Optimisation of Signal Timings in a Road Network (original) (raw)
Related papers
2015
In the ever-growing travel demand, traffic congestion on freeways and expressways recurs more frequently at a higher number of locations and for longer durations with added severity. This becomes especially true in large metropolitan areas. Particular to the urban areas, excessive crowdedness caused by inefficient traffic control also results in urban street networks operating in near or over-saturated conditions, leading to unpleasant travel experience due to long delays at intersections. As a consequence, the recurrent traffic congestion on roadway segments and vehicle delays at intersections inevitably compromise energy efficiency, traffic mobility improvement, safety enhancement, and environmental impacts mitigation. All too often, neither restraining travel demand nor expanding system capacity is desirable and practical. Conversely, effectively utilizing the capacity of the existing transportation system has been increasingly thought of as the solution to congestion relief. Wit...
This study evaluated existing traffic signal optimization programs including Synchro, TRANSYT-7F, and genetic algorithm optimization using real world data collected in Virginia. As a first step, a microscopic simulation model, VISSIM, was extensively calibrated and validated using field data. Multiple simulation runs were then made for signal timing plans such that drivers' behavior, day-to-day traffic variation, etc were considered in the evaluation. Finally, long-term demand growth or changes were statistically modeled and evaluated, again using multiple simulation runs.
Evaluation of a Dynamic Signal Optimisation Control Model Using Traffic Simulation
IATSS Research, 2005
The objective of this paper is to demonstrate the feasibility of implementing a traffic signal optimisation model to improve real-time operations of traffic control systems. Advanced computer algorithms and traffic optimisation techniques can provide benefits over existing systems by reducing delays, improving travel times and reducing environmental emissions. The feasibility of the proposed approach is demonstrated by interfacing the traffic signal optimisation model to a microscopic traffic simulation tool, which enabled the evaluation of the benefits of the algorithm using computers in a controlled environment without disrupting traffic conditions. The main advantage of the proposed algorithm is its ability to detect dynamic changes in traffic flow conditions by using short-term historical demand data obtained from upstream vehicle loop detectors. The experimental results for under-saturated traffic conditions showed that the algorithm's performance was superior to optimal fixed time control. The results also confirmed that as traffic volumes reach saturated conditions, the performance of the algorithm decreased but remained better than what can be achieved by fixed time control systems.
Optimization Using Simulation of Traffic Light Signal Timings
Traffic congestion has become a great challenge and a large burden on both the governments and the citizens in vastly populated cities. The main problem, originally initiated by several factors, continues to threaten the stability of modern cities and the livelihood of its habitants. Hence, improving the control strategies that govern the traffic operations is a powerful solution that can solve the congestion problem. These improvements can be achieved by enhancing the traffic control performance through adjusting the traffic signal timings. This paper focuses on finding various solutions for the addressed problem through the optimization using simulation of traffic signal timings under oversaturated conditions. The system under study is an actual road network in Alexandria, Egypt; where, numerous data have been collected in different time intervals. A series of computer simulation models to represent the actual system as well as proposed solutions have been developed using the ExtendSim simulation environment. Furthermore, an evolutionary optimizer is utilized to attain a set of optimum/near-optimum signal timings to minimize the total time in system of the vehicles, resulting in an improved performance of the road network. Analysis of experimentation results shows that the adopted methodology optimizes the vehicular flow in a multiple-junction urban traffic network.
Arterial traffic signal systems, predominantly in the United States, deploy multiple signal timing plans to account for daily variability of traffic demand. Those types of traffic flow deviations should be anticipated when timing plans are designed and, therefore, serviced satisfactorily. When traffic flow patterns are no longer predictable, a predetermined time-of-day (TOD) plan may no longer be the optimal one. This research aimed to examine signal timing optimality by applying a method similar to the selection of a traffic responsive plan to recognize automatically the best timing plan suited to current traffic conditions. The proposed method attempted to determine whether the optimality of signal timing settings could have been effectively estimated when systematic detector counts of the major approach were available. The study used 4 months of data from field microwave detectors coupled with data of turning-movement counts obtained over several days. The findings show that TOD signal timing plans mainly depended on adequate data collection that best describes a specific set of traffic conditions. Thus, the designed plan was as optimal as the related traffic information was reliable, whereas a problem arose in the case of limited-availability and low-quality data. New technologies are capable of collecting and storing massive amounts of data. Even if the granularity of collected data is low, the data can be used to improve traffic performance (i.e., reduce corridor delay). This realization could be of particular importance to traffic agencies that have installed, or plan to install, new field devices. Most urban traffic signal systems in the United States deploy multiple signal timing plans to account for within-day variability of traffic demand (i.e., morning peak, midday, evening peak, off peak, and nighttime). Signal groups forming a zone or section usually operate in a coordinated manner along an urban arterial. This coordination essentially means that signal timing plans change at the same time for all signals in a given group (zone, section etc.) to facilitate vehicle progression throughout a series of signals (1). Any type of unusual circumstances, such as incidents, construction, or severe weather, causes a significant change in anticipated traffic conditions. Traffic flow patterns are no longer predictable a priori, and a predetermined time-of-day (TOD) plan may substantially underperform under these conditions. In contrast, day-today and diurnal variations in traffic volumes and patterns are typically considered to be served in a satisfactory manner by the developed plans, because these deviations should be anticipated when the plans are originally designed. Traffic responsive plan selection (TRPS) and adaptive traffic control systems designed and deployed over the past several decades were intended to provide quicker response to constantly varying traffic conditions (2). A recent application included development of a real-time weather-responsive signal control (3). These advances attempted to incorporate more robustness into designed signal timing plans. Common existing engineering practice tends to rely on limited observations of relevant traffic patterns and volumes by considering a small data set only over several weekdays. Traffic signal settings (e.g., cycle length, splits, and offsets) are fixed within each TOD period, but traffic demands may still fluctuate significantly. Examining historical volume variations in daily traffic and corresponding responsiveness of the traffic control system can assist traffic engineers in assessing deficiencies in the state of the current traffic system. Well-designed signal control settings reduce delay and unnecessary stops at intersections and thus improve traffic flow without roadway widening. Hence, a key priority for transportation agencies is to ensure demand-suitable traffic signal timings. Yet, despite readily available detector counts, many do not regularly collect, review, or assess the quality of the traffic information they use when signal timings are designed and updated. This study attempts to demonstrate the benefit of using a large set of directional sensor data to estimate day-today variations in demand and proposing a straightforward method to evaluate current performance of TOD signal plans. The proposed approach estimates how the system would perform if it deployed an adaptive-TRPS signal control logic and whether the difference in performance warrants system retiming or upgrade. The practicality of this method is reflected in reducing the time and effort required by the existing signal design-retiming practice. Therefore, the purpose of this research is to devise a methodology to assess the extent to which existing timing plans along an arterial corridor are serving observed demands in a manner that is close to optimal and thereby to provide an upper bound on the potential
Development of an Integrated Microscopic Traffic Simulation and Signal Timing Optimization Tool
2007
A big segment of the traffic signal control systems in California and United States are closed-loop systems. Because wide-scale deployment of advanced adaptive control systems may be many years away due to the associated high costs, there is a significant need to improve the effectiveness of the state-of-the-practice closed-loop systems. To address the need, this project focuses on: 1) developing an integrated microsimulation/signal optimization tool to enhance the capability of generating efficient signal timing plans, and 2) developing a systematic approach to make closed-loop systems be more robust and traffic responsive.
A decomposition approach for signal optimisation in road networks
Transportation Research Part B: Methodological, 1996
The optimisation of signal timings plays an important role in the management of urban traffic, and in the full usage of existing and planned road networks. In recent years, considerable advances have been made in techniques for the optimisation of signal timings at isolated junctions operating under fixed-time control. This paper shows how these techniques can be applied in the optimisation of signal timings in coordinated networks by using a decomposition approach. The signal timings at a junction in a network can be specified fully by the sequence of stages, interstage structures, cycle time, stage durations and offset. Of these variables, the third, fourth and last are endogenous to network optimisation methods, the first and second being exogenous. Techniques have been developed recently to optimise all but the last variable (which is not there defined) at individual junctions, and these have been found to give considerable improvements in operational performance. The computational requirements of these methods is such that their direct extension to networks is not yet a practical proposition. This paper shows how the differences inherent between individual junction and network optimisation methods can be reconciled within a decomposition approach so that the latter can benefit from some of the advantages of the former. A simple example is used to illustrate the substantial benefits that can arise from this approach.
Kocaeli Journal of Science and Engineering
In the traffic network that we frequently use in our daily life, the primary demand of people has been to reduce the time they spend in traffic and to travel to the points they want to reach as quickly as possible. Developing countries want to meet this demand with the least cost in order to meet this demand. This study aims to manage the traffic network with the best times by optimizing the traffic signal durations in order to minimize the travel time for a road network chosen as a benchmark. For the optimization process, it is aimed to run a population-based heuristic algorithm with different numbers of individuals and obtain the best travel time. With the help of an open-source code traffic simulation program, which was run by modeling the benchmark road network, the received traffic data was also visually analyzed and compared. The effects of the heuristic algorithms applied with different numbers of individuals on the travel times according to the starting-destination points we...
Optimization of Traffic Signal Light Timing Using Simulation
Proceedings of the 2004 Winter Simulation Conference, 2004., 2004
Traffic congestion is one of the worst problems in many countries. Traffic congestion wastes a huge portion of the national income for fuel and traffic-related environmental and socioeconomic problems. Computer simulation is a powerful tool for analyzing complex and dynamic scenarios. It provides an appealing approach to analyze repetitive processes. Simulation helps decision makers identify different possible options by analyzing enormous amounts of data. Hence, computer simulation can be used effectively to analyze traffic flow patterns and signal light timing. This paper discusses a special-purpose simulation (SPS) tool for optimize traffic signal light timing. The simulation model is capable of optimizing signal light timing at a single junction as well as an actual road network with multiple junctions. It also provides signal light timing for certain time periods according to traffic demand. Traffic engineers at the University of Moratuwa, Sri Lanka are testing the developed tool for actual applications.