Transportation Research Interdisciplinary Perspectives最新文献

In this article, a utility function framework is developed, serving to determine the demand for an upcoming demand responsive transportation system. A linear’public-good game’ (PGG) model is modified in a way that maximizing the consumer surplus is assumed to determine individual decision-making. This modification allows for considering the endowment effect in the function, which is expected to enable for a more precise distinction among customer segments. The purpose of this approach is to create a possibility for including descriptive behavioral economic findings in a normative modeling concept. It shall serve as a theoretical basis for coming empirical investigations.

Flooding is among the costliest and deadliest weather disasters. Moreover, different types of flooding have significant impacts on the transportation network and infrastructure including flash, riverine, urban, coastal, and storm surge. The variety of flooding scenarios makes it challenging to quantify the impacts of flooding on transportation across spatial scales; however, such metrics would be beneficial both prior to and after the event. Pre-flood metrics can promote enhanced impact-based decision-support guidance and hazard communication, while post-flood metrics may include larger regional disruptions located away from the most inundated areas and their associated secondary societal impacts. This study developed a retrospective Roadway Flood-Severity Index (RFSI) from 1982 to 2020 capable of integrating geo-located hydrometeorological data and transportation mobility information across localized and multi-state, sub-national regions to (1) categorize larger-scale, flood-related transportation disruptions, (2) understand the origins of those disruptions, and (3) identify severity risk levels of individual road segments and broader regions of transportation disruption during flood events. The fundamental question is, as flooding events unfold, can past hydrometeorological inundation information be coupled with transportation system network and mobility data to identify the most vulnerable roadway segments and regions? The overall mobility impacts of flooding on transportation were highly variable and relatively uncommon throughout the study period. Given this variability in other mobility data (e.g., vehicle speeds), hydrometeorological parameters were used exclusively as model inputs and crowdsourced Waze flood reports were used as the target response variable. A logistic regression based RFSI was found to best align with the dataset providing a “no flood” or “flood” classification. Eventually, this retrospective analysis will be extended to provide predictive capability as well. The RFSI is intended to provide transportation agencies with a quantitative metric to classify, categorize, and communicate the potential impacts of flood events throughout the transportation network.

Transportation-related activity scheduling is becoming more complex due to the growing number of potential locations and extensive opportunities to visit various places. Throughout the years, in the field of transportation several attempts were made to optimize travelers’ activity chains with different parameters to set, but there is a lack of comprehensive solutions. In this research, the activity chain optimization algorithm is applied, which requires high computational efforts. To provide an adequate calibration of the parameters, a sensitivity analysis is conducted. The aim of the analysis is to reveal how changes in the attribute values modify the final outcomes. The relevant parameters, activity chains, transport modes, optimization algorithms, and fitness functions, are identified and considered. For each parameter, an investigation is conducted to reveal its behavior throughout the runs. For example, changes in the population size and crossover function lead to more reliable results, while alteration in the number of generations and the mutation function have no effects on the outcomes. The analysis presents a peculiar behavior of the parameters related to the activity chains. The results can be useful for transportation planners and service providers in the adaptation of the existing network and transportation services to the travelers’ mobility patterns.