Optimizing Traffic Signal Timings for Mega Events

Most approaches for optimizing traffic signal timings deal with the daily traffic. However, there are a few occasional events like football matches or concerts of musicians that lead to exceptional traffic situations. Still, such events occur more or less regularly and place and time are known in advance. Hence, it is possible to anticipate such events with special signal timings. In this paper, we present an extension of a cyclically time-expanded network flow model and a corresponding mixed-integer linear programming formulation for simultaneously optimizing traffic signal timings and traffic assignment for such events. Besides the mathematical analysis of this approach, we demonstrate its capabilities by computing signal timings for a real world scenario

Optimization and simulation of fixed-time traffic signal control in real-world applications

This paper contributes to the question how to optimize fixed-time traffic signal coordinations for real-world applications. Therefore, two models are combined: An analytically model that optimizes fixed-time plans based on a cyclically time-expanded network formulation, and a coevolutionary transport simulation that is able to evaluate the optimized fixed-time plans for large-scale realistic traffic situations. The coupling process of both models is discussed and applied to a real-world scenario. Steps that were necessary to align the models and improve the results are presented. The optimized fixed-time signals are compared to other signal approaches in the application. It is found, that they also help to improve the performance of actuated signal control

RITThe Contributions of Traffic Management Centers in life Enhancement

This study focuses on investigating the contributions of traffic management centers to enhancing people’s driving experiences and impacting their level of satisfaction and happiness. Data was collected in the United Arab Emirates through two distinct surveys; the first aimed at drivers (number of respondents: 155), and the second aimed at traffic management center operators (number of respondents: 15). The drivers survey aimed to collect data about drivers’ pain points experienced while driving in the United Arab Emirates and showed that slow drivers on fast lanes and sudden lane changing are the biggest challenges reported. On the operators’ side, the data collected showed that operators reported observing these challenges from their side as well. Operators also notably reported the need for advanced technology to help better manage and respond to real time traffic situations remotely from traffic management centers. Both surveys conducted showed a need and potential for the contributions of traffic management centers in enhancing and upgrading the quality of life for citizens through the application of technological solutions and the development of supporting legislation. Supplementary data from similar surveys was also used to validate, expand the knowledge and provide a holistic view of the topic. The study indicated that traffic management centers can impact the happiness and satisfaction of citizens by enhancing their driving experience, given that they are designed and equipped in a way that suits the city and society trends and cultures. Recommendations for implementation of such design choices were given along five pillars considering administration (based on best practice and Benchmarking), technology (results of local and international TMC surveys), media and communication (international survey and the expansion of technology and social media), operations and legislation (Based on results of the driver’s survey, that shows some gaps in the legislations which can be enhanced)

Optimizing Traffic Signal Settings for Public Transport Priority

In order to promote public transport many municipalities use traffic signal control with a priority for buses or trams. In this paper, we address the problem of finding optimal passive transit signal priority settings. Building on a cyclically time-expanded network model for the combined traffic assignment traffic signal coordination problem, we introduce a suitable queuing model and several modifications to model public transport vehicles appropriately. We evaluate the applicability of this approach by computing and analyzing optimal solutions for several instances of a real-world scenario

Simulation of the Impact of Connected and Automated Vehicles at a Signalized Intersection

Intersections are locations with higher likelihood of crash occurences and sources of traffic congestion as they act as bottlenecks compared with other parts of the roadway networks. Consequently, connected and automated vehicles (CAVs) can help to improve the efficiency of the roadways by reducing traffic congestion and traffic delays. Since CAVs are expected to take control from drivers (human control) in making many important decisions, thus they are expected to minimize driver (human) errors in driving tasks. Therefore, CAVs potential benefits of eliminating driver error include an increase in safety (crash reduction), smooth vehicle flow to reduce emissions, and reduce congestion in all roadway networks. Since CAV implementations are currently in early stages, researchers have found that the use of traffic modeling and simulation can assist decision makers by quantifying the impact of increasing levels of CAVs, helping to identify the effect this will have on future transportation facilities. The main objective of the current study was to simulate the potential impacts CAVs may have on traffic flow and delay at a typical urban signalized intersection. Essentially, to use a microscopic traffic simulation software to test future CAV technology within a virtual environment, by testing different levels of CAVs with their associated behaviors across several scenarios simulated. This study tested and simulated the impact of CAVs compared with conventional vehicles at a signalized intersection. Specifically, I analyzed and compared the operations of the signalized intersection when there are only conventional vehicles, conventional vehicles mixed with CAVs, and when there are only CAVs

A Microscopic Simulation Study of Applications of Signal Phasing and Timing Information in a Connected Vehicle Environment

The connected vehicle technology presents an innovative way of sharing information between vehicles and the transportation infrastructure through wireless communications. The technology can potentially solve safety, mobility, and environmental challenges that face the transportation sector. Signal phasing and timing information is one category of information that can be broadcasted through connected vehicle technology. This thesis presents an in-depth study of possible ways signal phasing and timing information can be beneficial as far as safety and mobility are concerned. In total, three studies describing this research are outlined. The first study presented herein focuses on data collection and calibration efforts of the simulation model that was used for the next two studies. The study demonstrated a genetic algorithm procedure for calibrating VISSIM discharge headways based on queue discharge headways measured in the field. Video data was used to first compute intersection discharge headways for individual vehicle queue position and then to develop statistical distributions of discharge headways for each vehicle position. Except for the 4th vehicle position, which was best fitted by the generalized extreme value (GEV) distribution, the Log-logistic distribution was observed to be the best fit distribution for the rest of vehicle positions. Starting with the default values, the VISSIM parameters responsible for determining discharge headways were heuristically adjusted to produce optimal values. The optimal solutions were achieved by minimizing the Root Mean Square Error (RMSE) between the simulated and observed data. Through calibration, for each vehicle position, it was possible to obtain the simulated headways that reflect the means of the observed field headways. However, calibration was unable to replicate the dispersion of the headways observed in the field mainly due to VISSIM limitations. Based on the findings of this study, future work on calibration in VISSIM that would account for the dispersion of mixed traffic flow characteristics is warranted. The second study addresses the potential of connected vehicles in improving safety at the vicinity of signalized intersections. Although traffic signals are installed to reduce the overall number of collisions at intersections, rear-end collisions are increased due to signalization. One dominant factor associated with rear-end crashes is the indecisiveness of the driver, especially in the dilemma zone. An advisory system to help the driver make the stop-or-pass decision would greatly improve intersection safety. This study proposed and evaluated an Advanced Stop Assist System (ASAS) at signalized intersections by using Infrastructure-to-Vehicle (I2V) and Vehicle-to-Vehicle (V2V) communication. The proposed system utilizes communication data, received from Roadside Unit (RSU), to provide drivers in approaching vehicles with vehicle-specific advisory speed messages to prevent vehicle hard-braking upon a yellow and red signal indication. A simulation test bed was modeled using VISSIM to evaluate the effectiveness of the proposed system. The results demonstrate that at full market penetration (100% saturation of vehicles equipped with on-board communication equipment), the proposed system reduces the number of hard-braking vehicles by nearly 50%. Sensitivity analyses of market penetration rates also show a degradation in safety conditions at penetration rates lower than 40%. The results suggest that at least 60% penetration rate is required for the proposed system to minimize rear-end collisions and improve safety at the signalized intersections. The last study addresses the fact that achieving smooth urban traffic flow requires reduction of excessive stop-and-go driving on urban arterials. Smooth traffic flow comes with several benefits including reduction of fuel consumption and emissions. Recently, more research efforts have been directed towards reduction of vehicle emissions. One such effort is the use of Green Light Optimal Speed Advisory (GLOSA) systems which use wireless communications to provide individual drivers with information on the approaching traffic signal phase and advisory speeds to arrive at the intersection on a green phase. Previously developed GLOSA algorithms do not address the impact of time to discharge queues formed at the intersection. Thus, this study investigated the influence of formed intersection queues on the performance of GLOSA systems. A simulation test-bed was modeled inside VISSIM to evaluate the algorithm’s effectiveness. Three simulation scenarios were designed; the baseline with no GLOSA in place, scenario 2 with GLOSA activated and queue discharge time not considered, and scenario 3 with GLOSA activated and where queue dissipation time was used to compute advisory speeds. At confidence level the results show a significant reduction in the time spent in queue when GLOSA is activated (scenarios 2 and 3). The change in the average number of stops along the corridor was found not to be significant when the base scenario was compared against scenario 2. However, a comparison between scenarios 2 and 3 demonstrates a significant reduction in the average number of stops along the corridor, and also in the time spent waiting in queue

A Multifaceted Look at Starlink Performance

In recent years, Low-Earth Orbit (LEO) mega-constellations have emerged as a promising network technology and have ushered in a new era for democratizing Internet access. The Starlink network from SpaceX stands out as the only consumer-facing LEO network with over 2M+ customers and more than 4000 operational satellites. In this paper, we conduct the first-of-its-kind extensive multi-faceted analysis of Starlink network performance leveraging several measurement sources. First, based on 19.2M crowdsourced M-Lab speed test measurements from 34 countries since 2021, we analyze Starlink global performance relative to terrestrial cellular networks. Second, we examine Starlink's ability to support real-time web-based latency and bandwidth-critical applications by analyzing the performance of (i) Zoom video conferencing, and (ii) Luna cloud gaming, comparing it to 5G and terrestrial fiber. Third, we orchestrate targeted measurements from Starlink-enabled RIPE Atlas probes to shed light on the last-mile Starlink access and other factors affecting its performance globally. Finally, we conduct controlled experiments from Starlink dishes in two countries and analyze the impact of globally synchronized "15-second reconfiguration intervals" of the links that cause substantial latency and throughput variations. Our unique analysis provides revealing insights on global Starlink functionality and paints the most comprehensive picture of the LEO network's operation to date.Comment: In submissio

Diesel low temperature combustion: an experimental study

Diesel engine emissions of oxides of nitrogen and particulate matter can be reduced simultaneously through the use of high levels of exhaust gas recirculation (EGR) to achieve low temperature combustion (LTC). Although the potential benefits of diesel LTC are clear, the main challenges to its practical implementation are the requirement of EGR levels that can exceed 60%, high fuel consumption, and high unburned hydrocarbon and carbon monoxide emissions. These limit the application of LTC to medium loads. In order to implement the LTC strategy in a passenger vehicle engine, a transition to conventional diesel operation is required to satisfy the expected high load demands on the engine. The investigation presented in this thesis was therefore aimed at improving the viability of the high-EGR LTC strategy for steady-state and transient operation. An experimental investigation was carried out on a single cylinder high-speed direct injection diesel engine. This thesis presents research on engine in-cylinder performance and engine-out gaseous and particulate emissions at operating conditions (i.e. EGR rate, intake pressure, fuel quantity, injection pressure) likely to be encountered by an engine during transient and steady-state operation. At selected operating points, further investigation in terms of in-cylinder spray and combustion visualization, flame temperature and soot concentration measurements provided deeper insight into the combustion and emissions phenomena. Increased intake pressure at single injection high-EGR LTC operation was investigated as a strategy to reduce the emissions of partial combustion by-products and to improve fuel economy. The higher intake pressure, although effective in reducing partial combustion by-products emissions and improving fuel economy, increased the EGR requirement to achieve LTC. A split fuel injection strategy with advanced injection timing on the other hand was effective in reducing the EGR requirement for LTC from 62% with single injection to 52% with split injections at 120 kPa (absolute) intake pressure. Unburned hydrocarbon emissions and fuel economy were particularly sensitive to intake oxygen mass fraction, and injection and dwell timings with the split injection strategy. In-cylinder soot formation and oxidation mechanisms with the split injection strategy were found to be significantly different from the single injection high-EGR LTC case. Transient simulation of an engine during combustion mode transition identified engine operating parameters on a cycle-by-cycle basis. Steady-state investigation of these test conditions provided significant insight into the combustion conditions and their effect on emissions and performance. The results from this thesis demonstrated the importance of optimizing both the air handling system performance and the fuel injection system during engine transients. The increased emissions and impaired performance due to slow response of the EGR and turbocharger systems during transitions to and from LTC modes can in part be mitigated through split injections optimized for the specific transient point. This provides a clear direction for engine developers to pursue in optimizing engine calibration when running with LTC-conventional diesel dual-mode strategies

High-Performance DRAM System Design Constraints and Considerations

The effects of a realistic memory system have not received much attention in recent decades. Often, the memory controller and DRAMs are modeled as a fixed-latency or random-latency system, which leads to simulations that are less accurate. As more cores are added to each die and CPU clock rates continue to outpace memory access times, the gap will only grow wider and simulation results will be less accurate. This thesis proposes to look at the way a memory controller and DRAM system work and attempt to model them accurately in a simulator. It will use a simulated Alpha 21264 processor in conjunction with a full system simulator and memory system simulator. Various SPEC06 benchmarks are used to look at runtimes. The process of mapping a memory location to a physical location, the algorithm for choosing the ordering of commands to be sent to the DRAMs and the method of managing the row buffers are examined in detail. We find that the choice in these algorithms and policies can affect application runtime by up to 200% or more. It is also shown that energy use can vary by up to 300% by changing changing the address mapping policy. These results show that it is important to look at all the available policies to optimize the memory system for the type of workload that a machine will be running. No single policy is best for every application, so it is important to understand the interaction of the application and the memory system to improve performance and reduce the energy consumed

Private 5G and its Suitability for Industrial Networking

5G was and is still surrounded by many promises and buzzwords, such as the famous 1 ms, real-time, and Ultra-Reliable and Low-Latency Communications (URLLC). This was partly intended to get the attention of vertical industries to become new customers for mobile networks, which shall be deployed in their factories. With the allowance of federal agencies, companies deployed their own private 5G networks to test new use cases enabled by 5G. But what has been missing, apart from all the marketing, is the knowledge of what 5G can really do? Private 5G networks are envisioned to enable new use cases with strict latency requirements, such as robot control. This work has examined in great detail the capabilities of the current 5G Release 15 as private network, and in particular its suitability with regard to time-critical communications. For that, a testbed was designed to measure One-Way Delays (OWDs) and Round-Trip Times (RTTs) with high accuracy. The measurements were conducted in 5G Non-Standalone (NSA) and Standalone (SA) net-works and are the first published results. The evaluation revealed results that were not obvious or identified by previous work. For example, a strong impact of the packet rate on the resulting OWD and RTT was found. It was also found that typically 95% of the SA downlink end-to-end packet delays are in the range of 4 ms to 10 ms, indicating a fairly wide spread of packet delays, with the Inter-Packet Delay Variation (IPDV) between consecutive packets distributed in the millisecond range. Surprisingly, it also seems to matter for the RTT from which direction, i.e. Downlink (DL) or Uplink (UL), a round-trip communication was initiated. Another important factor plays especially the Inter-Arrival Time (IAT) of packets on the RTT distribution. These examples from the results found demonstrate the need to critically examine 5G and any successors in terms of their real-time capabilities. In addition to the end-to-end OWD and RTT, the delays caused by 4G and 5G Core processing has been investigated as well. Current state-of-the-art 4G and 5G Core implementations exhibit long-tailed delay distributions. To overcome such limitations, modern packet processing have been evaluated in terms of their respective tail-latency. The hardware-based solution was able to process packets with deterministic delay, but the software-based solutions also achieved soft real-time results. These results allow the selection of the right technology for use cases depending on their tail-latency requirements. In summary, many insights into the suitability of 5G for time-critical communications were gained from the study of the current 5G Release 15. The measurement framework, analysis methods, and results will inform the further development and refinement of private 5G campus networks for industrial use cases