Predictability is important in decision-making in many fields, including transport. The ill-predictability of time-varying processes poses severe problems for traffic and transport planners. The ...sources of ill-predictability in traffic phenomena could be due to uncertainty and incompleteness of data and models and/or due to the complexity of the processes itself. Traffic counts at intersections are typically consistent and repetitive on the one hand and yet can be less predictable on the other hand, in which on any given time, unusual circumstances such as crashes and adverse weather can dramatically change the traffic condition. Understanding the various causes of high/low predictability in traffic counts is essential for better predictions and the choice of prediction methods. Here, we utilise the Hurst exponent metric from the fractal theory to quantify fluctuations and evaluate the predictability of intersection approach volumes. Data collected from 37 intersections in Sydney, Australia for one year are used. Further, we develop a random-effects linear regression model to quantify the effect of factors such as the day of the week, special event days, public holidays, rainfall, temperature, bus stops, and parking lanes on the predictability of traffic counts. We find that the theoretical predictability of traffic counts at signalised intersections is upwards of 0.80 (i.e., 80%) for most of the days, and the predictability is strongly associated with the day of the week. Public holidays, special event days, and weekends are better predictable than typical weekdays. Rainfall decreases predictability, and intersections with more parking spaces are highly predictable.
Autonomous vehicles are being viewed with scepticism in their ability to improve safety and the driving experience. A critical issue with automated driving at this stage of its development is that it ...is not yet reliable and safe. When automated driving fails, or is limited, the autonomous mode disengages and the drivers are expected to resume manual driving. For this transition to occur safely, it is imperative that drivers react in an appropriate and timely manner. Recent data released from the California trials provide compelling insights into the current factors influencing disengagements of autonomous mode. Here we show that the number of accidents observed has a significantly high correlation with the autonomous miles travelled. The reaction times to take control of the vehicle in the event of a disengagement was found to have a stable distribution across different companies at 0.83 seconds on average. However, there were differences observed in reaction times based on the type of disengagements, type of roadway and autonomous miles travelled. Lack of trust caused by the exposure to automated disengagements was found to increase the likelihood to take control of the vehicle manually. Further, with increased vehicle miles travelled the reaction times were found to increase, which suggests an increased level of trust with more vehicle miles travelled. We believe that this research would provide insurers, planners, traffic management officials and engineers fundamental insights into trust and reaction times that would help them design and engineer their systems.
Road traffic congestion continues to manifest and propagate in cities around the world. The recent technological advancements in intelligent traveler information have a strong influence on the route ...choice behavior of drivers by enabling them to be more flexible in selecting their routes. Measuring traffic congestion in a city, understanding its spatial dispersion, and investigating whether the congestion patterns are stable (temporally, such as on a day-to-day basis) are critical to developing effective traffic management strategies. In this study, with the help of Google Maps API, we gather traffic speed data of 29 cities across the world over a 40-day period. We present generalized congestion and network stability metrics to compare congestion levels between these cities. We find that (a) traffic congestion is related to macroeconomic characteristics such as per capita income and population density of these cities, (b) congestion patterns are mostly stable on a day-to-day basis, and (c) the rate of spatial dispersion of congestion is smaller in congested cities, i.e. the spatial heterogeneity is less sensitive to increase in delays. This study compares the traffic conditions across global cities on a common datum using crowdsourced data which is becoming readily available for research purposes. This information can potentially assist practitioners to tailor macroscopic network congestion and reliability management policies. The comparison of different cities can also lead to benchmarking and standardization of the policies that have been used to date.
The structural performance of metallic components is a significant challenge especially when it comes to operating conditions in real-world applications. Friction stir additive manufacturing (FSAM) ...is a solid-state additive manufacturing (AM) that provides controlled microstructure with homogenous grains and excellent structural performance. In this study, the FSAM technique was utilized to fabricate a lightweight laminated AA6061/AA7075 metal matrix composite with improved mechanical properties. The feasibility of the FSAM was demonstrated to build multi-functional, multi-material components for aerospace, automotive, and defence industries to enable lightweight, high-strength components. The FSAM tool was designed with an optimum shoulder length, shoulder diameter, pin length, and pin diameter considering the plate thickness. Afterward, optimized process parameters were designed using the Taguchi L9 orthogonal array (OA) technique. Microstructural features and their effect on mechanical properties such as microhardness and ultimate tensile strength (UTS) were evaluated in the FSAM build. FSAM build improved in microhardness (from 107±1.2 to 138.4 ±2.8 HV0.2) and tensile strength (from 310 to 384 MPa) as compared to base material AA6061. Corrosion resistance was also studied to understand the feasibility of the FSAM technique in various environmental conditions. The overall performance of the FSAM build shows promising results compared to the base materials.
Current transportation management systems rely on physical sensors that use traffic volume and queue-lengths. These physical sensors incur significant capital and maintenance costs. The ubiquity of ...mobile devices has made possible access to accurate and cheap traffic delay data. However, current traffic signal control algorithms do not accommodate the use of such data. In this paper, we propose a novel parsimonious model to utilize real-time crowdsourced delay data for traffic signal management. We demonstrate the versatility and effectiveness of the data and the proposed model on seven different intersections across three cities and two countries. This signal system provides an opportunity to leapfrog from physical sensors to low-cost, reliable crowdsourced data.
Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, ...the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. These reports must be processed before any statistical analysis, which is cumbersome and time-consuming. Our dataset presents the processed disengagement data from 2014 to 2019, crash data till the 10
of March 2020 and supplementary road network and land-use data extracted from OpenStreetMap. Primary data are manually assessed and converted into an easily processed format. Our processed data will be advantageous to the research community and enable accelerated research in this domain. For example, the data can be utilised to discern trends in disengagement, observe the distribution of disengagement causes, and investigate the contributory factors of the crashes. Such investigations can subsequently improve the reporting protocols and make policies and laws for the smooth deployment of this disruptive technology.
Machining of polymeric composite is inevitable during assembly of components. In view of making holes on structural composites, drilling is essential and a study to optimize the machining parameters ...is very important. The present study has been made to investigate the defaces and cutting forces associated during drilling of natural fiber reinforced plastics. Plastic composite has been manufactured using chemically treated
vetiveria zizanioides
as the reinforcement and polyester as the matrix. The composite has been drilled several times on the basis of central composite design. Speed and feed rate of the spindle, point angle and diameter of the tool are considered as the input parameters. Deface of each hole during entry and exit, thrust force and torque have been measured as the output parameters. A fuzzy model has been created and a comparative study between the central composite design and fuzzy model is made. The design has been optimized with the objective of minimizing the output parameters and a set of confirmatory experiments have been conducted. The central composite model has been validated by comparing it with the fuzzy model and confirmatory runs. The comparison presented only a minimal error and hence the modeling by central composite design and fuzzy are consummate.
Determining an appropriate segment length for highway safety evaluations in low- and middle-income countries (LMICs) poses a significant challenge. This study aims to address this issue by ...recommending a suitable segment length for such evaluations in India, using a 167 km intercity expressway as a case study. We employed negative binomial (NB) models on datasets segmented from 100 m to 1000 m with 100 m increments. Our findings strongly suggest that segment lengths from 300 m to 700-m suit various safety assessments. However, the study reveals that parameter estimates vary significantly with both segment length and sample size. This highlights the sensitivity of parameters to data aggregation and sample size across different segment lengths, making it difficult to identify a single optimal length. Therefore, we propose selecting the segment length and segmentation approach based on specific local conditions, highway context, data availability and quality. The methodology presented here can guide policymakers in LMICs to make informed choices regarding segment length for safety evaluations, including blackspot identification and treatment on their highways.
•This study shows that the segmentation approach and segment length vary according to the highway context.•The study recommends a fixed-length segmentation methodology for limited data-availability scenarios in LMICs.•It is impractical to suggest a point estimate for an adequate segment length.•A segment length from 300 m to 700 m is adequate for building parsimonious crash prediction models for Indian rural highways.•The local conditions, highway context, data availability and quality shall dictate the segmentation approach.
Connected and automated vehicles (CAVs) have the potential to revolutionise the transportation industry, with a plethora of research already revealing considerable gains in safety, travel time and ...mobility, as well as reduced congestion and pollution. As the number of CAVs on the road grows, rigorous testing for various market penetration rates (MPRs) of CAVS is essential to determine under what conditions the benefits can be realised. For the studies investigating the impact of CAVs on travel time reliability specifically, the MPRs in which the network most thrives have been inconsistent. The majority of the research is concerned with highway networks with only a few travel time reliability studies that focus on urban networks. In this simulation study, the impact of varying MPRs of CAVs on travel time reliability is evaluated in an urban network for different traffic demands. Travel time reliability metrics are assessed, including the standard deviation, buffer time index and misery index. The study demonstrated that from 0% to 100% MPR, the overall weighted average travel time decreased by 28%, and the standard deviation of the weighted average travel time declined by 35%, highlighting the significant increase in travel time reliability. Travel time improvements were visible from the MPR of 10%; however, the reliability metrics highlighted the greatest benefits occurred at higher MPRs. This study presents valuable results about the reliability that CAVs can bring to urban networks during the fleet transition to CAVs.
In this study, an attempt is made to determine the interaction effect of two closely spaced strip footings using Pasternak model. The study considers small strain problem and has been performed using ...linear as well as nonlinear elastic analysis to determine the interaction effect of two nearby strip footings. The hyperbolic stress-strain relationship has been considered for the nonlinear elastic analysis. The linear elastic analysis has been carried out by deriving the equations for the interference effect of the footings in the framework of Pasternak model equation; whereas, the nonlinear elastic analysis has been performed using the finite difference method to solve the second order nonlinear differential equation evolved from Pasternak model with proper boundary conditions. Results obtained from the linear and the nonlinear elastic analysis are presented in terms of non-dimensional interaction factors by varying different parameters like width of the foundation, load on the foundation and the depth of the rigid base. Results are suitably compared with the existing values in the literature.
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