Search

This study aims to relate organizational characteristics on preferences for project delivery methods (PDMs) in construction industry of Pakistan. Artificial Neural Network (ANN) based model is developed for predicting proportion of projects done by different types of organizations under various PDMs. It is found that ANN model give satisfactory accuracy in predicting these proportions for test and training datasets. It is found that client organizations are more inclined towards traditional methods, especially Design-Bid-Build (DBB). Consultant organizations had relatively higher proportion of projects done by Design-Build (DB) and other non-traditional methods. Most of the construction organizations belong to the private sector which showed an inclination towards DBB and DB methods. The non-traditional PDMs had relatively higher preference for organizations who are involved in infrastructure or other specialized projects. Organizations who have more projects showed more tendency towards non-traditional PDMs. [ABSTRACT FROM AUTHOR]

Recently, multirotor Unmanned Aerial Vehicles(UAVs) or drones have become increasingly popular for a vast variety of civil applications. Efficient traffic data collection and extraction of various flow parameters are some of the futuristic applications of this technology. However, such applications still need to be streamlined and thoroughly explored for varying traffic and infrastructural conditions. In this paper, the focus is on the authentication of the application of small multirotor UAVs for traffic data collection and subsequent analysis of traffic streams at urban roundabouts. This paper presents an analytical methodology to evaluate the performance of roundabouts by extracting various parameters and performance indicators. The performance evaluation methodology is based on: (i) determining traffic volume via OD matrices for each leg, and (ii) analyzing drivers’ behavior via gap-acceptance analysis. The overall analytical process is principally based on the authors’ previously proposed automated UAV video-processing framework for the extraction of vehicle trajectories. The extracted trajectories are further employed to extract useful traffic information. The experimental data to analyse roundabout traffic flow conditions was obtained in the city of Sint-Truiden (Belgium). The results reflect the value of flexibility and bird-eye view provided by UAV videos; thereby depicting the overall applicability of the UAV-based traffic analysis system. With the significant increase in the usage of UAVs expected in the coming years, such studies could become a useful resource for practitioners as well as future researchers. The future research will mainly focus on further extensions of the UAV-based traffic applications. [ABSTRACT FROM AUTHOR]

With the rise of ride-sharing services available in the world, it has ease users to commute with app based services and cashless transactions. The introduction of ride-sharing companies in the start gave the users the liberty to use one application and account to be used universally. However, with the rise of such services, one question that does ring a bell is the passenger safety, especially in countries with loose law controls. This paper focuses on the aspect of passenger safety in ride-sharing services. There have been reports of harassment, assault and robbing passengers on these rides. However, no strict measures could be taken because of the company not having full control over the driver, vehicle and ride. Poor feedback system has also added fuel to the fire. As much as they are filling the gap of better services across the world, there is a dire need of having possible security measures to make sure that rider safety is ensured from the start of the journey till he/she reaches the destination. Different suggestions that have been given include the introduction of mandatory dash cams in the rides through which the rider can put a live transmission of his/her ride on social media or YouTube, in order to have more eyes. Moreover, an introduction of watchdog network, which can volunteer to monitor rides, can also keep an eye on the transmission and can contact lawmakers in case of emergency. A distress alarm on the app can be made available, which can report discomfort of the rider or suspicious behaviour of the driver. Other measures like keeping indoor lights on during after-dark hours, display of ride sharing company’s sticker on front and rear of the car and introduction of passenger insurance add-on in the ride type can also enhance security of the rider. [ABSTRACT FROM AUTHOR]

Informational interventions are considered important to bring positive changes in attitudes and perception about pro-environmental life styles among individuals. In relation to mobility aspects, it is vital to identify relatively easier changes that have potential to reduce negative impacts of mobility on environment and individual health. This paper provides a comprehensive methodological framework and developed a computation algorithm that helps identify such an easy changes in the travel behavior of an individual. The development of algorithm is based on a variety of different data sources such as activity-travel diaries and related constraint information, meteorological conditions, bicycle and public transport supply data. A variety of rules that are part of the computational algorithm are taken from the transport modelling literature, where constraints and factors were examined for various activity-travel decisions. Three major aspects of activity-travel behavior such as lesser car use, cold start of car engines and participation in non-mandatory outdoor activities are considered in assessing pro-environmental potential. The algorithm is applied to data collected, using citizens from Hasselt and their pro-environmental potential is determined, which has been found significant. [ABSTRACT FROM AUTHOR]

When simulating individuals’ daily plan, lots of unexpected events need to be considered, like traffic jam and weather changes. Therefore, there will be a mismatch between the original plan and the executed one. Faced with this situation, individuals need to adjust the rest of the activities to make a new schedule. This paper analyzes the causes of rescheduling, and establishes a new rescheduling model, combining strengths of existing rescheduling models. The model in this paper considers the rescheduling possibilities and choices as much as possible. It takes time pressure and schedule similarity into consideration when updating a schedule. Furthermore, this paper analyzes joint trip/activity execution by studying the cooperation between agents during the rescheduling process. [ABSTRACT FROM AUTHOR]

The degradation of visibility due to foggy weather conditions is a common trigger for road accidents and, as a result, there has been a growing interest to develop intelligent fog detection and visibility range estimation systems. In this contribution, we provide a brief overview of the state-of-the-art contributions in relation to estimating visibility distance under foggy weather conditions. We then present a neural network approach for estimating visibility distances using a camera that can be fixed to a roadside unit (RSU) or mounted onboard a moving vehicle. We evaluate the proposed solution using a diverse set of images under various fog density scenarios. Our approach shows very promising results that outperform the classical method of estimating the maximum distance at which a selected target can be seen. The originality of the approach stems from the usage of a single camera and a neural network learning phase based on a hybrid global feature descriptor. The proposed method can be applied to support next-generation cooperative hazard & incident warning systems based on I2V, I2I and V2V communications. [ABSTRACT FROM AUTHOR]

Agent-Based modelling has been around us for quite some time now and has thus become a crucial factor for executing prediction-based planning, such as the transportation models for metropolitan cities. This paper undertakes the fundamental understanding of the agent-based modeling and simulation and its application to the transportation models while discussing the scope of its applications and advantages too. The paper then presents the concepts attributed to the social behaviors in conjunction with the agent-based modelling techniques applied so far. The literature review conducted in lieu of this work has resulted in agreement with the fact that the potential of agent-based modelling is by far greater than ever due to the ever-improving computing speeds and capabilities, while the understanding of complex human behavior will continue to be a challenge for simulations and automation techniques developed so far. [ABSTRACT FROM AUTHOR]

The performance evaluation of an agent platform is central in the agent-based modeling field. The agent platform and the hardware as well as the operating system modules, including any virtual machines, influence this performance. The impact of these hardware and operating system modules should be understood and evaluated due to their high impact on the global performances. In order to evaluate these two components, this paper proposes the scoring approach, named SARL Experience Index. The score is based on CPU, memory and disk sub-scores. We advocate this score may be helpful for the agent platform users for determining quickly the positive or negative impacts of a new deployment platform for an agent framework. [ABSTRACT FROM AUTHOR]

Abstract: Due to budget constraints public transportation (PT) can no longer be deployed in regions where it attracts insufficient customers. Novel techniques like demand-responsive collective transportation (DRT) are evaluated to cut costs. This requires detailed simulations that are able to predict travel demand and include trip execution. Simulating facilities acting as feeder services to time-table based PT services requires detailed and accurate information about the PT infrastructure on a network. However, there are no public data sources that combine network and PT infrastructure data with the preferred level of detail. A newly developed bus stop mapping technique is presented. It uses the OpenStreetMap (OSM) and General Transit Feed Specification (GTFS) open data sources, which are maintained independently. Merging the data into a single database requires alignment. Developing bus stop mapping algorithms is challenging due to (i) inaccurate location data, (ii) inconsistent data sources and (iii) the vastly interconnected PT network and services. Due to the inaccuracy in the GTFS stop locations and in the OSM network, pure geometric considerations might lead to multiple candidate solutions to map a stop to the network. The new technique handles all GTFS trips at once and operates under the assumption that PT operators minimize the total distance driven to complete all trips. [ABSTRACT FROM AUTHOR]

Abstract: This research paper is a literature review on the behavioral shift using agent-based modeling. We will go through different topics based on agent-based modeling. This research paper points out on different sayings on behavioral shifts. Moreover, it explains the modern research on this topic and many pros and cons on a behavioral shift by using agent-based modeling. [ABSTRACT FROM AUTHOR]

Abstract: Demand responsive collective transportation might be a solution to serve thin flows that occur when the average demand per time unit for travel between particular locations is small. Small capacity and/or specially equipped vehicles are deployed to serve low population density areas and mobility impaired passengers. The variability of the demand and the low vehicle capacity require daily optimal planning of routes. The cost for daily tours heavily depends on the temporal and spatial distribution of the demand. This paper proposes a co-simulation model to evaluate the profitability of thin flow service providers over multiple years of operation under specific condition of public compensation (subsidizing). [ABSTRACT FROM AUTHOR]

Research on demand-responsive collective transportation facilities that can act as feeder services to time-table based public transportation (PT) requires detailed and accurate information about the PT infrastructure, including the attachment of bus stops to the appropriate network link. Due to the size of the infrastructure, the data integration shall be automated. This paper describes the effort to prepare data from publicly available OpenStreetMap (OSM) and General Transit Feed Specification (GTFS) sources. Procedures are proposed (i) to build a network derived from OSM suitable for simulations in transportation, (ii) to extract bus stops from GTFS and remove anomalies and (iii) to find candidate network links to attach them. [ABSTRACT FROM AUTHOR]

A multitude of studies have been motivated on the association between land use, urban settings and transport infrastructure to assist policy makers in sustainable planning. Alike, incorporation of cross-border trips have been an integral part of transportation demand models through external surveys. The present study seeks to explore the Incoming Cross Border Traffic (ICBT) into a study area based on the characteristics of a study area that attracts cross-border trips from outside region. This paper presents an analysis of cross-border trips in Karachi Metropolis, largest city of Pakistan, through Household Individual Survey (HIS-2010) and land use data from alternative resources. Results reveal that land use particulars, socioeconomic characteristics and travel attributes of individuals significantly influences cross-border trips and this effect varies spatially. Work, shopping and Education trips are discussed through separate models in this paper with a number of practical insights to policy makers for sustainable development of city. This study contribute in elucidating travel behaviour through land use parameters and also persuade professionals to integrate estimation of cross-border trips by socioeconomic parameters, in transport forecasting models. [ABSTRACT FROM AUTHOR]