Household trip generation choice—Alternative empirical approaches

Trip generation models have generally received less attention than other aspects of travel decision making. This article presents some explorations into the structure of trip decisions for shopping, using data from weekly shopping diaries. The paper compares alternative formulations of the naturally-ordered choice model used by Sheffi (1979) to avoid the problems inherent in multinomial logit models. Firstly, imposing cross-alternative restrictions on some of the coefficient values is termed the constrained model. Secondly, when no such restrictions are imposed, the model decomposes into a sequence of binary models, and this is termed the unconstrained model, which can be used to test the validity of the restrictions. The variables used include both shopping expenditures and locational factors, both of which are found to play a key role in shopping travel decisions, as well as more conventional socio-economic variables. A clearer understanding of the role of car ownership in travel decisions is obtained.     

The importance of time in transit and reliability of transit time for shippers,receivers, and carriers

Reliability of transit time is reputed to be the most important variable influencing freight transport today, according to shipper surveys. Average transit time also plays a major role. A model is developed that shows how a cost-minimizing shipper will adjust its economic order quantity as reliability and/or time in transit changes. Such changes impact on average inventory costs, ordering costs, expected shortage costs and expected excess costs. The model is developed for both discrete and continuous transit time distributions. Reliability is defined as the variance of transit time. A matrix is prepared for some sample data, which shows the minimum cost attainable with each mean/variance of transit time distribution. Comparing across rows and columns of the matrix enables one to show the value (reduction in total cost) obtainable by improving reliability and/or mean transit time. In addition, value can be obtained by improving reliability while increasing average transit time. It is suggested that the model can be used for shippers in negotiating service improvements with carriers and by carriers in negotiating service improvements with shippers. In the former case, the carrier can determine how much they are willing to pay for the improvement, whereas in the latter case, the carriers can determine how much they are able to charge for the improvement.     

A fuzzy method for predicting the demand for rail freight transportation

The demand for rail freight transportation is a continuously changing process over space and time and is affected by many quantitative and qualitative factors. In order to develop a more rational transport planning process to be followed by railway organizations, there is a need to accurately forecast freight demand under a dynamic and uncertain environment. In conventional linear regression analysis, the deviations between the observed and the estimated values are supposed to be due to observation errors. In this paper, taking a different perspective, these deviations are regarded as the fuzziness of the system's structure. The details of fuzzy linear regression method are put forward and discussed in the paper. Based on an analyzes of the characteristics of the rail transportation problem, the proposed model was successfully applied to a real example from China. The results of that application are also presented here.     

Transportation and energy—A future confrontation

An examination of the relationship between energy supplies and transportation systems indicates that a major confrontation is forthcoming. Predictions of the world's petroleum supplies and the primary dependence of transportation systems on petroleum show that there will be a depletion of these supplies in the next 50 years unless major changes in transportation and energy planning and policy making are forthcoming. A closer examination of specific transportation systems through the use of the transportation/ energy efficiency indicates that automobiles, aircraft and intercity trucking are most inefficient on a mobility per unit of petroleum basis. Recommendations on the difficult problem of how to account for the depletion characteristics of transportation systems are given. These include coordinated transportation and energy planning, restricted petroleum and transportation toll and tax rates, research and development on propulsion systems less dependent on petroleum, and a shifting of emphasis to higher transportation/energy efficiency systems such as compact automobiles, buses and trains.     

考虑牵引作用的独立旋转车轮导向转向架的运行性能

提出了一种新型独立旋转车轮导向转向架,数值分析和缩尺模型试验均表明,该转向架在牵引力矩作用下,仍具备自导向能力,能够平稳运行。     

Modelling passenger demand for parkway rail stations

Interest in Parkway stations emerged in the 1980s. These act as convenient out-of-town stations for inter-urban rail journeys. There were 13 so-called Parkway stations in Great Britain in 1999 and two have subsequently been opened. This paper reports the development and application of a new Parkway forecasting model which was conducted for the Association of Train Operating Companies (ATOC), undertaken as part of an extensive update to the Passenger Demand Forecasting Handbook, which recommends demand forecasting frameworks and associated parameters that are widely used in the railway industry in Great Britain. The objective was to develop a model that had more desirable properties and was more straightforward to apply than the previously recommended procedure. The focus is entirely upon inter-urban journeys of over 80 km.The model forecasts the demand for Parkway stations based solely on rail ticket sales data and its properties are illustrated with two case study applications. The nature of Parkway stations forces consideration of competition, and it is demonstrated that the inclusion of a station choice component leads to a somewhat improved explanatory power and a more plausible generalised cost elasticity.In addition to the methodological developments, the model has provided generally reasonable elasticities and forecasts and shown that Parkway users have different preferences to rail travellers in general. In a test based around a newly opened Parkway station, its forecasts are more accurate than the procedure it replaces.     

Wave data assimilation with the Kalman filter

A new data assimilation method for ocean waves is presented, based on an efficient low-rank approximation to the Kalman filter. Both the extended Kalman filter and a truncated second-order filter are implemented. In order to explicitly estimate past wind corrections based on current wave measurements, the filter is extended to a fixed-lag Kalman smoother for the wind fields. The filter is tested in a number of synthetic experiments with simple geometries. Propagation experiments with errors in the boundary condition showed that the KF was able to accurately propagate forecast errors, resulting in spatially varying error correlations, which would be impossible to model with time-independent assimilation methods like OI. An explicit comparison with an OI assimilation scheme showed that the KF also is superior in estimating the sea state at some distance from the observations. In experiments with errors in the driving wind, the modeled error estimates were also in agreement with the actual forecast errors. The bias in the state estimate, which is introduced through the nonlinear dependence of the waves on the driving wind field, was largely removed by the second-order filter, even without actually assimilating data. Assimilation of wave observations resulted in an improved wave analysis and in correction of past wind fields. The accuracy of this wind correction depends strongly on the actual place and time of wave generation, which is correctly modeled by the error estimate supplied by the Kalman filter. In summary, the KF approach is shown to be a reliable assimilation scheme in these simple experiments, and has the advantage over other assimilation methods that it supplies explicit dynamical error estimates.     

A dynamic cordon pricing scheme combining the Macroscopic Fundamental Diagram and an agent-based traffic model

Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior in terms of travelers’ choices and heterogeneity. This integrated approach is superior to traditional pricing schemes. On one hand, traffic simulators (including car-following, lane-changing and route choice models) consider travel behavior, i.e. departure time choice, inelastic to the level of congestion. On the other hand, most congestion pricing models utilize supply models insensitive to demand fluctuations and non-stationary conditions. This is not consistent with the physics of traffic and the dynamics of congestion. Furthermore, works that integrate the above features in pricing models are assuming deterministic and homogeneous population characteristics. In this paper, we first demonstrate by case studies in Zurich urban road network, that the output of a agent-based simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram (MFD). We then develop and apply a dynamic cordon-based congestion pricing scheme, in which tolls are controlled by an MFD. And we investigate the effectiveness of the proposed pricing scheme. Results show that by applying such a congestion pricing, (i) the savings of travel time at both aggregated and disaggregated level outweigh the costs of tolling, (ii) the congestion inside the cordon area is eased while no extra congestion is generated in the neighbor area outside the cordon, (iii) tolling has stronger impact on leisure-related activities than on work-related activities, as fewer agents who perform work-related activities changed their time plans. Future work can apply the same methodology to other network-based pricing schemes, such as area-based or distance-traveled-based pricing. Equity issues can be investigated more carefully, if provided with data such as income of agents. Value-of-time-dependent pricing schemes then can also be determined.     

Fatigue life reliability prediction of a stub axle using Monte Carlo simulation

A stub axle is a part of a vehicle constant-velocity system that transfers engine power from the transaxle to the wheels. The stub axle is subjected to fatigue failures due to cyclic loads arising from various driving conditions. The aim of this paper was to introduce a probabilistic framework for fatigue life reliability analysis that addresses uncertainties that appear in the mechanical properties. Service loads in terms of response-time history signal of a Belgian pave were replicated on a multi-axial spindle-coupled road simulator. The stress-life method was used to estimate the fatigue life of the component. A fatigue life probabilistic model of a stub axle was developed using Monte Carlo simulation where the stress range intercept and slope of the fatigue life curve were selected as random variables. Applying the goodness-of-fit analysis, lognormal was found to be the most suitable distribution for the fatigue life estimates. The fatigue life of the stub axle was found to have the highest reliability between 8000–9000 cycles. Because of uncertainties associated with the size effect and machining and manufacturing conditions, the method described in this paper can be effectively applied to determine the probability of failure for mass-produced parts.