Xuehao Chu

WHY PEOPLE CROSS WHERE THEY DO: THE ROLE OF STREET ENVIRONMENT

The role of the street environment in the way people cross roads in urban settings is modeled. Respondents were placed in real traffic conditions at the curbside of street blocks in the Tampa Bay, Florida, area for 3-min observations of the street environments. Without crossing the blocks, respondents stated their crossing preference at each of six blocks. The origin and destination of each crossing were hypothetically set and varied across the blocks. So were the options available: two options for crossing at an intersection and up to four options for crossing at midblock locations. Within the framework of discrete choice models, the stated preferences are explained with the street environment, including traffic conditions, roadway characteristics, and signal-control characteristics. All three components of the street environment are considered: midblock locations, intersections, and roadside environment. The data are described; a nested logit model of pedestrian street-crossing behavior is estimated; and its implications to researchers and practitioners are discussed.

PEDESTRIAN LEVEL OF SERVICE FOR MIDBLOCK STREET CROSSINGS

A level-of-service methodology for pedestrians crossing streets at midblock locations was developed. The methodology can provide a measure of effectiveness that indicates pedestrians’ perceived quality of service in crossing roads at midblock locations. An objective was to determine what variables are correlated with pedestrians’ perceived quality of service for midblock crossings. A statistical calibration and validation process involved the collection of actual site characteristics and stated levels of quality of service by a sample of persons at a selection of midblock crossing locations. The variables included those that are most important to the Florida Department of Transportation and local governments for the purpose of improving pedestrian mobility, safety, and livability. Results showed that the levels of crossing difficulty tend to increase with the width of painted medians, signal spacing, and turning movements. They also showed that both the presence of pedestrian signals and cycle length are statistically significant, although they were hypothesized to be indeterminate. Finally, the results further indicated that people tend to find that the presence of pedestrian signals lowers their level of crossing difficulty.

Crossing Locations, Light Conditions, and Pedestrian Injury Severity

This paper assesses the role of crossing locations and light conditions in the severity of pedestrian injuries through a multivariate regression analysis to control for many other factors that also may influence pedestrian injury severity. Crossing locations include midblock and intersections, and light conditions include daylight, dark with street lighting, and dark without street lighting. The paper formulates a theoretical framework on the determinants of pedestrian injury severity and specifies an empirical model accordingly. The paper applies the ordered probit model to the KABCO severity scale of pedestrian injuries that occurred while attempting street crossing in the years 1986-2003 in Florida. In terms of crossing locations, the probability of a pedestrian dying when struck by a vehicle is higher at midblock locations than at intersections for any light condition. The odds of sustaining a fatal injury are 49% lower at intersections than at midblock locations under daylight conditions, 24% lower under dark-with-street-lighting conditions, and 5% lower under dark-without-street-lighting conditions. Relative to dark conditions without street lighting, daylight reduces the odds of a fatal injury by 75% at midblock locations and by 83% at intersections, whereas street lighting reduces the odds by 42% at midblock locations and by 54% at intersections.

Density and Captivity in Public Transit Success: Observations from the 1995 Nationwide Personal Transportation Study

The new millennium provides a good time to reflect on transportation-industry trends in some fundamental external factors that influence transportation behavior and planning response. In the public-transit industry, urban density and transit captivity have long been fundamental conditions driving transit planning and service and facility investment decisions. In light of demographic and economic changes, it is useful to revisit the issue of the importance of these factors to the transit market. Findings from a comprehensive analysis of the 1995 Nation-wide Personal Transportation Study (NPTS), which explored current transit-travel behavior, are reported. Two key findings reflect on two historical axioms in transit: (a) the extent to which density influences transit use and (b) the importance of the transit-dependent market. The research findings reiterate the significant influence that development density has on public transit mode share and bring to light some revealing data on the influence of urban-area size on transit use. The importance of transit dependency on transit use is documented, and trends in transit dependency over the past few decades are revealed. Finally, the implications of these trends for the public-transit industry are discussed.

Forecasts of Future Vehicle Miles of Travel in the United States

Transportation infrastructure demand is driven by a need to replace existing infrastructure and to provide capacity to meet future travel demands. Thus, long-term transportation policy and financial planning benefit from an understanding of future investment needs. The hypothesis that the United States has reached a critical juncture in underlying sociodemographic conditions and travel behavior that will result in more moderate rates of future vehicle miles of travel (VMT) growth is explored. Two simple model formulations for predicting VMT are proposed, and historical trends for establishing inputs for scenario forecasts of future VMT are examined. An understanding of future VMT demand is critical for policy decision making and infrastructure investment planning. The VMT predicting formulas enable National Household Travel Survey information to be used to predict input components in forecasting future VMT. Two VMT predictions are provided and compared with a forecast reported in 2002 Status of the Nations Highways, Bridges, and Transit: Conditions and Performance. While this study builds a case for slowing VMT growth, it hypothesizes that there may continue to be declining system performance despite slower VMT growth because more of the roadway system is at or near critical congestion levels and hence more susceptible to performance deterioration with modest increases in travel demand. It also suggests that land use pattern effects on travel behavior and person travel time budget growth are the least understood factors and possibly weak links in reaching conclusions about the ultimate pace of VMT growth.

MEASURING PEDESTRIAN QUALITY OF SERVICE FOR MIDBLOCK STREET CROSSINGS: SELECTION OF POTENTIAL DETERMINANTS

The Florida Department of Transportation is in the process of developing a statistically estimated model of pedestrian quality of service for midblock street crossings as part of its Multimodal Quality of Service Program. This model is to be used in evaluating the level of service of street segments for pedestrian street crossing. The actual development of the model, including methodological issues explored, data collection, and model calibration and validation, is reported separately. A process was used to select potential determinants of perceived pedestrian quality of service for midblock street crossings. This process is structured and involves two steps. The first step involves the selection of a set of potential determinants through a theoretical analysis of pedestrian behavior for street crossing. The theoretical consideration ensures that these potential determinants have a sound behavioral foundation. The second step involves narrowing down this theoretical set through a practical analysis of planning needs and data requirements by an advisory committee. This practical consideration ensures that the final set of potential determinants and the model both are practically relevant.

Considering build-later for major transit investments

This paper uses a theoretical model of benefit-cost analysis to consider the timing of major transit investments. The model takes into account the net benefits of a project, the variation of net benefits with project age and investment timing, capital cost and its growth, and the discount rate. Three questions are examined: (1) when might build-later be evaluated? (2) how do changes in the discount rate and other parameters of an investment affect its optimal timing? and (3) how significantly do differences in the stream of net benefits from an investment affect its optimal timing? The first two questions are examined analytically, and the last question is examined numerically. Implications are discussed with respect to planning for major transit investments.

Timing rules for major transportation investments

The timing decision for major transportation investments – when to build – typically is made without an objective approach for considering the economic value of implementation at different times. This paper uses a model of benefit-cost analysis and derives rules for timing major transportation investments. Three sets of conditions are considered, depending on whether annual benefits of an investment are uncertain and whether the objective is to maximize net present value or simply to achieve positive net present value. The timing rules under each set of conditions are stated in three forms: benefit-cost ratio, annual benefits, and implementation time. The paper compares these timing rules analytically, discusses potential applications, and illustrates them with a numerical example. Consequences of incorrectly using the timing rules are also examined with the example.

Ridership Accuracy and Transit Formula Grants

The accuracy of annual unlinked passenger trips reported to the National Transit Database (NTD) at the agency level is examined by using a two-step approach. The first step compares ridership reported to the American Public Transportation Association (APTA) with ridership reported to NTD. NTD ridership can be as high as 50% more than APTA rider-ship, and such significant positive deviation exists persistently over time across many agencies. The second step explores potential sources of these deviations by examining their components. Random errors, including both sampling errors and some of the nonsampling errors, do not help explain these one-sided deviations, nor do occasional annual adjustments, such as special-events ridership in the NTD ridership. Much of this deviation appears to be attributable to systematic nonsampling sources that result from undercounting in direct counts, from unintentional biases in procedures, or perhaps from intentional manipulation. Although mechanisms and incentives exist f...

Considering Build-Later as an Alternative in Major Transit Investment Analyses

How the stream of benefits, discount rate, and other parameters of a major transit project affect its optimal timing are examined. A theoretical model of the timing of public infrastructure projects is used. The model takes into account the net benefits of a project, the variation of benefits with project age and timing of investment, construction cost and its growth, and discount rate. The model is used to examine three questions: Under what conditions is build-later optimal? How do changes in the discount rate and other parameters of an investment affect its optimal timing? How significantly do differences in the stream of net benefits from an investment affect its optimal timing? The first two questions are examined analytically, and the last question is examined numerically. When the stream of net benefits stays constant, declines, or shifts parallel with the timing of investment, build-later is not optimal. When the stream of net benefits grows over time, however, build-later can be optimal. A necessary condition for build-later to be optimal is that initial net benefits be relatively small. When build-later is optimal, how much later to build varies significantly.