Search

• Taxi ridership began to fall about one day ahead of hurricane landfall. • Highly educated people and transit dependents favor taking taxi on affected days. • The impact of hurricanes on taxi ridership varies by time-of-day and day-of-week. • Adverse weather conditions (such as heavy rain or strong wind) reduce ridership. Extreme weather days were usually removed as outliers in past studies of taxi ridership. However, taxis play an important role during extreme weather events when other public transportation service is suspended. Thus, estimating spatio-temporal variations of taxi ridership during extreme weather conditions can provide valuable information on heretofore relatively unknown behavior of taxi riders and help identify areas with unusual taxi demands. In this study, New York City (NYC) taxi ridership shortly before the landfall of Hurricanes Irene and Sandy was analyzed. It was found that taxi ridership began to drop about 24 h before each hurricane made landfall. Six multisource regression models were estimated to explain the variation of taxi ridership in the last 24 h. Characteristics of the approaching hurricane, local weather conditions, and zonal socio-demographic variables were entered as explanatory variables. It was found that taxi ridership during hurricane-affected periods has a strong linear association with the ridership in unaffected periods but the proportion decreases as the storm approaches; a storm has the greatest impact on taxi ridership during weekend and at night, and the least impact on a weekday during the day; and taxi users make fewer trips during conditions of heavy rain or strong wind. [ABSTRACT FROM AUTHOR]

• Taxi trip records can be used to study transient behavior in emergencies. • Evacuated transients were most likely to leave 18–24 h before the storm. • Non-evacuated transients made more shopping trips before the storm. • Some transients chose to leave once airport service was resumed after the storm. • Some transients chose to relocate on the second day after the storm. Transients, such as tourists or business travelers, often fly into large cities and subsequently have to rely on public transportation for movement within the city. It is difficult to observe transient behavior in the event of a disaster through traditional survey methods. Thus, transient behavior has not been understood as well as resident behavior, which presents a challenge to emergency management. This study used taxi trip records that are passively collected year-round in New York City (NYC) to observe transient behavior during Hurricane Sandy (2012). The linkage between transients and taxi trips was built upon the fact that many transients choose hotels as accommodation and depend on taxis during their travel in NYC. This study extracted and analyzed taxi trips originating from hotels shortly before and after the hurricane landfall, which cover transient outbound activities in a week. In the pre-landfall period, it was found that transients who evacuated out of Manhattan were more likely to leave hotels about 18–24 h before hurricane landfall; and those who stayed made more shopping trips within Manhattan. In the post-landfall period, transients were more likely to relocate on the second day after hurricane landfall; some transients headed to local airports once limited service was resumed. This is believed to be the first study to use passively collected data to observe transient travel behavior in the event of a hurricane as well as on normal days. [ABSTRACT FROM AUTHOR]

Highlights • Mode and destination type choice were found to be joint choices in this study. • Variables describing social interactions are important to model the joint choice. • Attributes of alternatives are also important, such as transit level of service. • Characteristics of the study area were also found to have an impact. Abstract Since Hurricane Katrina, transit evacuation service has been seen to serve critical needs in affected cities and an increasing number of hurricanes have struck the east coast where more people rely on public transportation to evacuate. Thus, it is important to model mode choice in evacuation for a better estimation of evacuation transit demand. In this study, a joint mode and destination type choice model was estimated based on multiple post-storm behavioral surveys from the northeastern seaboard to the Gulf coast. A Nested Logit model specification was used to estimate this joint choice model. The estimated model showed a significant linkage between mode and destination type choice, which validated the choice of a nested structure for the model. Selected variables include both household and zonal characteristics, reflecting the attributes of alternatives (e.g., hotel price and occupancy), the characteristics of households (e.g., residential stability and community density), and the interactions between them (e.g., average accessibility to a destination type). The use of multiple-storm data allowed the use of some variables that have not been considered in the past because of few variations in their values in a single dataset. Overall, the findings of this study provide insight into the factors affecting mode and destination type choice of residents during hurricane evacuation. [ABSTRACT FROM AUTHOR]

Abstract: The study compares two alternative ways of reducing congestion in Baton Rouge, Louisiana: construction of a northern bypass and improvement of the existing road network. Baton Rouge provides a very interesting case study because it is ranked the worst for congestion among medium sized urban areas in the nation. A travel demand model is used to estimate total travel for each alternative as well as for the status quo. Reduction in total travel resulting from implementation of each alternative over the status quo is evaluated in terms of the estimated change in vehicle miles traveled (VMT) and vehicle hours traveled (VHT). The reduction in travel is compared with the estimated construction cost of each alternative. The analysis revealed that improving the existing road network was more effective in reducing traffic congestion and cost approximately one-third of the cost of the northern bypass. Applying tolls on the bypass did not improve the situation and further proved the superiority of the improved network in reducing traffic congestion. [Copyright &y& Elsevier]

Revealed preference is the traditional method to collect hurricane evacuation behavior data. However, revealed preference surveys have the disadvantage that they are unable to collect time-sensitive and policy-sensitive data needed to test evacuation policies. In contrast, data collected from time-dependent, audio-visual, stated-choice surveys allow researchers to collect not only time-sensitive and policy-sensitive data but also information that will allow testing potential new evacuation policies. However, no research has been conducted to establish the methodology of such surveys. To fill the gap, this study is aimed at developing a new time-dependent, audio-visual, stated-choice method to collect evacuation behavior data. To achieve the objective, nine animations of hypothetical storms were developed based on recent hurricane history. To test the new methodology and its effectiveness, data was collected using both the methods, for new and traditional methods, in New Orleans and surrounding parishes. In a new method survey respondents had to watch the animations and answer questions related to their intended behavior while in the traditional method they reported on their behavior in a recent storm, hurricane Gustav. Preliminary results indicate that the new stated-choice method is easy to use and effective in collecting time-sensitive and policy-sensitive data. The new method appears to have the potential of evolving into a survey instrument that can be used by researchers and practitioners working in hurricane evacuation area. [ABSTRACT FROM AUTHOR]

The objective of this study was to reveal the trend in highway construction costs following Hurricanes Katrina and Rita in Louisiana. The means of measuring highway construction cost was the Louisiana Highway Construction Index, an index made up of the cost of labor, equipment, and six major materials used in highway construction. Data from projects let by the Louisiana Department of Transportation and Development from the second quarter of 2003 to the second quarter of 2007 were used to track the change in construction costs. Index values from hurricane-impacted areas (GO Zones) were compared with those in Non-GO Zones. The indices revealed that two quarters after Hurricanes Katrina and Rita, the highway construction cost jumped about 20% statewide and 51% in GO Zone. Two years after the hurricanes, the cost has stabilized to around 30% increase over the pre-Katrina and Rita period. This study provides valuable information for the state agency to estimate cost escalation in ongoing projects and to estimate future disaster response to highway construction costs. [ABSTRACT FROM AUTHOR]

The objective of this research was to develop a procedure that estimates the escalation of highway construction costs over time. An artificial neural network model was developed which relates overall highway construction costs, described in terms of a highway construction cost index, to the cost of construction material, labor, and equipment, the characteristics of the contract and the contracting environment prevailing at the time the contract was let. Results demonstrate that the model is able to replicate past highway construction cost trends in Louisiana with reasonable accuracy. Future construction input costs are estimated from commercially available forecasts of indicator variables closely associated with the price of construction labor, construction equipment, and a representative set of highway construction materials. Future contract characteristics and the contracting environment that is likely to exist in the future are estimated from past trends or stipulated to be consistent with policy decisions in the future. The predictions produced by the model estimate that highway construction costs in Louisiana will double between 1998 and 2015. [ABSTRACT FROM AUTHOR]

This paper draws on the results of studies conducted around the world on the effect of speed limits on speed and safety. It is observed that, generally, motorists do not adhere to speed limits but instead choose speeds they perceive as acceptably safe. Perceptions of safety are influenced by the environment in which travel takes place such as whether the road is a controlled access facility, the nature of adjoining land use, the geometry of the road and existing weather conditions. The relationship between speed and safety is influenced by factors such as the type of road, driver age and vehicle safety devices. Research shows that speed cannot be linked statistically to the incidence of accidents, although it is statistically significant in accident severity. If speed limits are increased only on controlled-access facilities, while retaining lower speed limits on other facilities, system-wide safety may not be adversely affected. The main benefits of increasing speed limits seem to be in improving their credibility with the public and regaining control of speed behaviour on highways. [ABSTRACT FROM AUTHOR]

Focuses on how successfully remote-sensing observations can be made on two-lane roads to identify the factors that affect the success with which observations are made, and to quantify the relationship. Impact of traffic characteristics on successful observation; Empirical and theoretical analyses; Description of the remote-sensing equipment.

Full and partial transfer results of trip-production models among intercity, intracity, and intraregional locations are reported in this paper. Nineteen models were transferred 208 times among the locations. The variety of transfer conditions and number of transfers permitted inferences to be drawn on the conditions influencing transferability. It was observed that the quality of local data seriously affects the ability to discern transferability, and may account for the variable results observed in the literature. It was also observed that model quality and income affect transferability. For all transfers conducted in this study, the transferred models explained an average of 57% of the variation in trip-making behavior explained by locally estimated models. When locally estimated constants were used to replace transferred constants in the model, the transfer models explained, on average, 87% of the variation in trip-making behavior explained by locally estimated models. It was concluded that the adjustment of transfer-model parameters with local information (partial transfer) has the potential to improve transferability to such an extent that the need to predict transferability becomes redundant. [ABSTRACT FROM AUTHOR]

Abstract: Studies on the interrelationship between land use and travel behavior are often at some aggregate geographic unit such as the census tract, traffic analysis zone (TAZ), or the zip code level, and results have been inconclusive. This paper uses a multi-level modeling approach to examine the combined effects of land use types and socio-demographics (including both individual and neighborhood attributes) on commuting. Data used in this research include the Baton Rouge Personal Transportation Survey (BRPTS) of individual households and the Census Transportation Planning Package (CTPP) at the TAZ level. Land uses include agricultural, commercial/office and residential of various densities. A localized job-housing balance ratio is computed to measure job accessibility and also to capture the degree of mixed land uses around each residential location, and its effect on commuting behavior is examined. Commuting is measured by both travel distance and time in order to capture the spatial separation of residence and workplace as well as road conditions. The results indicate that land use types are significant in explaining commuting time, and socio-demographic characteristics of both individuals and neighborhoods play an important role in shaping individuals’ commuting behavior. [Copyright &y& Elsevier]

A common travel analysis technique is to ascribe capacities to links in a planning network based on functional classification or facility type, under which a four-lane divided arterial, for example, would be assigned the same capacity everywhere, irrespective of the surrounding land use, the presence of traffic signals, and whether turning lanes are provided or not. While this practice has been used for many years and is typically adequate for the analysis of large road networks, there are penalties (in terms of lost accuracy) that accompany its use. The objective of this research was to evaluate different techniques to determine what information was necessary to reasonably estimate link capacity while decreasing the time, effort, and cost of data collection. It was found that assigning capacities on a link-specific basis produced significant differences when compared to the practice of assigning average capacities, suggesting that travel demand modeling could be improved by using link-by-link estimates of capacity. The results of this study also supported the concept that improvements gained by using all Highway Capacity Manual adjustment factors were marginal compared to the improvement achieved by including only the g/C ratio and number of lanes; suggesting further that ignoring other factors like lane widths, heavy vehicles, turning movements, etc. will still result in reasonably accurate estimates of volume, travel time, and travel speed. [ABSTRACT FROM AUTHOR]