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

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.

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

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.

High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the crash risk on long and short term basis. Therefore, the main focus of the research in this dissertation is to provide a framework of risk assessment to promote safety and enhance mobility on freeways and expressways. Multi-level Safety Performance Functions (SPFs) were developed at the aggregate level using historical crash data and the corresponding exposure and risk factors to identify and rank sites with promise (hot-spots). Additionally, SPFs were developed at the disaggregate level utilizing real-time weather data collected from meteorological stations located at the freeway section as well as traffic flow parameters collected from different detection systems such as Automatic Vehicle Identification (AVI) and Remote Traffic Microwave Sensors (RTMS). These disaggregate SPFs can identify real-time risks due to turbulent traffic conditions and their interactions with other risk factors. In this study, two main datasets were obtained from two different regions. Those datasets comprise historical crash data, roadway geometrical characteristics, aggregate weather and traffic parameters as well as real-time weather and traffic data. iii At the aggregate level, Bayesian hierarchical models with spatial and random effects were compared to Poisson models to examine the safety effects of roadway geometrics on crash occurrence along freeway sections that feature mountainous terrain and adverse weather. At the disaggregate level; a main framework of a proactive safety management system using traffic data collected from AVI and RTMS, real-time weather and geometrical characteristics was provided. Different statistical techniques were implemented. These techniques ranged from classical frequentist classification approaches to explain the relationship between an event (crash) occurring at a given time and a set of risk factors in real time to other more advanced models. Bayesian statistics with updating approach to update beliefs about the behavior of the parameter with prior knowledge in order to achieve more reliable estimation was implemented. Also a relatively recent and promising Machine Learning technique (Stochastic Gradient Boosting) was utilized to calibrate several models utilizing different datasets collected from mixed detection systems as well as real-time meteorological stations. The results from this study suggest that both levels of analyses are important, the aggregate level helps in providing good understanding of different safety problems, and developing policies and countermeasures to reduce the number of crashes in total. At the disaggregate level, real-time safety functions help toward more proactive traffic management system that will not only enhance the performance of the high speed facilities and the whole traffic network but also provide safer mobility for people and goods. In general, the proposed multi-level analyses are useful in providing roadway authorities with detailed information on where countermeasures must be implemented and when resources should be devoted. The study also proves that traffic data collected from different detection systems could be a useful asset that should be utilized iv appropriately not only to alleviate traffic congestion but also to mitigate increased safety risks. The overall proposed framework can maximize the benefit of the existing archived data for freeway authorities as well as for road users.