Freeway work zones with lane closures can adversely affect mobility, safety, and sustainability. Capacity drop phenomena near work zone areas can further decrease work zone capacity and exacerbate traffic congestion. To mitigate the negative impacts caused by freeway work zones, many variable speed limits (VSL) control methods have been proposed to proactively regulate the traffic flow. However, a simple yet robust VSL controller that considers the nonlinearity induced by the associated capacity drop is still needed. Also, most existing studies of VSL control neglected the impacts of traffic sensor failures that commonly occur in transportation systems. Large deviations of traffic measurements caused by sensor faults can greatly affect the reliability of VSL controllers. To address the aforementioned challenges, this research proposes a fault-tolerant VSL controller for a freeway work zone with consideration of sensor faults. A traffic flow model was developed to understand and describe the traffic dynamics near work zone areas. Then a VSL controller based on sliding mode control was designed to generate dynamic speed limits in real time using traffic measurements. To achieve VSL control fault tolerance, analytical redundancy was exploited to develop an observer-based method and an interacting multiple model with a pseudo-model set (IMMP) based method for permanent and recurrent sensor faults respectively. The proposed system was evaluated under realistic freeway work zone conditions using the traffic simulator SUMO. This research contributes to the body of knowledge by developing fault-tolerant VSL control for freeway work zones with reliable performance under permanent and recurrent sensor faults. With reliable sensor fault diagnosis, the fault-tolerant VSL controller can consistently reduce travel time, safety risks, emissions, and fuel consumption. Therefore, with a growing number of work zones due to aging road infrastructure and increasing demand, the proposed system offers broader impacts through congestion mitigation and consistent improvements in mobility, safety, and sustainability near work zones. / Thesis / Doctor of Philosophy (PhD) / Freeway work zones can increase congestion with higher travel time, safety risk, emissions and fuel consumption. This research aims to improve traffic conditions near work zones using a variable speed limits control system. By exploiting redundant traffic information, a variable speed limit control system that is insensitive to traffic sensor failures is presented. The proposed system was evaluated under realistic freeway work zone conditions in a simulation environment. The results show that the proposed system can reliably detect sensor failures and consistently provide improvements in mobility, safety and sustainability despite the presence of traffic sensor failures.

Recent research at UCF into defining surrogate measures for identifying crash prone conditions on freeways has led to the introduction of several statistical models which can flag such conditions with a good degree of accuracy. Outputs from these models have the potential to be used as real-time safety measures on freeways. They may also act as the basis for the evaluation of several intervention strategies that might help in the mitigation of risk of crashes. Ramp Metering and Variable Speed Limits are two approaches which have the potential of becoming effective implementation strategies for improving the safety conditions on congested freeways. This research evaluates both these strategies in different configurations and attempts to quantify their effect on risk of crash on a 9-mile section of Interstate-4 in the Orlando metropolitan region. The section consists of 17 Loop Detector stations, 11 On-ramps and 10 off-ramps. PARAMICS micro-simulation is used as the tool for modeling the freeway section. The simulated network is calibrated and validated for 5 minute average flows and speeds using loop detector data. Feedback Ramp Metering algorithm, ALINEA, is used for controlling access from up to 7 on-ramps. Variable Speed Limits are implemented based on real-time speed conditions prevailing in the whole 9-mile section. Both these strategies are tested separately as well as collectively to determine the individual effects of all the parameters involved. The results have been used to formulate and recommend the best possible strategy for minimizing the risk of crashes on the corridor. The study concluded that Ramp Metering improves the conditions on the freeway in terms of safety by decreasing variance in speeds and decreasing average occupancy. A safety benefit index was developed for quantifying the reduction in crash risk and it indicated that an optimal implementation strategy might produce benefits of up to 55%. The condition on the freeway section improved with increase in the number of metered ramps. It was also observed that shorter signal cycles for metered ramps were more suitable for metering multiple ramps. Ramp Metering at multiple locations also decreased the segment wide travel-times by 5% and was even able to offset the delays incurred by drivers at the metered on-ramps. Variable Speed Limits (VSL) were individually not as effective as ramp metering but when implemented along with ramp metering, they were found to further improve the safety on the freeway section under consideration. By means of a detailed experimental design it was observed that the best strategy for introducing speed limit changes was to raise the speed limits downstream of the location of interest by 5 mph and not affecting the speed limits upstream. A coordinated strategy - involving simultaneous application of VSL and Ramp Metering - provided safety benefits of up to 56 % for the study section according to the safety benefit index. It also improved the average speeds on the network besides decreasing the overall network travel time by as much as 21%.

Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence. iv In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type v based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics. In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson- vi lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence. Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear- vii end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level’s diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the singlevehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence. Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an viii extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL’s impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL’s safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.

Changing speed limit leads to proportional changes in average speeds which may affect the number of traffic accident occurrences. It is however critical and challenging to evaluate the impact of a speed limit alteration on the number and severity of accidents due primarily to the unavailability of adequate data and the inherent limitations of existing approaches. Although speed is regarded as one of the main contributory factors in traffic accident occurrences, research findings are inconsistent. Independent of the robustness of their statistical approaches, accident frequency models typically use accident grouping concepts based on spatial criteria (e.g. accident counts by link termed as a link-based approach). In the link-based approach, the variability of accidents is explained by highly aggregated average measures of explanatory variables that may be inappropriate, especially for time-varying variables such as speed and volume. This thesis re-examines accident-speed relationships by developing a new accident data aggregation method that enables improved representation of the road conditions just before accident occurrences in order to evaluate the impact of a potential speed limit increase on the UK motorways (e.g. from 70 mph to 80 mph). In this work, accidents are aggregated according to the similarity of their pre-accident traffic and geometric conditions, forming an alternative accident count dataset termed as the condition-based approach. Accident-speed relationships are separately developed and compared for both approaches (i.e. link-based and condition-based) by employing the reported annual accidents that occurred on the Strategic Road Network of England in 2012 along with traffic and geometric variables. Accident locations were refined using a fuzzy-logic-based algorithm designed for the study area with 98.9% estimated accuracy. The datasets were modelled by injury severity (i.e. fatal and serious or slight) and by number of vehicles involved (i.e. single-vehicle and multiple-vehicle) using the multivariate Poisson lognormal regression, with spatial effects for the link-based model under a full Bayesian inference method. The results of the condition-based models imply that single-vehicle accidents of all severities and multiple-vehicle accidents with fatal or serious injuries increase at higher speed conditions, particularly when these are combined with lower volumes. Multiple-vehicle slight injury accidents were not found to be related with higher speeds, but instead with congested traffic. The outcomes of the link-based model were almost the opposite; suggesting that the speed-accident relationship is negative. The differences between the results reveal that data aggregation may be crucial, yet so far overlooked in the methodological aspect of accident data analyses. By employing the speed elasticity of motorway accidents that was derived from the calibrated condition-based models it has been found that a 10 mph increase in UK motorway speed limit (i.e. from 70 mph to 80 mph) would result in a 6-12% increase in fatal and serious injury accidents and 1-3% increase in slight injury accidents.

Driving a vehicle is considered a demanding task in a complex dynamic environment. For instance, driving a vehicle on urban roads, where motorized vehicles meet vulnerable road users (VRUs) creates a multifaceted environment with difficult trade-offs and interactions. Additionally, in-vehicle technology developments are being introduced to ease drivers with the driving task. However, these developments are changing “traditional” driving increasing drivers’ response in terms of information processing, thus making the driving task more demanding in some respects. Therefore, the aim of the present research is to further investigate drivers’ speed choice under varying traffic management regulations and in-vehicle warning systems. / <p>QC 20131114</p> / New Speed Limits in Built-Up Areas / COOPERS

Recent years have seen a renewed interest in Variable Speed Limit (VSL) strategies. New opportunities for VSL as a freeway metering mechanism or a homogenization scheme to reduce speed differences and lane changing maneuvers are being explored. This paper examines both the macroscopic and microscopic effects of different speed limits on a traffic stream, especially when adopting low speed limits. To that end, data from a VSL experiment carried out on a freeway in Spain are used. Data include vehicle counts, speeds and occupancy per lane, as well as lane changing rates for three days, each with a different fixed speed limit (80 km/h, 60 km/h, and 40 km/h). Results reveal some of the mechanisms through which VSL affects traffic performance, specifically the flow and speed distribution across lanes, as well as the ensuing lane changing maneuvers. It is confirmed that the lower the speed limit, the higher the occupancy to achieve a given flow. This result has been observed even for relatively high flows and low speed limits. For instance, a stable flow of 1942 veh/h/lane has been measured with the 40 km/h speed limit in force. The corresponding occupancy was 33%, doubling the typical occupancy for this flow in the absence of speed limits. This means that VSL strategies aiming to restrict the mainline flow on a freeway by using low speed limits will need to be applied carefully, avoiding conditions as the ones presented here, where speed limits have a reduced ability to limit flows. On the other hand, VSL strategies trying to get the most from the increased vehicle storage capacity of freeways under low speed limits might be rather promising. Additionally, results show that lower speed limits increase the speed differences across lanes for moderate demands. This, in turn, also increases the lane changing rate. This means that VSL strategies aiming to homogenize traffic and reduce lane changing activity might not be successful when adopting such low speed limits. In contrast, lower speed limits widen the range of flows under uniform lane flow distributions, so that, even for moderate to low demands, the under-utilization of any lane is avoided. These findings are useful for the development of better traffic models that are able to emulate these effects. Moreover, they are crucial for the implementation and assessment of VSL strategies and other traffic control algorithms.

This research evaluates Intelligent Transportation System (ITS) implementation strategies to improve the safety of a freeway once a potential of a crash is detected. Among these strategies are Variable Speed Limit (VSL) and ramp metering. VSL are ITS devices that are commonly used to calm traffic in an attempt to relieve congestion and enhance throughput. With proper use, VSL can be more cost effective than adding more lanes. In addition to maximizing the capacity of a roadway, a different aspect of VSL can be realized by the potential of improving traffic safety. Through the use of multiple microscopic traffic simulations, best practices can be determined, and a final recommendation can be made. Ramp metering is a method to control the amount of traffic flow entering from on-ramps to achieve a better efficiency of the freeway. It can also have a potential benefit in improving the safety of the freeway. This thesis pursues the goal of a best-case implementation of VSL. Two loading scenarios, a fully loaded case (90% of ramp maximums) and an off-peak loading case (60% of ramp maximums), at multiple stations with multiple implementation methods are strategically attempted until a best-case implementation is found. The final recommendation for the off-peak loading is a 15 mph speed reduction for 2 miles upstream and a 15 mph increase in speed for the 2 miles downstream of the detector that shows a high crash potential. The speed change is to be implemented in 5 mph increments every 10 minutes. The recommended case is found to reduce relative crash potential from .065 to -.292, as measured by a high-speed crash prediction algorithm (Abdel-Aty et al. 2005). A possibility of crash migration to downstream and upstream locations was observed, however, the safety and efficiency benefits far outweigh the crash migration potential. No final recommendation is made for the use of VSL in the fully loaded case (low-speed case); however, ramp metering indicated a promising potential for safety improvement.

Since the introduction of motor vehicles, the number of fatalities and accidents has been a concern for society.The number of fatalities on roads is amongst the most common causes of mortality worldwide (WHO, 2015).Even in industrialized countries the number of fatalities remains unacceptable. Therefore, in the last decades, anumber of approaches have emerged to support and boost traffic safety towards a system free from fatalities andserious impairment outcomes. ‘Sustainable Safety’ and ‘Vision Zero’ are well-known examples aiming to avoidfatalities within the traffic system and reduce injury severity when a traffic accident is inevitable. However, thenumber of fatalities and seriously injured accidents are still relatively high. More specifically, vulnerable roadusers remain involved in fatal and serious accidents even in industrialized countries. Therefore, further advancesin traffic safety studies are needed. This thesis aims at evaluating the impact of road characteristics, traffic rulesand information provision towards a safer traffic system. The thesis is composed of five scientific papers whichsummarizes the main contributions of this work. / <p>QC 20161109</p>

Transdisciplinary focused work concentrates on the possibilities of the application of the system thinking in the various science branches. Out of system disciplines it studies in detail the system dynamics -- specifically Archetypes (general structures). Introduction to the general system theory can be found in the first section of the theoretical part. Next sections are more particular and refer to the main ideas of system dynamics and Archetypes. Next part of the work focuses on common methods of the economic analysis. Apart from their brief description there is also discussion about their main theoretical flaws. The economic analysis of the specific socio-economic issue (road speed limits) is performed in the last part of the work and it includes substantial usage of the Archetypes and general system-thinking attitude. Primary aim of this part is to confirm or disprove the hypothesis of the utility of Archetypes in the economic analysis.

La congestion des autoroutes est un problème qui apparait de façon récurrente et qui a un large impact économique, environnemental et social. Ce problème peut être résolu en augmentant la capacité des autoroutes ou en diminuant la demande de trafic. Ces solutions sont longues à mettre en oeuvre et sont très coûteuses. Une solution accessible à plus court terme consiste à mettre en oeuvre un système de gestion du trafic. Dans cette optique, plusieurs actions et mesures de contrôle ont été développées pour améliorer l’efficacité des autoroutes. Parmi ces actions, on peut citer le contrôle d’accès et la limitation dynamique de la vitesse. Le contrôle d’accès consiste en une régulation du flux de véhicules désirant entrer sur une autoroute à partir d’une rampe. Nous avons développé la stratégie DFC (Différence de Flux Caractérisée par une densité désirée). Elle vise à maintenir sur la chaussée principale, au niveau de la rampe d’entrée,une densité inférieure à une cible déterminée au préalable à l’aide de simulations. Cette nouvelle stratégie a été comparée aux stratégies existantes telles que ALINEA et PI-ALINEA. La stratégie DFC présente l’intérêt de ne pas générer de phénomènes oscillatoires dans les trajectoires du flux et de ne pas nécessiter de paramètres à régler. La limitation dynamique de la vitesse impose sur plusieurs tronçons de la chaussée principale une limitation de vitesse qui dépend des conditions de circulation. L’objectif est d’éviter la congestion au niveau d’un goulot d’étranglement qui se trouve en aval. Nous avons proposé plusieurs stratégies de limitation dynamique de la vitesse. Elles utilisent toutes le modèle de trafic METANET. Deux des méthodes proposées exploitent le terme d’anticipation du modèle METANET et la troisième est basée sur le flux. Enfin, les différentes stratégies de limitation dynamique de la vitesse ont été utilisées en coordinationavec le contrôle d’accès DFC. La coordination permet d’obtenir des résultats meilleurs qu’un contrôle d’accès utilisé seul ou une limitation dynamique de la vitesse utilisée seule. / The highways congestion is a problem which appears in a recurring way and which has a wide economic, environmental and social impact. This problem can be resolved by increasing the highways capacity or by decreasing the traffic demand. These solutions are long to operate and are very expensive. An accessible solution in the shorter run consists in implementing a traffic management system.In this optics, several actions and control measures were developed to improve the efficiency of highways. Among these actions, we can quote the ramp metering control and the dynamic speed limits.The ramp metering consists of a regulation of the vehicles flow wishing to enter on a highway from an on-ramp. We developed the DFC strategy (Différence de Flux Characterisée par une densité désirée). It aims at maintaining on the main road, at the vicinity of the on-ramp, a density lower than a target beforehand determined by means of simulations. This new strategy was compared with the existing strategies such as ALINEA and PI-ALINEA. The DFC strategy presents the interest not to generate oscillatory phenomena in the trajectories of flow and not to require parameters to be adjusted. The dynamic speed limits imposes on several sections of the main road a speed limit which depends on traffic conditions. The objective is to avoid the congestion at a downstream bottleneck. We proposed several strategies of dynamic speed limits. They use quite the METANET model of traffic. Two of the proposed methods exploit the model METANET anticipation term and the third is based on the flow. Finally, the various strategies of dynamic speed limits were used in coordination with the DFC ramp metering. The coordination allows to obtain the results better than ramp metering used only or dynamic speed limits used only.