On the variance of recurrent traffic flow for statistical traffic assignment

This paper generalizes and extends classical traffic assignment models to characterize the statistical features of Origin-Destination (O-D) demands, link/path flow and link/path costs, all of which vary from day to day. The generalized statistical traffic assignment (GESTA) model has a clear multi-level variance structure. Flow variance is analytically decomposed into three sources, O-D demands, route choices and measurement errors. Consequently, optimal decisions on roadway design, maintenance, operations and planning can be made using estimated probability distributions of link/path flow and system performance. The statistical equilibrium in GESTA is mathematically defined. Its multi-level statistical structure well fits large-scale data mining techniques. The embedded route choice model is consistent with the settings of O-D demands considering link costs that vary from day to day. We propose a Method of Successive Averages (MSA) based solution algorithm to solve for GESTA. Its convergence and computational complexity are analyzed. Three example networks including a large-scale network are solved to provide insights for decision making and to demonstrate computational efficiency.     

On a link-based day-to-day traffic assignment model

In this paper, we perform a rigorous analysis on a link-based day-to-day traffic assignment model recently proposed in He et al. (2010). Several properties, including the invariance set and the constrained stability, of this dynamical process are established. An extension of the model to the asymmetric case is investigated and the stability result is also established under slightly more restrictive assumptions. Numerical experiments are conducted to demonstrate the findings.     

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.     

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.     

聚脂纤维沥青混合料性能的试验研究

在沥青混合料中掺加聚脂纤维,通过室内试验对沥青混合料的高温稳定性、低温抗裂性、水稳定性等路用性能进行研究,对试验得出的各项路用性能指标进行有针对性的分析,得出加入聚脂纤维能有效改善沥青混合料的路用性能,但在使用上应根据具体工程的交通条件和气候条件,通过试验进行科学的选择.     

船用柴油机应对IMO Tier Ⅲ排放法规的路线选择

首先对比了国内外柴油机的排放水平现状,然后对船用柴油机NOX减排技术进行了介绍,并从成熟度和经济性方面,对其中能够满足IMO Tier III排放法规的EGR、SCR以及DF技术进行了对比分析,最后从短期和长期两方面,对我国船用柴油机排放控制技术路线的选择进行了探讨,并给出了相关建议。     

长丰县城乡公交需求和现状一体化分析

为了进一步加强城乡经济社会的协调发展,同时缩短城乡差距,加强综合交通网络,并提高城市和农村地区的综合交通运输网络,城乡公交一体化便是公共交通的主流发展。文章在深入安徽省合肥市长丰县实地调研的基础上,探究了长丰县公交一体化的发展状况,为长丰经济发展助力。     

Managing Beach Amenities to Reduce Exposure to Coastal Hazards: Storm Water Pollution

Despite posted warnings and educational campaigns warning about the health risks associated with storm water pollution, swimmers continue to swim in coastal areas polluted by storm water runoff. This study uses a simple spatial model of beach visitation to show how beach amenities and storm drains influence the way in which beach goers choose to locate themselves at beaches in Santa Monica Bay, California. The estimated models indicate that passive means of preventing exposure to marine pollution (e.g., posted signs) could be made significantly more effective if combined with the active management of other beach amenities. Similar methods also could be used to reduce risks to swimmers from other hazards including riptides and boat traffic.     

Choice of parking: Stated preference approach

Over recent years, parking policy has become a key element of transport policy in many countries. Parking policy measures can affect many different dimensions of travel behaviour but are likely to be most significant in terms of travellers' choice of parking type and location. This dimension of travel choice has, to date, received comparatively little attention, yet is of vital importance if we are to properly understand and predict the effects of parking policy measures.This paper presents two studies addressing this issue carried out in the United Kingdom and Germany. Both studies used a stated preference approach in order to collect disaggregate data on travellers responses to changes in parking attributes and used these data to build simple logit models of parking type choice. The studies were designed in order to allow comparable choice models to be estimated from the two datasets. The results obtained strongly indicate the need to separately identify the costs associated with different components of the parking activity (e.g., general in-vehicle time, parking search time, egress time) and also point to the existence of significant differences in the relative valuation of these components across different journey purposes. Where possible, the results of the choice modelling exercises are also compared with existing revealed and stated preference results and are found to be generally in line with prior expectations.     

铁路站场最优进路研究

本文介绍了计算机联锁进路搜索的现状以及基于图论理论建立的铁路站场控制的图模型，阐述了通过最短路原理实现的铁路站场最优进路控制的方法。