Subjective Well-Being in Two Himalayan Communities, Post Road Development

Although the first road to ever be built into Humla, Nepal is still under construction, it has already spurred numerous sociocultural and economic changes, including an increased integration into the market economy, changing access to market-purchased foods, and new kinds of health-seeking behavior. This paper is part of a larger research project where we examined changing health and nutrition outcomes co-synchronous with the arrival of this road. In this paper, we focus on whether and how the road is affecting villagers’ subjective well-being (SWB). We studied this while living and working with people from two Humli villages, one that is on the road, and one that is far from it. In these villages, we developed two local models of SWB, using the villagers’ own conceptual frameworks and sense of the factors that play a role in wellbeing. Our analyses showed that villagers’ conceptualization of SWB varied substantially according to road proximity. Additionally, we quantified indices from villagers’ SWB assessments and tested which variables were significant determinants of wellbeing. We discovered a significant relationship between an individual’s well-being level and two variables: available resources per household and levels of social support. The purpose of this paper is threefold: to better understand how villagers from Upper Humla define SWB, to identify which subset of the population is not benefitting in terms of their SWB from the new road, and to present a mixed-methods, anthropologically-based approach for the development of a locally meaningful measure of SWB

Automated Shuttles as Traffic Calming: Evidence from a Pilot Study in City Traffic

Discourse about the real-world effects of automated vehicles has intensified over the last decade, but few observational studies have been made examining their integration in real traffic. This research is based on the dataset prepared by Beauchamp et al. in [1] where video footage from two pilot projects involving automated shuttles in Montreal and Candiac in 2019 was analyzed to compute safety indicators from road user trajectories. The study showed that automated shuttles have safer interactions with other road users compared to human drivers following the same trajectories. Yet, this may not be the only characteristic of automated shuttles. These vehicles are notoriously slow, 10 to 15 km/h slower than human-driven cars in city traffic [1], which on city streets is bound to influence other road users, in particular following cars. lt is therefore hypothesized that automated shuttles may have a traflic calming effect, slowing other motorized vehicles [2]. Slower speed and the predictability of automated shuttles, obeying the rules of the road and yielding more willingly to vulnerable road users (pedestrians and cyclists) may also have an impact on these users' behavior [3]: for example, cyclists may pass the shuttle, pedestrians may cross outside of crosswalks. The present study aims to explore the potential effects of automated shuttles, with their slower spceds and more predictable behavior, on the behavior of other road users. [from Introduction

Fuzzy logic traffic signal controller enhancement based on aggressive driver behavior classification

The rise in population worldwide and especially in Egypt, together with the increase in the number of vehicles present serious complications regarding traffic congestion and road safety. The elementary solution towards improving congestion is to expand road capacities by building new lanes. This, however, requires time and effort and therefore new methodologies are being implemented. Intelligent transportation systems (ITS) try to approach traffic congestion through the application of computational and engineering techniques. Traffic signal control is a branch of intelligent transportation systems which focuses on improving traffic signal conditions. A traffic signal controllers’ main objective is to improve this assignment in a way which reduces delays. This research proposes a new approach to enhancing traffic signal control and reducing delays of a single intersection, through the integration of an aggressive driving behavior classifier. Previous approaches dealt with traffic control and driver behavior separately, and therefore their successful integration is a new challenging area in the field. Multiple experiment sets were conducted to provide an indication to the effectiveness of our approach. Firstly, an aggressive driver behavior classifier using feed-forward neural network was successfully built utilizing Virginia Tech 100-car naturalistic driving study data. Its performance was compared against long short-term memory recurrent neural networks and support vector machines, and it resulted in better performance as shown by the area under the curve. To the best of our knowledge, this classifier is the first of its kind to be built on this 100-car study data. Secondly, a representation of aggressive driving behavior was constructed in the simulated environment, based on real life data and statistics. Finally, Mamdani’s fuzzy logic controller was modified to accommodate for the integration of the aggressive behavior classifier. The integration results were encouraging and yielded significant improvements at higher traffic flow volumes when compared against the built Mamdani’s controller. The results are promising and provide an initial step towards the integration of driver behavior classification and traffic signal control

Mechanical Characterization and Chemical Identification of Clear Binders for Road Surface Courses

The development of non‐black asphalt mixtures for surface courses may play a significant role to improve functional, aesthetic and environmental issues of road pavements. Nowadays, the development of clear binders as substitutes for traditional bitumen in asphalt mixtures, which combine durability and mechanical properties, exalting the color of pavements for a better integration of road networks in urban and environmentally sensitive areas, is undoubtedly a timing challenge. However, the selection and classification of clear binders are often based only on color and standard requirements referred to traditional bitumen that do not describe consistently the binder behavior. A better understanding on clear binder properties is required to guide the aggregate selection and the mix design for surface layer, merging safety, aesthetical and environmental benefits into long lasting pavement. This paper presents a comprehensive experimental program, including empirical tests, infrared spectrum analysis, and rheological testing over a wide range of temperature and frequency, to determine the overall mechanical behavior of three clear binders. Results highlighted that the selected clear binders differ from traditional bitumen in terms of mechanical behavior. Different composition or origin can induce to completely different performance. Moreover, the combination of several testing procedures allowed suggesting specific application methods and uses for the three clear binders

Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles

Abstract—This paper describes the application of state-estimation techniques for the real-time prediction of the state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, approaches based on the well-known Kalman Filter (KF) and Extended Kalman Filter (EKF), are presented, using a generic cell model, to provide correction for offset, drift, and long-term state divergence—an unfortunate feature of more traditional coulomb-counting techniques. The underlying dynamic behavior of each cell is modeled using two capacitors (bulk and surface) and three resistors (terminal, surface, and end), from which the SoC is determined from the voltage present on the bulk capacitor. Although the structure of the model has been previously reported for describing the characteristics of lithium-ion cells, here it is shown to also provide an alternative to commonly employed models of lead-acid cells when used in conjunction with a KF to estimate SoC and an EKF to predict state-of-health (SoH). Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior to more traditional techniques, with accuracy in determining the SoC within 2% being demonstrated. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

The Impact of First-Person Perspective Text and Images on Drivers’ Comprehension, Learning Judgments, Attitudes, and Intentions Related to Safe Road-Sharing Behaviors

Drivers and cyclists lack an alignment of road sharing knowledge, attitudes, and expectations, resulting in unnecessary fatalities. Educational countermeasures need to present information that captures drivers’ interest by being personally relevant, facilitate elaboration and synthesis of new information with existing knowledge, and change attitudes, intentions, and behavior. Well-documented health-related communication methods were employed to determine their effectiveness in a transportation domain. Health countermeasure designers use first-person perspective to improve narrative instruction outcomes, based on the Elaboration Likelihood Model (ELM; Petty & Cacioppo, 1986). Exploring narrative perspective-taking as a design tool requires the integration of multiple disciplines. Our design case stems from the existing Virginia road-sharing safety educational handbook. The first study evaluated the effects of text-based information written from a first- and third-person perspective on cognitive and affective learning outcomes. The Theory of Planned Behavior framework (TPB; Ajzen, 1991) was used to interpret the following outcome measurements that are predictive of behavior: comprehension, judgments of learning, attitudes, and intentions. The second study employed the Cognitive Theory of Multimedia Learning (CTML; Mayer, 1997) to understand the interactions between text and visual perspectives on cognitive and affective learning outcomes. In addition, cognitive load, multiple knowledge types, and three behavioral intention components were also considered when evaluating the efficacy of first-person perspective. It was found that the first-person perspective effect used in the health domain does not transfer to a transportation domain. The data were explored further and discussed, as well as key limitations and possible future directions

Subjective Well-Being in Two Himalayan Communities, Post Road Development

Although the first road to ever be built into Humla, Nepal is still under construction, it has already spurred numerous sociocultural and economic changes, including an increased integration into the market economy, changing access to market-purchased foods, and new kinds of health-seeking behavior. This paper is part of a larger research project where we examined changing health and nutrition outcomes co-synchronous with the arrival of this road. In this paper, we focus on whether and how the road is affecting villagers’ subjective well-being (SWB). We studied this while living and working with people from two Humli villages, one that is on the road, and one that is far from it. In these villages, we developed two local models of SWB, using the villagers’ own conceptual frameworks and sense of the factors that play a role in wellbeing. Our analyses showed that villagers’ conceptualization of SWB varied substantially according to road proximity. Additionally, we quantified indices from villagers’ SWB assessments and tested which variables were significant determinants of wellbeing. We discovered a significant relationship between an individual’s well-being level and two variables: available resources per household and levels of social support. The purpose of this paper is threefold: to better understand how villagers from Upper Humla define SWB, to identify which subset of the population is not benefitting in terms of their SWB from the new road, and to present a mixed-methods, anthropologically-based approach for the development of a locally meaningful measure of SWB

Safety Assessment of Road Vehicle in Crosswind Considering Driver Behavior

With expansion of the economy, more and more highway networks extend to coastal areas and mountain valley areas. Vehicles will be exposed to strong crosswinds when driven on these highway roads, especially in hurricane season and in winter in these two different topographic areas. Strong crosswinds threaten the safety of transportation infrastructure and passing vehicles in forms of vehicle accidents that usually result in traffic blockage and driver injury, posing negative effects on economic growth. This dissertation aimed to evaluate the vehicle safety when running through crosswinds in consideration of driver behaviors. Firstly, the aerodynamic characteristics of road vehicles were identified using computational fluid dynamic method. Aerodynamic coefficients of a high-side lorry running in crosswinds using both traditional resultant-wind velocity method and relative-motion approach were compared. In addition, the aerodynamic coefficients of multiple types of vehicles were investigated. The curves of aerodynamic coefficients for different vehicle types against wind yaw angles were obtained. Secondly, an experimental investigation on the vehicle performance and driver behavior was conducted by taking advantage of the LSU’s driving simulator. This study revealed the repeatability of driver behavior and the effect of crosswind speeds on the vehicle performance and drivers’ behavior through a statistical analysis. More scenarios were considered, such as driving in windy-rainy conditions. A regression model of the steering wheel angle turned by drivers was obtained. Finally, safety assessment of vehicles was performed based on an improved wind-vehicle-bridge coupled system and considering driver’s behavior using a series of driver behavior models. For different types of road vehicles, rigid frame vehicle model and flexible frame vehicle model were developed. Accident criteria of lateral side slip, rotational deviation, and rollover were considered. To investigate the influence of driver models, four driver models were considered in different integration methods. Results between cases from different driver models were compared

INTEGRATING ACTIVITY-BASED TRAVEL DEMAND AND DYNAMIC TRAFFIC ASSIGNMENT MODEL: A BEHAVIORAL USER EQUILIBRIUM APPROACH

Recently, the focus of transportation planning has evolved from accommodating long-term mobility needs to providing near-term and more efficient transportation systems management and operations (TSMO) solutions, the result of limited transportation funding and road capacity build-out. This planning-for-operation concept calls for modeling tools that are sensitive to dynamic interactions between travel behavior and network supply so that the impacts of emerging TSMO strategies (e.g., variable road pricing, ramp metering, etc.) can be accurately estimated. The integration of activity-based travel demand models (ABM) and dynamic traffic assignment (DTA) models offer a perfect solution. However, existing operational integrated ABM-DTA models suffer from several limitations, including excessively long runtime and poor convergence quality, which severely hinders large-scale implementations. This dissertation proposes to integrate operational ABM and DTA models based on an innovative behavioral foundation: behavior user equilibrium (BUE). Different from the normative behavior theory (i.e., user equilibrium, or UE), BUE is based on a positive theory of travel behavior that avoids impractical assumptions, such as complete information and perfect rationality. BUE describes what travelers actually do in the system and thus emphasizes the role of information acquisition, knowledge updating, and learning in travel decision-making. The BUE-based model saves runtime because DTA models no longer need to run iteratively to reach UE internally and fewer agents undergo behavioral adjustments through iterations. In addition to runtime savings, the BUE principle proposes an alternative way to explain the behavior adjustment process and provides improved behavioral realism. This BUE-based integration framework is applied to the Washington-Baltimore Metropolitan Area as a case study. The integrated model includes InSITE, an ABM developed for the Baltimore Metropolitan Council (BMC), and DTALite, a mesoscopic DTA model. The BUE-based integrated model is then compared with a traditional, sequentially integrated benchmark regarding model convergence and performance. Lastly, to enhance the transferability of the BUE-based integration approach, this dissertation develops a calibration method that estimates parameters associated with the BUE principle using readily available local data so that this integration framework can be easily applied to operational ABM and DTA models elsewhere

Determination of cornering stiffness through integration of a mathematical model and real vehicle exploitation parameters

U radu je prikazan prilaz identifikaciji otpora povođenju kao najznačajnijem parametru u sistemima upravljivosti i stabilnosti motornih vozila kroz integraciju empirijskih modela i parametara realne eksploatacije. Ovaj prilaz se zasniva na analizi matematičkog modela pneumatika, identifikaciji ključnih parametara iz realne eksploatacije i integraciji mehatronskog sistema za praćenje opterećenja pneumatika. Merenjem opterećenja pneumatika, i kasnijom integracijom izmerenih vrednosti u razvijeni softverski modul, obezbeđuje se precizno definisanje otpora povođenju na određenom kontaktu vozila i puta. Istraživanje podrazumeva integraciju matematičkog modela, mehaničkih, elektronskih i informacionih tehnologija u cilju obezbeđivanja sveobuhvatnog sagledavanja ponašanja pneumatika u pogledu definisanja otpora povođenju.This paper demonstrates the approach to determination of cornering stiffness as the most important parameter of motor vehicle steering and stability systems through integration of empirical models and real exploitation parameters. The approach is based on the analysis of a tire mathematical model, identification of key real exploitation parameters and integration of a mechatronic system for tire load monitoring. Measurement of tire load and subsequent integration of measured values into developed software module provide a precise definition of cornering stiffness for a certain vehicle and road contact patch. This research assumes integration of a mathematical model and mechanical, electronic and information technologies with the aim of comprehensive understanding of tire behavior in terms of cornering stiffness determination