Traffic modeling software for IVHS applications

Intelligent Vehicle-Highway Systems (IVHS) is a major U.S. Department of Transportation initiative to improve the safety and efficiency of our nation's highways. IVHS includes five related components: Advanced Traffic Management Systems (ATMS); Advanced Traveler Information Systems (ATIS); Commercial Vehicle Operations (CVO); Advanced Vehicle Control Systems (AVCS); and, Advanced Public Transportation Systems (APTS). Although the Federal Highway Administration has initially chosen to address each of these components separately, a number of issues are shared by all components. One critical common element deals with the capabilities of the humans in the system. Appropriate guidelines that consider the needs and capabilities of operators, maintainers, and users will be critical for efficient functioning of each system. Efforts are underway to define and resolve critical human factors issues related to IVHS components. This symposium addresses four of the five more highway related IVHS components. For each of these components, presenters will define the key engineering characteristics, hypothetical scenarios that focus on human-system interfaces, and examples of human factors issues that must be considered in the design of IVHS systems.

Advanced Traffic Management Systems (ATMS) are those components of Intelligent Vehicle Highway Systems (IVHS) that integrate traffic detection, communication, and control functions to be responsive to dynamic traffic conditions and increase the efficiency of existing traffic networks. ATMS provide the management foundation that will enable and integrate other IVHS components such as Commercial Vehicle Operations, Advanced Traveler Information Systems, Advanced Vehicle Control Systems, and Advanced Public Transportation Systems. This paper defines Advanced Traffic Management Systems. It also describes the functions that may take place within an ATMS-class Traffic Management Center (TMC), a scenario that a future TMC operator may encounter, and some of the human factors issues that must be addressed in the design of an ATMS-class TMC.

The status of plans and projects for intelligent vehicle-highway systems (IVHS) in Europe, Japan, and the US is examined. The four broad areas covered by IVHS are described. They are advanced traffic management systems. advanced traveler information systems commercial vehicle operations systems, and advanced vehicle control systems. A variety of projects in Europe, Japan, and the US which aim at proving the feasibility and practicality of IVHS are described. Socioeconomic factors then could delay or even arrest the development of IVHS are examined.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

&lt;div class="htmlview paragraph"&gt;The concept of the intelligent Vehicle/Highway System (IVHS) is a direct descendent of earlier work on “roadway automation”. Recent advances in a variety of technologies have now made automatic control of the operation of road vehicles a much more realistic proposition than it was even in the recent past. This paper begins by identifying three stages in the likely evolution of these advanced vehicle control systems (AVCS), showing how AVCS is related to the other IVHS functions. The technological elements of AVCS, corresponding to needed research and technology development work, are then described. The current international state of the art in these technologies is reviewed, and the paper concludes with a discussion of an evolutionary progression that could be followed to lead from present-day driving to the long-term concept of an automated freeway network.&lt;/div&gt;

&lt;div class="htmlview paragraph"&gt;Traffic congestion has become a major problem in the United States. Advanced technologies, referred to as Intelligent &lt;b&gt;Vehicle/Highway&lt;/b&gt; Systems (IVHS), offer the best solution. IVHS allow communication between vehicle and highway. IVHS include Advanced Traffic Management Systems, Advanced Driver Information Systems, Commercial Vehicle Operations, and Automated Vehicle Control Systems. IVHS offer to reduce congestion, enhance safety, increase productivity, and improve U.S. competitiveness. IVHS development programs are underway in Europe and Japan. No national IVHS program exists in the United States. Three questions are asked. Is there need for a national IVHS program? Which system is intelligent, the vehicle or the highway? Which system comes first, the vehicle or the highway? Public and private sector cooperation is needed. The federal government will coordinate efforts between state and local governments and private industry. The public and Congress must be convinced that IVHS are beneficial.&lt;/div&gt;

Traffic congestion is increasingly becoming a severe problem in many large cities around the world. The problem is more complex in developing countries where cities are growing at a much faster rate than those in the developed world. Advanced Traffic Management Systems (ATMS) are one of the Intelligent Transport Systems (ITS) technologies that have been recommended and used as a tool to ease congestion problems in many large cities in the developing world. However, it is unknown how specific local conditions commonly observed in these cities, such as poor lane discipline and complex road user interactions, affect the performance of these systems. GETRAM (Generic Environment for Traffic Analysis and Modeling) was used in this research as a tool to develop microscopic traffic simulation models for the city of Bandung in Indonesia. The field data in this research, comprising throughputs, queue lengths and travel times, were collected during peak and off peak periods from all 90 signalised intersections connected to SCATS (Sydney Co-ordinated Adaptive Traffic System). This field data is believed to comprise one of the largest sets of “real world” data available for the development and validation of microscopic traffic simulation models. Two data sets were collected for this research: the first was used to develop and calibrate the simulation model and the second was used for validation. A number of statistical tests were used to determine the adequacy of the model in replicating traffic conditions. The results of statistical tests clearly showed that all of the calibrated and validated models reproduced field conditions with an acceptable degree of confidence. Therefore, the models were accepted as accurate and valid replications of the “real world”. The validated models were then used to evaluate the performance of SCATS which was implemented in Bandung in June 1997 as a pilot project. The results of comparative evaluation of the models under SCATS and under the Fixed Time control (without SCATS) demonstrated that SCATS did not necessarily always produce better results than the Fixed Time control. Furthermore, the performance of SCATS was strongly influenced by specific local conditions in the city. The multiple regression method was used to investigate the relationship between the traffic performance measures and significant basic variables. Based on this analysis, the main findings were: first, throughput was found to increase at intersections with higher v/c (volume to capacity) ratios. Second, throughput was found to decrease at intersections with higher numbers of phases and movements, longer widths of leg intersections, and farther distances to adjacent intersections. Third, queue length was found to increase at intersections with higher numbers of phases and movements. Based on the above findings, a number of improvements were recommended to enhance the performance of SCATS. This research also used traffic simulation to evaluate the impacts of these recommended improvements in increasing the performance of SCATS. The main findings from this evaluation were: first, restricted number of phases and movements at selected intersections substantially increased the traffic flow (78%) and decreased the queue length (by 55 to 67%) at the intersection. Second, making leg intersections wider—without physically building additional road capacity but by changing the stream with higher road hierarchy and higher v/c ratio from a two-way road into a one-way road—has a great impact on enhancing the performance of SCATS. Traffic flows were found to increase between 7 and 106%, and queue lengths were found to markedly decrease between 77 and 100% at all the suggested intersections. Third, the application of SCATS at intersections which are not closely spaced was not effective. Therefore, it is recommended that intersections which are not closely spaced remain under the Fixed Time control. The results and findings from this study provide road authorities in developing countries with an appreciation and enhanced understanding of the factors that influence the performance of traffic management systems in cities with similar characteristics to those in Bandung. These findings will also assist traffic engineers determine the best practices for the implementation of advanced traffic control systems in their cities.

An integrated macroscopic traffic model is proposed, which integrates a macroscopic urban traffic flow model with a microscopic traffic emission model for individual vehicles. As a macroscopic model, the integrated model is fast enough for on-line control purposes. Nevertheless, the model can still capture the traffic emissions for vehicles in different states compared with using a macroscopic traffic emission model, because of the accuracy of the microscopic traffic emission model. Model Predictive Control is applied to control urban traffic areas based on the integrated traffic model, aiming at reducing both travel delays and traffic emissions.

Intelligent Transportation System (ITS) includes eight wide areas of applications such as Advanced Traffic Information System, Advanced Traffic Management Systems, Automatic Vehicle Control System, Commercial Vehicle Operations, Advanced Public Transport Systems, Emergency, Infotainment Expectations, and Comfort to Drivers and Passengers, Safety, Electronic Payments etc. Safety, Mobility, Comfort are the three basic reasons for increasing the involvement of electronics in vehicles and in turn in Intelligent Transportation system.

Traffic flow prediction models are expected to play an important role in intelligent vehicle highway systems. This paper demonstrate that the nearest neighbour models have the potential to serve as accurate and portable traffic flow prediction models. Furthermore the models have the advantages of being easily understood by field personnel.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Roadway accidents significantly contribute to intermittent congestion and increased CO2 emissions on freeways. This research introduces a statistical approach designed to predict the rise in CO2 emissions resulting from traffic disturbances or jams triggered by such incidents. It also assesses the influence of varying levels of accident management effectiveness in different situations. To construct these scenarios, the study employs VISSIM, a traffic modeling software, incorporating diverse factors such as traffic volume, vehicle types, incident durations, and freeway lane counts. It then produces traffic flow characteristics in the form of vehicle paths. The emission estimates are derived by correlating these simulated vehicle paths with emission rates from the MOVES model. The study then applies a regression analysis to examine the connection between the increase in emissions and various influencing factors. The findings indicate that this approach efficiently reflects the impact of variables like accident duration, vehicle mix, and traffic volume on CO2 emissions across different lane configurations. The accuracy of these predictions is also confirmed. The outcomes suggest the model’s potential usage in guiding efforts to lower emissions and determining the optimal duration of incident management, particularly in terms of lane closure, to mitigate emission impacts. This paper also discusses the limitations of the model and the future improvement direction.

The evaluation of ITS measures, such as advanced traveler information systems and advanced traffic management systems depend heavily on the use of faster than real time traffic simulation methods. Although many micro-simulation traffic models have already been developed, their execution times are still too slow for large-scale ITS applications. This has lead to the development of mesoscopic simulation and traffic assignment methods. These are simpler traffic models, which trade off some of the fidelity of the results for significant gains in computation time. This paper presents a new dynamic traffic assignment model that is based on the mesoscopic space-time queue network loading method developed by Mahut (2000). This hybrid optimization simulation method was applied to a portion of the Stockholm road network, which consists of 220 zones, 2080 links and 5000 turns.

This paper studies the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the switching-mode model (SMM), is presented; it is a piecewise-linearized version of Daganzo's cell transmission model (CTM). The observability and controllability properties of the SMM modes are reviewed because these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semiautomated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data-fitting approach is applied to loop detector data to determine free-flow speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and on-ramp flows. The calibration method wa...

This paper studies the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the switching-mode model (SMM), is presented; it is a piecewise-linearized version of Daganzo's cell transmission model (CTM). The observability and controllability properties of the SMM modes are reviewed because these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semiautomated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data-fitting approach is applied to loop detector data to determine free-flow speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and on-ramp flows. The calibration method was tested with loop detector data from Interstate 210 westbound (I-210W) in Southern California. The main traffic data source was the performance measurement system. Parameters were calibrated for a 2-mi (3-km) subsection of I-210W and were tested on both the SMM and CTM, which were shown to perform similarly and to reproduce the general behavior of traffic congestion.

This paper presents an acyclic real-time traffic signal control model with transit priority based on a rolling horizon process for isolated intersections. The developed model consists of two components, including: an Improved Genetic Algorithm (IGA)-based signal optimization module and a microscopic traffic simulation module. The acyclic real-time traffic signal control model optimizes the phase sequence and the phase length with the aim to minimize the total delay of both transit vehicles and general vehicles for the next decision horizon. Numerical results show that the proposed IGA signal optimization module could provide a more efficient search for optimal solutions. The results also show that the acyclic real-time traffic signal control model outperforms the fixed-time control model. It prioritizes transit vehicles while minimizing the impact on the general vehicles.

There is a need for advanced traffic management systems (ATMS) on a local and network level to effectively utilize today`s transportation system. An automated operating system, with round the clock incident detection, would help to initiate the required action on time in case of an accident and would minimize the effect of the incident. One of the key elements of ATMS is the vehicle detection unit. The most commonly used inductive loop detectors have a relatively short life span and frequently malfunction. Any maintenance of loop detectors requires road closures. Also, safety of the crew is an issue. An overview of currently available technologies for traffic control and monitoring is presented, with special emphasis on systems that can be installed and maintained without significantly interfering with the traffic. The paper presents the available technologies, provides comparative information about them, and discusses the technical and conceptual problems typically arising during the deployment. The paper describes video detection systems that currently seem to be the most attractive alternative to the traditional intrusive methods. The new perspectives for traffic monitoring and management not available so far are drawn. The typical architecture of these systems is described, and a few popular video systems aremore » presented in some detail. The most critical deployment issues, such as the choice of the equipment, are described, the location of the sensors is discussed, and data transmission problems are considered.« less