Micro-simulation of daily activity-travel patterns for travel demand forecasting

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns. This revised version was published online in June 2006 with corrections to the Cover Date.     

Role of the built environment on mode choice decisions: additional evidence on the impact of density

Density is a key component in the recent surge of mixed-use neighborhood developments. Empirical research has shown an inconsistent picture on the impact of density. In particular, it is unclear whether it is the density or the variables that go long with density that affect people’s travel behavior. Many existing studies on density neglect confounding factors, for example, residential self-selection, generalized travel cost, accessibility, and access to transit stations. In addition, most still use a single trip as their observation unit, even though trip chaining is well recognized. The goal of this paper is to assess the role of density in affecting mode choice decisions in home-based work tours, while controlling for confounding factors. Using the dataset collected in the New York Metropolitan Region, we estimated a simultaneous two-equation system comprising two mutually interacting dependent variables: car ownership and the propensity to use auto. The results confirm the role of density after controlling for the confounding factors; in particular, employment density at work exerts more influence than residential density at home. The study also demonstrates the importance of using tour as the analysis unit in mode choice decisions. The study advances the field by analyzing the role of the built environment on home-based work tours. New knowledge is obtained in the relative contribution of density vs. a set of correlated factors, including generalized travel cost, accessibility, and access to transit stations.

Inter-annual variability of hypoxic conditions in a shallow estuary

Water quality data from two monitoring programs in the Pamlico River Estuary (PRE) were analyzed for dissolved oxygen (DO), salinity, temperature, and nutrient concentrations. Data were collected bi-weekly at 8 stations from 1997 to 2003 by East Carolina University and continuously at three stations from 1999 to 2003 by the U.S. Geological Survey. Hypoxic conditions were observed mostly in the upper to middle estuary, but the frequency of hypoxic events varied between years. During June to October in 1997–1999 (referred to as the oxic summers) bottom water hypoxia (DO < 2 mg l^− 1) was found in 8.7% of the observations. By contrast, during June to October in 2001–2003 (referred to as the hypoxic summers), 37.9% of the total measurements had DO concentrations less than 2 mg l^− 1. The more frequent and/or prolonged hypoxic conditions during the hypoxic summers were closely associated with stronger salinity stratification and greater loadings of nutrient and particulate matter.Salinity stratification appeared to be governed by patterns of freshwater discharge, and frequency of wind mixing events. The “oxic” summers were characterized by continuous low freshwater inflow (except one extremely high flow event due to hurricanes), stronger northeastward wind, and more frequent wind mixing events. In contrast, the hypoxic summers were characterized by frequent moderate freshwater inflow events, and fewer wind mixing events.The greater loadings of nutrient (nitrate, ammonium, and phosphate) and particulate matter during the hypoxic summers were primarily due to higher river discharges. At the head of the PRE, no significant differences were found in concentrations of nutrient and particulate nitrogen between the oxic and the hypoxic summers. In addition, chlorophyll a concentrations were averaged above 30 μg l^− 1 (maximum 167 μg l^− 1) during the hypoxic summers, significantly higher than those during the oxic summers (averaged around 15 μg l^− 1).     

What is responsible for the response lag of a significant change in discretionary time use: the built environment,family and social obligations,temporal constraints,or a psychological delay factor?

In this paper, we used the 10-wave Puget Sound Panel Dataset to investigate the response lag of a significant change in discretionary time use. In particular, we want to quantify the relative magnitude of the following factors: the built environment, family and social obligations, temporal constraints, or a psychological delay factor (people delay a behavioral change until the next life shock). To answer this question, we developed a survival model to treat (1) left-censoring, (2) partial observation, and (3) multi-type exits. The results suggest that family and social obligations, as well as temporal constraints, appear to play a more important role than the built environment. Support for the psychological delay factor is not evident. We also found that the probability of having a significant change in discretionary time use is negatively related to time progression, supporting the human adaptivity hypothesis.

Tradeoffs between Time Allocations to Maintenance Activities/Travel and Discretionary Activities/Travel

This paper focuses on the tradeoff in time allocation between maintenance activities/travel and discretionary activities/travel. We recognize that people generally must travel a minimum amount of time in order to allocate one unit of time to the activity. This minimum amount of travel is represented by the travel time price, a ratio obtained by dividing the total amount of time traveling to maintenance or discretionary activities by the total amount of time spent on activities of the same type; it is the time equivalent of the monetary price for performing an activity. Using the San Francisco Bay Area 1996 Household Travel Survey data and applying the Almost Ideal Demand System (AIDS) of demand equations, we found that with respect to the time equivalent of income elasticities of maintenance and discretionary activities, the former is less than unity and the latter is greater than unity. In other words, maintenance activities are a necessity and discretionary activities are a luxury. With respect to the own travel time price elasticities, if the travel time price of performing a certain type of activity increases (for reasons such as traffic congestion), one would reduce the time allocated to that type of activity. Time spent on maintenance activities is less elastic than the time spent on discretionary activities. As for the cross travel time price elasticities (changes in time allocated to activity type i in responses to changes in the time price for activity type j), we found that ɛ_dm>0 and ɛ_md>0, suggesting a substitution effect between maintenance and discretionary activities.     

Making an Informed Vehicle Scrappage Decision

Abstract

According to the US Federal Highway Administration (FHWA), the number of publicly owned vehicles in the USA reached 3 913 999 in 2003. In order to maintain a stable vehicle fleet, government agencies must repeatedly make vehicle scrappage decisions because older vehicles must first retire to make room for newer vehicles. Typically, these decisions are made based on a deterministic ranking evaluation model to select candidate vehicles for replacement. The paper applied an objective and probabilistic method to a vehicle dataset collected by the DuPage County Forest Preserve District ((DCFPD), in the state of Illinois). A Weibull‐form survival model with time‐varying covariate and unobserved heterogeneity was estimated on the dataset. The results suggest that in addition to the fact that vehicle age is negatively related to the vehicle’s survival probability, there are other variables that also appear influential. The survival probabilities of alternative fuel vehicles are similar to those of reformulated unleaded gasoline vehicles. The results suggest that a probabilistic and objective model can benefit government agencies in their vehicle scrappage decisions.     

Rescuing the captive [mode] user: an alternative approach to transport market segmentation

The prevailing approach to transport market segmentation which identifies two distinct groups, “captive” and “choice” users, has widely been used by professionals and scholars despite the ambiguity associated with these terms. Furthermore, conflicting interpretations from the point of view of decision makers and individuals may result in negative policy implications where the needs of captive users are neglected in favour of attracting new users. This study attempts to address these concerns by proposing an alternative segmentation framework that could be applied to any mode of transport, in any regional context, by users and decision makers alike to better guide the development of transport policies. Using the results of a large-scale transportation survey, a series of clustering techniques are employed to derive this alternative approach for segmenting walkers, cyclists, transit and automobile users. The main factors considered in the final clustering analysis are the level of trip satisfaction and practicality. The analysis yielded four market segments: captivity, utilitarianism, dedication and convenience. Using this theoretical framework to understand the distribution of travellers among market segments is essential in identifying distinct and appropriate policy interventions to improve trip conditions. It is hoped that the segmentation approach and policy framework proposed here will encourage a better balance between pragmatic and idealistic goals in transportation policy.     

The role of the built environment on perceived safety from crime and walking: examining direct and indirect impacts

This study examines the connection between the built environment, perceived safety from crime and walking behaviour by conducting a travel survey in King County, Washington State, U.S. and employing a two-stage least squares model. We seek to answer two research questions: how does the built environment affect perceived safety from crime and walking behaviour; and how does one’s perception of safety from crime affect his/her walking behaviour. Our results show that the built environment is not only significantly related to walking behaviour, as previous research has identified, but also correlated with people’s perception of safety. In addition, a significant association between perceived safety from crime and walking behaviour is found, revealing possible indirect impacts of the built environment on walking. In specific, people living in neighborhoods with good accessibility and pedestrian facilities tend to perceive their neighborhoods safer while density has an opposite impact. Moreover, residents in safe and high-density areas are more likely to walk.