A Modeling Framework for Bus Rapid Transit Operations Evaluation and Service Planning

Abstract

In this paper, we present a dynamic traffic assignment-simulation modeling framework (DYNASMART-P) to support the evaluation and planning of Bus Rapid Transit (BRT) services in urban transportation networks. The model represents the different characteristics associated with BRT operations such as: exclusive right-of-way lanes, limited-stop service, signal prioritization at congested intersections, and enhanced bus stops to reduce passenger boarding times. A set of simulation experiments is conducted using the model to study the impact of introducing a hypothetical BRT service in the Knoxville area in the State of Tennessee. In these experiments, the different operational characteristics of BRT are evaluated in terms of potential impact on transit ridership and on the interacting auto traffic. The results illustrate the advantages of BRT for increasing transit ridership and improving overall system performance.     

Optimization of Fare Structure and Service Frequency for Maximum Profitability of Transit Systems

Abstract

Providing efficient public transportation has been recognized as a potential way of alleviating congestion, improving mobility, mitigating air pollution, and reducing energy consumption. Many people use public transportation systems for their daily commute, while others use different transportation modes (e.g. cars, taxis, carpools, etc.). Inexpensive fares with good transit service encourages ridership, and the resulting revenue may be used to provide better service. Optimization of transit service frequency and its associated fare structure is desirable in order to increase revenue at reasonable transit operating expenditure. The objective of the study reported here is to maximize profit subject to service capacity constraint, while elastic demand is considered. The solution methodology is developed and applied to solve the profit maximization problem in a case study based on Newark, NJ, USA. Numerical results, including optimal solutions and sensitivity analyses, are presented. It is found that an optimal temporal headway and differential fare structure that maximizes total profit for the studied subway system can be efficiently solved.     

In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers

The development of self-driving cars or autonomous vehicles has progressed at an unanticipated pace. Ironically, the driver or the driver-vehicle interaction is a largely neglected factor in the development of enabling technologies for autonomous vehicles. Therefore, this paper discusses the advantages and challenges faced by aging drivers with reference to in-vehicle technology for self-driving cars, on the basis of findings of recent studies. We summarize age-related characteristics of sensory, motor, and cognitive functions on the basis of extensive age-related research, which can provide a familiar to better aging drivers. Furthermore, we discuss some key aspects that need to be considered, such as familar to learnability, acceptance, and net effectiveness of new in-vehicle technology, as addressed in relevant studies. In addition, we present research-based examples on aging drivers and advanced technology, including a holistic approach that is being developed by MIT AgeLab, advanced navigation systems, and health monitoring systems. This paper anticipates many questions that may arise owing to the interaction of autonomous technologies with an older driver population. We expect the results of our study to be a foundation for further developments toward the consideration of needs of aging drivers while designing self-driving vehicles.     

A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles

This paper describes the methodology we set up to gather appropriate data to study the impact of real life experience with electric vehicles (EVs) over a relatively long period of time on individual preferences and attitudes. We used stated choices (SC) to elicit individual preferences because EVs and their associated charging infrastructure are not yet fully integrated onto the market. Furthermore, to measure the extent to which the experience of using an EV may affect individual preferences and attitudes, we set up a “long panel” survey, where data was gathered before and after individuals experienced an EV in real life during a three-month period. We also measured attitudinal effects (AE) that might affect the choice of an EV by individuals. To our knowledge, this represents the first example of a “long panel” SC/AE and the first attempt to measure the formation of preferences and attitudes for this emerging product. Our results show that preferences and attitudes are indeed affected by real life experience. In the SC experiment, the respondents only chose the EV half as often as compared to the situation where they had not yet tried it. Furthermore, we measured a change in attitude for statements regarding the use of EVs. On the whole, respondents got a more positive view of the EV driving performance and this change is significantly greater for women than for men. However, respondents expressed more concern about being able to maintain current mobility with an EV. The data gathered in this survey should also serve to analyse the changes generated by direct experience with EVs, and eventually to formulate and estimate advanced discrete choice models that allow insights into factors relevant for improved understanding of market behaviour.     

Development of an intelligent CAE system for auto-body concept design

The concept design phase is a critical step in auto-body design, as it has a great effect on later design work. This paper describes the implementation of an auto-body structure design in the early stages of a new auto-body developing program. In order to reduce the long design period and analysis error that plagues traditional auto-body concept design, an intelligent CAE system has been successfully developed and implemented based on the UGS NX/API opening platform. This system, the so-called ACD-ICAE (Auto-body concept design-intelligent computer aided engineering) System that means concept design-intelligent computer aided engineering system, employs a fully parametrized template method to build the conceptual auto-body geometry model and FEM model quickly and easily. It also integrates auto-body modeling, analysis and optimization on only one CAD platform via a parametric variables database. Moreover, all parametric variables are shared and updated in different phases of the ACD-ICAE System. A wizard User Interface (UI) based on knowledge of auto-body engineering was developed and used in this system. The procedures implementing the functional diagram of the ACD-ICAE system are also provided. A typical example of a car body concept design with four doors shows that the ACD-ICAE system is efficient and accurate.     

无伸缩缝桥梁研究综述

综述了无伸缩缝桥梁(简称“无缝桥”)技术发展,介绍了无缝桥优点、应用和研究热点,分析了无缝桥纵桥向受力特点、桩-土相互作用、台后土压力与抗震性能,指出了新技术研发与应用的现状与发展方向。分析结果表明：无缝桥技术受到许多国家的重视,已开展了大量的实桥监测和其他研究;在纵桥向受力方面,温度变形是其主因,现有规范中所给出的平均温差与实桥监测结果相差较大,应研究精度更高的计算方法;桩-土相互作用是整体桥受力的特点与研究的难点,在计算土抗力时,m法应限于小位移的无缝桥,位移较大时宜采用p-y曲线法;桥台桩基受力复杂,H型钢桩存在屈服、疲劳、屈曲的破坏可能,混凝土桩则易出现开裂病害;无缝桥温升时台后土压力增大,是研究的热点与难点,它随水平变形量和往复变形次数增大而增大的机理、量值和分布未达成共识,有待今后深入、系统的研究;纵桥向受力分析应建立全桥有限元模型,考虑结构-土相互作用和节点非线性性能;钢主梁受压稳定性和混凝土主梁抗裂性能是研究与设计的关键;引板是无缝桥的病害易发构件,面板式引板应减小板底摩阻力,避免开裂和末端沉降,而斜埋入式引板应控制其末端之上接线路面的隆起和下陷;许多无缝桥新技术已被提...     

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

Transportation - Traditional approaches to travel behaviour modelling primarily rely on household travel survey data, which is expensive to collect, resulting in small sample sizes and infrequent...     

Numerical Simulation of Vehicle Behavior during Straight Line Keeping on Undulating Road Surfaces

Numerical design of vehicles having optimal straight line stability on undulating road surfaces requires an accurate vehicle model based on knowledge of the relevant phenomena. Therefore, vehicle behavior on undulating straight roads has been analyzed and modeled. Measurements on a flat road surface have shown that the dedicated vehicle model yields accurate simulation results of the steering response to medium steering wheel angle inputs. In addition, the model has been validated by measuring two vehicle responses during normal driving on an undulating straight road: viz. the responses to the small steering wheel angle input and to the input by the global inclination of the road surface.     

Impact of high occupancy vehicle lanes on carpooling behavior

High occupancy vehicle lanes have become an integral part of regional transportation planning. Their purpose is to increase ridesharing by offering a travel time advantage to multiple occupant vehicles. This paper examines the extent to which an HOV facility increases ridesharing. Using data from the Route 55 HOV facility in Orange Country, California, changes in the carpooling rate on Route 55 are compared to that of a control group of freeway commuters. The analysis shows that the carpooling rate among peak period commuters, and particularly those who use the entire length of the facility, has increased. However, there has been no significant increase in ridesharing among the entire population of Route 55 commuters. Results suggest that barriers to increased ridesharing are formidable, that travel time savings must be large in order to attract new carpoolers, and that further increases in capooling will likely require development of extensive HOV lane systems.