Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

Promoting public bike-sharing: A lesson from the unsuccessful Pronto system

In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.     

A traffic-condition-based route guidance strategy for a single destination road network

Most of existing route guidance strategies achieves user optimal equilibrium by comparing travel time. Measuring travel time, however, might be uneasy on an urban road network. To contend with the issue, the paper mainly considers easily obtained inflow and outflow of a link and road capacity as input, and proposes a route guidance strategy for a single destination road network based on the determination of free-flow or congested conditions on alternative routes. An extended strategy for a complex network and a feedback approximation for avoiding forecast are further explored. Weaknesses of the strategy are also explicitly analyzed. To test the strategy, simulation investigations are conducted on two networks with multiple parallel routes. The results indicate that the strategy is able to provide stable splitting rates and to approximate user optimal equilibrium in different conditions, in particular when traffic demand is high. This strategy has potential to be applied in an urban road network due to its simplicity and easily obtained input data. The strategy is also applicable for single destination if some alternatives and similar routes are available.     

对地铁信号系统列车运行速度制约因素的探讨

信号系统是保障地铁运行安全及提高运行效率的重要设备,列车超速防护功能是信号系统一个非常关键的功能。信号系统防护下的列车运行速度由车辆、线路、轨道、限界及信号系统等条件共同决定。由于相关专业对信号系统安全制动模型不了解,在实际工程中易造成"速度浪费"现象。从信号系统安全制动模型的原理出发,对车辆、线路、轨道、限界等专业对列车运行速度的制约因素进行分析,提出建议。     

呼和浩特市优先发展城市公共交通探讨

通过对呼和浩特市城市公共交通现状的分析,指出呼和浩特市公共交通存在的问题,进一步说明保证呼和浩特市公共交通优先发展在缓减交通压力、提高城市公共客运效益、环境保护方面的重要意义,同时提出呼和浩特市优先发展公共交通应采取的措施.     

The effects of planned and unplanned transfers on public transport users' perception of transfer routes

Many authorities are investing in new infrastructure to improve the quality of public transport (PT) services in the hope to increase mode switch from cars. The goal is to provide users with an integrated multimodal PT network by facilitating transfers. There exists a lack in the clarity of the attributes which defines a planned transfer and the effects of planned transfers on users' willingness to use routes with transfers. The present study provides approximate effects of ‘planned’ and ‘unplanned’ transfers on PT users' decisions to use transfer routes. The study focuses on two attributes of ‘planned’ transfers, integrated physical connection of transfers and information integration. A user preference survey was undertaken in Auckland, New Zealand. Analysis of the results shows that physical integration is more important than information integration for current PT users. Results also suggest that information integration has a greater influence on users of transfer services which are more closely aligned to being ‘unplanned’.     

The generators of paratransit trips by persons with disabilities

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.     

Detection of nonlinearity effects in structural integrity monitoring methods for offshore jacket-type structures based on principal component analysis

The detection of changes in the dynamic behavior of structures is an important issue in structural safety assessment. The development of detection methods assumes greater significance in the case of offshore platforms because the inherent problems are compounded by the harsh environment. Here, we describe an instrumented physical model for the structural health monitoring of an offshore jacket-type structure and the results of tests in several different damage scenarios. In a comparative investigation of two different methods, we discuss the difficulties of implementing damage detection techniques for complex structures, such as offshore platforms. The combined algorithm of a fuzzy logic system and a model updating method are briefly discussed, and a method based on stochastic autoregressive moving average with exogenous input is adopted for the structure. The consideration of uncertainties and the effects of nonlinearity were major objectives. So, the methods were also investigated based on the test scenarios consisting of the physical model with a geometric nonlinearity. The principal component analysis method was utilized for the detection of nonlinearity in the recorded data. The results show that the developed methods are suitable for damage classification, but the quality of the acquired signals must be considered an important factor influencing successful classification. The development of these methods may be extremely useful, as such technologies could be applied for offshore platforms in service, enabling damage detection with fewer false alarms.     

圆形隧道施工对不同深度地层沉降影响的模型试验研究

为了预测圆形隧道施工引起地表以下不同埋深地层沉降特征,首先,通过理论推导不同地层最大沉降位移与沉降槽宽度系数的函数关系;然后,建立包括试验台架、地层模型、圆形隧道开挖模型以及测量地层变形装置的平面应变模型试验系统。通过理论解析和模型试验可知:1)地表以下地层的最大沉降位移与沉降槽宽度系数成反比;2)不同深度地层的沉降位移随着地层埋深的增加而增大,且地表以下地层沉降槽曲线仍然符合正态分布;3)通过对模型试验数据进行回归分析,得到黏土地表以下不同深度地层沉降槽宽度系数的计算公式,从而为预测圆形隧道施工地表以下不同深度地层竖向位移提供了一种可靠的计算方法。