Road Properties Research Articles

Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data

Road segments with identical site-specific attributes often exhibit significantly different crash counts due to unobserved reasons. The extent of unobserved heterogeneity associated with a road feature is to be estimated prior to selecting the relevant safety treatment. Moreover, crash count data is often over-dispersed and spatially correlated. This paper proposes a spatial negative binomial specification with random parameters for modeling crash counts of contiguous road segments. The unobserved heterogeneity is incorporated using a finite multi-variate normal mixture prior on the random parameters; this allows for non-normality, skewness in the distribution of the random parameters, facilitates correlation across the random parameters, and relaxes any distributional assumptions. The model extracts the inherent groups of road segments with crash counts that are equally sensitive to the road attributes on an average; the heterogeneity within these groups is also allowed in the proposed framework. The specification simultaneously accounts for potential spatial correlation of the crash counts from neighboring road segments. A Gibbs sampling framework is proposed that leverages recent theoretical developments on data-augmentation algorithms, and elegantly sidesteps many of the computational difficulties usually associated with Bayesian inference of count models. Empirical results suggests the presence of two latent groups and spatial correlation within the study road network. Road features with significantly different effect on crash counts across two latent groups of road segments were identified.

Automatic Update of Road Attributes by Mining GPS Tracks

AbstractDespite advances in cartography, mapping is still a costly process which involves a substantial amount of manual work. This article presents a method for automatically deriving road attributes by analyzing and mining movement trajectories (e.g. GPS tracks). We have investigated the automatic extraction of eight road attributes: directionality, speed limit, number of lanes, access, average speed, congestion, importance, and geometric offset; and we have developed a supervised classification method (decision tree) to infer them. The extraction of most of these attributes has not been investigated previously. We have implemented our method in a software prototype and we automatically update the OpenStreetMap (OSM) dataset of the Netherlands, increasing its level of completeness. The validation of the classification shows variable levels of accuracy, e.g. whether a road is a one‐ or a two‐way road is classified with an accuracy of 99%, and the accuracy for the speed limit is 69%. When taking into account speed limits that are one step away (e.g. 60 km/h instead of the classified 50 km/h) the classification increases to 95%, which might be acceptable in some use‐cases. We mitigate this with a hierarchical code list of attributes.

Impact of Street’s Physical Elements on Walkability: a Case of Mawlawi Street in Sulaymaniyah, Iraq

A pleasant walking environment is a precondition for living in a sustainable city. Appropriate street design can increase quality and quantity of walking. However, the adequacy and quality of physical elements as the most significant components of street can seriously affect walkability in the streets. The objective of this study was to critically assess the walkability level in terms of physical elements of Mawlawi Street, a famous commercial street located in the city center of Sulaymaniyah, Iraq. The qualitative research based on interview with locals, direct observation and quantitative research via questionnaire with pedestrians were conducted in this study. First, site observation was carried out through PEDS (Pedestrian Environment Data Scan) audit tool and the taking of photographs in order to observe the streetscape features. In this regard, four criteria as environment, pedestrian facility, road attributes, walking environment, and subjective assessment were considered as well serving the purpose of providing a broad direction about streetscape features. Then, a 5 point Likert scale questionnaire with pedestrians was conducted to triangulate the findings from observation. Later on, the findings were validated through an interview with locals regarding their subjective ideas about those criteria. The study showed that inadequate and poor quality of street’s physical elements changed the street to an unsafe and uncomfortable environment for walking with weak and low level of street connectivity and accessibility for pedestrians.

A new model for optimizing waste disposal based on customers' time windows and road attributes

A new model for optimizing waste disposal based on customers' time windows and road attributes

Developing a Road Safety Review Tool to Identify Design Standard and Safety Deficits on High Risk Road Sections

The ESReT (European Safety Review Tool) project has developed a tool to support the review of road sections that have been identified as ‘high risk’ according to network screening processes. The tool provides a methodology to practitioners for the collection and analysis of road attribute data using low cost, non-specialist equipment. The overall result is a consistent and repeatable approach to the investigation and assessment of high risk road sections.There are two main parts of the assessment performed by the tool. The first part is a comparison of road attributes against design standards; the optional second part is a comparison of road attributes against ‘safety rules’. The road design standard check allows road authorities to compare the attributes of existing heritage roads with current design standards. This allows road authorities to identify where, and in what way, modern design rules are not met. Various design standard attributes are included in the tool including: median width, lane width, shoulder type and width, verge width, curve radius, crests and sags, stopping sight distance and intersection type. The optional ‘safety’ check allows the road authority to see where key safety rules are violated. This means aspects of the road that may contribute to high severity crashes are identified along with aspects of the road that may lack credibility to the road user. Attributes relating to safety include median type, clear zones (median and roadside), intersection type and frequency, stopping sight distance, adjacent land use, presence of pedestrian and cycle facilities etc.The ESReT system allows road attribute information to be visualised and reviewed by the road authority, and presents the results of the road design standard and safety checks by showing deficits both in tabular form and on interactive maps. The ESReT system does not aim to provide a definite design solution to the road authority, rather it provides experienced practitioners with standardised information about the road along with suggestions so that they can develop the best solutions based on their experience and local knowledge.This research was carried out as part of the CEDR Transnational Road Research Programme Call 2013. The funding for the research was provided by the national road administrations of the Netherlands, Germany and Ireland.

Optimum Route Selection for Vehicle Navigation

The objective of Optimum Route Selection for Vehicle Navigation System (ORSVNS) article is to develop a system, which provides information about real time alternate routes to the drivers and also helps in selecting the optimal route among all the alternate routes from an origin to destination. Two types of query systems, special and general, are designed for drivers. Here, the criterion for route selection is introduced using primary and secondary road attributes. The presented methodology helps the drivers in better decision making to choose optimal route using fuzzy logic. For experimental results ORSVNS is tested over 220 km portion of Haryana state in India.

Active Travel And Exposure To Air Pollution: Implications For Planning Healthy Cities

Introduction: Promoting bicycling and walking is a promising strategy for designing healthy cities. Air pollution concentrations are elevated on roadways; the spatial patterns of both active travel and air pollution influence exposure. Methods: We use available spatial models to map block-level estimates (n=13,569) of bicycle traffic, pedestrian traffic, and particulate air pollution concentrations in Minneapolis, MN. Then, we investigate spatial patterns of population-level exposure. We test if certain built environment variables (e.g., attributes of roads, population density, land use mix) and socio-demographic factors (e.g., household income, share of non-white residents) are correlated with active travel and particulate air pollution. Findings: Most active travel occurs on major (i.e., high-traffic) roads or near activity centers where particulate concentrations are highest. Few locations (~1%) are “healthy” (i.e., high active travel, low concentrations). Based on our spatial estimates, we identified 846 blocks (~1%) where minor shifts to bicycle facilities may reduce exposure (e.g., moving bicycle lanes away from major roads to adjacent low-traffic roads). Land use mix is correlated with active travel but not air quality, suggesting that locating clusters of mixed-uses in areas with low concentrations could create more “healthy” neighborhoods. Active travel and particulate concentrations are highest in low-income, non-white neighborhoods, underscoring the importance of efforts to address environmental injustice. Discussion: Our models of active travel describe where people actually bike or walk rather than their likelihood to walk or bike based on home location (e.g., “walkability”). Our models of particulate air pollution describe small-scale changes in concentrations that a sparsely distributed monitor network cannot. Using these models in combination allows for exploration of how the built environment impacts population-level exposures during active travel.

Fatality rates for crashes involving heavy vehicles on highways: A random parameter tobit regression approach

ABSTRACTFew studies have analyzed the impacts of freight movements (large truck) on crash fatality rates. This study explores a novel application of a method, namely the random parameters tobit regression model to large truck fatality rates by using the nationwide Fatality Analysis Reporting System. By utilizing random parameter tobit regression the authors examined crash rates (instead of frequencies) in per million truck-miles traveled and ton-miles of freight in the United States as continuous censored variables. The empirical and statistical results illustrate that the random-parameters tobit regression model provides a better understanding of the fatality rates per million truck-miles traveled and ton-miles of freight over the fixed parameter tobit model. Factors related to the crash mechanism, temporal and spatial characteristics, road and environmental attributes, vehicle configuration, drivers and passenger attributes were found to be statistically significant. Some exposure to injury severity related factors also were found to be significant with random parameters that vary across the observations.

Spatiotemporal variation in selection of roads influences mortality risk for canids in an unprotected landscape

Ecologists are increasingly documenting individual variation in resource selection across populations in response to temporal or spatial environmental context. These behavioral patterns are assumed to be adaptive although previous studies have not linked them directly to survival and reproductive data to verify the assumed relationship between behavior and fitness. Recent work documented that higher density of secondary roads within home ranges of free‐ranging canids (wolves, coyotes and hybrids) increased mortality risk in the hybrid zone adjacent to Algonquin Park in Ontario, Canada. Here, we examine individual behavioral responses of canids to spatially varying levels of human‐disturbance and determine whether these responses to secondary roads resulted in differential mortality risk for canids across the hybrid zone. Specifically, we investigated resource selection within home ranges with GPS telemetry to determine whether canids selected roads more at night than during the day to minimize dangerous encounters with humans. Next, we modeled individual variation in spatial and temporal responses to secondary roads to evaluate the relative importance of intrinsic (Canisancestry) and extrinsic (resource availability) influences on their behavior. Behavioral responses to roads were not well explained by variation inCanisancestry. Instead, canids avoided roads more during day than at night as a non‐linear function of increased road availability. Furthermore, canids that survived exhibited a stronger relationship between day–night selection of roads and road availability than canids that died suggesting an adaptive nature of this behavior. By modifying their selection of roads between day and night, canids appear to be able to exploit the beneficial attributes of roads while mitigating human‐caused mortality risk. However, not all canids responded adaptively highlighting the importance of explicitly linking patterns of resource selection to components of fitness to accurately model and interpret individual variation in resource selection behavior of animals.

Fast automatic three-dimensional road model reconstruction based on mobile laser scanning system

In the Traffic, Urban planning, and Construction domain, rich three-dimensional information models are throughout a whole life cycle for road application, such as road planning, road development, road operation, road reuse, and road renewal. These three-dimensional models are often constructed using dense three-dimensional point clouds obtained from laser scanning systems. The latest mobile terrestrial laser scanning systems provide an efficient technique for acquiring very dense point clouds along road corridors, so that fast and automated procedures for recognizing or extracting road attributes and reconstructing road three-dimensional models can be developed. In this paper, every major step of the whole road model reconstruction process, from the input point clouds to the finished model, is presented in detail. The results show that the mobile laser scanning system allows an efficient and automatic reconstruction for urban road three-dimensional model.

A Full Bayesian multivariate count data model of collision severity with spatial correlation

This study investigated the inclusion of spatial correlation in multivariate count data models of collision severity. The models were developed for severe (injury and fatal) and no-injury collisions using three years of collision data from the city of Richmond and the city of Vancouver. The proposed models were estimated in a Full Bayesian (FB) context via Markov Chain Monte Carlo (MCMC) simulation. The multivariate model with both heterogeneous effects and spatial correlation provided the best fit according to the Deviance Information Criteria (DIC). The results showed significant positive correlation between various road attributes and collision severities. For the Richmond dataset, the proportion of variance for spatial correlation was smaller than the proportion of variance for heterogeneous effects. Conversely, the spatial variance was greater than the heterogeneous variance for the Vancouver dataset. The correlation between severe and no-injury collisions for the total random effects (heterogeneous and spatial) was significant and quite high (0.905 for Richmond and 0.945 for Vancouver), indicating that a higher number of no-injury collisions is associated with a higher number of severe collisions. Furthermore, the multivariate spatial models were compared with two independent univariate Poisson lognormal (PLN) spatial models, with respect to model inference and goodness-of-fit. Multivariate spatial models provide a superior fit over the two univariate PLN spatial models with a significant drop in the DIC value (35.3 for Richmond and 116 for Vancouver). These results advocate the use of multivariate models with both heterogeneous effects and spatial correlation over univariate PLN spatial models.

Road hierarchy with integration of attributes using fuzzy-AHP

Road objects in a network data model are categorised into a hierarchical structure in accordance with their functions and capacities. In this study; five road attributes derived from semantic, geometric and topological properties of network data set (i.e. road class, road length and centralities of degree, closeness and betweenness) are utilised for the creation of road network hierarchy. The relationships with each attributes except road class and their effects on the determination of road importance are analysed by using a distribution graph and the equation of Pearson correlation coefficient. For creating road network hierarchy, integration process is achieved through the application of fuzzy analytic hierarchy process assuming attributes as the fuzzy criteria. The integration process is followed by the calculation of new priority attribute that indicates the importance of road objects. At the end of the process, road class, which is the most important attribute, is also used for the validation of proposed methodology. The results show that the new priority value of a road is superior to its each attribute value in hierarchical organisation.

Towards an Authoritative OpenStreetMap: Conflating OSM and OS OpenData National Maps’ Road Network

The quality aspects of OpenStreetMap (OSM), as the global representation of crowd-sourced mapping, have always been of priomary concern to academics. While the methodologies for checking its quality against the national maps have been implemented by a number of studies, there are minimal works on how to practically improve the quality of OSM towards being an authoritative map source. This paper presents a method for conflating road attributes, namely the name and reference code, of OSM with the Open Data provided by Ordnance Survey (the British national mapping agency). The added values in the proposed methodology include the daily updates and serving of the conflated maps via open Web Services. More importantly, the OSM crowd correction is facilitated by frequently highlighting and web-serving the individual differences. There are currently over 5,800 differences in matching road names and references between the two datasets. In addition to describing the conflation methodology, the different geographic distribution patterns of the identified differences are discussed. A negative effect of the road density on the ratio of the mismatched features between the two datasets is observable, evidenced by their different geographical distribution over the map. It is shown that the best correspondence between attributes exists in the very dense areas, followed by the very low density areas, and lastly in the middle to large sized cities.

Corrigendum to Determination of an Optimal Return-Path on Road Attributes for Mobile Robot Recharging

This corrigendum is offered as a means to correct errors in “Determination of an Optimal Return-path on Road Attributes for Mobile Robot Recharging” (Fei Liu, Shan Liang, Xiaodong Xian, International Journal of Advanced Robotic Systems, vol.8, no.5, pp. 83–92, 2011). The error is due to the fact that we reckoned without taking into account the energy consumed by the sensors on the robot. Please see the corrections below. Page 85–86 (1) In column 2, the last paragraph should read: (c) The cost that the robot will pay for passing each segment includes two parts: energy consumption ce and the influence of vibration on the robot body cb that describes the probability of the robot's equipment failure. Actually, ceincludes two parts, the part that the sensors on the robot will consume, and secondly, the energy used for driving the motor. Here, we use csto describe the first part and use ĉeto describe the second part. Therefore, [Formula: see text] Then the cost Ccan be described as[Formula: see text] Page 86 (1) In column 2, the chapter title “4.2.1 Mathematical Model of ce “ should read: “4.2.1 Mathematical Model of ĉe”. (2) In column 2, the paragraphs after Equation (9) and before Equation (11) , all ce should be replaced by ĉe. (3) In column 2, Equation (10) should be [Formula: see text] (4) In column 2, Equation (11) should be [Formula: see text] Page 87 (1) In column 2, Equation (20) should be [Formula: see text] Page 88 (1) In column 1, after Equation (25) in chapter 4.2.2, the following should be added: 4.2.3 Mathematical Model of cs First, we define rsas the energy consumption rate, which describes how much energy the sensor will consume when the robot walks for a unit distance. The value of rsis always stable, so for any road segment, for passing distance pml, we have the energy consumption[Formula: see text] (2) In column 2, chapter title “4.2.3 Computing the Idle Time” should be replaced by “4.2.4 Computing the Idle Time”. Page 89 (1) In column 1, after the first paragraph in chapter 5.1, the following should be added: [Formula: see text] Here, we do not measure rsdirectly, on the contrary, we first measure the consumption rate for unit time, which can be termed τ s(unit: V/ s). If Vstart(unit: V) is the voltage value when the robot is just powered on, and after a period of time t, the value decreases to V end(unit: V), we get[Formula: see text] We assume that the robot walking for distance pml at average speed v̄ (unit: m/s), then [Formula: see text] In our experiment, we set Vstart = 12.7 V, Vend = 11.3 V, v̄ = 0.75 m/ s, then it is measured that t = 4.5 h, therefore, rs is measure to be [Formula: see text] (2) Equation (38) should be [Formula: see text] (3) Equation (39) should be [Formula: see text] (4) Equation (40) should be [Formula: see text] (5) Equation (41) should be [Formula: see text] (6) Equation (42) should be [Formula: see text] Page 90 (1) Equation (45) should be [Formula: see text] (2) In the penultimate paragraph of column 2, the following corrections should be made: As listed in Table 2 , the cost CRD0 n is (0.0520,0.8693×10−3) and the idle time TIDLE_ RD0 is 346.834 s. [Table: see text] (3) Equation (50) should be [Formula: see text] Page 91 (1) Table 2 should be replaced by (2) In column 2, in the paragraph below Table 2 , the following corrections should be made: Statistically, if the robot returns to recharge four times a day on average and δ TIDLE = 20.694 s is taken as an example, ( 3 ) Equation (51) should be [Formula: see text] (4) Equation (52) should be [Formula: see text]

Intersection Support System for Powered Two-Wheeled Vehicles: Threat Assessment Based on a Receding Horizon Approach

This paper reports a novel intersection support (IS) system for motorcycles developed through the SAFERIDER project (IS). The IS function described is built on a receding horizon approach that is designed for a set of predefined intersection scenarios. In the receding horizon scheme, a nonlinear optimal control problem is repetitively solved in real time, yielding a reference motion plan. The initial value of the longitudinal jerk (control input) of each plan is used as a measure of the correction that the rider has to apply to conform to an optimal-safe maneuver. This technique has the advantage of yielding a homogenous measure of the threat independent of the scenario, and it is directly linked with the control variable that the rider should use to accordingly change the vehicle's longitudinal dynamics. Additionally, the receding horizon approach naturally accommodates road geometry and constraint attributes, motorcycle dynamics, rider input, and riding styles. Warning feedback is given to the rider by an appropriate combination of human-machine interface elements, such as the haptic throttle, the vibrating glove, and the visual display. This paper explains the IS concept, discusses the implementation aspects of the proposed receding horizon approach, and presents the results of pilot tests conducted on a top-of-the-range riding simulator.

Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment

In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers’ route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses.

Road bank and vehicle roll angles estimation based on Proportional-Integral observer

RésuméRoad bank angle plays a crucial role on the vehicle lateral dynamics; unfortunately, this parameter is not measured by low cost sensor. For this reason, we present in this paper a virtual sensor to estimate the road bank and vehicle roll angles. This virtual sensor is based on a proportional-integral observer introduced by Koenig (2006). This observer uses a simple lateral vehicle model which offers a better approximation of the vehicle's dynamic behavior under moderate driving situations. Moreover, the estimation process uses some measurements like sideslip angle, roll rate, yaw rate and steering angle. Notice that in this study the road bank angle is considered as an unknown input. An important part of this work is devoted to the experimental validation of the PI observer. This validation gives an appropriate estimation of the vehicle roll and road bank angles, these results show the ability of this observer to estimate simultaneously the road attributes and vehicle dynamics parameters.

Steering control and road bank angle estimation to evaluate the vehicle behaviour under high dynamic loads: Experimental evaluation

AbstractDriving safely can be ensured by a better understanding of the risk and critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic behaviors. This paper proposes two algorithms: the first one is dedicated to a new estimation process which was designed to estimate the vehicle roll and road bank angles, in order to make the road trajectory more realistic. This estimator is based on an unknown input sliding mode observer and a LPV model. The second concerns a robust LPV state output feedback control designed via LMI optimization and gain-scheduling method. The steering control strategy is designed to simulate the non linear four wheel vehicle model under higher dynamic demands. The steering vehicle control and the observer developed here have been validated experimentally using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA. These algorithms were developed for an application known as “Itinerary Rupture Diagnosis”: to evaluate the physical limits of a vehicle negotiating a bend.

Determination of An Optimal Return-Path on Road Attributes for Mobile Robot Recharging

Optimal path-planning for mobile robot recharging is a very vital requirement in real applications. This paper proposes a strategy of determining an optimal return-path in consideration of road attributes which include length, surface roughness, road grade and the setting of speed-control hump. The road in the environment is partitioned into multiple segments, and for each one, a model of cost that the robot will pay for is established under the constraints of the attributes. The cost consists of energy consumption and the influence of vibration on mobile robot that is induced by motion. The return-path is constituted by multiple segments and its cost is defined to be the sum of the cost of each segment. The idle time, deduced from the cost, is firstly used as the decision factor for determining the optimal return-path. Finally, the simulation is given and the results prove the effectiveness and superiority of the strategy.

Factors Affecting Autumn Deer–Vehicle Collisions in a Rural Virginia County

Vehicular collisions with white-tailed deer (Odocoileus virginianus) are a safety and economic hazard to motorists. Many efforts to reduce deer-vehicle collisions (DVCs) have proven unsuccessful, but deer reduction has been a primary management tool in several states. The Virginia Department of Transportation geo-located all known DVCs in Clarke County, Virginia, from August through December 2005 (n = 246) and 2006 (n = 259). We estimated harvest intensity, deer population density, amount of forest and housing development, presence of row crops, and traffi c volume and speed for 228 road segments (each 500 m in length) within the county to determine which factors are correlated with increased DVCs. A step-wise general linear model indicated that deer density (range 5-47 deer/km 2 ), and deer harvest levels (range 1-18 deer/km 2 for 9-km 2 blocks) were not correlated with the location of DVCs. Road attributes (traffi c volume and road type) and the amount of housing development were important attributes of road segments when predicting DVCs. The locations of DVCs during the rut were not markedly different from collisions outside the rut. Over the range of deer densities and harvest levels found in this rural county, there was little evidence that these factors infl uence the number of DVCs. Management efforts should include changing motorist behavior or road attributes.