The modeling of nonmotorized travel demand has mostly been conducted at the large spatial level (e.g., city, county, or census tract level) by using data from the Bureau of the Census and the National Household Travel Survey. This paper introduces a modeling approach for estimating the mode share of nonmotorized trips by using data from multiple sources at a finer spatial scale. The correlations between a number of socioeconomic, environmental, and infrastructural factors and the nonmotorized share of the daily commute are analyzed at the level of the census block group. A neighborhood analysis concept is developed to take the length of non-motorized trips into consideration. Multiple regression analysis shows that employment density, the percentage of the student population, median household income, and average sidewalk length together provide the strongest power for prediction of the nonmotorized mode share. The potential applications of the methodology and the implications for data collection are also discussed.
Abstract:On 28 December 2014, the Beijing subway's fare policy was changed from "Two Yuan" per trip to the era of Logging Ticket Price, charging users by travel mileage. This paper aims at investigating the effects of Beijing subway's new fare policy on the riders' attitude, travel pattern and demand. A survey analysis was conducted to identify the effects of the new fare policy for Beijing subway on riders' satisfaction degree and travel pattern associated with the potential influencing factors using Hierarchical Tree-based Regression (HTBR) models. The model results show that income, travel distance and month of travel have significant impacts on the subway riders' satisfaction degree, while trip purpose, car ownership and travel frequency significantly influence the riders' stated travel pattern. Overall, the degree of satisfaction could not be effectively recovered within five months after the new fare policy, but the negative public attitude did not depress the subway demand continuously. Based on the further time sequence analyses of the passenger flow volume data for two years, it is concluded that the new policy made the ridership decrease sharply in the first month but gradually came back to the previous level four months later, and then the passenger flow volume kept steady again. The findings in this study indicate that the new fare policy realized the purpose of lowering the government's financial pressure but did not reduce the subway ridership in a long term perspective.
Traffic safety evaluation for traffic analysis zones (TAZs) plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI), which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.
In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency were taken into consideration for distinguishing between rural and urban road segment safety. The GIS-based crash data during four and half years in Pikes Peak Area, US were applied for the analyses. The comparative statistical results show that the crash rates in rural segments are consistently lower than urban segments. Further, the regression results based on Zero-Inflated Negative Binomial (ZINB) regression models indicate that the urban areas have a higher crash risk in terms of both total crash frequency and injury and fatal crash frequency, compared to rural areas. Additionally, it is found that crash frequencies increase as traffic volume and segment length increase, though the higher traffic volume lower the likelihood of severe crash occurrence; compared to 2-lane roads, the 4-lane roads have lower crash frequencies but have a higher probability of severe crash occurrence; and better road facilities with higher free flow speed can benefit from high standard design feature thus resulting in a lower total crash frequency, but they cannot mitigate the severe crash risk.
There tend to be more crashes occurring in freeway diverging segments due to increasing traffic conflicts between diverging vehicles and nondiverging vehicles. The diverging segments have a safety impact on the precedent basic segments and the following off ramps. It is always a challenge to accurately define the safety influential area of freeway diverging segments. In previous studies, fixed buffer in size is pregiven for crash frequency analysis in diverging segments, which lacks theoretical and practical support. In this study, the safety influential area was investigated from the statistical point of view. Data from a geocoded GIS crash database for Colorado Springs metropolitan area was used; the statistically significant factors associated with crash frequency were examined for the spatial influence of freeway diverging segments. Also, the generalized linear models with negative binomial link function were applied to predict the crash frequency for freeway diverging segments and off ramps based on the influential area. The results may give some insights into the causation of crashes on diverging segments and off-ramp intersections. Hindawi Publishing Corporation
This study presents a methodology for estimating the benefit–cost ratio for transportation projects by using a regional travel demand model and benefit–cost analysis. The benefit–cost ratio can provide an objective measure with which decision makers can quantitatively evaluate the regional benefits and costs of each proposed transportation project under certain assumptions. This methodology shows the impact of one project on the entire regional transportation network. The key to this methodology is use of the total savings in vehicle hours traveled (VHT) resulting from each proposed project, converted into dollar benefits. The total VHT is estimated with congested travel time and trips instead of a simple summation of each link's VHT. A second key aspect of this methodology is estimating the economic development benefits of the proposed transportation investments. For this process, the Pikes Peak Area Council of Governments used the Transportation Economic Development Impact System (TREDIS) web-based software. The input that TREDIS requires for new capacity transportation projects is total VHT or vehicle miles traveled (VMT) before a project and total VHT or VMT after the project, by trip purpose and travel mode. TREDIS offers default values such as economic value factors for driver and occupant time-saving benefits (dollars per VHT or VMT) and the vehicle cost factor for vehicle cost savings (dollars per VHT or VMT). The case study suggests that the proposed approach can be useful and effective in assessing regional transportation projects by considering their economic impacts.
There has been increasing interests in developing land use models for small urban areas for various planning applications such as air quality conformity analysis. The output of a land use model can serve as a major input to a transportation model; conversely, transportation model output can provide a critical input to a land use model. The connection between the two models can be achieved by an accessibility measure. This paper presents an iterative approach to solving a regression-based land use model and a transportation model with combined trip distributionassignment. A case study using data from a small urban area is presented to illustrate the application of the proposed modeling framework. Tests show that the procedures can converge, and the modeling framework can be a valuable tool for planners and decision-makers in evaluating land use policies and transportation investment strategies.Key words: integrated land use and transportation model; urban model; travel demand model; combined trip distribution and assignment model; urban planning
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