Transportation safety has been recognized as a public health issue worldwide, consequently, transportation researchers and practitioners have been attempting to provide adequate safety performance for the various transportation components and facilities to all road users given the usually scarce resources available. Safety engineers have been trying to make decisions affecting safety based on the knowledge extracted from different types of statistical models and/or observational before-after analysis. It is generally recognized that this type of factual knowledge is not easily obtained either statistically or empirically. Despite the intuitive link between road safety and observed crashes, a good understanding of the sequence of events prior to the crash can provide a more rational basis for the development of engineering countermeasures. The development of more comprehensive mechanistic models for safety assessment is heavily dependent on detailed vehicle tracking data that is not readily available. The potential of microscopic simulation in traffic safety and traffic conflict analysis has gained increasing interest mostly due to recent developments in human behaviour modelling and real-time vehicle data acquisition. In this thesis, we present a systematic investigation of the use of existing behavioural microscopic simulation models in short-term road safety studies. Initially, a microscopic framework is introduced to identify potentially unsafe vehicle interactions for different vehicle movements based on three types of traffic behaviour protocols: car-following, lane change and gap acceptance. This microscopic model for safety assessment applies a safety performance measure based on pairwise comparisons of spacing and speed differential between adjacent vehicles and individual braking power in real-time. A calibration/validation procedure using factorial analysis is presented to select best model input parameters for this safety performance measure by using high resolution vehicle tracking data. The ability of the proposed safety performance measure to reflect real-life observed high-risk vehicular interactions is explored in three intuitive tests using observed crash data. Finally, the usefulness of the model is illustrated through its application to investigate the safety implications of two different geometric and operational traffic strategies. The overall results indicate that, notwithstanding the fact that actual behavioural microscopic algorithms have not been developed strictly to model crashes, they are able to replicate several factors directly related to high risk situations that could lead to crashes with reasonable accuracy. With the existing upward trend in computing power, modelling techniques and increasing availability of detailed vehicle tracking data, it is likely that safety studies will be carried out using a more mechanistic and inclusive approach based on disruptive driving behaviour rather than ultimate unpredictable and heavily restrictive crash events.

This study adopted the traffic conflict technique, investigated and applied it for evaluation of freeway weaving section safety performance. Conflicts between vehicles were identified based on the state of interactions between vehicles in the traffic stream at microscopic level. The VISSIM microscopic simulation model was employed to simulate traffic operation. Surrogate safety measures were formulated based on deceleration rate required to avoid crash and these simulation-based measures were statistically compared and validated using crash data collected from the same study site. Three study sites located in Houston and Dallas areas were selected. Geometric and traffic data were collected using various technique including the use of traffic surveillance cameras and pneumatic tubes. The study revealed the existence of links between actually observed crashes and the surrogate safety measures. The study findings support the possible the use of microscopic simulation to evaluate safety performance of weaving areas and other transportation facilities.

This thesis reports the use of Paramics microscopic simulation software to model the differences between the performance of ten Christchurch intersections under the existing New Zealand road rule which requires left turning vehicles to give way to vehicles turning right into the same road, and a changed rule that would see the right turning vehicle have priority. Previous research concerning this issue is reviewed and the history of the existing road rule and recent moves to change it are discussed. At each of the ten intersections a range of traffic volume combinations was assessed and the journey times and queue lengths were compared. The ten intersections represent a range of different layouts and forms of control including give way signs, stop signs and traffic signals. The impact of a rule change on the use of shared lanes at intersections using a Paramics model of the Christchurch Central Business District, as developed for the Christchurch City Council, is also reported. Conclusions are drawn about which types of intersections and traffic volume combinations are likely to be affected by a rule change. The features of intersections that contribute to this susceptibility are identified and conclusions drawn about whether positive or negative effects are likely. It is concluded that there is no compelling intersection performance reason why the rule could not be changed. The successful implication of such change would require a review of the road network to identify critical intersections. Some monitoring and mitigation measures may also be required.

In order to attract pedestrians to travel with public transport instead of private cars, the layout of interchange stations is important and should be designed in an effective way. Microscopic simulation of pedestrians can be used to evaluate different layout scenarios or a future increase in flow. The simulation software Viswalk was investigated, where the movements of pedestrians are based on a social force model,. The purpose of this thesis was to investigate simulated walking speeds for different flow levels and to investigate the effects of dividing pedestrians into types with different desired speeds. The aim was to find a desired speed distribution that can be used for different flow levels. Field studies have been performed to collect pedestrian traffic data with a video camera at Stockholm Central Station. Two disjoint flow levels were identified and used to investigate if the same desired speed distribution could be used for different flow levels. The average observed walking speed was 1.33 metres per second at the low flow level and 1.25 metres per second at the high flow level. The error was 4.5 percent between the average observed walking speed and the average simulated walking speed when the optimal desired speed distribution at the low flow level was used at the high flow level. Effects of using different desired speed distributions for different pedestrian types have also been investigated. The error between the average of the observed and the simulated walking speeds varies between 2.3 and 4.1 percent when dividing pedestrians into different types when the optimal desired speed distributions at the low flow level are used at the high flow level. A sensitivity analysis of some parameters of the social force model in Viswalk has also been performed. Several adjustments of the parameters show that some parameters had great impact of the simulated walking speeds. The final conclusion is that the parameter configuration and how the pedestrians are divided into different types affect the average simulated walking speed.

The target of this diploma thesis is to create and compare variants dealing with a complicated traffic situation in Brno-Komín. Two dynamic responsive signal-controlled junctions situated in close proximity constitute the researched area. The situation is complicated by the presence of a streetcar crossing. Conducted traffic surveys represent the first part of the thesis. Data supplied by a junction's administrator are then added to the survey results. All acquired data serve as background information for designing possible solutions. Most of the work is connected with a capacity analysis which is done according to valid regulations. A microscopic simulation is implemented to examine impacts of selected concepts. The presented concepts are then evaluated financially. Finally, an optimal variant for implementation is suggested.

This thesis presents the use of microscopic traffic simulation models to evaluate the effects of operational-level transportation projects such as ITS. A detailed framework outlining the construction and calibration of microscopic simulation models is provided, as well as the considerations that must be made when analyzing the outputs from these models. Two case studies are used to reinforce the concepts presented. In addition, these case studies give valuable insight for using the outlined approach under real-world conditions. The study indicates a promising future for the use of microsimulation models for the purpose of evaluating operational-level projects, as the theoretical framework of the models is sound, and the computational strategies used are feasible. There are, however, instances where simulation models do not presently model certain phenomena, or where simulation models are too computationally intensive. Comprehensive models that integrate microscopic simulation with land use planning and realistic predictions of human behavior, for instance, cannot practically be modeled in contemporary simulation packages. Other than these instances, the largest obstacles to using simulation packages were found to be the manpower required and the complexity of constructing a model. Continuing research efforts and increasing computer speeds are expected to resolve the former issues. Both of the latter concerns are alleviated by the approach presented herein. Within the approach framework detailed in this thesis, particular emphasis is given to the calibration aspects of constructing a microscopic simulation model. Like the simulation process as a whole, calibration is both an art and a science, and relies on sound engineering judgement rather than indiscriminate, formulaic processes. / Master of Science

No description available.

Bus Rapid Transit (BRT) corridors and systems have emerged in the past three decades as affordablesolutions of medium capacity public transport services to highly urbanized areas, especially in LatinAmerica and Asia. In Stockholm, trunk bus lines have gained priority over mixed traffic over the yearsthrough exclusive bus lanes, signal priority, and reliability control, for example, but no complete BRTsolution has been implemented yet. Among the inner-city trunk lines, Line 4 is the most demanded witharound 70,000 passengers boarding the service daily. This thesis proposes, then, to assess theoperational impacts that BRT solutions as segregate median lanes, stations with off-board farecollection and platform level boarding and alighting through all bus doors, full signal priority andheadway control strategy, would have in bus Line 4, using a microscopic simulation approach. Twoscenarios were simulated, and the results compared to the existing conditions (Base Scenario).Scenario 1 considered a 5-minute headway service and Scenario 2, 3-minute headways. Overall, theproposed scenarios reduce travel times by 37.6-49.1%, increase average operational speeds (includingdwell times) by 60.4-96.6%, decrease dwell times by 57.9-65.6%, decrease delays by 18.4-36%,decrease vehicle occupancy rates by 3.5-44.9% and improve the Coefficient of Variation of theheadways from 0.83-0.85 in the Base Scenario to 0.1 in Scenario 1 and 0.2 in Scenario 2. As a resultof the reduction in travel times, a BRT service would need 13 buses to operate a 5-minute headwayand 21 buses for a 3-minute headway, against 27 vehicles that are used currently for a 4 to 6-minuteheadway during peak hour.

This thesis is focused on two topics. The first topic is the General Aviation (GA) demand forecasting models. The contributions to this topic are three fold: 1) we calibrated an econometric model to investigate the impact of fuel price on the utilization rate of GA piston engine aircraft, 2) we adopted a logistic model to identify the relationship between fuel price and an aircraft's probability of staying active, and 3) we developed an econometric model to forecast the airport-level itinerant and local GA operations. Our calibration results are compared with those reported in literature. Demand forecasts are made with these models and compared with those prepared by the Federal Aviation Administration. The second topic is to model the air traffic in the Organized Track System (OTS) over the North Atlantic. We developed a discrete-time event model to simulate the air traffic that uses the OTS. We proposed four new operational procedures to improve the flight operations for the OTS. Two procedures aim to improve the OTS assignments in the OTS entry area, and the other two aim to benefit flights once they are inside the OTS. The four procedures are implemented with the simulation model and their benefits are analyzed. Several implementation issues are discussed and recommendations are given. / Ph. D.

Vehicle recognition and trajectory tracking plays an integral role in many aspects of Intelligent Transportation Systems (ITS) applications; from behavioral modeling and car-following analyses to congestion prevention, crash prediction, dynamic signal timing, and active traffic management. This dissertation aims to improve the tasks of multi-object detection and tracking (MOT) as it pertains to urban traffic by utilizing the domain knowledge of traffic flow then utilize this improvement for applications in real-time traffic performance assessment, safety evaluation, and driver behavior modeling. First, the author proposes an ad-hoc framework for real-time turn count and trajectory reconstruction for vehicles passing through urban intersections. This framework introduces the concept of virtual traffic lanes representing the eight standard National Electrical Manufacturers Association (NEMA) movements within an intersection as spatio-temporal clusters utilized for movement classification and vehicle re-identification. The proposed framework runs as an additional layer to any multi-object tracker with minimal additional computation. The results obtained for a case study and on the AI City benchmark dataset indicate the high ability of the proposed framework in obtaining reliable turn count, speed estimates, and efficiently resolving the vehicle identity switches which occur within the intersection due to detection errors and occlusion. The author then proposes the utilization of the high accuracy and granularity trajectories obtained from video inference to develop a real-time safety-based driver behavior model, which managed to effectively capture the observed driving behavior in the site of study. Finally, the developed model was implemented as an external driver model in VISSIM and managed to reproduce the observed behavior and safety conflicts in simulation, providing an effective decision-support tool to identify appropriate safety interventions that would mitigate those conflicts. The work presented in this dissertation provides an efficient end-to-end framework and blueprint for trajectory extraction from road-side traffic video data, driver behavior modeling, and their applications for real-time traffic performance and safety assessment, as well as improved modeling of safety interventions via microscopic simulation. / Doctor of Philosophy / Traffic crashes are one of the leading causes of death in the world, averaging over 3,000 deaths per day according to the World Health Organization. In the United States alone, there are around 40,000 traffic fatalities annually. Approximately, 21.5% of all traffic fatalities occur due to intersection-related crashes. Intelligent Transportation Systems (ITS) is a field of traffic engineering that aims to transform traffic systems to make safer, more coordinated, and 'smarter' use of transport networks. Vehicle recognition and trajectory tracking, the process of identifying a specific vehicle's movement through time and space, plays an integral role in many aspects of ITS applications; from understanding how people drive and modeling that behavior, to congestion prevention, on-board crash avoidance systems, adaptive signal timing, and active traffic management. This dissertation aims to bridge the gaps in the application of ITS, computer vision, and traffic flow theory and create tools that will aid in evaluating and proactively addressing traffic safety concerns at urban intersections. The author presents an efficient, real-time framework for extracting reliable vehicle trajectories from roadside cameras, then proposes a safety-based driving behavior model that succeeds in capturing the observed driving behavior. This work is concluded by implementing this model in simulation software to replicate the existing safety concerns for an area of study, allowing practitioners to accurately model the existing safety conflicts and evaluate the different operation and safety interventions that would best mitigate them to proactively prevent crashes.