Joseph L. Schofer

A SIMPLE TIME SEQUENTIAL PROCEDURE FOR PREDICTING FREEWAY INCIDENT DURATION

The objective of this study is to develop a methodology for incident duration prediction. First, we develop an understanding of factors that influence incident duration. Then, we use a series of truncated regression models to predict incident duration. The models account for the fact that incident information at a Traffic Operations Center is acquired over the life of the incident. The implications of this simple methodology for incident duration prediction are discussed.

Evaluation with traffic assignment under demand uncertainty

The impact of demand uncertainty on the evaluation of network improvements when using traffic assignment is addressed. Theoretical results indicate that the expected value of the performance of the traffic system is not necessarily equivalent to the performance of the system at the expected value of demand, and therefore the expected demand cannot be used with disregard of the variance in demand forecasts. Using expected demand tends to overestimate performance of the network and could lead to erroneous choice of improvements. Alternative possibilities for dealing with this problem are explored, including an approach in which the demand is inflated. This yield benefits not only in terms of selecting improvements with lower expected total system travel time but also significant reductions in the variance associated with this measure. Demand inflation should take place after a budget has been set, so that decisions resulting from inflation do not dictate that more infrastructure be built but that different improvements be selected. Furthermore, numerical examples indicate that there is a significant probability that the deterministic traffic assignment procedure will incorrectly rank improvement policies. This poses a serious concern for decisions based on this procedure, so potential actions are discussed to address the problem.

Behavioral issues in the design and evaluation of advanced traveler information systems

Decisions about implementing Advanced Traveler Information Systems (ATIS) should be based on the individual and social benefits expected from such technologies, which will be strongly dependent on the ways travelers respond to these new information sources. This paper explores the behavioral issues important to understanding traveler reactions to ATIS; it discusses evaluation strategies, including stated preference methods and observation of revealed behavior in laboratory simulations and field tests with various degrees of control and complexity. Advantages and disadvantages of different approaches are reviewed, and the experimental design challenges of site selection, recruitment of test subjects, and measurement of behavior are explored.

Arterial incident detection using fixed detector and probe vehicle data

This paper describes incident detection algorithms for urban arterial streets using two distinct data sources: fixed traffic detectors and probe vehicles. The data sources are used independently to obtain two distinct algorithms. This approach is undertaken to increase the overall coverage of incident detection capabilities as early implementation will result in relatively few cases when data is available from both fixed detectors and probe vehicles on the same link and during the same time period. The algorithms were developed using simulation data for the ADVANCE ITS operational test; they will subsequently be recalibrated with field data collected during the ADVANCE demonstration project. Discriminant analysis was used to estimate a variety of models based on different traffic flow measures from each data source. Various functions of fixed detector measures (volume and occupancy) and probe vehicle travel times were considered for inclusion in the fixed detector and probe vehicle algorithms, respectively. The most effective variables for detecting incidents were volume divided by occupancy (which is related to average speed) for fixed detectors and average speed for probe vehicles. In both cases, traffic measures for the incident link were most useful for incidents located in the downstream portion of the link and for the next upstream link for incidents located at the upstream end or in the middle portion of the link. Further, it was generally found that data from a single link provided almost equally good incident detection as data obtained from pairs of links. This led to the development of an algorithm that uses data from a single detector or link, thereby supporting incident detection on any link that has a current data independent of data availability from other links. The performance of the algorithms was evaluated using detection rates and false alarm rates, which were found to be in the same range for both the algorithms. The fixed detector algorithm showed better detection ability, but its use is limited by the number of detectorized links in the network, while the performance of the probe vehicle algorithm was dependent on the number of reports available per time period.

Trend curve optimal control model for highway pavement maintenance: Case study and evaluation

This paper presents a control theoretic dynamic model for optimizing the timing and intensity of major highway pavement maintenance actions. The solution procedure is demonstrated through a simple case study, and the worthiness as a problem-solving tool is discussed through a systematic evaluation of the solutions.

MARKET RESEARCH EVALUATION OF ACTIONS TO REDUCE SUBURBAN TRAFFIC CONGESTION: COMMUTER TRAVEL BEHAVIOR AND RESPONSE TO DEMAND REDUCTION ACTIONS

This research paper is directed toward obtaining a better understanding of current work trip mode choice of commuters in suburban areas and the effectiveness of alternate demand reduction actions in alleviating congestion, based on a Chicago area study. The paper is particularly concerned with an evaluation of the effectiveness of demand reduction actions that encourage the use of ridesharing modes (carpool, vanpool and transit) and/or discourage the use of drive-alone auto for the work trip. A conceptual framework of current mode-choice behavior and behavioral response to demand reduction actions is developed. The empirical analysis suggests that in the midwest suburban setting, any substantial increase in ridesharing propensity appears to require a combination of ridesharing incentives in the form of improved service characteristics and direct auto-use disincentives in the form of substantially increased parking costs. Our analysis also suggests that ridesharing propensity is greater for women and individuals in households with fewer autos. Individuals who have a great need for independence, make additional trips on their way to and from work, frequently stay late at work, and have a high income tend to be less inclined to use ridesharing modes.

Design and implementation of ADVANCE: The Illinois dynamic navigation and route guidance demonstration program

A demonstration program to design, implement and evaluate an in-vehicle navigation and route guidance system with dynamically updated travel time information is being undertaken on a suburban arterial road system in Northeast Illinois. In July, 1991, the Illinois Department of Transportation, Federal Highway Administration, Motorola, Inc., and Illinois Universities Transportation Research Consortium agreed to proceed with the design and test phase of the demonstration program. This phase will design the route guidance system demonstration, implement the software design for the Traffic Information Center and conduct a system test. Detailed plans for monitoring and assessing the systems performance will also be prepared. These designs will guide the studies to be performed during the implementation phase of the demonstration program expected to commence in 1993.

CHILD PEDESTRIAN INJURY TAXONOMY BASED ON VISIBILITY AND ACTION

With data from multidisciplinary investigations of child pedestrian injuries in Chicago, a new and simpler four-category taxonomy is presented based on the process that led to the collision. Two dimensions are recognized: the visibility of the child and/or the vehicle immediately prior to the event and the rapidity of action, either movement or change in direction, of the victim or the vehicle. The taxonomy is neutral with respect to responsibility for the collision and accommodates the findings of other researchers. This classification scheme is tested empirically using objective data elements such as child gender and age and event location. It is further tested using the results of a multidisciplinary causal sequence reconstruction of each injury event, based on such factors as childs psychological character, traffic risks, driver behavior, visibility obstructions, whether the child negotiated part of the street before being struck, and childs activities immediately prior to the injury. The results show that events in the categories in this new taxonomy are distinctly different from each other, and that the structure is useful for identifying and organizing interventions.

Effect of traffic reports on commuters' route and departure time changes

Considerable public and private resources are devoted to the collection and dissemination of real-time traffic information in the Chicago area. Such information is intended to help drivers make more informed trip decisions, yet its effect on driver behavior remains largely unexplored. This study was conducted to evaluate the effect of traffic reports on route and departure time changes. Downtown Chicago automobile commuters were surveyed during the AM peak period by giving them mail-back questionnaires. Drivers indicated whether or not they had changed their route and departure time decisions based on traffic reports. Further, drivers indicated how they perceived the traffic information system in terms of key attributes. Respondents also evaluated suggested improvements to the traffic information system. A majority (more than 60%) of drivers reported that they used traffic reports for modifying their trip decisions. Drivers perceived radio traffic reports positively in terms of information system attributes. Commuters were more likely to use traffic reports for their route changes if they perceived traffic reports to be accurate and timely, frequently listened to traffic reports, perceived their regular route as congested, knew multiple alternate routes, were male and higher income. Drivers were more likely to change departure times if they perceived traffic reports to be accurate and relevant, frequently listened to traffic reports and perceived their regular route as congested. Drivers indicated a relatively lower level of overall satisfaction with traffic reports indicating the existence of opportunities for improvement. One promising improvement is near-term prediction of traffic conditions on congested and unreliable routes (where conditions may change rapidly). This is because: • Drivers generally want to know the conditions at any given point (or link) along their route when they reach that point. • Drivers would be able to make better and more informed judgments regarding their trip decisions due to reduced uncertainty of traffic conditions. • The possibility that drivers may find traffic conditions significantly better or worse would be reduced. This would improve the credibility of radio traffic reports.

Perspectives on Driver Preferences for Dynamic Route Guidance Systems

Insights about the design of route guidance systems based on the needs and desires of drivers who are familiar with the travel network are provided. Results from the ADVANCE Intelligent Transportation System operational test, in which more than 100 drivers used vehicles equipped with dynamic route guidance systems for 2-week periods, suggest that such drivers value real-time traffic information, and they want to incorporate their own knowledge and perspectives into the development of route plans, which they expect to be superior to those prepared by the navigation computer. This suggests that future route guidance systems likely to be targeted at familiar drivers should be based on a sharing of tasks between computer and driver that takes greater advantage of driver knowledge than that considered in current designs. Specifically, the driver should be able to take more responsibility for route planning, with the computer responsible mainly for traffic congestion data acquisition, organization and storage, and evaluation of driver-defined routes.