Evaluating Effects of Transportation Demand Management Strategies on Trip Generation by Using Poisson and Negative Binomial Regression

1999 ◽  
Vol 1682 (1) ◽  
pp. 70-77 ◽  
Author(s):  
Brett Wallace ◽  
Fred Mannering ◽  
G. Scott Rutherford
Keyword(s):  
Negative Binomial ◽  
Demand Management ◽  
Management Strategies ◽  
Negative Binomial Regression ◽  
Trip Generation ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
Binomial Regression

Evaluating the Effects of Traveler and Trip Characteristics on Trip Chaining, with Implications for Transportation Demand Management Strategies

2000 ◽  
Vol 1718 (1) ◽  
pp. 97-106 ◽  
Author(s):  
Brett Wallace ◽  
Jennifer Barnes ◽  
G. Scott Rutherford
Keyword(s):  
Urban Form ◽  
Negative Binomial ◽  
Demand Management ◽  
Management Strategies ◽  
Relative Effect ◽  
Negative Binomial Regression Model ◽  
Transportation Demand Management ◽  
Relative Significance ◽  
Transportation Demand ◽  
Trip Chaining

The relative effect that each of a wide variety of factors has on the extent to which a traveler will chain trips was investigated. The objectives were to empirically determine which factors influence a traveler’s tendency to chain two or more trips within one tour, as well as the relative significance of these considerations; to more specifically determine the level of influence that urban centers have on trip chaining; and to evaluate the potential effects on trip-chaining behavior of specific transportation demand management (TDM) strategies through examination of variables that describe effects associated with TDM. A negative binomial regression model was developed in which the number of trips in a chain is related to household characteristics, traveler characteristics, trip characteristics, and urban form. After the model was estimated, the significance of individual variables was analyzed. Characteristics from each of these categories were found to be statistically significant. A number of the significant variables help to describe effects of specific TDM strategies, and the relative effects of these variables on trip-chaining behavior were addressed. Some of the variables representing TDM strategies increased the level of trip chaining, whereas other variables decreased the level of chaining. Potential policy conflicts between trip chaining and specific TDM programs are discussed.

Household Trip Generation and the Built Environment: Does More Density Mean More Trips?

2019 ◽  
Vol 2673 (5) ◽  
pp. 596-606
Author(s):  
Qin Zhang ◽  
Kelly J. Clifton ◽  
Rolf Moeckel ◽  
Jaime Orrego-Oñate
Keyword(s):  
Built Environment ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Trip Generation ◽  
Transportation Demand ◽  
Home Based ◽  
Environment Variables ◽  
Binomial Regression ◽  
Demand Models ◽  
New Development

Trip generation is the first step in the traditional four-step trip-based transportation model and an important transport outcome used in evaluating the impacts of new development. There has been a long debate on the association between trip generation and the built environment, with mixed results. This paper contributes to this debate and approaches the problem with two hypotheses: 1) built environment variables have significant impacts on household total trip generation; and 2) built environment variables have different impacts on trip generation by purpose. This study relied on data from the Portland, Oregon, metropolitan area to estimate negative binomial regression models of household trip generation rates across all modes. Results show that the built environment does have significant and positive influences on trip generation, especially for total number of trips, total number of tours, and home-based shopping-related trips. Moreover, log likelihood ratio tests implied that adding built environment to the base model contributed significantly to improving model explanatory and predictability. These findings suggest that transportation demand models should be more sensitive to the effects of the built environment to better reflect the variations in trip making across regions.

Analysis Public Transportation City of Dili to Improve Service with Users Characteristics

2021 ◽  
Vol 8 (8) ◽  
pp. 254-262
Author(s):  
Florentino Pereira ◽  
Nunung Widyaningsih ◽  
Hermanto Dwiatmoko
Keyword(s):  
Public Transport ◽  
Public Transportation ◽  
Traffic Accidents ◽  
Demand Management ◽  
Service Level ◽  
Generation Model ◽  
Trip Generation ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
The Government

Many public transport drivers in City of Dili do not apply various regulations from the government. Located on Becora-Baidi, Becora-Bidau, and Tasi Tolu-Bidau Road. This causes congestion and traffic accidents, and impact on economy. The purpose of study is to determine the trip generation model and its factors, city transportation service performance, and how to formulate TDM concept in public transport. The survey conducted was daily volume of public transport, questionnaires, and interviews 2020. Looking for value of angkot generation with instrument test and multiple regression (IBM SPSS 22). To analyze services used parameters and Severy Index. Then, concept of Transportation Demand Management (TDM) with Guttman Scale. After analyzing, the trip generation value, Y = -1,3920 + 0,0275.X1 + 0,4958.X2 + 0,1734.X3 – 0,0601. X4 - 0,0657.X5 - 0,0001.X6 - 0,0193.X7 - 0,7670.X8 + 0,8801.X9 + 0,6721.X10 + 0,1058.X11, positive value is factor that most influences the respondent's decision to trips using public transportation: gender (X1), age (X2), job (X3), duration of trip (X9), number of passengers (X10), and waiting time for public transportation (X11). However, in service level is still “low” category. Then, for TDM concept gets 87% in 51%-99% range. Means that angkot users agree, if TDM concept is propose to the government of Dili City, and public transportation will be better in the future. Keywords: Trip Generation, Public Transportation Mode, Public Transportation Services, Transportation Demand Management, TDM.

Freight and Service Parking Needs in Historical Centers: A Case Study in São João Del Rei, Brazil

2020 ◽  
Vol 2674 (11) ◽  
pp. 352-366
Author(s):  
Kaique Silva ◽  
Renato da Silva Lima ◽  
Roberta Alves ◽  
Wilfredo F. Yushimito ◽  
José Holguín-Veras
Keyword(s):  
Demand Management ◽  
Trip Generation ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
Management Measures ◽  
New Locations ◽  
Independent Variable ◽  
Loading And Unloading ◽  
Historical Center

The objective of this study is to analyze the demand for loading and unloading parking spaces in the center of São João Del Rei, a historical city in the State of Minas Gerais, Brazil, through freight trip generation models. To generate the models, the number of employees is used as an independent variable. Results show that the historical center receives an average of 710 freight trips per day, which would require at least 43 spaces for loading and unloading. As the center has only eight such spaces available, representing 18% of total demand, this study proposes new locations and suggests transportation demand management measures that could be used in conjunction with the allocation of new parking spots.

Effective Transportation Demand Management: Combining Parking Pricing, Transit Incentives, and Transportation Management in a Commercial District of Portland, Oregon

2000 ◽  
Vol 1711 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Martha J. Bianco
Keyword(s):  
Demand Management ◽  
Management Strategies ◽  
Transportation Demand Management ◽  
Transportation Management ◽  
Transportation Demand ◽  
Before And After ◽  
Residential District ◽  
Parking Pricing ◽  
The Relationship ◽  
The City

The Lloyd District is a high-density commercial and residential district located a short distance from downtown Portland, Oregon. To address parking and congestion problems, the city of Portland implemented a Lloyd District Partnership Plan in September 1997. This plan consists of a number of elements aimed at curbing single-occupancy vehicle use for the commute to and from the district. This plan included parking pricing in the form of meters (whereas on-street parking had been free), discounted transit passes, and other transportation demand management strategies. The effects of these strategies on travel and parking behavior were assessed, with an emphasis on the relationship between parking pricing and mode choice. A random sample of 1,000 employees in the Lloyd District was surveyed about their travel and parking behavior before and after the installation of the new meters. Research found that, during the 1 year that had elapsed between the implementation of the Lloyd District transportation management programs and the survey information collected, the drive-alone mode for the trip to work by employees in the Lloyd District had decreased by 7 percent. For the district as a whole, the drive-alone commute share is now about 56 percent. The program strategies that have emerged as the most significant in effecting this decrease are the installation of the meters and the discounted transit pass program.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

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