Georgia's Commute Atlanta Value Pricing Program

2005 ◽  
Vol 1931 (1) ◽  
pp. 28-37 ◽  
Author(s):  
Jennifer Ogle ◽  
Randall Guensler ◽  
Vetri Elango
Keyword(s):  
Travel Behavior ◽  
Research Team ◽  
Survey Methods ◽  
Activity Data ◽  
Recruitment Methods ◽  
Main Research ◽  
Driving Patterns ◽  
Instrumented Vehicle ◽  
Vehicle Activity ◽  
Value Pricing

The Commute Atlanta program is an instrumented vehicle research program funded by the FHWA Value Pricing Program and the Georgia Department of Transportation. A major objective for the multiyear program is to assess the effects of converting fixed automotive costs into variable driving costs. The main research hypothesis is that given a per mile pricing system, participants will modify their driving patterns in an effort to reduce their total costs, pocketing the savings. The Commute Atlanta project includes the parallel collection of instrumented vehicle data, household sociodemographic surveys, 2-day travel diaries, and employer commute options surveys. The research team will monitor the changes in driving patterns and will use statistical analyses of household characteristics, vehicle travel, and relevant employer survey data to examine the relationships between the incentives offered and subsequent travel behavior changes. This paper focuses on the recruitment methods and travel diary response rates for the 2-day diary surveys conducted in February and March 2004. As in other instrumented vehicle studies, researchers collected data that allow the comparison of reported diary travel with monitored vehicle travel. However, this paper focuses on a new type of comparison. Because the households had been recruited into the study 8 months before the diary study and their vehicles were transmitting activity data, the research team could examine whether there were differences in household vehicle activity between that 77% of households that completed the diary data collection and the 23% that did not. The differences were significant at both the high and low ends of the travel-reporting spectrum and may have some major implications for evolving household travel survey methods.

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

2018 ◽  
Vol 2672 (42) ◽  
pp. 280-291 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Yafei Han ◽  
Shlomo Bekhor ◽  
Fang Zhao ◽  
Christopher Zegras ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Leisure Activities ◽  
Behavior Modeling ◽  
Machine Learning Techniques ◽  
Initial Field ◽  
Activity Data ◽  
Large Variability ◽  
Tel Aviv ◽  
Household Travel Surveys

Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

Energy Consumption and Emissions Modeling of Individual Vehicles

2017 ◽  
Vol 2627 (1) ◽  
pp. 93-102 ◽  
Author(s):  
Randall Guensler ◽  
Haobing Liu ◽  
Yanzhi (Ann) Xu ◽  
Alper Akanser ◽  
Daejin Kim ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
High Performance ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Operating Conditions ◽  
Modeling Framework ◽  
Activity Data ◽  
Emissions Modeling ◽  
Vehicle Activity ◽  
Fuel Consumption And Emissions

This study demonstrated an approach to modeling individual vehicle second-by-second fuel consumption and emissions on the basis of vehicle operations. The approach used the Motor Vehicle Emission Simulator (MOVES)–Matrix, a high-performance vehicle emissions modeling system consisting of a multidimensional array of vehicle emissions rates (pulled directly from EPA’s MOVES emissions model) that could be quickly queried by other models to generate an applicable emissions rate for any specified on-road fleet and operating conditions. For this project, the research team developed a spreadsheet-based MOVES-Matrix calculator to simplify connecting vehicle activity data with multidimensional emissions rates from MOVES-Matrix. This paper provides a walk-through of the calculation procedures, from basic vehicle information and driving cycles to second-by-second emissions rates. The individual vehicle emissions modeling framework was incorporated into Commute Warrior, a trademarked travel survey application for Android smartphones, to provide real-time fuel consumption and emissions rate estimates from concurrently obtained GPS-based speed data.

Katy Freeway High-Occupancy Vehicle Lane Value Pricing Project, Houston, Texas: Evaluation of Usage

2000 ◽  
Vol 1732 (1) ◽  
pp. 32-41
Author(s):  
Mark Hickman ◽  
Quanta Brown ◽  
Alejandro Miranda
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Demographic Data ◽  
First Year ◽  
Mode Shift ◽  
Frequency Of Use ◽  
Travel Time Savings ◽  
Time Savings ◽  
Time Of Travel ◽  
Value Pricing

Usage of the QuickRide program on the Katy high-occupancy vehicle (HOV) lane in Houston, Texas, is described. The QuickRide program allows two-person carpools to use the HOV lane for $2.00 during peak periods when the lane is restricted to three or more persons. Use of QuickRide during its first year is described, and an analysis of the demand for the program is presented. QuickRide usage, reported travel behavior, and demographic data are used to analyze user travel patterns, travel time savings, and frequency of use. In the 1-year demonstration, demand averaged slightly over 100 vehicles per day, with more than 60 percent of these vehicles traveling in the morning peak. Participants' average use of QuickRide was only about 0.9 times per week, and very few participants used it more than five times per week. Yet a sampling of travel days indicates that, for the $2.00 fee, the average vehicle saves about 20 min of travel time. Responses to a mail-back survey show a significant mode shift from drive-alone to QuickRide, amounting to more than 50 percent of QuickRide trips. A substantial shift was also seen in the time of travel into the peak hour, totaling about one-third of QuickRide trips. Finally, larger household sizes and higher incomes appear to be good predictors of QuickRide use. Interestingly, previous use of the HOV lane was not a good indicator, either positively or negatively, for the frequency of use of QuickRide. These results suggest that ( a) the total demand for HOV-2 value pricing may be limited in major travel corridors, despite large potential time savings; ( b) substantial shifts in mode and time of travel are possible with HOV-2 value pricing; and ( c) household size and income are good indicators, but HOV lane use is a poor indicator, of the frequency of use of an HOV-2 value pricing program.

scholarly journals Leisure travel behavior of generation Y & Z at the destination and post-purchase

2019 ◽  
pp. 147
Author(s):  
Iva Slivar ◽  
Dražen Aleric ◽  
Sanja Dolenec
Keyword(s):  
Generation Y ◽  
Travel Behavior ◽  
Online Survey ◽  
Geographical Area ◽  
Online Reviews ◽  
Purchase Behavior ◽  
Tourist Destination ◽  
Main Research ◽  
Generation Z ◽  
Post Purchase

Researching travel trends of new generations is the first step for tourism providers towards modifying their offers in order to match target markets’ needs. The above represents this paper’s primary purpose. The motivation and behavior of the new generations, also known as Millennials or Generation Y and Post-Millennials or Generation Z, influence the contemporary tourism characteristics. They are both more than familiar with recent technology trends and usage. There are two main goals of this paper. The first is to determine the behavior of Generation Y and Z members during their stay in the tourist destination and their preferences in terms of company, accommodation and transport options. The second goal of this paper focuses on exploring the behavior of the Y and Z generation members related the dissemination of information about their stay in a tourist destination. Questions covered issues regarding review writing about a tourist destination or accommodation, the timing of writing - during or after returning from a tourist destination, the announcement of their travel intentions on social networks etc. A significant number of respondents post on social media and write online reviews regarding their travel experiences. The originality of the papers steams from the insufficient studies of the topic. The research methodology applied an online survey as the main research instrument. The main limitations are related to the minor geographical area researched. Keywords: online tourism behavior, generation Y, generation Z, buying behavior in tourism, visit phase, post purchase behavior in tourism.

Analysis of Travel Behavior Using Sequence Alignment Methods

1998 ◽  
Vol 1645 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Clarke Wilson
Keyword(s):  
Sequence Alignment ◽  
Travel Behavior ◽  
Daily Activity ◽  
Traffic Management ◽  
Activity Patterns ◽  
General Social Survey ◽  
Quantitative Measure ◽  
Activity Data ◽  
Statistics Canada ◽  
Daily Activity Patterns

Sequence alignment methods are applied to daily activity data derived from the Statistics Canada 1992 General Social Survey on Time Use, with special emphasis on travel episodes and the activities that generate travel. Sequence alignment is a combinatorial procedure that gives a quantitative measure of the similarity of character sequences, which may be used to represent daily activity patterns. It accommodates all the details supplied from activity diaries including the ordering of activity episodes, their duration, and patterns of transitions from one activity to another. Analysis of daily activity patterns by using such methods offers a new way of improving understanding of travel behavior. Such an understanding is especially critical when public transport policy is being driven increasingly by budget constraints, and traffic management through congestion is considered an acceptable response to increasing travel demands. The method successfully identifies groupings of behavioral patterns, which then may be further described by using multivariate analysis of sociodemographic characteristics. A key issue in the application of the method is to determine the circumstances in which activity sequences should or should not reflect episode duration.

Modeling of membrane separation and applying combined operations at biosystems

2013 ◽  
Vol 9 (1) ◽  
pp. 3-25 ◽  
Author(s):  
C. Hodúr ◽  
Sz. Kertész ◽  
A. Szép ◽  
G. Keszthelyi-Szabó ◽  
Zs. László
Keyword(s):  
Wastewater Treatment ◽  
Reverse Osmosis ◽  
Research Team ◽  
Membrane Separation ◽  
Research Area ◽  
Water And Wastewater Treatment ◽  
Separation Processes ◽  
Main Research ◽  
Combined Operations ◽  
Water And Wastewater

The importance of the treatment of water and wastewater has been steadily increasing because of the ever greater demands to eliminate environmental pollution. Pressure-driven membrane separation processes, including ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), have been widely used in water and wastewater treatment and are applied on an industrial scale worldwide. The aim of our paper is to introduce the results of our research team on this field. The main research area within the membrane separation was the reduction of resistances. The effect of ozonation, vibration and application of dolly particles were examined in our scientific works.

Vehicle Activity–Based Procedure for Estimating Emissions of Heavy-Duty Vehicles

2003 ◽  
Vol 1842 (1) ◽  
pp. 64-72 ◽  
Author(s):  
Herbert Weinblatt ◽  
Robert G. Dulla ◽  
Nigel N. Clark
Keyword(s):  
Environmental Protection Agency ◽  
Correction Factors ◽  
Heavy Duty ◽  
Protection Agency ◽  
Activity Data ◽  
Initial Implementation ◽  
Vehicle Activity ◽  
Validation Tests ◽  
The U.S ◽  
Heavy Duty Vehicles

A new procedure for estimating the emissions of heavy-duty vehicles (HDVs) is presented. This procedure combines second-by-second data on actual in-use speed and acceleration of HDVs with data on average emissions rates of HDVs operating at corresponding speeds and acceleration rates. The initial implementation of this procedure used a limited amount of newly collected emissions data and a somewhat larger amount of previously collected HDV activity data. Validation tests provide a reasonable level of confidence about the validity of the nitrogen oxide (NOx) emissions factors produced using this initial implementation. However, these tests also indicate that the small amount of emissions data used in the initial implementation is insufficient to produce meaningful estimates of emissions factors for carbon monoxide or particulate matter. The research, the procedure that was developed, the validation tests, the results for NOx emissions, and NOx speed correction factors derived from these results are briefly described. The speed correction factors are of particular interest. The minimum values for these factors occur at speeds higher than those currently used by the U.S. Environmental Protection Agency, and the factors grow more slowly at higher speeds than do the factors generated by MOBILE.

Effect of Light Duty Vehicle Performance on a Driving Style Metric

2018 ◽  
Vol 2672 (25) ◽  
pp. 67-78 ◽  
Author(s):  
Shams Tanvir ◽  
H. Christopher Frey ◽  
Nagui M. Rouphail
Keyword(s):  
Activity Data ◽  
Driving Style ◽  
Vehicle Performance ◽  
Improve Energy Efficiency ◽  
Traffic Characteristics ◽  
Activity Measurements ◽  
Light Duty Vehicle ◽  
Naturalistic Driving ◽  
Vehicle Activity ◽  
Effect Of Light

Eco-driving involves alterations to driving style to improve energy efficiency. The observed driving style reflects the combined effects of roadway, traffic, driver, and vehicle performance. Although the effect of roadway and traffic characteristics can be inferred from microscale driving activity data, the effect of vehicle performance on driving style is not properly understood. This paper addresses two questions: (1) how different is an individual driver’s driving style when operating vehicles with differences in performance?; and (2) how dissimilar are the driving styles of different drivers when operating vehicles that have similar performance? To answer these questions, we have gathered microscale vehicle activity measurements from 17 controlled real-world driving schedules and two years of naturalistic driving data from five drivers. We also developed a metric for driving style termed “envelope deviation,” which is a distribution of gaps between microscale activity (1 Hz) and fleet average envelope. We found that there is significant inter-driver heterogeneity in driving styles when controlling for vehicle performance. However, no significant inter-vehicle heterogeneity was present in driving styles while controlling for the driver. Findings from this study imply that the choice of vehicle does not significantly alter the natural driving style of a driver.

scholarly journals Vehicle Emission Computation Through Microscopic Traffic Simulation Calibrated Using Genetic Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Yun Wei ◽  
Ying Yu ◽  
Lifeng Xu ◽  
Wei Huang ◽  
Jianhua Guo ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Vehicle Emissions ◽  
Traffic Simulation ◽  
Urban Region ◽  
Vehicle Emission ◽  
Activity Data ◽  
Microscopic Traffic Simulation ◽  
Emission Models ◽  
Vehicle Activity

Abstract Vehicle emission calculation is critical for evaluating motor vehicle related environmental protection policies. Currently, many studies calculate vehicle emissions from integrating the microscopic traffic simulation model and the vehicle emission model. However, conventionally vehicle emission models are presented as a stand-alone software, requiring a laborious processing of the simulated second-by-second vehicle activity data. This is inefficient, in particular, when multiple runs of vehicle emission calculations are needed. Therefore, an integrated vehicle emission computation system is proposed around a microscopic traffic simulation model. In doing so, the relational database technique is used to store the simulated traffic activity data, and these data are used in emission computation through a built-in emission computation module developed based on the IVE model. In order to ensure the validity of the simulated vehicle activity data, the simulation model is calibrated using the genetic algorithm. The proposed system was implemented for a central urban region of Nanjing city. Hourly vehicle emissions of three types of vehicles were computed using the proposed system for the afternoon peak period, and the results were compared with those computed directly from the IVE software with a trivial difference in the results from the proposed system and the IVE software, indicating the validity of the proposed system. In addition, it was found for the study region that passenger cars are critical for controlling CO, buses are critical for controlling CO and VOC, and trucks are critical for controlling NOx and CO2. Future work is to test the proposed system in more traffic management and control strategies, and more vehicle emission models are to be incorporated in the system.

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