Improvement Of Traffic Flow Research Articles

Marginal costs of freeway traffic congestion with on-road pollution exposure externality

The health cost of on-road air pollution exposure is a component of traffic marginal costs that has not previously been assessed. The main objective of this paper is to introduce on-road pollution exposure as an externality of traffic, particularly important during traffic congestion when on-road pollution exposure is highest. Marginal private and external cost equations are developed that include on-road pollution exposure in addition to time, fuel, and pollution emissions components. The marginal external cost of on-road exposure includes terms for the marginal vehicle’s emissions, the increased emissions from all vehicles caused by additional congestion from the marginal vehicle, and the additional exposure duration for all travelers caused by additional congestion from the marginal vehicle. A sensitivity analysis shows that on-road pollution exposure can be a large portion (18%) of marginal social costs of traffic flow near freeway capacity, ranging from 4% to 38% with different exposure parameters. In an optimal pricing scenario, excluding the on-road exposure externality can lead to 6% residual welfare loss because of sub-optimal tolls. While regional pollution generates greater costs in uncongested conditions, on-road exposure comes to dominate health costs on congested freeways because of increased duration and intensity of exposure. The estimated marginal cost and benefit curves indicate a theoretical preference for price controls to address the externality problem. The inclusion of on-road exposure costs reduces the magnitudes of projects required to cover implementation costs for intelligent transportation system (ITS) improvements; the net benefits of road-pricing ITS systems are increased more than the net benefits of ITS traffic flow improvements. When considering distinct vehicle classes, inclusion of on-road exposure costs greatly increases heavy-duty vehicle marginal costs because of their higher emissions rates and greater roadway capacity utilization. Lastly, there are large uncertainties associated with the parameters utilized in the estimation of health outcomes that are a function of travel pollution intensity and duration. More research is needed to develop on-road exposure modeling tools that link repeated short-duration exposure and health outcomes.

Autonomous Navigation and Obstacle Avoidance of a Micro-Bus

At present, the topic of automated vehicles is one of the most promising research areas in the field of Intelligent Transportation Systems (ITS). The use of automated vehicles for public transportation also contributes to reductions in congestion levels and to improvements in traffic flow. Moreover, electrical public autonomous vehicles are environmentally friendly, provide better air quality and contribute to energy conservation. The driverless public transportation systems, which are at present operating in some airports and train stations, are restricted to dedicated roads and exhibit serious trouble dynamically avoiding obstacles in the trajectory. In this paper, an electric autonomous mini-bus is presented. All datasets used in this article were collected during the experiments carried out in the demonstration event of the 2012 IEEE Intelligent Vehicles Symposium that took place in Alcalá de Henares (Spain). The demonstration consisted of a route 725 metres long containing a list of latitude-longitude points (waypoints). The mini-bus was capable of driving autonomously from one waypoint to another using a GPS sensor. Furthermore, the vehicle is provided with a multi-beam Laser Imaging Detection and Ranging (LIDAR) sensor for surrounding reconstruction and obstacle detection. When an obstacle is detected in the planned path, the planned route is modified in order to avoid the obstacle and continue its way to the end of the mission. On the demonstration day, a total of 196 attendees had the opportunity to get a ride on the vehicles. A total of 28 laps were successfully completed in full autonomous mode in a private circuit located in the National Institute for Aerospace Research (INTA), Spain. In other words, the system completed 20.3 km of driverless navigation and obstacle avoidance.

고속도로 영업소의 자동 요금 징수 시스템 도입에 따른 소형 경유 화물트럭의 배출가스 저감 효과 분석

Electronic Toll Collection System (ETCS), so called "Hi-Pass" in Korea, has improved traffic flow at toll gate of highways. It is known that the improvement of traffic flow should reduce air pollutants and <TEX>$CO_2$</TEX> from vehicles. In this study, real driving emission of a light duty truck with Portable Emission Measurement System(PEMS) has been measured to evaluate the emission reduction effect due to ETCS. The correlations between driving variables and emissions have been analyzed to verify its effect on traffic flow improvement and emission reduction at toll gate. We considered average vehicle speed, Relative Positive Acceleration (RPA), and the distance of queue as driving variables. Compared to passing Manual Toll Collection System (MTCS) lane without queue, ETCS was able to reduce 38.7% of <TEX>$NO_x$</TEX>, 21.6% of soot, and 27.7% of <TEX>$CO_2$</TEX>. The results showed that the higher the average vehicle speed, the lower RPA and no queue in ETCS contributed to the emission reductions. Linear equation models with RPA and queue have been established by the multiple linear regression method. The linear models resulted in the higher coefficient of determination than those with only average vehicle speed used for establishing vehicle emission factors.

Influence of inter-vehicle communication on peak hour traffic flow

Mixed traffic flow consisting of vehicles equipped with wireless inter-vehicle communication devices and non-equipped vehicles is analyzed using bidirectionally coupled network traffic and road traffic simulators in a peak hour scenario. For equipped vehicles a strategy to stabilize traffic flow and to reduce travel time is proposed. The strategy comprises rules to determine both how and when to change driving behavior. Vehicles that detect perturbations downstream try to keep a larger gap to their predecessor by which they aim to compensate traffic inhomogeneities. Improvement of traffic flow was observed even for a ratio of equipped vehicles as low as five percent.

Mitigating Traffic Congestion and Accidents in Thailand with Intelligent Transportation System Technology

Geometrical features of intersections, such as T-intersections and four-leg intersections, can give rise to several conflict points at those intersections. Without proper control at such conflict points, accidents can occur. In Thailand, the application of intelligent transportation system (ITS) technology for improvement of traffic flow and road safety is still in its infancy. This paper describes one of the pioneering uses of ITS technology to mitigate congestion and reduce accidents at intersections. The intersections under study are located in suburban Bangkok, Thailand, where major accidents have occurred as a result of red light running and speeding. Through the use of accident analysis modeling and ITS technology, it is possible to improve traffic flow and reduce the number of crashes. ITS technology, including an image-sensing concept for adaptive synchronization (green wave), was used to detect headway, spacing, number of speeding vehicles, angle of lane changing, and number of vehicles changing lanes. In particular, the image-sensing concept of traffic classified counting was used to calculate and evaluate signal phasing and cycle times for adaptive synchronization. In this operation, two closed-circuit television cameras and electronic equipment installed at each intersection were used to track vehicles passing through virtual loops, similar to the way in which induction loops in pavement detect vehicles. A variable message sign was used to flash a warning to errant drivers. After the implementation of this locally developed ITS technology, traffic flow improved significantly and the number of accidents caused by red light running and speeding decreased drastically.

Offset Optimizing with CTM and Genetic Algorithms: Results from Field Studies in Hannover

The Cell Transmission Model (CTM) by Daganzo in combination with an offset optimization algorithm based on genetic algorithms was integrated in a graphical user interface and applied to a test area in Hannover, Germany. The optimized traffic control proved a significant improvement of traffic flow considering reduction of travel time and number of stops.

Traffic Management of Special Events in Small Communities

Planned special events (PSE), such as sporting events and concerts, produce nonrecurring congestion as attendees simultaneously attempt to exit the event and overload the local transportation network. These types of events can have a significant impact on traffic operations, particularly in small urban and rural environments, where limited infrastructure is available to access and egress the PSE venue. The research presented here applied a variety of traffic management strategies to manage congestion resulting from football games at Montana State University in Bozeman, Montana, in fall 2007. These strategies included the provision of real-time travel information, road closures, traffic signal retiming, and real-time traffic monitoring. Results indicated that these strategies could be successfully applied in a rural community to manage the congestion arising from PSEs. For example, results indicated that signal retiming and manual traffic control strategies allowed for improvements in traffic flow on approaches that served game traffic.

Improvement of Traffic Flow by Preview Speed Control with Communications

Improvement of Traffic Flow by Preview Speed Control with Communications

AIS 및 전자해도 기반 해상교통량 분석 시스템 개발에 관한 연구

Maritime traffic engineering is a technical field that observes the flow of vessels` traffic in accurate and describes the feature of ship`s movement statistically, then contributes for the improvement of traffic flow and the safety of traffic. The flow of marine traffic can be controlled by carrying out assessment and analysis of vessel`s traffic. It can realize the safety of marine traffic by accurate research and analysis of vessel`s traffic, understanding its flow and analysis data of vessel traffic. This study shows the analysis system of marine traffic connected with Radar, AIS based on ENC(Electronic Navigational Chart). The marine traffic analysis system contributes to the safety of marine traffic through the design of marine traffic route, harbour facilities and improvement of vessels` traffic flow.

Induced Travel and Emissions from Traffic Flow Improvement Projects

Two scenarios for improving traffic flow are simulated and analyzed using the VISSIM microsimulation model and the Comprehensive Modal Emissions Model. Short-run and long-run emissions of CO, HC, NOx, and CO2 and fuel consumption are estimated. In the short run, with traffic volumes held constant, results demonstrate that the smoothing of traffic flow will result in reduced emissions. Long-run emissions are simulated by synthetically generating new trips into the simulated networks to represent potential induced travel. This is done until a “break-even” level of emissions for each pollutant and fuel consumption is reached that is equivalent to the base level before the traffic flow improvement was added. By also calculating short-run changes in travel time from the improvement, the travel time elasticity equivalents for each pollutant are calculated. These values are compared with travel time elasticities in the literature to evaluate whether long-run emissions benefits are likely to endure. Simulations are conducted using different assumptions of vehicle soak time to simulate cold-start and hot-stabilized operating modes. Results indicate that, in most cases, long-run emissions reductions are unlikely to be achieved under the two scenarios evaluated.

Using Global Positioning System Data for Field Evaluation of Energy and Emission Impact of Traffic Flow Improvement Projects: Issues and Proposed Solutions

Traffic-operational projects typically are evaluated by using several measures of effectiveness, including vehicle delay, queue sizes, and vehicle stops. Other emerging measures include vehicle fuel consumption and emissions. Although these emerging measures are difficult to determine in the field, they can be estimated by using second-by-second speed measurements of individual vehicles with Global Positioning System (GPS) technologies. GPS can provide such information with relatively high accuracy (within 1 m/s), but the presence of any erroneous data in the measured data as a result of signal losses may result in unrealistic vehicle fuel consumption and emission estimates. The ability of various data-smoothing techniques to remove such erroneous data without significantly altering the underlying vehicle speed profile is investigated. The techniques reviewed involve differentiating the measured speed profile to generate an acceleration profile that is checked for validity. Several smoothing techniques are then applied to the acceleration profile, including data trimming, simple exponential smoothing, Epanechnikov kernel smoothing, robust kernel smoothing, and robust simple exponential smoothing. The results of the analysis indicate that the application of robust smoothing (kernel of exponential) to vehicle acceleration levels, combined with a technique to minimize the difference between the integral of the raw and smoothed acceleration profiles, removes invalid GPS data without significantly altering the underlying measured speed profile. A sensitivity analysis also demonstrates that the proposed datasmoothing technique can efficiently smooth random variations in speed profiles due to errors in GPS speed measurements.

Improvement of Traffic Flow on Highway Network with Area Control Scheme under Ealthquake Environment

Improvement of Traffic Flow on Highway Network with Area Control Scheme under Ealthquake Environment

Assessing Impacts of Improved Signal Timing as a Transportation Control Measure Using an Activity-Specific Modeling Approach

Metropolitan areas in nonattainment for transportation-related air pollutants rely on transportation control measures (TCMs) to reduce emissions and meet clean-air goals. However, since traditional transportationrelated air quality models use emission rates based on average speeds, only TCMs that either increase or decrease vehicle activity to speeds in which emissions are lower show reductions in output of air pollutants. In recent years, transportation air quality analysis has shifted to an activityspecific modeling approach that correlates emissions to vehicle operating mode. With an activity-specific approach, the emission reduction potential of a TCM can be evaluated by its ability to decrease time spent in modes in which emissions are disproportionately elevated. Signal timing improvements are attractive TCMs for traffic flow improvement. However, with traditional modeling, they may greatly decrease extremes in modal activity yet not show significant emission reduction if only moderate changes in average speed are realized. The benefits of using activityspecific modeling for evaluation of improved signal coordination as a TCM are described. A brief overview of the development of an activityspecific carbon monoxide emission rate model is provided, data collection for on-road vehicle activity estimates is briefly outlined, and a comparison of traditional emission modeling versus activity-specific modeling is provided to estimate the air quality benefits from improved coordination at a study intersection. Results for the study intersection indicate that more significant reductions in carbon monoxide emissions are realized using an activity-specific approach than with traditional methods.

Dynamic Behavioral Data Collection Using an Instrumented Vehicle

A significant problem that has become increasingly apparent in the development of models of driver behavior over the last few years is the absence of reliable data with which simulated processes, such as car following, may be compared. Obtaining such data, and the associated increase in model validity that this would allow, is clearly becoming of greater importance since a reliable baseline is required against which improvements in traffic flow and safety produced by many advanced transport telematics systems can be judged. One source of such data is an instrumented vehicle; a vehicle equipped with relative distance- and speed-measuring sensors that may be deployed in the traffic stream to collect data that are realistic, accurate, and dynamic. The opportunities for data collection afforded by instrumented vehicles are examined, in particular, the construction and testing of a new facility fitted with an optical speedometer, a radar rangefinder (capable of measuring the distance to, and relative speed of, the next vehicle in the traffic stream), and forward- and rear-looking video camera. Examples are given of the use of the vehicle in several current research projects, the operational strategies for which will be presented and discussed along with output. These include experiments on close-following, lane-changing, and the perception of relative speed. In conclusion, future areas of research and development are examined.

The Evolving Roles of Vehicular Navigation

This paper examines existing and potential applications of navigation technology to motor vehicles that operate primarily upon streets and highways. Applications are described and representative systems approaches are outlined in three broad categories; driver information, traffic management, and fleet management. Driver information systems include those that develop and present navigation information in various forms to aid the driver in reaching the desired destination. The traffic management category includes navigation systems that consider real-time traffic conditions in determining optimum routes and, consequently, contribute to the overall improvement of traffic flow. Fleet management applications include automatic vehicle location monitoring systems (which do not necessarily provide navigation information to vehicle drivers) as well as systems which provide routing or step-by-step route guidance. The most comprehensive fleet management applications of vehicular navigation may also include command and control functions.

A Report on Urban Traffic Control Research Conducted by the Federal Highway Administration

The Urban Traffic Control System (UTCS) was installed by the Federal Highway Administration for the purpose of developing advanced traffic signal control strategies that will reduce congestion in the nation’s urban areas. This research has included development of procedures for detector placement, development of predictor algorithms and development of three generations of traffic control strategies. The first generation of control is equivalent to the majority of systems currently being installed in the United States. It uses stored signal timing patterns based either upon time of day, measured traffic conditions, or operator selection. Second and third generations of control are traffic responsive strategies that compute the timing patterns on-line based upon measured traffic conditions. To date, the various operating modes of the first generation have been evaluated. The evaluation results indicate that improvements in traffic flow are possible with the responsive modes of first generation.Other research activities taking place on the project include the development of new prediction techniques, development of a detector placement methodology, and a comparative analysis of alternative evaluation techniques. All of these activities have produced results that are currently available for implementation in operational traffic control systems.

Federal Research in Urban Traffic Control

In May 1968, the Federal Highway Administration initiated a major emphasis research project titled Urban Traffic Control System (UTCS). This was later expanded to include a Bus Priority System (BPS). The ultimate objective of the UTCS/BPS is to provide the nation’s urban centers with completely tested examples of computer programs incorporating advanced operational control technique and strategies which will result in a marked improvement in traffic flow. It follows that the main products of this research will be general advancement in urban traffic control technology and development of operational software in particular. It is anticipated that this effort will also provide added momentum to the modernization of traffic equipment in our cities with resulting benefits to the traveling public and to the industry.

The application of a digital computer for traffic control

The use of digital computers in traffic is becoming more common, after years of experimentation and promise. Both the theoretical requirements of such systems and a description of the physical and programming characteristics of systems in operation in several locations in the United States will be dealt with. The improvements in traffic flow and the managerial, manpower, and organizational requirements will be discussed. Finally, the probable short-range and long-range direction of new systems will be hypothesized.

Improvement of traffic flow and safety by longitudinal control

Improvement of traffic flow and safety by longitudinal control

Improvement of traffic flow and safety by longitudinal control

Improvement of traffic flow and safety by longitudinal control