Intelligent Transportation Systems and supporting technologies have been an active area of research for some time. Human drivers exhibit slower response times and errors in judgment that can have serious adverse affects on traffic flow. These types of errors can be reduced or eliminated from the driving experience by introducing computer control systems into the automotive arena. The purpose of this research was to develop a scale model platform for the rapid prototyping and testing of ITS systems and technologies. Specifically, this body of work was concerned with the development of an automatic headway control system that utilized ultrasonic sensors. This control system was intended to automatically maintain headway distance in an effort to create an adaptive cruise control system for this scale model vehicle. Implementation of such systems could conceivably reduce driver fatigue by removing the burden of maintaining safe following distance from the driver. System dynamics of car-like robots with nonholonomic constraints were employed in this research to create a controller for an autonomous path following vehicle. The application of a working kinematic model describing car-like robotic systems allowed the development of a simple first order controller, as well as a sliding mode controller. Following the development and simulation of these two control laws, the system was applied to the FLASH project scale model vehicle to assess the practical use of the system on a mock highway. A satisfactory result is produced after testing was completed, and the application of such systems to scale model platforms is feasible. / Master of Science

<p>Analizom procesa kretanja vozila duž linije identifikovani su parametri koji utiču na širenje poremećaja intervala sleđenja. Na osnovu utvrđenih relacija između parametara, formiran je deterministički model. Modelom je predstavljeno širenje i slaganje više prostih poremećaja intervala sleđenja po stajalištima duž linije i po polascima u redu vožnje na jednoj liniji javnog gradskog prevoza putnika. U radu je izvršena matematička analiza složenog uticaja različitih parametara na širenje poremećaja intervala sleđenja vozila. Rezultati analize su pokazali da je u fazi projektovanja sistema u velikoj meri moguće uticati na sekundarne poremećaje intervala sleđenja i preventivno delovati na povećanje stepena ravnomernosti intervala sleđenja na liniji. U skladu sa zaključcima analize modela razvijen je postupak optimizacije kojim se sa aspekta vremena boravka putnika u sistemu i dostignute ravnomernosti intervala sleđenja, vrednuje podela dijametralne linije na dve radijalne.</p> / <p>An analysis of the process of vehicle movement along the line was used to identify the parameters which influence irregular headway propagation. The established relations between the parameters were used to form a deterministic model. The model describes the propagation and concurrence of numerous primary headway irregularities by the stops along the line and by the scheduled departure times at one urban public transport system line. The paper presents a mathematical analysis of the complex effect of various parameters on the irregular headway propagation. The results of the analysis have shown that the secondary headway irregularites could be largely affected during the transport system design phase, thus preventing the increase in the degree of headway uniformity along the line. In accordance with the conclusions of the model analysis, an optimisation method has been developed, which is used to evaluate the division of the diametrical line into two radial lines from the aspect of on-line travel time and the achieved headway uniformity.</p>

The operational performance of an existing or proposed roundabout can be assessed through capacity models. In order to provide improved capacity predictions for existing and proposed Georgia roundabouts, the 2010 HCM roundabout capacity equations need to be locally calibrated based on Georgia drivers. The purpose of this study is to collect field data necessary to calculate follow-up and critical headways at Georgia roundabouts in order to calibrate the 2010 HCM capacity equations to yield improved capacity predictions. The research team filmed 28 approaches at thirteen Georgia roundabouts for a total of 56.5 hours. The video was processed manually using an in-house computer program. Based on analyst keystrokes during the video review the program would extract timestamps of events that are necessary for calculating follow-up and critical headway. The follow-up and critical headway values were calculated for two different data sets: 1) including exiting vehicles and 2) excluding exiting vehicles. The critical and follow-up headway for an analysis including exiting vehicles is 4.192 seconds and 2.788 seconds respectively. The critical and follow-up headway for an analysis excluding exiting vehicles is 4.747 seconds and 3.265 seconds respectively. This study found that including the exiting vehicles impacts the capacity. The capacity increases or decreases based on the percentage of conflicting vehicles that are exiting vehicles. In addition, this study’s calibrated model excluding exiting vehicles predicts higher capacity than the 2010 HCM model that GDOT recommends which also excludes exiting vehicles.

Tailgating (maintaining an inadequate headway) is a major road safety concern that emerges because drivers tend to misperceive their following distance. Drivers seldom receive enough feedback to correct this error, leaving them vulnerable to rear-end collisions. While there have been attempts to address this issue through vehicle automation and warning systems, these approaches have not been sensitive to the needs of young drivers. The present investigation sought to implement a headway evaluation system: an in-vehicle display designed to provide motorists with real-time as well as aggregate headway feedback. This system was designed to teach drivers to recognize safe headways and to motivate adherence. Compared to drivers selecting their own headway or those attempting to count a two second headway, drivers using the headway evaluation system maintained longer headways that would be conducive to collision avoidance. This system may be beneficial as a training device for new drivers. / AUTO21, the Ontario Innovation Trust, the Canada Foundation for Innovation, and the Natural Sciences and Engineering Research Council of Canada

For decades, vehicle time-headway distribution models have been studied by many researchers and traffic engineers. A good time-headway model can be beneficial to traffic studies and management in many aspects; e.g. with a better understanding of road traffic patterns and road user behaviour, the researchers or engineers can give better estimations and predictions under certain road traffic conditions and hence make better decisions on traffic management and control. The models also help us to implement high-quality microscopic traffic simulation studies to seek good solutions to traffic problems with minimal interruption of the real traffic environment and minimum costs. Compared within previously studied models, the mixed (SPM and GQM) mod- els, especially using the gamma or lognormal distributions to describe followers headways, are probably the most recognized ones by researchers in statistical stud- ies of headway data. These mixed models are reported with good fitting results indicated by goodness-of-fit tests, and some of them are better than others in com- putational costs. The gamma-SPM and gamma-GQM models are often reported to have similar fitting qualities, and they often out-perform the lognormal-GQM model in terms of computational costs. A lognormal-SPM model cannot be formed analytically as no explicit Laplace transform is available with the lognormal dis- tribution. The major downsides of using mixed models are the difficulties and more flexibilities in fitting process as they have more parameters than those single models, and this sometimes leads to unsuccessful fitting or unreasonable fitted pa- rameters despite their success in passing GoF tests. Furthermore, it is difficult to know the connections between model parameters and realistic traffic situations or environments, and these parameters have to be estimated using headway samples. Hence, it is almost impossible to explain any traffic phenomena with the param- eters of a model. Moreover, with the gamma distribution as the only common well-known followers headway model, it is hard to justify whether it has described the headway process appropriately. This creates a barrier for better understanding the process of how drivers would follow their preceding vehicles. This study firstly proposes a framework developed using MATLAB, which would help researchers in quick implementations of any headway distributions of interest. This framework uses common methods to manage and prepare headway samples to meet those requirements in data analysis. It also provides common structures and methods on implementing existing or new models, fitting models, testing their performance hence reporting results. This will simplify the development work involved in headway analysis, avoid unnecessary repetitions of work done by others and provide results in formats that are more comparable with those reported by others. Secondly, this study focuses on the implementation of existing mixed models, i.e. the gamma-SPM, gamma-GQM and lognormal-GQM, using the proposed framework. The lognormal-SPM is also tested for the first time, with the recently developed approximation method of Laplace transform available for lognormal distributions. The parameters of these mixed models are specially discussed, as means of restrictions to simplify the fitting process of these models. Three ways of parameter pre-determinations are attempted over gamma-SPM and gamma-GQM models. A couple of response-time (RT) distributions are focused on in the later part of this study. Two RT models, i.e. Ex-Gaussian (EMG) and inverse Gaussian (IVG) are used, for first time, as single models to describe headway data. The fitting performances are greatly comparable to the best known lognormal single model. Further extending this work, these two models are tested as followers headway distributions in both SPM and GQM mixed models. The test results have shown excellent fitting performance. These now bring researchers more alternatives to use mixed models in headway analysis, and this will help to compare the be- haviours of different models when they are used to describe followers headway data. Again, similar parameter restrictions are attempted for these new mixed models, and the results show well-acceptable performance, and also corrections on some unreasonable fittings caused by the over flexibilities using 4- or 5- parameter models.

Public transportation, although modest in the United States carrying about 2 percent trips, still serves millions of people as the main and only means of transportation. Recently released data set by Census, the 2006 American Community Survey (ACS) shows the main mode of travel for work commute is not surprisingly the automobile with over 86 percent and public transportation with nearly 5 percent users. Transit agencies strive to provide effective, convenient, and desirable transport. Because of the constant changes in our environment, being able to predict the response of riders to different network or system changes is extremely useful. Ridership can be described as a function of the amount of service supplied such as frequency, span of service, and travel time. One of the methods for estimating ridership forecasts and evaluating ridership response is to use the new state-of-art software TBEST. TBEST stands for Transit Boardings Estimation and Simulation Tool and is the third generation of such transit models sponsored by the Florida Department of Transportation (FDOT). Designed for comprehensive transit network and short term transit planning, it offers great benefits to its users. TBEST is a user friendly, yet very advanced transit ridership forecasting graphical software which is interfaced with ArcGIS. This paper evaluates different sensitivity tests and compares the results to known industry used elasticities. Because the current TBEST experience is modest, the results will provide users with a general idea of the model's sensitivity and help in the process of model refinements. Sensitivity tests such as service frequency, span of service, service allocation, and travel time will be carried out in a systematic order for all six time periods as defined by TBEST. Results showed that TBEST Model is overestimating and is highly sensitive to headway changes, specifically headway decrease. The opposite effect of almost no sensitivity is shown for the in-vehicle travel times.

Models based on micro-simulation of traffic flows have proven to be useful tools in the study of various traffic systems. Today, there is a wealth of traffic microsimulation models developed for freeway and urban street networks. The road mileage is however in many countries dominated by rural highways. Hence, there is a need for rural road traffic simulation models capable of assessing the performance of such road environments. This thesis introduces a versatile traffic micro-simulation model for the rural roads of today and of the future. The developed model system considers all common types of rural roads including effects of intersections and roundabouts on the main road traffic. The model is calibrated and validated through a simulation study comparing a two-lane highway to rural road designs with separated oncoming traffic lanes. A good general agreement between the simulation results and the field data is established. The interest in road safety and the environmental impact of traffic is growing. Recent research has indicated that traffic simulation can be of use in these areas as well as in traditional capacity and level-of-service studies. In the road safety area more attention is turning towards active safety improving countermeasures designed to improve road safety by reducing the number of driver errors and the accident risks. One important example is Advanced Driver Assistance Systems (ADAS). The potential to use traffic simulation to evaluate the road safety effects of ADAS is investigated in the last part of this thesis. A car-following model for simulation of traffic including ADAS-equipped vehicles is proposed and the developed simulation framework is used to study important properties of a traffic simulation model to be used for safety evaluation of ADAS. Driver behavior for ADAS-equipped vehicles has usually not been considered in simulation studies including ADAS-equipped vehicles. The work in this thesis does however indicate that modeling of the behavior of drivers in ADAS-equipped vehicles is essential for reliable conclusions on the road safety effects of ADAS. / <p>Report code: LiU-Tek-Lic-2005:60.</p>

This thesis investigates the effect of a feedback-reward system on speeding and tailgating behaviours. Data utilized in this study were collected from 37 participants through a field trial commissioned by Transport Canada. In this trial, a feedback-reward system was investigated, which provided feedback and rewards to the drivers based on speed limit compliance and safe headway maintenance. The trial consisted of three phases: baseline, intervention, and post-intervention. During the intervention phase, real-time feedback was provided on an in-vehicle display. Participants also accumulated reward points and could view related information on a website. Results indicate that the intervention resulted in a significant increase in speed limit compliance, and this positive effect, although dampened, was still apparent after system removal. Similarly, results on headway compliance rate indicate a positive intervention effect, however, this effect did not sustain after system removal. These findings have implications for developing better aids to improve driving behaviour.

This thesis investigates the effect of a feedback-reward system on speeding and tailgating behaviours. Data utilized in this study were collected from 37 participants through a field trial commissioned by Transport Canada. In this trial, a feedback-reward system was investigated, which provided feedback and rewards to the drivers based on speed limit compliance and safe headway maintenance. The trial consisted of three phases: baseline, intervention, and post-intervention. During the intervention phase, real-time feedback was provided on an in-vehicle display. Participants also accumulated reward points and could view related information on a website. Results indicate that the intervention resulted in a significant increase in speed limit compliance, and this positive effect, although dampened, was still apparent after system removal. Similarly, results on headway compliance rate indicate a positive intervention effect, however, this effect did not sustain after system removal. These findings have implications for developing better aids to improve driving behaviour.

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