Use of Heading Direction for Recreating the Horizontal Alignment of an Existing Road

This article proposes a new method for fitting the horizontal alignment of a road to a set of (x, y) points. Those points can be obtained from digital imagery or GPS‐data collection. Unlike current methods that represent road alignment through its curvature, the proposed method describes the horizontal alignment as a sequence of headings. An analytic–heuristic approach is introduced. The proposed method produces unique solutions even for complex horizontal alignments. Some examples and a case study are presented. This solution may not be accurate enough for road redesign, but it allows researchers and departments of transportation to obtain accurate geometric features.     

GPS–GIS-Based Procedure for Tracking Vehicle Path on Horizontal Alignments

Abstract:   This article presents a global positioning system–geographic information system (GPS–GIS)-based procedure for the deduction of the horizontal alignment of a road based on the path of a control vehicle. Using differential GPS surveying, field data were collected at a 0.1-second interval, under different speed conditions on a 25-km section of a two-lane rural highway in eastern Ontario. The raw GPS data were post-processed to filter out the possible errors and then imported into a GIS environment for analysis and interpretation of the results. An extension for ArcView was written to determine the geometric features of the highway horizontal alignment, including the tangents, spirals, and circular curves. Values were obtained for the radius and length of nine circular curves, length of spirals, and the lateral position of the vehicle path along the straight and curved segments. These values were compared with the same features of the actual highway alignment. The results showed that the developed procedure and ArcView extension could produce the horizontal alignment of a road quickly, accurately, and for a relatively low cost. In addition to the extraction of the horizontal alignment of a road, the procedure can be used to track the actual vehicle path under normal driving conditions and compare it with the horizontal alignment of a road in an investigation concerning driver behavior.     

A sequential exploration algorithm for the design optimization of horizontal road alignment

Most computer-aided optimization procedures for horizontal alignment optimization of roads require the use of information such as horizontal points of intersection (PIs) to determine an alignment. In these methods, to obtain parameters such as the radius of the curve corresponding to a specific PI, the previous and next PIs must be known. In this paper, a sequential exploration algorithm (SEA) is proposed, and the algorithm continuously explores the entire optimization space through certain steps. Only the parameters of the previous node are required to determine the current node's parameters during the exploration process, avoiding the tight coupling between PIs in traditional optimization algorithms. Furthermore, the proposed SEA does not require assumptions about the positions and numbers of the PIs, and it can design near-optimal road alignments that match geometric restrictions and automatically take transition curves into account. Another feature of the proposed algorithm is that it directly optimizes the geometric element parameters based on the actual milepost, and it is a fully collaborative optimization approach that does not require secondary optimization nesting during the optimization process. Analyses comparing the optimization effects of different algorithms are performed on a numerical case, that is, a problem of avoiding obstacles, and two actual cases from the literature, that is, a new road design problem and an existing road reconstruction problem. It is discovered that the proposed SEA results in an approximately 3% to 10% improvement in optimization effects when compared to two current cutting-edge optimization algorithms. This work offers a new perspective on road alignment optimization by merging discrete and continuous optimizations, with a discrete component handling optimization accuracy and a continuous component handling real optimization.     

Automatic geometry measurement for curved ramps using inertial measurement unit and 3D LiDAR system

Although road geometry data can be automatically collected using instruments mounted on survey vehicle, measurement of curved ramp geometry is still of low effectiveness and accuracy due to manual or semi-automatic detection of PC (Point of Curvature)/PT (Point of Tangent) as well as influences of vehicle vibration and wandering. In this study a new method is presented for automatic measurement of ramp geometry in network level using IMU (Inertial Measurement Unit) and 3D LiDAR (Light Detection And Ranging) system. Firstly, horizontal alignment measurements are implemented: 1) an improved K-Mean clustering method and linear fitting method are integrated for automatic PC/PT station detection; 2) an algorithm is developed for automatic lane marking identification and localization for vehicle's trajectory calibration; 3) curve radius and length are measured based on roadway centerline. Subsequently, pavement slope is calibrated using IMU and transverse profiling data. Finally, nine segments are chosen from highway ramps as test bed, and validation tests are conducted using the field measurement. The test results show the average errors for curve detection and curve radius measurement are 5.89% and 1.99% respectively, and the P-value for longitudinal and cross slope measurement are 0.621 and 0.989 respectively, which indicate the proposed method is robust in ramp geometry measurement. The significant of the proposed method is three folds. First, it integrates and synchronizes the IMU and 3D LiDAR system in geometry measurement. Second, it solves the common problems of mobile survey on vehicle wandering and vibration. Third, it is of high accuracy and effectiveness, and can be used for roadway survey in network level.     

An Unmanned Aerial Vehicle‐Based Imaging System for 3D Measurement of Unpaved Road Surface Distresses1

Abstract: Road condition data are important in transportation management systems. Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of pavement condition data. However, the assessment of unpaved road conditions has been rarely addressed in transportation research. Unpaved roads constitute approximately 40% of the U.S. road network, and are the lifeline in rural areas. Thus, it is important for timely identification and rectification of deformation on such roads. This article introduces an innovative Unmanned Aerial Vehicle (UAV)‐based digital imaging system focusing on efficient collection of surface condition data over rural roads. In contrast to other approaches, aerial assessment is proposed by exploring aerial imagery acquired from an unpiloted platform to derive a three‐dimensional (3D) surface model over a road distress area for distress measurement. The system consists of a low‐cost model helicopter equipped with a digital camera, a Global Positioning System (GPS) receiver and an Inertial Navigation System (INS), and a geomagnetic sensor. A set of image processing algorithms has been developed for precise orientation of the acquired images, and generation of 3D road surface models and orthoimages, which allows for accurate measurement of the size and the dimension of the road surface distresses. The developed system has been tested over several test sites with roads of various surface distresses. The experiments show that the system is capable for providing 3D information of surface distresses for road condition assessment. Experiment results demonstrate that the system is very promising and provides high accuracy and reliable results. Evaluation of the system using 2D and 3D models with known dimensions shows that subcentimeter measurement accuracy is readily achieved. The comparison of the derived 3D information with the onsite manual measurements of the road distresses reveals differences of 0.50 cm, demonstrating the potential of the presented system for future practice.     

A 3D Model for Optimizing Infrastructure Costs in Road Design

In this article, the optimal design of a road joining two terminals is investigated. A geometric model is proposed including horizontal transition curves and vertical curves, obtaining parameterizations for the central axis of the road as well as for its entire surface. These parameterizations allow to express and compute, with great simplicity, the major infrastructure costs, including land acquisition, clearance, pavement, maintenance, and earthwork, where multiple layers of materials with different costs can be handled. The road design problem is formulated as a smooth constrained optimization problem and a two‐stage algorithm is suggested for its numerical resolution. Finally, numerical results are presented in an academic test and in a case study that propose designing a bypass in a Spanish national road (N‐640) to avoid crossing Monterroso's town center.     

A Method to Identify and Classify the Vertical Alignment of Existing Roads

A detailed knowledge of the geometric characteristics of already built roads is necessary for various tasks related to their exploitation. However, sufficiently accurate or updated information about their geometric characteristics is frequently not available. Therefore, it is common to collect data of road geometry normally by means of a vehicle equipped with various sensors and, from the data obtained, generate analytically a geometric design that fits reality as closely as possible. There are several procedures to recreate the horizontal alignment of existing roads. However, no such effort has been made for vertical alignment. Knowledge of vertical profile's geometry is important for safety traffic studies as sight distance. This article presents a method of obtaining the geometrical elements of the vertical profile of highways through the longitudinal slope of their centerline points. The procedure has been successfully validated by its application on five rural highways in Spain.     

A semi-automated method for extracting vertical clearance and cross sections in tunnels using mobile LiDAR data

The applications of laser scanning technology are rapidly expanding in the civil engineering domain. LiDAR technology is now commonly used in the surveying and monitoring of large infrastructures. In particular, tunnels have become key transport infrastructures, subjected to maintenance processes that allow quality checks for tunnel modifications or tunnel clearance and profile checks.The research described in this paper targets developing an approach to semi-automatically retrieve the tunnel vertical clearance based on ground based mobile LiDAR data. The steps of this approach include extraction of cross sections orthogonal to the vehicle trajectory and road markings based on radiometric information, and conversion of cross section to a two-dimensional profile to estimate the vertical clearance.The validation of the developed approach is done using real-life case study, a road tunnel in southern Galicia, Spain. An accuracy of 100% in detection of cross sections is achieved. Only one of the cross sections shows a relative error in vertical clearance measurement higher than 1%. The results demonstrated the effectiveness of the developed approach for computing vertical clearances and demonstrating that tunnel management activities can definitely benefit from using mobile LiDAR by minimizing survey time and increasing productivity in dangerous environments.     

A Method for Automatically Recreating the Horizontal Alignment Geometry of Existing Railways

Periodic recreation of existing railway horizontal alignment geometry is needed for smoothing the deviations arising from train operations. It is important for calibrating track and rebuilding existing railways to ensure safety and comfort. Track calibration repairs the existing distorted track centerline to match the smoothed recreated alignment, which may differ considerably from the originally designed track centerline. Identifying the boundaries of all the geometric elements including tangents, circular curves, and transition curves is the key problem. Existing methods recreate the horizontal alignment semi‐automatically and can only generate a locally optimized solution while considering a few constraints. Based on the principle that the attributions of all the measured points to geometric elements should be consistent with the ranges of recreated geometric elements (i.e., for points‐alignment consistency), a method called swing iterations is proposed to reclassify point placements and identify all the tangents, circular curves, and transition curves simultaneously. In a swing iteration, the boundary of a geometric element segment repeatedly changes from left to right, then from the right to left, and finally stabilizes. Before the swing iterations, preliminary tangents and curves are identified based on the heading gradient (i.e., the rate of change of heading), and are set as initial values for the swing iterations. A genetic algorithm is developed to further refine the entire recreated alignment after the swing iterations. In the above processes, multiple constraints are handled. Applications demonstrate that this method can identify all horizontal geometric elements automatically and generate an optimized recreated alignment geometry for an existing railway while satisfying all the applicable constraints.     

Road Infrastructure Data Acquisition Using a Vehicle-Based Mobile Mapping System

Abstract:   This study presents the technology of a vehicle-based mobile mapping system to maintain an updated transportation database. The mobile mapping system that integrates the global positioning system (GPS), the inertial navigation system (INS), and digital cameras has been developed to collect data on position and attributes of road infrastructure. The vehicle-based mobile mapping system works by having the GPS and INS record the position and attitude data, and digital cameras take road images. The stereovision system can determine the position of objects that are visible on the image pair in the global coordinate system with GPS and INS data. As field data acquisition is a very expensive task, a mobile mapping system offers a greatly improved solution. In this study, we successfully created a road infrastructure map with mobile mapping technology and proposed automatic algorithms for detecting and identifying road signs from road images. The proposed detection algorithm includes line and color region extraction processes and uses the Hopfield neural networks. The identification algorithm uses seven invariant moments and parameters that present geometric characteristics. With this combined method, we could successfully detect and identify road signs.     

A Polynomial Parametric Curve (PPC‐CURVE) for the Design of Horizontal Geometry of Highways

Abstract: The use of transition curves in the road design is a solution to make the gradual evolution of curvature and, at the same time, to improve the comfort level of drivers and provide a good visual perception of the curve. Clothoid is the most widely used transition curve in road design so far, because it ensures the continuity of the curvature with the other geometric elements of the alignment. However, several researches allow the use of polynomial functions as an alternative to the clothoid. Such use is permitted in accordance with the verification of allowable vehicle–road dynamics. Polynomial solutions of transition curves can be a valuable alternative for the traditional solutions (first transition curve, circular arc, second transition curve). A fifth‐degree polynomial parametric curve (PPC‐curve) for the design of highway alignment is proposed in this article. An analysis of the theoretical aspects to solve more complex geometrical problems recurring in practical highway geometric design is carried out. With regard to this problem, a shape parameter giving flexibility to the polynomial solution in relation to project needs has also been introduced. To implement the procedure, an original computer program has been developed. Numerical applications have been performed for comparison with the traditional solutions.     

Automated Road Sign Inventory System Based on Stereo Vision and Tracking

Abstract: Detection, recognition, and positioning of road signs are critical components of a roadway asset management system. In this research, a stereo vision‐based system is developed to conduct automated road sign inventory. The system in real time integrates and synchronizes the data streams from multiple sensors of high‐resolution cameras, Differential Global Positioning System receivers, Distance Measurement Instrument, and Inertial Measurement Unit. Algorithms are developed based on data sets from the multiple positioning sensors to determine the positions of the moving vehicle and the orientation of the cameras. The key findings from the research include feature extraction and analysis that are applied for automated sign detection and recognition in the Right‐of‐Way (ROW) images, implementing a tracking algorithm of the candidate sign region among the image frames so the same signs are not counted more than once in an image sequence, and implementing stereo vision technique to compute the world coordinates of the road sign from the stereo‐paired ROW images. Particular techniques are employed to conduct all data acquisition and analysis in real time onboard the vehicle. This system is an advanced alternative to traditional inventory methods in terms of safety and efficiency.     

Estimating dynamic origin–destination demand: A hybrid framework using license plate recognition data

This article proposes a hybrid framework for estimating dynamic origin–destination (OD) demand that fully exploits the information available in license plate recognition (LPR) data. A Bayesian path reconstruction model is initially developed to replenish the lost information resulting from the recognition error and insufficient coverage rate of the LPR system. The link flows, initial OD demand, left‐turning flows, and partial path flows are derived based on the reconstructed data. Subsequently, with the information derived, a two‐step ordinary least squares (OLS) OD estimation model is formulated, which incorporates the output from the Bayesian model and coestimates the OD demand and assignment matrix. The proposed framework is qualitatively validated using the real‐world LPR data collected from Langfang City, Hebei Province, China, and is quantitatively validated using the synthesized simulation data for the simplified road network of Langfang. The results show that the proposed model can estimate OD demand distribution with a mean absolute percentage error (MAPE) of about 30%. We also tested the model with different LPR coverage rates, with results showing that an LPR coverage rate of over 50% is required to obtain reasonable results.     

Numerical verification of properties of the fictitious elastic axis in asymmetric multistorey buildings

In the present paper, the properties of the vertical fictitious elastic axis and of the horizontal fictitious principal axes of multistorey buildings were investigated using an extended parametric study. The parametric investigation has proved that the fictitious elastic centre, i.e. the point from which the vertical fictitious elastic axis (optimum torsion axis) and the horizontal fictitious principal axes of a multistorey building pass through, has properties which are close to the properties of the real elastic centre and the real horizontal principal axes of the single‐storey building. Therefore, the definition of the static eccentricity and torsional stiffness radii of gyration of a multistorey building are achieved using the fictitious elastic centre of the building. Copyright © 2005 John Wiley & Sons, Ltd.     

Optimizing Design of Highway Horizontal Alignments: New Substantive Safety Approach

Abstract:   Highway agencies are continually facing safety problems on highways, especially on horizontal alignments. Traditionally, the geometric design implicitly considers safety through satisfying minimum design requirements for different geometric elements. This article presents a new substantive-safety approach for the design of horizontal alignments based not only on minimum design guidelines, but also on actual collision experience. The curve radii, spiral lengths, lane width, shoulder width, and tangent lengths are determined to optimize the mean collision frequency along the highway. The model allows the parameters of the horizontal alignment to vary within specified ranges. The model also considers any specified physical obstructions in selecting the optimal alignment. Collision experience is addressed using existing collision prediction models for horizontal alignments and cross sections. The model is applicable to two-lane rural highways for which collision prediction models exist. Application of the model is presented using numerical examples. The proposed substantive-safety approach takes horizontal alignment design one step further beyond the minimum-guideline concept, and therefore should be of interest to highway designers.     

A modified motion planning algorithm for horizontal highway alignment development

A horizontal alignment can be represented by three key factors: number of horizontal points of intersection (HPIs), their locations, and corresponding horizontal curve radii. Deciding all the three factors simultaneously requires extensive effort, which is not practically feasible in the manual alignment development process. Most available computer‐aided methods prioritize some or all the three factors in the automated alignment development processes. However, approximation in HPI location or pre‐selection of HPI number and curve radius are the few limitations of these methods. This study presents a modified motion‐planning based algorithm for developing new horizontal alignments with optimized costs and impacts. It simultaneously uses a low‐discrepancy sampling technique to develop increasingly dense potential HPIs, rapidly exploring random trees to find a suitable number of intermediate HPIs at appropriate locations and sequential quadratic algorithm to select optimally fitted curve radii. The proposed algorithm is integrated with the GIS database for realistic location‐dependent cost and environmental impact assessment. Two real‐world study areas were selected to compare the results with the one reported in the literature and to evaluate backtracking capability. Results indicated the proficiency of the proposed algorithm in developing new alignments. The sensitivity analyses revealed the effect of design speed and right‐of‐way width on the alignment generation. The proposed algorithm can automate the new horizontal highway alignment development process and support highway engineers in planning and development.     

Modeling Road Centerlines and Predicting Lengths in 3-D Using LIDAR Point Cloud and Planimetric Road Centerline Data

Abstract:   Transportation is one of a few engineering domains that work with linear objects—roads. Accurate road length information is critical to numerous transportation applications. Road lengths can be obtained via technologies such as ground surveying, global positioning systems (GPS), and Distance Measurement Instruments (DMI). But using these methods for data collection and length determination is time-consuming, labor intensive, and costly. The purpose of this study was to assess the accuracy and feasibility of an alternative. This article reports on a study that provides an alternative to obtaining road centerline lengths by measurement; instead it proposes using geographic information systems (GIS) and light detection and ranging (LIDAR) point cloud data. In this study, a three-dimensional (3-D) vector model based on linear referencing systems (LRS) concepts was developed to represent road centerlines in a 3-D space and to predict their 3-D lengths. A snapping approach and an interpolation approach to obtain 3-D points along lines when working with LIDAR point clouds were proposed and discussed. Quality control measures were initiated to validate the approach. The accuracy of the predicted 3-D distances was evaluated via a case study by comparing them to distances measured by DMI. The results were also compared to road lengths obtained by draping planimetric road centerlines on digital elevations models (DEMs) constructed from LIDAR points. The effects of the average density of 3-D points on the accuracy of the predicted distances were evaluated. This study concluded that the proposed 3-D approach using LIDAR data was efficient in obtaining 3-D road lengths with an accuracy that was satisfactory for most transportation applications.     

Surrogate‐Based Optimization of Expensive‐to‐Evaluate Objective for Optimal Highway Toll Charges in Transportation Network

This article adopts a family of surrogate‐based optimization approaches to approximate the response surface for the transportation simulation input–output mapping and search for the optimal toll charges in a transportation network. The computational effort can thus be significantly reduced for the expensive‐to‐evaluate optimization problem. Meanwhile, the random noise that always occurs through simulations can be addressed by this family of approaches. Both one‐stage and two‐stage surrogate models are tested and compared. A suboptimal exploration strategy and a global exploration strategy are incorporated and validated. A simulation‐based dynamic traffic assignment model DynusT (Dynamic Urban Systems in Transportation) is utilized to evaluate the system performance in response to different link‐additive toll schemes implemented on a highway in a real road transportation network. With the objective of minimizing the network‐wide average travel time, the simulation results show that implementing the optimal toll predicted by the surrogate model can benefit society in multiple ways. The travelers gain from the 2.5% reduction (0.45 minutes) of the average travel time. The total reduction in the time cost during the extended peak hours would be around US$65,000 for all the 570,000 network users assuming a US$15 per hour value of time. Meanwhile, the government benefits from the 20% increase of toll revenue compared to the current situation. Thus, applying the optimized pricing scheme in real world can be an encouraging policy option to enhance the performance of the transportation system in the study region.     

A Customized Particle Swarm Method to Solve Highway Alignment Optimization Problem

Abstract: Optimizing highway alignment requires a versatile set of cost functions and an efficient search method to achieve the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. Moreover, because of the infinite number of possible solutions for the problem and the continuous search space, highway alignment optimization is a complex problem. In this study, a customized particle swarm optimization algorithm was used to search for a near‐optimal highway alignment, which is a compound of several tangents, consisting of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet the constraints of highway design while minimizing total cost as the objective function. The model uses geographical information system (GIS) maps as an efficient and fast way to calculate right‐of‐way costs, earthwork costs, and any other spatial information and constraints that should be implemented in the design process. The efficiency of the algorithm was verified through a case study using an artificial map as the study region. Finally, we applied the algorithm to a real‐world example and the results were compared with the alignment found by traditional methods.     

Collecting comprehensive traffic information using pavement vibration monitoring data

Traffic data is essential for intelligent traffic management and road maintenance. However, the enormous effort used for data collection and analysis, combined with conventional approaches for traffic monitoring, is inefficient due to its high energy consumption, high cost, and the nonlinear relationships among various factors. This article proposes a new approach to obtain traffic information by processing raw data on pavement vibration. A large amount of raw data was collected in real time by deploying a vibration‐based in‐field pavement monitoring system. The data was processed with an efficient algorithm to achieve the monitoring of the vehicle speed, axle spacing, driving direction, location of the vehicle, and traffic volume. The vehicle speed and axle spacing were back‐calculated from the collected data and verified with actual measurements. The verification indicated that a reasonable precision could be achieved using the developed methods. Vehicle types and vehicles with an abnormal weight were identified by a three‐layer artificial neural network and the k‐means++ cluster analysis, respectively, which may help law enforcement in determining on an overweight penalty. A cost and energy consumption estimation of an acceleration sensing node is discussed. An upgraded system with low cost, low energy consumption, and self‐powered monitoring is also discussed for enabling future distributed computing and wireless application. The upgraded system might enhance integrated pavement performance and traffic monitoring.