Arterial traffic signal optimization: a person-based approach

This paper presents a traffic responsive signal control system that optimizes signal settings based on minimization of person delay on arterials. The system's underlying mixed integer linear program minimizes person delay by explicitly accounting for the passenger occupancy of autos and transit vehicles. This way it can provide signal priority to transit vehicles in an efficient way even when they travel in conflicting directions. Furthermore, it recognizes the importance of schedule adherence for reliable transit operations and accounts for it by assigning an additional weighting factor on transit delays. This introduces another criterion for resolving the issue of assigning priority to conflicting transit routes. At the same time, the system maintains auto vehicle progression by introducing the appropriate delays for when interruptions of platoons occur. In addition to the fact that it utilizes readily available technologies to obtain the input for the optimization, the system's feasibility in real-world settings is enhanced by its low computation time. The proposed signal control system was tested on a segment of San Pablo Avenue arterial located in Berkeley, California. The findings have shown the system's capability to outperform static optimal signal settings and have demonstrated its success in reducing person delay for bus and in some cases even auto users

17-11 Evaluation of Transit Priority Treatments in Tennessee

Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

Evaluation of Transit Signal Priority Implementation for Bus Transit along a Major Arterial Using Microsimulation

Transit Signal Priority (TSP) provides preferential treatment for public transit vehicles at signalized intersections when implemented. TSP is usually provided by interrupting the typical signal timings and extending the green or truncating the red for the signal phases that serve transits. This study investigates the impact of implementing a TSP treatment along a major arterial. A microsimulation approach was used to model, assess, and evaluate the potential benefits of implementing this treatment to bus transit vehicles. The network was built in a VISSIM multimodal microsimulation environment to test the traffic network performance with and without priority treatments. The study considered different peak hours for performance assessment. Three transit routes were considered in the microscopic modeling. The results showed a significant benefit of implementing TSP for the transit vehicles. The travel time was reduced by more than 40% in some cases, which can be translated into lower transit delay and more reliable transit service. The results also showed that TSP has a minimal negative effect on the general traffic. In fact, the general traffic along the studied transit routes benefited from the TSP implementation because of the better traffic progression and additional green times. 2018 The Authors. Published by Elsevier B.V.This report was made possible by UREP award (UREP18-054-2-020) from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Calibrating and Evaluating Dynamic Rule-Based Transit-Signal-Priority Control Systems in Urban Traffic Networks

Setting the traffic controller parameters to perform effectively in real-time is a challenging task, and it entails setting several parameters to best suit some predicted traffic conditions. This study presents the framework and method that entail the application of the Response Surface Methodology (RSM) to calibrate the parameters of any control system incorporating advanced traffic management strategies (e.g., the complex integrated traffic control system developed by Ahmed and Hawas). The integrated system is a rule-based heuristic controller that reacts to specific triggering conditions, such as identification of priority transit vehicle, downstream signal congestion, and incidents by penalizing the predefined objective function with a set of parameters corresponding to these conditions. The integrated system provides real time control of actuated signalized intersections with different phase arrangements (split, protected and dual). The premise of the RSM is its ability to handle either single or multiple objective functions; some of which may be contradicting to each other. For instance, maximizing transit trips in a typical transit priority system may affect the overall network travel time. The challenging task is to satisfy the requirements of transit and non-transit vehicles simultaneously. The RSM calibrates the parameters of the integrated system by selecting the values that can produce optimal measures of effectiveness. The control system was calibrated using extensive simulation-based analyses under high and very high traffic demand scenario for the split, protected, and dual control types. A simulation-based approach that entailed the use of the popular TSIS software with code scripts representing the logic of the integrated control system was used. The simulation environment was utilized to generate the data needed to carry on the RSM analysis and calibrate the models. The RSM was used to identify the optimal parameter settings for each control type and traffic demand level. It was also used to determine the most influential parameters on the objective function(s) and to develop models of the significant parameters as well as their interactions on the overall network performance measures. RSM uses the so-called composite desirability value as well as the simultaneous multi-objective desirabilities (e.g., the desirability of maximizing the transit vehicles throughput and minimizing the average vehicular travel time) estimates of the responses to identify the best parameters. This study also demonstrated how to develop “mathematical” models for rough estimation of the performance measures vis-à-vis the various parameter values, including how to validate the optimal settings. The calibrated models are proven to be significant. The optimal parameters of each control type and demand level were also checked for robustness, and whether a universal set of relative parameter values can be used for each control type. For the high traffic demand level, the optimal set of parameters is more robust than those of the very high traffic demand. Besides, the dual actuated controller optimal setting under the very high traffic demand scenario is more robust (than other control types settings) and shows the best performance

Doctor of Philosophy

dissertationTraffic congestion is an increasing problem in most urban areas in the United States. One of the sources of this problem is the automobile-oriented development that encourages automobile use and suppresses other transportation modes. A good transit system can satisfy most of the requirements of a transportation system user. A transit system must be efficient, safe, comfortable, and competitive to private cars in order to attract more riders. Transit Signal Priority (TSP) is an operational strategy that facilitates transit vehicles at signalized intersections. It improves transit efficiency and helps transit offer travel times competitive to private cars. A lot of studies conducted in the past 40 years show the major possibilities and benefits of TSP. The goal of this research is to develop a simulation-based methodology for the evaluation and improvement of TSP strategies. The objectives consist of evaluating existing and future TSP systems, and developing field-ready algorithms that provide adaptive ways for achieving different levels of TSP and improving its operation. The focus of the research is on using traffic microsimulation to evaluate and improve TSP, but it also looks into some field-based implementations and evaluations for additional support. The analysis of different TSP strategies is performed on existing and future rapid transit mode implementations, namely Bus Rapid Transit (BRT) and Light Rail Transit (LRT). The results from the presented studies show the major benefits of TSP implementations for transit operations and small disruptions for vehicular traffic. Depending on the selected strategies and level of TSP, the travel time savings for transit can be between 10% and 30%, the reduction in intersection delay can exceed 60%, while running time reliability and headway adherence are greatly improved. These improvements in transit operations can make transit more efficient and competitive to private cars, justifying the TSP implementation. This research offers significant contributions to the state of TSP practice and research. It provides detailed insights into TSP operations, develops methods for its evaluation, and describes algorithms for achieving different levels of TSP. A significant part of the research is dedicated to the use of Software-in-the-Loop (SIL) traffic controllers in microsimulation. Through this research, SIL is proven to be a powerful tool for simulating complex traffic signal operations and TSP

Arterial traffic signal optimization: a person-based approach

This paper presents a real-time signal control system that optimizes signal settings based on minimization of person delay on arterials. The system’s underlying mixed integer linear program minimizes person delay by explicitly accounting for the passenger occupancy of autos and transit vehicles. This way it can provide signal priority to transit vehicles in an efficient way even when they travel in conflicting directions. Furthermore, it recognizes the importance of schedule adherence for reliable transit operations and accounts for it by assigning an additional weighting factor on transit delays. This introduces another criterion for resolving the issue of assigning priority to conflicting transit routes. At the same time, the system maintains auto vehicle progression by introducing the appropriate delays associated with interruptions of platoons. In addition to the fact that it utilizes readily available technologies to obtain the inputs for the optimization, the system’s feasibility in real-world settings is enhanced by its low computation time. The proposed signal control system is tested on a four-intersection segment of San Pablo Avenue arterial located in Berkeley, California. The findings show the system’s capability to outperform pretimed (i.e., fixed-time) optimal signal settings by reducing total person delay. They have also demonstrated its success in reducing bus person delay by efficiently providing priority to transit vehicles even when they travel in conflicting directions

Regional Data Archiving and Management for Northeast Illinois

This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the regional transportation agencies, from both technical and business perspectives, about building such a comprehensive transportation information system. Several implementation alternatives are identified and analyzed. This research is carried out in three phases. In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect information on all data elements that they store, including the format, system, and granularity. Their perception of a data archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the hardware, software, labor, and resource requirements. We also identify possible revenue opportunities. A few implementation options for the archive system are summarized in this report; namely: 1. System hosted by a partnering agency 2. System contracted to a university 3. System contracted to a national laboratory 4. System outsourced to a service provider The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe

TRA-950: A DYNAMIC PROGRAMMING APPROACH FOR ARTERIAL SIGNAL OPTIMIZATION IN A CONNECTED VEHICLE ENVIRONMENT

Within the Connected Vehicle (CV) environment, vehicles are able to communicate with each other and with infrastructure via wireless communication technology. The collected data from CVs provide a much more complete picture of the arterial traffic states and can be utilized for signal control. Based on the real-time traffic information from CVs, this paper enhances an arterial traffic flow model for arterial signal optimization. Then a dynamic programming optimization model is created to solve the signal optimization application. A real-world arterial corridor is modeled in VISSIM to validate the algorithms. This approach is shown to generate good results and may be superior to well-tuned fixed-time control

Transit Preferential Treatments at Signalized Intersections: Person-based Evaluation and Real-Time Signal Control

Efficient public transportation has the potential to relieve traffic congestion and improve overall transportation system performance. In order to improve transit services, Transit Preferential Treatments (TPT) are often deployed to give transit vehicles priority over other vehicles at an intersection or along a corridor. Examples of such treatments are exclusive bus lanes, queue jumper lanes, and signal priority strategies. The objective of this study is threefold: 1) perform a person-based evaluation of alternative TPTs when considered individually and in combination, 2) develop a bus travel time prediction model along a signalized arterial, and 3) develop a real-time signal control system, which minimizes total person delay at an isolated intersection accounting for stochasticity in transit vehicle arrivals. This study first develops analytical models to estimate person delay and person discharge flow when various spatial and time TPTs are present at signalized intersections with and without near-side bus stops. This part of the research has contributed to the modeling of traffic along signalized arterials by improving the previous models to evaluate various TPT strategies with and without nearside bus stops. Next, a robust method to predict bus travel time along a signalized arterial is developed. This part of the research contributes to the bus travel time prediction models by estimating the status of traffic signals using automated vehicle location (AVL) data. The model decomposes bus travel time along signalized arterials and infers trajectories of the transit vehicles. Finally, the real-time signal control system is developed to provide priority to transit vehicles by assigning weights to transit vehicle delays based on their passenger occupancies as part of the optimization objective function. The system optimizes the movements by minimizing total person delay at the intersection. The system estimates bus arrival time at the intersection stopline and uses the developed analyitical models in the first part of the research to evaluate the person delay measure. This part of the research contributes to the real-time signal control systems by providing a priority window to account for the stochasticity in bus arrival times