Volatility of car ownership, commuting mode and time in the UK

This paper has two objectives: to examine the volatility of travel behaviour over time and consider the factors explaining this volatility; and to estimate the factors determining car ownership and commuting by car. The analysis is based on observations of individuals and households over a period of up to 11 years obtained from the British Household Panel Survey (BHPS). Changes in car ownership, commuting mode and commuting time over a period of years for the same individuals/households are examined to determine the extent to which these change from year-to-year. This volatility of individual behaviour is a measure of the ease of change or adaptation. If behaviour changes easily, policy measures are likely to have a stronger and more rapid effect than if there is more resistance to change. The changes are “explained” in terms of factors such as moving house, changing job and employment status. The factors determining car ownership and commuting by car are analysed using a dynamic panel-data models.     

Park-and-ride lot choice model using random utility maximization and random regret minimization

This research aims to understand the park-and-ride (PNR) lot choice behaviour of users i.e., why PNR user choose one PNR lot versus another. Multinomial logit models are developed, the first based on the random utility maximization (RUM) concept where users are assumed to choose alternatives that have maximum utility, and the second based on the random regret minimization (RRM) concept where users are assumed to make decisions such that they minimize the regret in comparison to other foregone alternatives. A PNR trip is completed in two networks, the auto network and the transit network. The travel time of users for both the auto network and the transit network are used to create variables in the model. For the auto network, travel time is obtained using information from the strategic transport network using EMME/4 software, whereas travel time for the transit network is calculated using Google’s general transit feed specification data using a backward time-dependent shortest path algorithm. The involvement of two different networks in a PNR trip causes a trade-off relation within the PNR lot choice mechanism, and it is anticipated that an RRM model that captures this compromise effect may outperform typical RUM models. We use two forms of RRM models; the classical RRM and µRRM. Our results not only confirm a decade-old understanding that the RRM model may be an alternative concept to model transport choices, but also strengthen this understanding by exploring differences between two models in terms of model fit and out-of-sample predictive abilities. Further, our work is one of the few that estimates an RRM model on revealed preference data.

     

Flight delays,capacity investment and social welfare under air transport supply-demand equilibrium

This paper analyzes benefits from aviation infrastructure investment under competitive supply-demand equilibrium. The analysis recognizes that, in the air transportation system where economies of density is an inherent characteristic, capacity change would trigger a complicated set of adjustment of and interplay among passenger demand, air fare, flight frequency, aircraft size, and flight delays, leading to an equilibrium shift. An analytical model that incorporates these elements is developed. The results from comparative static analysis show that capacity constraint suppresses demand, reduces flight frequency, and increases passenger generalized cost. Our numerical analysis further reveals that, by switching to larger aircraft size, airlines manage to offset part of the delay effect on unit operating cost, and charge passengers lower fare. With higher capacity, airlines tend to raise both fare and frequency while decreasing aircraft size. More demand emerges in the market, with reduced generalized cost for each traveler. The marginal benefit brought by capacity expansion diminishes as the capacity-demand imbalance becomes less severe. Existing passengers in the market receive most of the benefit, followed by airlines. The welfare gains from induced demand are much smaller. The equilibrium approach yields more plausible investment benefit estimates than does the conventional method. In particular, when forecasting future demand the equilibrium approach is capable of preventing the occurrence of excessive high delays.     

Hot lane policies and their implications

This research examined the major changes in a corridor due to high occupancy/toll (HOT) lane implementation. This was accomplished by comparing the impacts of HOT lanes on three pairs of HOT lanes with similar design and operational characteristics. These pairwise comparisons of similar HOT lanes reduced the impact of exogenous factors and removed the issue of comparing HOT lanes that were so dissimilar it would be impossible to isolate the reasons for difference in results from the lanes. With strict registration requirements for free high occupancy vehicle (HOV) 3+ travel on the I-95 Express Lanes (ELs) in Miami there were indications that some carpoolers switched to lower occupancy modes. Tolled access for HOV2s on I-95 and the SR-91 ELs near Los Angeles resulted in lower usage of those ELs by the HOV2s as compared to most HOV lanes where HOV2 access is free. On the SR167 (Seattle) and I-25 (Denver) HOT lanes, exogenous factors like the price of gas and the economic recession seemed to be the primary influence on the usage of those HOT lanes. In both cases, carpool usage increased along with the price of gas. On I-25, the increasing unemployment rate coincided with a decrease in toll paying travelers. On SR 167 there were also indications of mode shifts among the transit, carpool and toll paying SOVs due to the fluctuating price of gas.     

运用OBD Ⅱ的模式6进行故障诊断

模式6?什么是模式6? EPA(美国环保署)和SAE(美国汽车工程师协会)将OBD Ⅱ系统的诊断根据所定义的内容划分为不同模式.在SAE的轻、中型车辆车载诊断标准手册中规定了这些模式以及它们的操作方式.该手册可从STS(维修技师协会)的网址www.sae.sts.org上购买到.     

A comparison of stochastic and deterministic traffic assignment over congested networks

The similarity between link flows obtained from deterministic and stochastic equilibrium traffic assignment models is investigated at different levels of congestion. A probit-based stochastic assignment is used (over a congested network) where the conditions for equilibrium are those given by Daganzo and Sheffi (1977). Stochastic equilibrium flows are generated using an iterative procedure with predetermined step sizes, and the resulting assignment is validated on the basis of the equilibrium criteria. The procedure is intended to assist in the choice of the most appropriate assignment algorithm for a given level of congestion.     

驾驶辅助系统（DAS）：多种传感器数据的融合

最新的驾驶辅助系统（DAS）技术通过“传感器数据融合”,把来自不同信息源的传感器数据结合起来,形成更全面的有关道路状况的报告,从而让车辆和道路更安全。     

Aggregation effects on the network design problem

This article examines the effects of various network extraction schemes on the network design problem. Given an original network, many criteria can be used to identify subnetworks on which the network design problem is solved. For the purposes of this article, these subnetworks are obtained using an extraction algorithm which preserves the magnitude of the user equilibrium flows on the links of these subnetworks. The results of the implementation of the network design problem on the original and the extracted subnetworks are presented and compared. We conclude that very good solutions to the network design problem can be obtained from the use of highly aggregate networks.     

A numerical investigation of the impact of uncertain demand and varying risk preferences on the pricing and capacity decisions of transportation firms: The case of airlines

In this paper, we attempt to motivate the importance of uncertain demand and varying risk preferences in understanding the behavior of transportation firms. Using specific functional forms, a numerical investigation of this issue is carried out for the case of airlines. The major finding is that changes in risk preferences do not significantly affect the choice of fare but do affect the choice of capacity. This finding is shown to be fairly robust as sensitivity tests are performed for some of the key parameters in the model. Finally, the relevance of the analysis in terms of characterizing the airlines' initial response to deregulation is briefly discussed.