Current Search: Lochrane, Taylor (x)
View All Items
- Title
- EVALUATING THE IMPACT OF OOCEA'S DYMANIC MESSAGE SIGNS (DMS) ON TRAVELERS' EXPERIENCE USING MULTINOMIAL AND ORDERED LOGIT FOR THE POST-DEPLOYMENT SURVEY.
- Creator
-
Lochrane, Taylor, Al-Deek, Haitham, University of Central Florida
- Abstract / Description
-
The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Post-Deployment DMS Survey analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes...
Show moreThe purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Post-Deployment DMS Survey analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA has added twenty-nine fixed DMS to their toll road network from 2006-2008. At the time of the post-deployment survey, a total of twenty-nine DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads were from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results for the post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interview. The post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. This thesis is using results of the multinomial logit model for diversion of traffic. This model takes into account the different diversion decisions from the post development survey (stay vs. divert all the way vs. divert and come back vs. abandon trip) and explains the differences in the diversion behavior. Drivers that use SunPass or Epass tend to stay on the toll road during unexpected congestion. Frequent SR 408 users are more likely to divert and stay off the toll road and frequent SR 417 users are more likely to divert and get back on the toll road. Drivers whose stated preference was to divert off the toll road were more likely to do the same in the real world. However, not too many of the respondents were likely to abandon their trips in the real world even if they said they would in a hypothetical congestion scenario. Users of 511 were more likely to divert and get back on the toll road or abandon their trips due to unexpected congestion. OOCEA can use this study to concentrate on keeping their toll roads more attractive during unexpected congestion to keep drivers from diverting all the way or abandoning their trips. For example, better incident management in clearing accidents more efficiently (thereby decreasing delay) and encouraging the use of SunPass or EPass could help drivers stay than divert or abandon their trip. This thesis also used ordered logit model for satisfaction. This model explains the levels of magnitude of satisfaction with traveler information on OOCEA toll roads. Drivers who acquired traveler information from DMS were less likely to be dissatisfied with traveler information provided on toll roads than other respondents. Drivers who were satisfied with accuracy and information on hazard warnings on DMS were more likely to be satisfied with information provided on toll roads than other respondents. This thesis provides a microscopic insight on the driver behavior on toll roads. This thesis expands the diversion and satisfaction models from previous studies in a way that OOCEA can identify specific groups of drivers related to a given response behavior (i.e., diverts off toll roads or dissatisfied with traveler information). Such analysis can be conducted in the future in the same study area or replicated in other areas to quantify the effects of individual and choice related attributes on choice behavior.
Show less - Date Issued
- 2009
- Identifier
- CFE0002711, ucf:48169
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002711
- Title
- A New Multidimensional Psycho-Physical Framework for Modeling Car-Following in a Freeway Work Zone.
- Creator
-
Lochrane, Taylor, Al-Deek, Haitham, Radwan, Essam, Oloufa, Amr, Harb, Rami, Uddin, Nizam, University of Central Florida
- Abstract / Description
-
As the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation...
Show moreAs the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation hypothesizes that drivers change their driving behavior as they drive through a freeway work zone compared to normal freeway conditions which has the potential to impact traffic operations and capacity of work zones. Psycho-physical car-following models are widely used in practice for simulating car-following. However, current simulation models may not fully capture car-following driver behavior specific to freeway work zones. This dissertation presents a new multidimensional psycho-physical framework for modeling car-following based on statistical evaluation of work zone and non-work zone driver behavior. This new framework is close in character to the Wiedemann model used in popular traffic simulation software such as VISSIM. This dissertation used two methodologies for collecting data: (1) a questionnaire to collect demographics and work zone behavior data and (2) a real-time vehicle data from a field experiment involving human participants. It is hypothesized that the parameters needed to calibrate the multidimensional framework for work zone driver behavior can be derived statistically by using data collected from runs of an Instrumented Research Vehicle (IRV) in a Living Laboratory (LL) along a roadway. The design of this LL included the development of an Instrumented Research Vehicle (IRV) to capture the natural car-following response of a driver when entering and passing through a freeway work zone. The development of a Connected Mobile Traffic Sensing (CMTS) system, which included state-of-the-art ITS technologies, supports the LL environment by providing the connectivity, interoperability and data processing of the natural, real-life setting. The IRV and CMTS system are tools designed to support the concept of a LL which facilitates the experimental environment to capture and calibrate natural driver behavior. The objective is to have these participants drive the instrumented vehicle and collect the relative distance and the relative velocity between the instrumented vehicle and the vehicle in the front of the instrumented vehicle. A Phase I pilot test was conducted with 10 participants to evaluate the experiment and make any adjustments prior to the full Phase II driver test. The Phase II driver test recruited a group of 64 participants to drive the IRV through an LL set up along a work zone on I-95 near Washington D.C. in order to validate this hypothesis In this dissertation, a new framework was applied and it demonstrated that there are four different categories of car-following behavior models each with different parameter distributions. The four categories are divided by traffic condition (congested vs. uncongested) and by roadway condition (work zone vs. non-work zone). The calibrated threshold values are presented for each of these four categories. By applying this new multidimensional framework, modeling of car-following behavior can enhance vehicle behavior in microsimulation modeling.This dissertation also explored driver behavior through combining vehicle data and survey techniques to augment the model calibrations to improve the understanding of car-following behavior in freeway work zones. The results identify a set of survey questions that can potentially guide the selection of parameters for car-fallowing models. The findings presented in this dissertation can be used to improve the performance of driver behavior models specific to work zones. This in return will more acutely forecast the impact a work zone design has on capacity during congestion.
Show less - Date Issued
- 2014
- Identifier
- CFE0005521, ucf:50326
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005521