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.     

中韩船舶油污损害赔偿制度的比较

韩国不论是从地理位置还是经济贸易往来,对于我国是很重要的邻国.由于海上运输的国际性,我国的船东有在该国卷入油污损害赔偿案件的可能,研究其油污损害赔偿制度能够更好的保护我国船东的权益,而且对于我国完善油污民事赔偿立法有一定的借鉴作用.本篇论文比较了中韩油污损害赔偿制度,并对完善我国油污损害赔偿制度提出几点建议.     

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。     

钩形外锁闭装置锁闭框组优化的探讨

钩形外锁闭装置在实践中逐步暴露出一些诸如转换不畅、卡阻,磨耗严重,适应尖轨窜动性不良等问题.为此研究探讨对既有的外锁闭装置锁闭框组（包括锁闭框、锁闭铁、耐磨板等）进行优化,提高道岔转换的可靠性.     

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.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.