Transportation - A sharing logistics platform for less-than-truckloads could increase efficiency in city pickup and last-mile deliveries under time window constraints by pairing (matching) truck... 相似文献
Transportation - Considerable recent work suggests that Millennials’ behaviors may be converging with those of Generation X as they enter later life stages, but few have investigated whether... 相似文献
In this study, we focused on a novel parallel mechanism for utilizing the motion simulator of a high-speed boat (HSB). First, we expressed the real behavior of the HSB based on a seakeeping trial. For this purpose, we recorded the motion parameters of the HSB by gyroscope and accelerometer sensors, while using a special data acquisition technique. Additionally, a Chebychev high-pass filter was applied as a noise filter to the accelerometer sensor. Then, a novel 3 degrees of freedom (DoF) parallel mechanism (1T2R) with prismatic actuators is proposed and analyses were performed on its inverse kinematics, velocity, and acceleration. Finally, the inverse dynamic analysis is presented by the principle of virtual work, and the validation of the analytical equations was compared by the ADAMS simulation software package. Additionally, according to the recorded experimental data of the HSB, the feasibility of the proposed novel parallel mechanism motion simulator of the HSB, as well as the necessity of using of the washout filters, was explored. 相似文献
Loop detectors are devices that are most commonly used for obtaining data at intersections. Multiple detectors are usually required to monitor a location, and this reduces the accuracy of detectors for collecting traffic volumes. The purpose of this paper is to increase the accuracy of loop detector counts using Adaptive Neural Fuzzy Inference System (ANFIS) and Genetic Programming (GP) based on detector volume and occupancy. These methods do not need microscopic analysis and are easy to employ. Four approaches for one intersection are used in a case study. Results show that the models can improve intersection detector counts significantly. Results also show that ANFIS produces more accurate counts compared to regression and GP. 相似文献
Modeling commuters’ choice behavior in response to transportation demand management (TDM) helps in predicting the consequences of TDM policies. Although research looking at choice behavior has evolved to investigate preference heterogeneity in response to factors influencing mode choice, as far as we know, no study has considered taste variation across commuters in response to multiple TDM policies. This paper investigates the presence of systematic preference heterogeneity across commuters, in response to the TDM policies that can be explained by their socio-economic or commuting-related characteristics. Analysis is based on results of a stated preference survey developed using a Design of Experiments approach. Five policies were assessed in order to study the impact they had on how commuters chose their mode of transportation. These include increasing parking cost, increasing fuel cost, implementing cordon pricing, reducing transit time and improving access to transit facilities. For the sake of assessing both systematic and random preference heterogeneity across car commuters, a form of the Mixed Multinomial Logit (MMNL) model that identifies sources of heterogeneity and consequently makes the choice models less restrictive in considering both systematic and random preference variation across individuals was developed. The sample includes 366 individuals who regularly commute to their workplace in the city center of Tehran, Iran. The likelihood function value of this model shows a significant improvement compared to the base MNL model, using the same variables. The MMNL model shows that taste variation across the studied commuters results in differences in influences estimated for three policies: increasing parking cost, reducing transit time and improving access to transit. The analysis examines several distributions for random parameters to test the impacts of restricting distributions to allow for only normality. The results confirm the potential to improve model fit with alternative distributions. 相似文献
This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model system consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is also examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited to some extent due to data availability, the results clearly indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling 相似文献
Transportation - Traditionally, transport planning model systems are estimated and calibrated in an unstructured way, which does not allow for interactions among included parameters to be... 相似文献
Calibration of a transport planning model system is a complex process. While trial-and-error methods and modelling expertise are still the backbone of calibration of transport models, analytical approaches automating the calibration process can improve the accuracy of the models. Introducing a model to guide modellers in the calibration process of large-scale transport planning model systems is the core of this study, where a systematic model for choosing the most appropriate models and parameters is discussed. The effectiveness of the proposed model is investigated by comparing three scenarios which are built on the Travel/Activity Scheduler for Household Agents model as a large-scale agent-based model system.