Measuring the Quality of Arterial Traffic Signal Timing – A Trajectory-based Methodology

Evaluating the benefits from traffic signal timing is of increasing interest to transportation policymakers, operators, and the public as integrating performance measurements with agencies’ daily signal timing management has become a top priority. This dissertation presents a trajectory-based methodology for evaluating the quality of arterial signal timing, a critical part of signal operations that promises reduced travel time and fewer vehicle stops along arterials as well as improved travelers’ perception of transportation services. The proposed methodology could significantly contribute to performance-oriented signal timing practices by addressing challenges regarding which performance measures should be selected, how performance measurements can be performed cost-effectively, and how to make performance measures accessible to people with limited knowledge of traffic engineering. A review of the current state of practice and research was conducted first, indicating an urgent research need for developing an arterial-level methodology for signal timing performance assessments as the established techniques are mostly based on by-link or by-movement metrics. The literature review also revealed deficiencies of existing performance measures pertaining to traffic signal timing. Accordingly, travel-run speed and stop characteristics, which can be extracted from vehicle GPS trajectories, were selected to measure the quality of arterial signal timing in this research.Two performance measures were then defined based on speed and stop characteristics: the attainability of ideal progression (AIP) and the attainability of user satisfaction (AUS). In order to determine AIP and AUS, a series of investigations and surveys were conducted to characterize the effects of non-signal-timing-related factors (e.g., arterial congestion level) on average travel speed as well as how stops may affect travelers’ perceived quality of signal timing. AIP was calculated considering the effects of non-signal-timing-related factors, and AUS accounted for the changes in the perceived quality of signal timing due to various stop circumstances.Based upon AIP and AUS, a grade-based performance measurement methodology was developed. The methodology included AIP scoring, AUS scoring, and two scoring adjustments. The two types of scoring adjustments further improved the performance measurement results considering factors such as cross-street delay, pedestrian delays, and arterial geometry. Furthermore, the research outlined the process for implementing the proposed methodology, including the necessary data collection and the preliminary examination of the applicable conditions. Case studies based on real-world signal re-timing projects were presented to demonstrate the effectiveness of the proposed methodology in enhancing agencies’ capabilities of cost-effectively monitoring the quality of arterial signal timing, actively addressing signal timing issues, and reporting the progress and outcomes in a concise and intuitive manner

Modelação interpretativa da segurança e emissões em corredores de rotundas e semáforos

Scientific research has demonstrated that the operational, environmental and safety performance for pedestrians depend on the geometric and traffic stream characteristics of the roundabout. However, the implementation of roundabouts may result in a trade-off among capacity, environmental, and safety variables. Also, little is known about the potential impacts for traffic from the use of functionally interdependent roundabouts in series along corridors. Thus, this doctoral thesis stresses the importance of understanding in how roundabout corridors affect traffic performance, vehicular emissions and safety for vulnerable users as pedestrians. The development of a methodology capable of integrating corridor’s geometric and operational elements is a contribution of this work. The main objectives of the thesis are as follows: 1) to analyze the effect of corridor’s design features in the acceleration patterns and emissions; 2) to understand the differences in the spatial distribution of emissions between roundabouts in isolation and along corridors; 3) to compare corridors with different forms of intersections such as conventional roundabouts, turbo-roundabouts, traffic lights and stop-controlled intersections; and 4) to design corridor-specific characteristics to optimize vehicle delay, and global (carbon dioxide – CO2) and local (carbon monoxide – CO, nitrogen oxides – NOX and hydrocarbons – HC) pollutant emissions. Vehicle dynamics along with traffic and pedestrian flow data were collected from 12 corridors with conventional roundabouts located in Portugal, Spain and in the United States, 3 turbo-roundabout corridors in the Netherlands, and 1 mixed roundabout/traffic-lights/stop-controlled corridor in Portugal. Data for approximately 2,000 km of road coverage over the course of 50 h have been collected. Subsequently, a microscopic platform of traffic (VISSIM), emissions (Vehicle Specific Power – VSP) and safety (Surrogate Safety Assessment Model – SSAM) was introduced to faithful reproduce site-specific operations and to examine different alternative scenarios. The main research findings showed that the spacing between intersections influenced vehicles acceleration-deceleration patterns and emissions. In contrast, the deflection angle at the entrances (element that impacts emissions on isolated roundabouts) impacted slightly on the spatial distribution of emissions. It was also found that the optimal crosswalk locations along mid-block sections in roundabout corridor was generally controlled by spacing, especially in the case of short spacing between intersections (< 200 m). The implementation of turbo-roundabout in series along corridors increased emissions compared to conventional two-lane roundabout corridors (1-5%, depending on the pollutant). By changing the location of a roundabout or turbo-roundabout to increase spacing in relation to upstream/downstream intersection resulted in an improvement of corridor emissions. Under conditions of high through traffic and unbalanced traffic flows between main roads and minor roads, vehicles along roundabout corridors produced fewer emissions (~5%) than did vehicles along signalized corridors, but they emitted more gases (~12%) compared to a corridor with stop-controlled intersections. This research contributed to the current state-of-art by proving a full comprehension about the operational and geometric benefits and limitations of roundabout corridors. It also established correlations between geometric variable of corridors (spacing), crosswalk locations or traffic streams, and delay, and CO2, CO, NOX or HC variables. With this research, it has been demonstrated that the implementation of a given intersection form within a corridor focused on minimizing CO2 may not be translated to other variables such as CO or NOX. Therefore, the develop methodology is a decision supporting tool capable of assessing and selecting suitable traffic controls according the site-specific needs.Estudos anteriores demonstram que os desempenhos operacional, ambiental e ao nível da segurança para os peões de uma rotunda dependem das suas características geométricas e dos fluxos de tráfego e de peões. Porém, a implementação de uma rotunda pode traduzir-se numa avaliação de compromisso entre as variáveis da capacidade, emissões de poluentes e segurança. Para além disso, a informação relativa às potencialidades de rotundas interdependentes ao longo de corredores é diminuta. Assim, esta tese de doutoramento centra-se na compreensão dos impactos no desempenho do tráfego, emissões e segurança dos peões inerentes ao funcionamento de corredores de rotundas. Uma das contribuições deste trabalho é o desenvolvimento de uma metodologia capaz de avaliar as características geométricas e operacionais dos corredores de forma integrada. Os principais objetivos desta tese são: 1) analisar o impacto dos elementos geométricos dos corredores de rotundas em termos dos perfis de aceleração e das emissões; 2) investigar as principais diferenças na distribuição espacial das emissões entre rotundas isoladas e em corredores; 3) comparar os desempenhos operacional e ambiental de corredores com diferentes tipos de interseções tais como rotundas convencionais, turbo-rotundas, cruzamentos semaforizados e interseções prioritárias; e 4) dimensionar um corredor de modo a otimizar o atraso dos veículos, e emissões de poluentes globais (dióxido de carbono – CO2) e locais (monóxido de carbono – CO, óxidos de azoto – NOx e hidrocarbonetos – HC). O trabalho de monitorização experimental consistiu na recolha de dados da dinâmica do veículo, e volumes de tráfego e pedonais. Para tal, foram selecionados 12 corredores com rotundas convencionais em Portugal, Espanha e Estados Unidos da América, 3 corredores com turbo-rotundas na Holanda e ainda um corredor misto com rotundas, sinais luminosos e interseções prioritárias em Portugal. No total foram recolhidos aproximadamente 2000 km de dados da dinâmica do veículo, num total de 50 h. Foi utilizada uma plataforma de modelação microscópica de tráfego (VISSIM), emissões (Vehicle Specific Power – VSP) e segurança (Surrogate Safety Assessment Model – SSAM) de modo a replicar as condições de tráfego locais e avaliar cenários alternativos. Os resultados mostraram que o espaçamento entre interseções teve um impacto significativo nos perfis de aceleração e emissões. No entanto, tal não se verificou para o ângulo de deflexão de entrada (elemento fulcral nos níveis de emissões em rotundas isoladas), nomeadamente nos casos em que as rotundas adjacentes estavam próximas (< 200 m). A implementação de corredores de turbo-rotundas conduziu ao aumento das emissões face a um corredor convencional de rotundas com duas vias (1-5%, dependendo do poluente). A relocalização de uma rotunda ou turbo-rotunda no interior do corredor, de modo a aumentar o espaçamento em relação a uma interseção a jusante e/ou a montante, levou a uma melhoria das emissões do corredor. Conclui-se também que em condições de elevado tráfego de atravessamento e não uniformemente distribuído entre as vias principais e secundárias, os veículos ao longo de um corredor com rotundas produziram menos emissões (~5%) face a um corredor com semáforos, mas emitiram mais gases (~12%) comparativamente a um corredor de interseções prioritárias. Esta investigação contribuiu para o estado de arte através da análise detalhada dos benefícios e limitações dos corredores de rotundas tanto ao nível geométrico como ao nível operacional. Adicionalmente, estabeleceram-se várias correlações entre variáveis geométricas do corredor (espaçamento), localização das passadeiras e volume de tráfego, o atraso, e emissões de CO2, CO, NOX e HC. Demonstrou-se ainda que a implementação de uma interseção ao longo do corredor com a finalidade de minimizar o CO2 pode não resultar na melhoria de outras variáveis tais como o CO ou NOX. Esta metodologia serve como apoio à decisão e, portanto, permite avaliar o tipo de interseção mais adequado de acordo com as especificidades de cada local.Programa Doutoral em Engenharia Mecânic

What Is an Effective Way to Measure Arterial Demand When It Exceeds Capacity?

This project focused on developing and evaluating methods for estimating demand volume for oversaturated corridors. Measuring demand directly with vehicle sensors is not possible when demand is larger than capacity for an extended period, as the queue grows beyond the sensor, and the flow measurements at a given point cannot exceed the capacity of the section. The main objective of the study was to identify and develop methods that could be implemented in practice based on readily available data. To this end, two methods were proposed: an innovative method based on shockwave theory; and the volume delay function adapted from the Highway Capacity Manual. Both methods primarily rely on probe vehicle speeds (e.g., from INRIX) as the input data and the capacity of the segment or bottleneck being analyzed. The proposed methods were tested with simulation data and validated based on volume data from the field. The results show both methods are effective for estimating the demand volume and produce less than 4% error when tested with field data

Real-time Queue Length Estimation Applying Shockwave Theory at Urban Signalized Intersections

Signal control is a basic need for urban traffic control; however, it is a very rough intervention in the free flow of traffic, which often results in queues in front of signal heads. The general goal is to reduce the delays caused, and to plan efficient traffic management on the network. For this, the exact knowledge of queue lengths on links is one of crucial importance. This article presents a link-based methodology for real-time queue length estimation in urban signalized road networks. The model uses a Kalman Filter-based recursive method and estimates the length of the queue in every cycle. The input of the filter, i.e. the dynamics of queue length is described by the traffic shockwave theory and the store and forward model. The method requires one loop-detector per link placed at the appropriate position, for which the article also provides suggestions

Evaluation of Safety and Mobility Benefits of Connected and Automated Vehicles by Considering V2X Technologies

The recent development in communication technologies facilitates the deployment of connected and automated vehicles (CAV) which are expected to change the future transportation system. CAV technologies enable vehicles to communicate with other vehicles through vehicle-to-vehicle (V2V) communications and the infrastructure through Vehicle-to-infrastructure (V2I) communications. Since the real-world CAV data is not currently available as of today, simulation is the most commonly used platform to evaluate the future V2X system. Although several studies evaluated the effectiveness of CAVs in a small roadway network, there is a lack of studies analyzing the impact of CAVs at the network level by considering both freeways and arterials. Also, none of the previous studies have attempted to differentiate the benefits of CAVs over only automated vehicles (AVs) by incorporating multiple preceding vehicles\u27 information (i.e., acceleration, position, etc.). On the other hand, most of the simulation-based studies assumed the uninterrupted communication between vehicles in the CAV environment which might not be feasible in reality. Hence, there is still a research gap that exists for which this study tried to fill this gap. Therefore, this study developed a calibrated and validated large-scale network for the deployment of CAV technologies by utilizing Dynamic Traffic Assignment (DTA) model in Orlando metropolitan area, Florida, using Multi-Resolution Modeling (MRM) technique. Also, the study proposed a signal control algorithm through V2I technology in order to elevate the performance of CAVs at intersections. Different car-following models were utilized to approximate different CAV technologies (CAV, AV, and CV (connected vehicle)) in the simulation environment. Hence, the study analyzed the benefits of CAV over AV with different market penetration rates (MPRs). Furthermore, the study considered the performance of different communication system along with the traffic condition by utilizing Dedicated Short-Range Communications (DSRC or IEEE 802.11p) and wireless access (IEEE 1609 protocol) for the application of vehicle ad-hoc network (VANET). To this end, the study evaluated the safety effectiveness of different communication protocols under the CAV environment. Aimsun Next and SUMO & OMNET++ based Veins simulator were used as the simulation platform. Different car-following models, signal control algorithm, and communication systems were coded by using the application programming interface (API) and C++ language. For the traffic efficiency, the study utilized travel time and travel time rate (TTR) while for the safety evaluation, different surrogate safety measures; speed, and crash-risk models were used. Also, several statistical tests (e.g., t-test, ANOVA) and modeling techniques (e.g., generalized estimating equation, logistic regression, etc.) were developed to analyze both safety and mobility. The results of this study implied that CAV could improve both safety and efficiency at the network level with different MPRs. Also, CAV is more efficient compared to the only AV in terms of both traffic safety and mobility. Different communication protocols have a significant effect on traffic safety under the CAV environment. Finally, the results of this study provide insight to transportation planners and the decision makers about the benefits of CAV at the network level, different CAV technologies, and the performance of different communication systems under the CAV environment

Data Support of Advanced Traveler Information System Considering Connected Vehicle Technology

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

Performing Short-Term Travel Time Prediction on Arterials

As urban centers become larger and more densely developed, their roadway networks tend to experience more severe congestion for longer periods of the day and increasingly unreliable travel times. Proactive traffic management (PTM) strategies such as proactive traffic signal control systems and advanced traveler information systems provide the potential to cost effectively improve road network operations. However, these proactive management strategies require an ability to accurately predict near-future traffic conditions. Traffic conditions can be described using a variety of measures of performance and travel time is one of the most valued by both travelers and transportation system managers. Consequently, there exists a large body of literature dedicated to methods for performing travel time prediction. The majority of the existing body of research on travel time prediction has focused on freeway travel time prediction using fixed point sensor data. Predicting travel times on signalized arterials is more challenging than on freeways mainly as a result of the higher variation of travel times in these environments. For both freeways and arterial environments, making predictions in real-time is more challenging than performing off-line predictions, mainly because of data availability issues that arise for real-time applications. Recently, Bluetooth detectors have been utilized for collecting both spatial (i.e. travel time) and fixed point (e.g. number of detections) data. Bluetooth detectors have surpassed most of the conventional travel time measuring techniques in three main capacities: (i) direct measurement of travel time, (ii) continuous collection of travel times provides large samples, and (iii) anonymous detection. Beside these advantages, there are also caveats when using these detectors: (i) the Bluetooth obtained data include different sources of outliers and measurement errors that should be filtered out before the data are used in any travel time analysis and (ii) there is an inherent time lag in acquiring Bluetooth travel times (due to the matching of the detections at the upstream and downstream sensors) that should be carefully handled in real-time applications. In this thesis, (1) the magnitude of Bluetooth travel time measurement error has been examined through a simulation framework; (2) a real-time proactive outlier detection algorithm, which is suitable for filtering out data anomalies in Bluetooth obtained travel times, has been proposed; (3) the performance of the existing real-time outlier detection algorithms has been evaluated using both field data and simulation data; and (4) two different data-driven methodologies, that are appropriate for real-time applications, have been developed to predict near future travel times on arterials using data obtained from Bluetooth detectors. The results of this research demonstrate that (1) although the mean Bluetooth travel time measurement error is sufficiently close to zero across all the examined traffic conditions, for some situations the 95% confidence interval of the mentioned error approaches 35% of the true mean travel time; (2) the proposed proactive filtering algorithm appropriately detects the Bluetooth travel time outliers in real time and outperforms the existing data-driven filtering techniques; (3) the performance of different outlier detection algorithms can be objectively quantified under different conditions using the developed simulation framework; (4) the proposed prediction approaches significantly improved the accuracy of travel time predictions for 5-minutre prediction horizon. The daily mean absolute relative errors are improved by 18% to 24% for the proposed k-NN model and 8% to 14% for the proposed Markov model; (5) prevailing arterial traffic state and its transition through the course of the day can be adequately modeled using data obtained from Bluetooth technology

Real-Time Traffic Performance Measurement of Signalized Intersections Using Connected Vehicle Data: A Simulation-Based Study

Traffic congestion has long become a major concern in many cities in Canada and around the world. It has been estimated that the annual total economic loss due to traffic congestion in major Canadian urban centers has reached nearly $4 billion. Real-time monitoring of traffic conditions and measurement of the performance of the underlying traffic management systems is a critical requirement for mitigating and minimizing the impact of traffic congestion in an urban road network. The latest advance in the Connected Vehicle (CV) technology has afforded a new opportunity for developing solutions that make use of high-resolution trajectory data for real-time urban traffic monitoring and performance measurement, such as Automated Traffic Signal Performance Measures (ATSPM). However, many critical issues still need to be addressed before the potential of CV can be fully realized. For example, in the context of ATSPM, what traffic performance measures could be derived from the CV data? Can non-recurrent congestion be detected in real-time and at what latency? What would be the optimal spatial and temporal data aggregation resolutions of CV data? What would be the effect of the CV market penetration rate on the reliability of specific performance measures? This research attempts to address some of these questions through a simulation study of a real-world signalized urban arterial corridor from Broward County, Florida, US, consisting of 17 signalized intersections with a wide range of layouts and congestion levels. An extensive set of simulation experiments have been conducted under a range of scenarios varying by facility types (single intersection vs. corridor), congestion level (from undersaturated to oversaturated), CV market penetration rates (1%-25%), and signal timing plans. Under each scenario, samples of vehicles at specific market penetration rates are randomly drawn from the simulated traffic population to represent the CVs and their trajectory data are used to calculate various signal performance measures, including average overall delay, percentile queue length, percentage of stopped vehicles and an average number of stops, at the spatial aggregation levels of movements, approaches, intersections, and corridor. A sensitivity analysis is subsequently conducted to assess the accuracy and reliability of the performance measures derived from CV data as related to some specific external conditions and factors. The results from the simulation experiments have underscored the significant potential of CV data, even under the current relatively low market penetration rate, for estimating various important traffic performance measures and detecting non-recurrent events or bottlenecks - a basic requirement for implementing ATSPM

Safety and Operational Impact of Truck Platooning on Geometric Design Parameters

The most well-known benefits of heavy commercial vehicle (HCV) platooning are fuel savings and emission reductions. HCV platooning under SAE automation level 4 or 5 would also address the truck driver shortage by eliminating the driver from one or more HCVs in a platoon. This dissertation investigates the safety and operational implications of SAE level 4 HCV platooning on North American roadways. The research develops modified analytical models and micro-simulation models (PTV VISSIM) for analyzing impacts on two-lane rural highways, urban arterial roadways, and freeways. The study considers different time headways (0.6 sec and 1.2 sec) between the platooning vehicles, and three market penetration rates (0%, 5%, and 10%). The two-lane rural highways chapter investigates the passing sight distance (PSD) required to overtake an HCV platoon. The urban arterial roadways chapter compares existing traffic controls with traffic signal priority (TSP) for HCV platoons. The freeways chapter investigates freeway acceleration lane length on merging segments for HCV platooning operations. The findings suggest that two-HCV platooning with 0.6 sec time headway and a 5% market penetration rate can be allowed on designated North American roadways. With proper passing lanes, two-HCV platoons can be operated on two-lane rural highways that already permit long combination vehicle operations. Even with TSP, HCV platooning on urban arterial roadways at penetration rates higher than 5% at our selected intersection may, however, cause significant delays and overwhelm the traffic system. On freeways, two-HCV platooning at a 5% market penetration rate where the freeway acceleration lane is at least 600m long appear to be feasible. The study will assist transportation professionals and policymakers in understanding the consequences of HCV platoons and deciding whether to allow HCV platooning on North American roadways