads but more importantly, for mapping the road network to create a unified tracking system which quantifies readiness at a national level.
Roads have numerous negative impacts for mammals, but may also serve as attractants due to altered vegetation or provisioning of resources.
We reviewed the use of roads and their associated features ...by mammals, in order to understand the ecological factors contributing to road use.
We documented 129 studies that recorded road use by 116 mammalian species, spanning 15 orders and 35 families, in six continents. Carnivora was the most common order (40 species, 34% of all 116 species), followed by Artiodactyla (24 species, 20%) and Rodentia (21 species, 18%). The species were placed in the IUCN categories Least Concern (88 species, 76% of all 116 species), Vulnerable (11 species, 9%), Near Threatened (9 species, 8%), Endangered (6 species, 5%), and Critically Endangered (2 species, 2%).
We assigned road use to five ecological categories, reflecting the reason for it, with subcategories where appropriate: (1) communication; (2) foraging (subcategories: anthropogenic food, herbivory, predation, salt, scavenging, water); (3) movement (subcategories: bridges, environmental alterations, habitat connectivity); (4) refuge (subcategories: avoidance, burrowing and denning, cover, roosting); and (5) thermoregulation. Foraging, movement, and refuge were the most common uses.
Roads provide a variety of resources to mammals, but road use is highly dynamic in time and space. We suggest that the use of roads by mammals is extensive, both geographically and taxonomically. Road use is likely to influence mammalian ecology while contributing to the risk of collisions with vehicles.
We reviewed the ecological factors that contribute to use of roads by mammals. We documented 129 studies that recorded road use by 116 mammalian species, spanning 15 orders and 35 families, in six continents. Reasons for road use included communication, foraging, movement, refuge and thermoregulation. We suggest that use of roads by mammals is geographically and taxonomically widespread, and likely influences mammalian ecology while contributing to risk of vehicle collisions.
There are hundreds of millions of kilometers of paved roads and many people live in proximity. Pollution from road transportation is a well-documented problem potentially leading to chronic health ...impacts. However, research on the raw material production, construction, operation, maintenance, and end-of-life phases of paved roads, and corresponding supply chains, is generally limited to energy consumption and greenhouse gas emissions. No previous research efforts on the life-cycle stages of pavements and road operation connect pollutant emission inventories to intake of inhaled pollutants and resulting damages to exposed populations. We have developed a first-of-its-kind model quantifying human exposure to fine particulate matter (PM2.5) due to emissions from routine pavement resurfacing and vehicle operation. We utilize the Intervention Model Pollution Source-Receptor Matrix to calculate marginal changes in ground-level PM2.5 concentrations and resulting exposure intake from a spatially resolved primary and secondary PM2.5 emission precursors inventory. Under a scenario of annual road-resurfacing practices within the San Francisco Bay Area in California (population: 7.5 million), resurfacing activities, material production and delivery (i.e. cement, concrete, aggregate, asphalt, bitumen), and fuel (i.e. gasoline, diesel) supply chains contribute almost 65% to the annual PM2.5 intake from all the sources included in the study domain (the remaining 35% being due to on-road tailpipe emissions). Exposure damages range from $170 to $190 million (2019 USD). Complete electrification of on-road mobile sources would reduce annual intake by 64%, but a sizable portion would remain from material supply chains, construction activities, and brake and tire wear. Future mitigation policies should be enacted equitably. Results show that people of color experience higher-than-average PM2.5 exposure disparities from the emission sources included in the study, particularly from material production.
Forestry best management practices (BMPs) reduce sedimentation by minimizing soil erosion and trapping sediment. These practices are particularly important in relation to road construction and use ...due to the heightened potential for sediment delivery at stream crossings. This study quantifies the implementation and effectiveness of BMPs at 75 randomly selected forest road stream crossings on recent timber harvests in the Mountains, Piedmont, and Coastal Plain regions of Virginia. Road characteristics at stream crossings were used to estimate erosion using the Universal Soil Loss Equation for Forests and the Water Erosion Prediction Project for Roads. Stream crossings were evaluated based on the Virginia Department of Forestry (VDOF) BMP manual guidelines and categorized as BMP−, BMP‐standard, or BMP+ based on the quality of road template, drainage, ground cover, and stream crossing structure. BMP implementation scores were calculated for each stream crossing using VDOF audit questions. Potential erosion effects due to upgrading crossings were estimated by adjusting ground cover percentage and approach length parameters in the erosion models. Results indicate that erosion rates decrease as BMP implementation scores increase (p < 0.05). BMP‐standard and BMP+ ratings made up 83% of crossings sampled, with an average erosion rate of 6.8 Mg/ha/yr. Hypothetical improvements beyond standard BMP recommendations provided minimal additional erosion prevention.
Research Impact Statement: Erosion rates at haul road stream crossings decreased as the implementation of water quality best management practices increased. Most crossings were found to be at recommended BMP levels or above.
A user's perception of road surface conditions is usually measured by a subjective 1-to-5 scale defined as the Present Serviceability Rating (PSR). The subjectivity associated with the scale can ...result in different PSR values for the same pavement section. In this paper, we use multivariate data analysis to identify potential groups of users sharing similar perceptions on the condition of urban roads. We conducted a survey of 137 drivers of different modalities (bus, car, taxi, truck) after they had driven over some selected road sections in Barranquilla, Colombia. The survey included socioeconomic questions and a rating questionnaire containing a list of statements related to the ride quality and the acceptance of possible pavement defects. The study included 115 urban road sections with different pavement surfaces and geometric characteristics (e.g. slopes, lane width). We used factor analysis to identify two distinct user latent preferences while driving over urban roads. Then, we applied cluster analysis on the latent preferences. Results suggest a possible classification for surveyed participants into (a) those wanting more infrastructure investment to guarantee an excellent ride quality, and (b) those who are more tolerant toward pavement surfaces in poor condition. We found significant differences in the mean rate of acceptance of urban roads within groups, suggesting that more experienced drivers tend to be more sensitive when riding over pavements in poor condition. Ignoring these differences in the preference of raters could lead to biased results when evaluating the level of pavement serviceability in urban contexts.
► Network fundamental diagram is exploited to improve mobility in saturated traffic conditions. ► Based on a simple but efficient feedback control structure, gating is applied to control urban ...congestion. ► Application of the gating strategy leads to substantial improvements compared to the non-gating case.
Traffic signal control for urban road networks has been an area of intensive research efforts for several decades, and various algorithms and tools have been developed and implemented to increase the network traffic flow efficiency. Despite the continuous advances in the field of traffic control under saturated conditions, novel and promising developments of simple concepts in this area remains a significant objective, because some proposed approaches that are based on various meta-heuristic optimization algorithms can hardly be used in a real-time environment. To address this problem, the recently developed notion of network fundamental diagram for urban networks is exploited to improve mobility in saturated traffic conditions via application of gating measures, based on an appropriate simple feedback control structure. As a case study, the proposed methodology is applied to the urban network of Chania, Greece, using microscopic simulation. The results show that the total delay in the network decreases significantly and the mean speed increases accordingly.
With the ever-increasing emphasis on maintaining road assets to a high standard, the need for fast accurate inspection for road distresses is becoming extremely important. Surface distresses on roads ...are essentially three dimensional (3-D) in nature. Automated visual surveys are the best option available. However, the imaging conditions, in terms of lighting, etc., are very random. For example, the challenge of measuring the volume of the pothole requires a large field of view with a reasonable spatial resolution, whereas microtexture evaluation requires very accurate imaging. Within the two extremes, there is a range of situations that require 3-D imaging. Three-dimensional imaging consists of a number of techniques such as interferometry and depth from focus. Out of these, laser imagers are mainly used for road surface distress inspection. Many other techniques are relatively unknown among the transportation community, and industrial products are rare. The main impetus for this paper is derived from the rarity of 3-D industrial imagers that employ alternative techniques for use in transportation. In addition, the need for this work is also highlighted by a lack of literature that evaluates the relative merits/demerits of various imaging methods for different distress measurement situations in relation to pavements. This overview will create awareness of available 3-D imaging methods in order to help make a fast initial technology selection and deployment. The review is expected to be helpful for researchers, practicing engineers, and decision makers in transportation engineering.
PDF
