This thesis examines three methods of public participation and their potential application to the design of internet-based Advanced Traveler Information Systems (ATISs). ATISs have the ability to reduce congestion by providing their users with real-time traffic information that can affect their travel decisions to avoid areas of high traffic. This study first uses a website evaluation method to determine a baseline of ATIS website quality. It then uses three forms of public participation, a survey, a future's workshop, and a feedback website to determine user preferences for Georgia's traveler information website, NaviGAtor. The results of the participation are then analyzed for their strengths and weaknesses and their applicability to ATIS development. The study concludes that the feedback website is the most applicable form of participation for ATIS design, followed by surveys that should be used periodically, and future's workshops that should be used rarely.

Originally presented as the author's Thesis (doctoral)--Technische Universität München. / "FGV-TUM." Includes bibliographical references (p. 127-135).

This research develops and evaluates an Advanced Traveler Information System (ATIS) model using a Vehicle-to-Vehicle (V2V) communication system (referred to as the GATIS-V2V model) with the off-the-shelf microscopic simulation model, VISSIM. The GATIS-V2V model is tested on notional small traffic networks (non-signalized and signalized) and a 6X6 typical urban grid network (signalized traffic network). The GATIS-V2V model consists of three key modules: vehicle communication, on-board travel time database management, and a Dynamic Route Guidance System (DRGS). In addition, the system performance has been enhanced by applying three complementary functions: Autonomous Automatic Incident Detection (AAID), a minimum sample size algorithm, and a simple driver behavior model. To select appropriate parameter ranges for the complementary functions a sensitivity analysis has been conducted. The GATIS-V2V performance has been investigated relative to three underlying system parameters: traffic flow, communication radio range, and penetration ratio of participating vehicles. Lastly, the enhanced GATIS-V2V model is compared with the centralized traffic information system. This research found that the enhanced GATIS-V2V model outperforms the basic model in terms of travel time savings and produces more consistent and robust system output under non-recurrent traffic states (i.e., traffic incident) in the simple traffic network. This research also identified that the traffic incident detection time and driver's route choice rule are the most crucial factors influencing the system performance. As expected, as traffic flow and penetration ratio increase, the system becomes more efficient, with non-participating vehicles also benefiting from the re-routing of participating vehicles. The communication radio ranges considered were found not to significantly influence system operations in the studied traffic network. Finally, it is found that the decentralized GATIS-V2V model has similar performance to the centralized model even under low flow, short radio range, and low penetration ratio cases. This implies that a dynamic infrastructure-based traffic information system could replace a fixed infrastructure-based traffic information system, allowing for considerable savings in fixed costs and ready expansion of the system off of the main network corridors.

Urban transportation networks are inefficient due to sub-optimal use by travelers. One approach to counter the increase in urban transportation demand is to provide better information to travelers, which would allow them to make better use of the network. Existing traveler information systems do this to a certain extent, but are limited by the data available and the scope of their implementation. These systems are vertically integrated and closed so that using any external elements for analysis, user interfacing etc. is difficult. The effects of such traveler information systems are reviewed via a comparative analysis of case studies available in the literature. It is found that information availability has a definite positive effect, but the social and environmental benefits are difficult to quantify. It is also seen that combining data by integrating systems can lead to additional uses for the same data and result on better quality of service and information. In this thesis, a regional platform for multi-modal traveler information is proposed that would support the development of traveler information systems. The architecture incorporates a central processing and storage module, which acts as an information clearinghouse and supports receiving, managing and sending data to and from multiple sources and interfaces. This setup allows sharing of data for analysis or application development, but with access control. The components are loosely coupled to minimize inter-dependencies. Due to this, the source, analysis, user interface and storage components can be developed independently of each other. To better develop the requirements and understand the challenges of the proposed concept, a limited implementation of the system is designed for the midtown Atlanta region, incorporating multiple data sources and user interfaces. The individual elements of the system are described in detail as is the testing and evaluation of the system.

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

This study used focus groups and surveys to provide a comprehensive evaluation of the Regional Traveler Information Center (RTIC) at UMass Amherst. The evaluation was completed by obtaining the awareness, usage, and perceived effectiveness of RTIC’s information by residents in the Pioneer Valley. It was found that awareness of RTIC is limited due to its lack of advertisement. Usage is focused primarily on its webcams and advisory information. Surveys showed that participants perceive RTIC to be useful, even though they may never have seen the information before (the survey provided a chance for them to become familiar with the service). Revealed preference data were collected regarding the travelers' most memorable instances where real-time traffic information was provided. A binary logit model of a traveler's switch decision (route, departure time, mode, destination, trip cancellation, or combinations of them) with real-time traffic information was specified and estimated. It was found that travelers have an increasing tendency to switch away from the original option when the resulting delay caused by congestion increases. Receiving congestion and crash information also provided a tendency to take an alternative travel method. It was found that males tend to switch more often than females, and young individuals switch less often.

This study was performed with two main goals in mind. The first goal was to understand and predict "red-lines" and "yellow-lines" in terms of what the CVO driver can process without hindering the primary task of driving. The second goal was to collect conventional secondary task data for CVO driving performance. An on-the-road experiment was performed with the help of 12 truck drivers. Type of task, presentation format, information density, and age were the independent variables used in the experiment. The 22 dependent measures collected were grouped into the following categories: eye glance measures, longitudinal driving performance, lateral driving performance, secondary task performance, and subjective assessment. The findings of this study strongly suggest that paragraphs should not be used under any circumstance to present information to the driver while the vehicle is in motion. On the other hand, the Graphics with Icons represent the most appropriate format in which driving instructions and information should be presented for IVIS/CVO tasks. In order to avoid a high visual attention demand to the driver due to a secondary task, only simple search tasks with the most important information shall be presented. Although the suggested format, type of task, and information density represent a higher visual attention demand than a conventional secondary task, these characteristics seem to bind a task with a moderate attentional demand. Other combinations of format, type of task, and information density will cause an increase in the driver's attentional demand that will consequently deteriorate their driving performance causing unsafe driving situations. / Master of Science

No description available.

Presently, the United States has yet to achieve the 1991 Intermodal Surface Transportation Efficiency Act's (ISTEA) goal of creating a seamless intermodal transportation system. In addition to the dearth of connections, the nation's poor transportation information systems limit intercity intermodal transportation. Travelers lack awareness of available transportation options and face too many separate portals for trip planning that both consume time and present inadequate information. This paper posits that the creation of an efficient and extensive web-based door-to-door intermodal trip planner can solve these problems. The proposed system will present travelers with a single portal to meet all their trip planning needs. Upon selecting specific trips, travelers can then decide to be directed to operators to make a purchase. The system will include operators from the major modal groups including intercity buses, intercity rail, commuter rail, transit, and airlines. It will also include taxis due to the disjointed nature of the US public transportation system and the need to connect users who are far from stations. The requirements to create this trip planner are explored, including the support systems, potential legal issues, and suitable entities for administration and management. A survey of 39 transportation system users revealed the existence of redundant and inadequate trip planners and that the lack of sufficient information on public transportation options is driving travelers to private vehicles for shorter distances even for those who prefer public means of transportation. Analysis of the costs and benefits of implementing the proposed system is drawn from interviews with key personnel within the transportation industry, and a review of nationwide trip planners in European countries. Finally, a roadmap is presented on how best to implement the system with inputs from both the public and private sector. Recommendations include the establishment of an industry-wide data standard, a national interagency database, and a cooperative structure that entices major players within each mode to participate in the system. Also suggested are incentives from the DOT and interested private sector members to encourage more operators to participate in the system. / Master of Science

Traveler information systems play a significant role in most travelers’ daily trips. These systems assist travelers in choosing the best routes to reach their destinations and possibly select suitable departure times and modes for their trips. Connected Vehicle (CV) technologies are now in the pilot program stage. Vehicle-to-Infrastructure (V2I) communications will be an important source of data for traffic agencies. If this data is processed properly, then agencies will be able to better determine traffic conditions, allowing them to take proper countermeasures to remedy transportation system problems under different conditions. This research focuses on developing methods to assess the potential of utilizing CV data to support the traveler information system data collection process. The results from the assessment can be used to establish a timeline indicating when an agency can stop investing, at least partially, in traditional technologies, and instead rely on CV technologies for traveler information system support. This research utilizes real-world vehicle trajectory data collected under the Next Generation Simulation (NGSIM) program and simulation modeling to emulate the use of connected vehicle data to support the traveler information system. NGSIM datasets collected from an arterial segment and a freeway segment are used in this research. Microscopic simulation modeling is also used to generate required trajectory data, allowing further analysis, which is not possible using NGSIM data. The first step is to predict the market penetration of connected vehicles in future years. This estimated market penetration is then used for the evaluation of the effectiveness of CV-based data for travel time and volume estimation, which are two important inputs for the traveler information system. The travel times are estimated at different market penetrations of CV. The quality of the estimation is assessed by investigating the accuracy and reliability with different CV deployment scenarios. The quality of volume estimates is also assessed using the same data with different future scenarios of CV deployment and partial or no detector data. Such assessment supports the identification of a timeline indicating when CV data can be used to support the traveler information system.