Discrete choice modeling is a fundamental part of travel demand forecasting. To date, this field has been dominated by parametric approaches (e.g., logit models), but non-parametric such as artificial neural networks (ANNs) possess much potential since problems can be assimilated to pattern recognition problems. In particular, ANN models are easily applicable with their higher capability identify nonlinear relationships between inputs and designated outputs predict behaviors. This article...

Predicting residential water demand is challenging because of two technical questions: (1) which data and variables should be used (2) modeling technique most appropriate for high prediction accuracy. To address these issues, this article investigates 12 statistical techniques, including parametric models machine learning (ML) models, to predict daily household use. In addition, scenarios are adopted, one with only 6 variables, generally available cities utilities (general scenario), all 19...

This article applies machine learning (ML) to develop a choice model on three alternatives related autonomous vehicles (AV): regular vehicle (REG), private AV (PAV), and shared (SAV). The learned is used examine users’ preferences behaviors uptake by car commuters. Specifically, this study gradient boosting (GBM) stated preference (SP) survey data (i.e., panel data). GBM notably possesses more interpretable features than other ML methods as well high predictive performance for data....

In modern society, vehicle accidents have been a factor that has adversely affected national development for long time. Many countries tried to solve this issue, and various solutions studied. This study aims design process analyzing support safety interventions. the data preprocessing section, resampling technique was used imbalance problem. Then, we applied five different machine learning models classification by applying hyperparameter optimization. After classification, model-agnostic...

This study investigates travel decisions (i.e. mode and destination) in Hanoi (Vietnam) using Support Vector Machine (SVM). First, a interview survey was conducted 311 responses were collected across Hanoi. Second, SVM model trained to predict compared with multinomial logit (MNL) (as benchmark). Third, the most important variables that affect ranked discussed. The results show achieves an accuracy of 76.1% (compared 72.9% for MNL). Moreover, proposed parking charges, household income, trip...

Urban Green Infrastructure (GI) provides promising opportunities to address today’s pressing issues in cities, mainly resulting from uncurbed urbanization. GI has the potential make significant contributions cities more sustainable by satisfying growing appetite for higher standards of living as well helping adapt extreme climate events. To leverage potentials GI, this article aims investigate effectiveness that can enhance social welfare benefits triple-bottom line urban sustainability....

Through the use of open data portals, cities, districts and countries are increasingly making available energy consumption data. These have potential to inform both policymakers local communities. At same time, however, these datasets large complicated analyze. We present activity-centered-design, from requirements evaluation, a web-based visual analysis tool explore in Chicago. The resulting application integrates census data, it possible for amateurs experts analyze disaggregated at...

This study addresses the critical issue of road safety in urban environments, with a specific focus on Greater London Area. Utilizing novel, theory-driven approach, investigates multifaceted impact fabric factors safety, operationalized through severity-weighted index accident frequency per capita. Through factorial analysis, six key (Urban Integration, Socioeconomic Challenges, Urban Amenities, Commuter Patterns, Housing and Mobility Barriers, Major Infrastructure) are identified. These...

Jane Jacob’s concepts of urban vitality and diversity have become prevailing planning philosophies in most countries for making cities more livable. Recent changes demographics the impacts COVID-19 exacerbated economic social challenges that commonly face, particularly spatiotemporal heterogeneities. Being able to understand these heterogeneities scalable approaches is fundamental tackling cities. Therefore, this article aims provide a new form estimation by using de facto population....

In this paper, we present a novel 3D interaction technique using smartphone for large screen such as TV and projector screen. Using our technique, could manipulate objects in environment with the virtual hand metaphor. Also, evaluate effects of various sensory inputs vibro-tactile, auditory visual inputs. The result user study shows that feedback is not significantly different from combinations other feedbacks. Our method evaluation can be applied to areas including shopping game.

In the development of safety-critical systems, it is important to perform failure modes and effects analysis (FMEA) identify potential failures. However, traditional FMEA activities tend be considered difficult time-consuming tasks. To compensate for difficulty task, various types tools are used increase quality effectiveness reports. This paper explains an automatic tool that integrates model-based design (MBD), FMEA, simulated fault injection techniques in a single environment. The has...

교통분야에서 교통안전에 대한 문제는 매우 중요한 이슈가 되었다. 1997년 스웨덴에서 시작한 비전제로 교통안전 정책이 알려진 이후로, 여러 국가에서 도로 문제를 해결하기 위해 다양한 정책과 관련 기술이 채택되어지고 있다. 정책의 실효성을 높이기 위해서는 이러한 처치가 교통사고 예방에 미치는 잠재적 영향에 평가가 필요하다. 그러나 자료의 한계와 방법론적 문제로 인해 안전정책의 효과를 정량화 하는데 한계가 기존 연구들은 통계적 타당성 검증, 경험적 베이지안 방법 등을 주로 채택하였지만 방법론은 교란요인을 제거하여 교통안전정책의 순수 측정하는데 순수효과를 알아보기 본 논문은 통제하는 성향점수매칭방법을 사용하여 교통안전체험교육 제시하였다. 분석결과 체험교육을 이수한 운전자는 이수하지 않은 운전자에 비해서 재발율이 16.4% 감소하는 것으로 나타났다. 연령별로 세분화하여 비교한 결과 70대가 36.7%, 60대가 28.5%로 고연령대가 저연령대에 비해 효과가 큰 나타났으며, 업종별로는...

One of the most popular applications for recommender systems is a movie recommendation system that suggests few movies to user based on user’s preferences. Although there wealth available data movies, such as their genres, directors and actors, little information new user, making it hard suggest what might interest user. Accordingly, several services explicitly ask users evaluate certain number which are then used create profile in system. In general, one can better if evaluates many at...

Metropolitan Planning Organizations (MPOs) are required to measure emissions impacts of transportation plans and programs utilizing an estimator such as MOtor Vehicle Emission Simulator (MOVES) or EMission FACtor (EMFAC) models demanding intensive data time consumption run for scenario planning sensitivity tests. Over time, practitioners have developed applied various sketch in Still, many require extensive collection/preparation overly complicated. This paper discusses approach a simple...

The outbreak of novel coronavirus disease 2019 (COVID-19) caused many consequences in almost all aspects our lives. pandemic dramatically changes people’s behavior urban areas and transportation systems. Many studies have attempted to analyze spatial present analysis data visually the process spreading COVID-19 provided limited temporal geographical perspectives. In this article, behavioral systems were analyzed throughout U.S.A. while spread over 2020. Specifically, assuming characteristics...