基于乘客需求的公交客流OD采集技术研究

为了提高公交服务水平和优化公交调度,在分析现有公交客流采集技术基础上,运用单片机技术、通信技术等,提出了基于乘客需求的公交客流OD采集技术,设计了由请求单元、公交车单元、数据中心组成的采集系统,实现了公交乘客的上下车请求、站点客流数据、公交OD数据的采集,可以为公交优化调度提供基础数据。     

有关汽车合乘问题的研究

城市道路上汽车低使用率问题和大城市汽车合乘现象的出现反映了汽车合乘存在和发展的必然性。从国内外合乘现状出发,在论述合乘含义的基础上,对合乘的类型划分、合乘途径、合乘实施的利弊以及合乘的实施保障等问题进行相关探讨,对于汽车合乘的后续研究有着重要意义。     

微观仿真在城市停车设施规划中的应用

为研究停车场规划和可达性对城市路网的影响,在世界范围内的三个不同城市应用微观仿真模型模拟停车设施规划。描述了三个城市采用的不同研究方法及得到的研究结果。三项研究都试图找到由驾驶人寻找停车位而造成的城市交通拥堵的解决方法。同时,在测试设计方案时,都使用了S-Paramics微观仿真模型。     

Driver models in automobile dynamics application

Understanding the driver of an automobile has been attractive to researchers from many different disciplines for more than half a century. On the basis of their acquirements, models of the (human) driver have been developed to better understand, analyse and improve the combined couple of driver and automobile. Due to distinctive demands on the models in accordance with different kinds of applications, a variety of driver models is available. An overview of driver models is given with respect to their application and different methodical modelling approaches. The emphasis is put on the interest of engineers, who generally focus on the automobile (like design and optimization of vehicle components and the overall vehicle dynamics behaviour) by applying their approved (mathematical) methods. Nonetheless, a brief look beyond is added to better complete the view on the involved task of driving and driver modelling for automobile dynamics application.     

Sustainable cold supply chain management under demand uncertainty and carbon tax regulation

Increasing awareness of sustainability in supply chain management has prompted organizations and individuals to consider environmental impacts when managing supply chains. The issues concerning environmental impacts are significant in cold supply chains due to substantial carbon emissions from storage and distribution of temperature-sensitive product. This paper investigates the impact of carbon emissions arising from storage and transportation in the cold supply chain in the presence of carbon tax regulation, and under uncertain demand. A two-stage stochastic programming model is developed to determine optimal replenishment policies and transportation schedules to minimize both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The performance and robustness of the matheuristic algorithm are analyzed using test instances in various sizes. A real-world case study in Queensland, Australia is used to demonstrate the application of the model. The results highlight that higher emissions price does not always contribute to the efficiency of the cold supply chain system. Furthermore, the analyses indicate that using heterogeneous fleet including light duty and medium duty vehicles can lead to further cost saving and emissions reduction.     

Machine learning applications in activity-travel behaviour research: a review

ABSTRACT

This paper reviews the activity-travel behaviour literature that employs Machine Learning (ML) techniques for empirical analysis and modelling. Machine Learning algorithms, which attempt to build intelligence utilizing the availability of large amounts of data, have emerged as powerful tools in the fields of pattern recognition and big data analysis. These techniques have been applied in activity-travel behaviour studies since the early ’90s when Artificial Neural Networks (ANN) were employed to model mode choice decisions. AMOS, an activity-based modelling system developed in the mid-’90s, has ANN at its core to model and predict individual responses to travel demand management measures. In the dawn of 2000, ALBATROSS, a comprehensive activity-based travel demand modelling system, was proposed by Arentze and Timmermans using Decision Trees. Since then researchers have been exploring ML techniques like Support Vector Machines (SVM), Decision Trees (DT), Neural Networks (NN), Bayes Classifiers, and more recently, Ensemble Learners to model and predict activity-travel behaviour. A large number of publications over the years and an upward trend in the number of published articles over time indicate that Machine Learning is a promising tool for activity-travel behaviour analysis and prediction. This article, first of its kind in the literature, reviews these studies and explores the trends in activity-travel behaviour research that apply ML techniques. The review finds that mode choice decisions have received wide attention in the literature on ML applications. It was observed that most of the studies identify the lack of interpretability as a serious shortcoming in ML techniques. However, very few studies have attempted to improve the interpretability of the models. Further, some studies report the importance of feature engineering in ML-based studies, but very few studies adopt feature engineering before model development. Spatiotemporal transferability of models is another issue that has received minimal attention in the literature. In the end, the paper discusses possible directions for future research in the area of activity-travel behaviour modelling using ML techniques.     

An ontological model to support communications of situation-aware vehicles

In an Intelligent Transport System (ITS) environment, the communication component is of great importance to support interactions between vehicles and roadside infrastructure. Previous studies have focused on the physical capability and capacity of the communication technologies, but the equally important development of suitable and efficient semantic content for transmission received notably less attention. Ontology is one promising approach for context modelling in ubiquitous computing environments, and in the transport domain it can be used both for context modelling and semantic contents for vehicular communications. This paper explores the development of an ontological model implementing relative geo-semantic information messages to support vehicle-to-vehicle communications. The proposed ontology model contains classes, objects, their properties/relations as well as some functions and query templates to represent and update the information of dynamic vehicles, inter-vehicle interactions and behaviour. This model was developed through a scenario enabling the evaluation of traffic conflict resolution approaches, by implementing a set of decision-making processes for intelligent vehicles. Given the scope of the proposed ontology modelling, it shows how vehicular communications can be used to update each vehicle’s context model. This work can be easily extended for more complex interactions among vehicles and the infrastructure.     

Centrifuge modelling of a combined pile-type anchor subjected to general inclined loading

One of the main challenges associated with anchoring offshore platforms is the logistic needed to install them in deep water. The growing need for high capacity anchors has prompted the development of new systems where the feasibility of transporting them out to sea is a crucial consideration. With respect to torpedo piles used by Petrobras in Brazil, new platforms installed in deep water required robust anchoring systems, and a cluster of small torpedoes was considered instead of one large torpedo. However, torpedo pile installation is hindered by deep water streams, which can deviate their trajectory during the fall. This is of great concern for the design of torpedo pile clusters because the distance between the piles cannot be controlled during installation. The present study aims to determine the variation in the load capacity of a cluster or array of single piles as a function of the distance between the piles and the load direction after installation on the seabed. To that end, a series of centrifuge tests were carried out on pile clusters installed in loose sand, varying the distance between the piles and the loading direction. The results show considerable interactions between the adjacent piles depending on the load direction and pile spacing. The optimal spacing for maximum cluster efficiency was determined, and comparisons were made with values from the literature for capped pile clusters.     

Modeling travel mode choice of young people with differentiated E-hailing ride services in Nanjing China

E-hailing ride service (ERS) has become increasingly popular globally and is changing the urban mobility landscape. There is insufficient research effort in understanding the impact of ERS on travel behavior, in particular among young people. This paper aims to start filling that research gap by first collecting mode choice preference data through a stated preference survey in City of Nanjing, China and then applying nested logit (NL) models and a series of post-estimation analysis to address a number of key research questions of mode choice behavior without and with ERS. Three ERS modes are considered in the Chinese context: DiDi Taxi (D-Taxi), DiDi Express (D-Express), and DiDi Premier (D-Premier), all provided by DiDi Chuxing, the dominant ERS service provider in China. The study finds that age makes little difference in mode choice preference when ERS is introduced between the two age groups considered (18–30 and 31–45). The study results also suggest that young travelers are naturally drawn to ERS for what it represents (a technology innovation) and its business (pricing) model. ERS appears to be a competitive alternative to the conventional modes especially when they are under performed. The study also finds that ERS will likely increase vehicle kilometers traveled (VKT) considerably, which will lead to increase in on-road vehicular emissions, unless some mechanism to switch users to ridesharing is in place.     

Design,modelling, and analysis of a large floating dock for spar floating wind turbine installation

Installation of floating wind turbines at the offshore site is a challenging task. A significant part of the time efficiency and costs are related to the installation methods which are sensitive to weather conditions. This study investigates a large floating dock concept, which can be used to shield a floating wind turbine during installation of tower, nacelle, and rotor onto a spar foundation. In this paper, the concept is described in detail, and a design optimisation is carried out using simple design constraints. Hydrodynamic analysis and dynamic response analysis of the coupled system of the optimum dock and spar are conducted. Two spars of different sizes are considered, and the motion responses of the spars with and without the dock in irregular waves are compared. Through analysis of the motion spectra and response statistics, dynamic characteristics of the coupled system is revealed. The present design of the dock reduces the platform-pitch responses of the spars and potentially facilitates blade mating, but may deteriorate the heave velocity of the spars in swell conditions. Finally, future design aspects of the floating dock are discussed.