Transportation Research Record: Journal of the Transportation Research Board

Truck safety in high-wind conditions–in particular, the use of intelligent transportation system technology for operating roadway segments during high-wind conditions–is examined. The frequent high-wind conditions in Wyoming cause trucks to overturn and often lead to the closure of a road, resulting in delays, economic impact, and a loss of system reliability. This paper addresses how critical weather conditions can be identified; what the various levels of operations can be, depending on these conditions; the means for identifying at-risk vehicles; and the benefits of implementing an advanced system for operating these high-hazard roadway segments.

Decentralized traffic information systems based on intervehicle communication have drawn increasing attention in recent years. On the assumption that intervehicle communication is instantaneous relative to vehicle movement, multihop connectivity between two equipped vehicles subject to arbitrary distribution patterns of vehicles, market penetration rates, and transmission ranges is studied. A modeling conceptual framework and definitions are discussed, and a Monte Carlo simulation model of multihop connectivity of instantaneous intervehicle communication systems is presented. With three different, well-chosen random number generators, it is demonstrated that the Monte Carlo simulation model yields results consistent with those in the literature that consider vehicle mobility and that cross-validate analytical models developed previously. The features of the simulation model facilitate determination of the connectivity of large-scale intervehicle communication systems.

An adaptive cruise control (ACC) strategy is presented in which acceleration characteristics, that is, driving styles, automatically adapt to different traffic situations. The three components of the concept are the ACC itself, implemented in the form of a car-following model; an algorithm for the automatic real-time detection of the traffic situation based on local information; and a driving strategy matrix to adapt the driving characteristics–that is, the parameters of the ACC controller–to the traffic conditions. As an option, intervehicle and roadside-to-car communication can be used to improve the accuracy for determining the local traffic states. The complete concept was simulated microscopically on a road section with an on-ramp bottleneck by using real loop-detector data for an afternoon peak period as input for the upstream boundary. A small percentage of traffic-adaptive ACC vehicles, a relatively modest local change in the maximum free flow, improves traffic stability and performance significantly. Although the traffic congestion in the reference case was completely eliminated when a proportion of 25% of ACC vehicles was simulated, travel times for the drivers were reduced in a relevant way for much lower penetration rates. The presented results are largely independent of details of the model, the boundary conditions, and the type of road inhomogeneity.

A major objective for providing real-time traffic information to drivers is to improve the efficiency of the road network, especially in incident situations. However, the subsequent effects depend on behavioral response, in both interpreting available information and reacting to it. Research focusing on the use of variable message signs (VMSs) was done in the urban network of Southampton, in the United Kingdom, a site chosen because of the innovative large-scale application of an urban VMS system and the availability of traffic data derived from urban traffic controls using the split-cycle offset optimisation technique (SCOOT) and other detectors. Although previous research regarding VMSs located in inter-urban areas such as motorways is well documented, the use of VMSs within urban areas is not widespread. The research analyzed several case studies by using detector data collected during incident scenarios at seven locations to assess driver response to VMS messages in terms of diversion rates. Positive driver responses were measured for all, with diversions ranging from 2% to 30%, although not all were solely attributable to VMS information. No relationships between the severity of VMS message and driver response could be identified. A simulation model was then used to quantify the potential network benefits of traffic information. A main finding was that if the diversionary route had sufficient spare capacity, substantial VMS benefits were potentially attainable, although these benefits were not distributed equally.

Vehicle infrastructure integration (VII) is receiving significant attention because of its potential to provide a wide range of benefits. However, to inform design, deployment, and operations decisions best, it will be necessary to evaluate potential VII-enabled applications fully. A research effort investigated a VII-enabled traffic monitoring application. First, the VII simulation environment developed to support the research was described. Next, traffic monitoring coverage as a function of VII roadside unit (RSU) configuration (i.e., number of units and placement) was investigated. The results of the study indicated that, on the basis of current guidance in the VII architecture, roughly 55% of the sections in the network would be within the direct range of an RSU. Finally, the accuracy and the coverage of monitored links were evaluated. The results of the analysis demonstrated that only 35% of RSU-covered sections were monitored at 1% penetration rates, but the combined effect of direct RSU coverage and indirect coverage through vehicle storage was quite high (around 60%) for a heavily traveled urban network. The results also illustrated that at low levels of vehicles equipped with VII (1% to 10%), the mean absolute error of speed estimation was about 4 mph. However, as the penetration rate increase to 30%, the error dropped to even lower values, roughly 2.5 mph. Finally, it was found that with a default buffer value of 30 snapshots of vehicle storage, the greatest error in indirectly covered sections for mean freeway section speed was 6 mph at 1% penetration rate.

A novel on-line dynamic traffic control strategy for an urban expressway-arterial corridor system is proposed. The corridor system comprises an expressway mainline, on and off-ramps, and surface streets (arterial roads). The ramps are not subjected to any ramp metering control. Assuming that the real-time vehicle arrival and departure can be obtained from the loop detectors on the expressway, the proposed traffic control strategy aims to maintain a predetermined level of service on a congested expressway section by disseminating the congestion information to drivers through various advanced traveler information system means. This strategy consists of three components: expressway mainline control (EMC), on-ramp control (OnC), and off-ramp control (OffC) mechanisms. The EMC mechanism is the major component that diverts vehicles from the expressway to the surface streets, and the OnC and OffC procedures protect the ramps and surface streets from excessive flow. This is because diverting the vehicles without taking into consideration the surface street capacity may cause the overall performance of the corridor system to deteriorate. A simulation-based modeling methodology is developed to evaluate the on-line dynamic traffic control strategy. The evaluation is carried out by performing sensitivity analysis tests of the control parameters used in the strategy. A case study based on a corridor system in Singapore has shown that the traffic control strategy is effective.

An approach is presented for quantifying commute disutility measures. The approach was demonstrated through a case study conducted for the Washington, D.C., metropolitan area by using an analytical technique called the heuristic on-line web-linked arrival time estimation. “Commute disutility” was defined as having pretrip, en route, and posttrip components on the assumption that there is disutility associated with a commuter's expectation of the trip before trip start, the en route trip experience, and the actual outcome of the trip. Three types of regular commuters were modeled: the nonuser who does not use any traveler information and two kinds of traveler information user–the radio listener who listens to commercial broadcast traffic advisories and the advanced traveler information service user who uses a notification-based service that provides route-specific travel time estimates. Analysis showed that compared to nonusers, traveler information users had lower commute disutility. They had fewer late arrivals at their destinations, and in fewer instances their trip expectation before trip start did not match their actual trip experience. They had fewer instances of feeling at intermediate waypoints along a trip that they were running behind schedule. They modified their trip start times or took alternate routes on more than 65% of the trips. This may have resulted in some disutility because of changes to the regular commute behavior, but they are more informed and therefore more confident of the potential trip outcome than is a nonuser.

An assessment of the use of dedicated short-range communications technology to perform travel time monitoring and automated incident detection on a segment of rural freeway is described. The assessment used the CorSim traffic simulation tool to simulate traffic and incidents on a segment of rural freeway. Output data from the simulation was subjected to postprocessing to convert it to probe and beacon data. An incident detection algorithm was developed by using a travel time threshold and a counter. An alarm was generated when a counter reached a preselected level. This algorithm was tested on selected data files, and the results were used to identify the optimum values of the travel time threshold and the counter alarm level. With these optimum values, the algorithm was applied to the probe and beacon data to determine how quickly the system could detect various traffic incidents. The analysis showed that the system could provide rapid and reliable detection of incidents. During the simulation and analysis, several parameters were varied so that their effect on the system performance could be observed. Each parameter proved to have a significant effect on the detection time, and the observed effects were consistent with logical expectations. In general, the time to detect an incident was reduced in response to (a) increased traffic volume, (b) increased incident severity, (c) increased transponder population, (d) reduced reader spacing, and (e) reduced distance from incident to next downstream reader.

Traffic surveillance cameras are becoming a viable replacement for inductive loop detectors. The effectiveness of these cameras, however, depends on video image processing algorithms that can alleviate common problems such as shadows, vehicle occlusion, reflection, and camera shake. Shadows have proved to be a major source of error in the detection and classification of vehicles. Three algorithms of increasing complexity are proposed to address the shadow problem. The algorithms each address the need to remove cast shadows from vehicles while preserving self-shadows, or those areas of a vehicle that are hidden from illumination. They are also geared toward real-time analysis, which requires that they can be implemented efficiently and cannot have complex training or learning requirements. The dual-pass Otsu method of shadow removal was the simplest in application but had the poorest performance. The proposed region growing technique, though showing considerable promise, failed when the pixel intensity varied widely in the shadow region. The last technique used edge imaging to recognize shadows as areas with few edges or with edges substantially similar to the background. This method clearly outperformed the other methods and was subsequently proved in a separate paper describing a prototype vehicle detection and classification system.

A methodology was established to assess the various benefits of an incident management program that is part of an advanced transportation management system. The methodology computes the benefits derived from the motorist assistance service, the reduction in delay, fuel consumption, secondary crashes, and the improvement in air quality attributable to the incident management program. A case study involving the Georgia NaviGAtor, Georgia's intelligent transportation system, reveals the resulting annual benefits of implementation of the methodology. The results indicated a substantial annual savings to motorists of 7.2 million vehicle hours of incident-related delay. The overall cost savings computed for a 12-month period during 2003 and 2004 was $187 million. On the basis of an annualized infrastructure, operations, and maintenance cost of the NaviGAtor system, the annual benefits-cost ratio was calculated to be 4.4:1.

A route choice model was devised for personalized route guidance; it can adaptively change its routing function according to the demands of the user. A strategy for personalized route guidance is to incorporate an adaptation process into the route selection rules. In a study, regularities in route selection were discovered by using a rule-based approach, the C4.5 algorithm, which had advantages over other methods because of its comprehendible model structure. The route choice model is combined with a user interface, enabling the efficient collection of user feedback. To examine the adaptability of the model, experiments in which user preferences are predefined and later changed during the tests were carried out. The results of the experiments indicate the applicability of the model in personalized route guidance.

The problem of finding the optimal roadway segment configuration for road-based surveillance technologies to estimate route travel times accurately is addressed. This problem is inherently a space discretization problem regardless of which travel time estimation function is used. Its ad hoc solution is the equidistant segment configuration, such as every half mile or every 1 mi. It is shown that the space discretization problem can be expressed as the common clustering problem. The novelty of the proposed approach is the use of preliminary vehicle trajectory data to obtain statistically significant traffic regime at the study route. Clustering of sample space-time trajectory data is proposed as a viable methodology for solving the optimal roadway segment configuration problem.

Commercially available forward collision warning systems (FCWS) have been designed for highway use, with traffic moving in regular patterns on roadways with modest curvature. The development and the evaluation of an FCWS for urban driving are described. An urban FCWS is significantly more complicated because of irregular movements of subject (equipped) and target vehicles, as well as the presence of many static objects close to the vehicle's path (parked cars, street furniture, etc.). The prototype FCWS was tested for 1 year on two urban transit buses in public service in San Mateo County, California, and Pittsburgh, Pennsylvania. Analysis of the data collected from these tests shows that the FCWS produced favorable changes in driving behavior, generally leading bus operators to drive more cautiously and consistently. The tests did not continue long enough to determine long-term changes in driving behavior or carryover effects after FCWS use ended, so additional testing is needed to address those issues.

Lane departure warning systems (LDWS) provide an effective counter-measure against road departure crashes. Much commercial development of these systems has concentrated on image processing-based systems. Because these systems depend on the detection and tracking of lane markings, it is logical to hypothesize that the visibility of the markings under different weather and lighting conditions may significantly influence the performance of LDWS. Work was done to determine the effects of environmental conditions such as rain and lighting on LDWS performance with typical lane-marking installations on limited-access facilities. The main performance measure used in this study is the efficacy rate (ER). This is defined as the ratio of the number of instances in which the lane departure warning device is able to provide lane crossing alarms in all instances in which an LDWS-equipped vehicle crosses the lane markings. The results indicate that in most cases the ER of the LDWS under dry and light rain conditions is 100%. However, it was found that performance of LDWS of lane markings was affected significantly by heavy rain conditions at night for typical lane-marking installations. With heavy-rain night conditions, most of the observed ER values were between 0% and 30%. It appears that the ER associated with night rain conditions increases with increased lane-marking retroreflectivity. Dusk conditions were found to drop the ER of LDWS by 15% to 18%. At a few locations that had yellow lane markings near the end of their service lives or had yellow markings on concrete pavements, LDWS had difficulty detecting the markings because of the low level of contrast between the yellow markings and the pavement.

Cooperative vehicle systems (CVS) can provide intelligent transportation systems services such as probe vehicle information and hazard warnings by exchanging data among suitably equipped vehicles as they travel. The sensitivity of the performance of CVS to the market penetration of suitably equipped vehicles is explained by using Monte Carlo analyses and simulations of wireless message propagation. The CVS functions are implemented by using wireless vehicle-vehicle data communications, which can be successful only when other equipped vehicles exist within wireless range to receive the messages and relay them to further vehicles. These relays may be accomplished by direct wireless transmission to nearby vehicles, but they may also be facilitated by transport relay, by which vehicles traveling in the opposite direction carry the messages and rebroadcast them to the vehicles that they pass. The effectiveness of both direct and transport relay mechanisms as a function of wireless communication range, market penetration, and traffic density and their influence on the speed of message propagation is shown. The direct relay is most effective with a high density of equipped vehicles, but when the density of equipped vehicles is low, the relays become much more dependent on the slower transport relay. When the market penetration is low early in the development of CVS, the most promising use cases are likely to be those that do not require rapid message propagation.