Tradable Parking Permits as a Transportation Demand Management Strategy: A Behavioural Investigation

2019 ◽  
Author(s):  
Helen X. H. Bao ◽  
Joelle Ng
Keyword(s):  
Management Strategy ◽  
Demand Management ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
Parking Permits

Exploratory Evaluation of a Concept Combining Incentivized On-Demand Ridesharing with Congestion Pricing

2021 ◽  
pp. 036119812110116
Author(s):  
Patrick DeCorla-Souza
Keyword(s):  
Demand Management ◽  
Congestion Pricing ◽  
Economic Benefits ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
Transportation Funding ◽  
On Demand ◽  
Federal Highway ◽  
Planning Tools ◽  
Management Concept

This paper presents an innovative transportation demand management concept involving congestion pricing synergistically combined with incentivized on-demand ridesharing. An exploratory evaluation of the concept was undertaken using sketch-planning tools developed by the Federal Highway Administration. The analysis suggests that the concept could be financially viable, achieve significant economic benefits, and potentially generate surplus revenues that could be sufficient to address transportation funding gaps.

Evaluating Travel and Air Quality Cost-Effectiveness of Transportation Demand Management Projects

1996 ◽  
Vol 1520 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Eric N. Schreffler ◽  
Theresa Costa ◽  
Carl B. Moyer
Keyword(s):  
Air Quality ◽  
Demand Management ◽  
Fine Particulate Matter ◽  
Large Data ◽  
Quantitative Information ◽  
Transportation Demand Management ◽  
Quality Cost ◽  
Transportation Demand ◽  
Vehicle Registration ◽  
Organic Gases

Many transportation planners and those implementing transportation demand management (TDM) programs have been frustrated by the lack of quantitative information on what types of TDM strategies work best and where. This underscores the need for sound evaluation of TDM programs and demonstration projects. However, many evaluations to date have used a variety of methods and assumptions when quantifying the travel and air quality impacts of TDM projects. A study funded under the AB 2766 vehicle registration fee program in southern California resulted in the development of a standardized methodology and then applied the method to 15 TDM demonstration projects. The method differed from most of the self-evaluations in that it discounted vehicle trip reduction to account for those who switched from one high-occupancy vehicle mode to another and for those who accessed the new commute alternative by driving alone to a pickup point; factored out the emission of shuttle and transit vehicles used in providing new service; and used standardized emission factors to determine reductions in reactive organic gases, carbon monoxide, nitrogen oxide, and fine particulate matter. Results of the application of the method to various TDM projects reveal a range of impacts and point to the inaccuracies of self-reported results, particularly in the area of total emission reductions. More standardization of TDM evaluation methods is called for so that a large data base of consistent and reliable information can be assembled across agencies with the goal of generalizing the effectiveness and transferability of various TDM strategies and programs.

Segment: Applicability of an Existing Segmentation Technique to Transportation Demand Management Campaigns in the United States

2019 ◽  
Vol 2673 (9) ◽  
pp. 227-239
Author(s):  
Amy B. Lester ◽  
Philip L. Winters ◽  
Minh Pham
Keyword(s):  
United States ◽  
Market Segmentation ◽  
Travel Behavior ◽  
Group Membership ◽  
Demand Management ◽  
The United States ◽  
Consumer Market ◽  
Transportation Demand Management ◽  
Transportation Demand ◽  
Segmentation Technique

This research was modeled after a consumer market-segmentation technique (SEGMENT) successfully used in Europe, for its usefulness to transportation demand management (TDM) campaigns in the United States. The SEGMENT project examined how consumer market-segmentation techniques can influence travel behavior choices in favor of more energy-sustainable modes of travel. Data were collected from 1,900 individuals in Florida, Oregon, and Virginia. The data contain approximately 200 fields with information about respondents’ demographics and attitudes toward different modes of transportation, such as car, train, bike, and walking. Clustering analysis was applied to divide the sample into segments so that members of the same group share similar travel attitudes. Next, a classification model was built to predict group membership. Dividing the sample into seven segments, three non-driver and four driver, was found to be the most stable and distinctive segmentation. Seventeen questions, referred to as “golden questions,” were found to separate segments most significantly and predict group membership with 84% accuracy. Significant differences in age and household distribution between segments were observed. Mean responses to each question were used to create an attitudinal profile for each group. Major contributions are the validation of an existing segmentation technique for applicability in the United States, which could improve the effectiveness of TDM campaigns on changing travel behavior. Golden questions can be added to existing surveys to gather information about the proportion of individuals that belong to segments in an area. Additionally, limited resources can be better allocated to target those segments most susceptible to behavior change.

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