Chanyoung Lee

Snowstorm Event-Based Crash Analysis

This study investigated the impact of snowstorms on a roadway system and assessed winter maintenance efforts in improving highway safety from a macroscopic perspective. The Wisconsin State Trunk Highway System was used as the data source. An inverse relationship between deicing material consumption and crash counts during snowstorms is reflected in the analysis; it also implies multiple causes of snowstorm crashes. Primary factors considered in this research were the effects of various weather conditions and winter maintenance. Results showed a mixed influence of both the snowstorm severity and winter maintenance investment on road safety. That is, severity of the snowstorm in regard to duration, intensity, and wind speed increases traffic crashes and casualties with simultaneous consumption of more deicing materials and labors. The research also explicitly proves that a proactive winter maintenance effort significantly improves traffic safety. Temporal distribution of crash occurrence during a snowstorm shows that a large percentage of crashes occurred during initial stages of the snowstorms, probably because snow removal activities had not yet begun. The pattern is quite similar for state-maintained highways and local roads, except that in the second half of a snowstorm, a higher percentage of crashes occur on local roads than on state highways, possibly suggesting that the different level of maintenance and use of deicing materials may play an important role. Additional research is required to quantify the effects of deicing materials specifically, particularly in regard to application rate and frequency, on highway safety.

A Hybrid Tree Approach to Modeling Alternate Route Choice Behavior With Online Information

One popular intelligent transportation systems (ITS) element that has been deployed in various areas of the United States is variable-message signs (VMSs). Such signs are part of advanced traveler information systems, and they can help drivers make better en route decisions regarding their trips. Unlike most other ITS elements (e.g., ramp metering, advanced signals), VMSs are not supported by mandatory regulations. Consequently, the expected benefit from implementing VMSs largely depends on the response of drivers. This study explored the factors affecting alternative route choices of car drivers with VMSs on the interstate highway system. This study adopted a method called LOTUS to analyze driver-compliance behavior with VMSs. Driver behavior under information provision through VMS data has been collected using the stated-preference approach. The study showed that travel-time saving is not the single dominant factor for driver route choice under information provision. This article explores variables that are associated with driver compliance.

Naturalistic Driving Study: Field Data Collection

This report describes the six Strategic Highway Research Program 2 (SHRP 2) naturalistic driving study (NDS) data collection centers and documents their data collection activities and strategies. The study centers were located in Bloomington, Indiana; State College, Pennsylvania; Buffalo, New York; Tampa, Florida; Durham, North Carolina; and Seattle, Washington. They collected data from more than 3,000 volunteer participants and their vehicles over a 3-year period. Information is provided on the recruitment and assessment of test participants, installation of NDS data acquisition systems into participant vehicles, management of the enrolled participants and their vehicles, retrieval of data from the vehicle fleet, and lessons learned. The report will be of interest to analysts wanting background on where and how the NDS data were collected and to researchers planning future large-scale NDS projects.

Development of Traffic Delay Assessment Tool for Short-Term Closures on Urban Freeways

A certain amount of delay in work zones is typically assumed to be unavoidable and often considered a cost of doing business when roadway improvements are in progress. Therefore, developing a method to predict delay, such that appropriate countermeasures to minimize delay can be implemented, is critical to successful work zone management. Predicting work zone delay in an effective and efficient manner should not require extensive data collection or long, complex coding efforts. The procedure should be customizable for local data availability, easy to use, and, for practitioners, easy to interpret. To this end, the Work Zone Capacity Analysis Tool (WZCAT) analytical software program was developed to predict delays and queues for short-term (daily) work zone closures. WZCAT queue-length predictions are based on a simple input-output model, with capacity of the work zone controlling the throughput. The purpose of this study was to evaluate and enhance WZCAT with field data as well as summarize various aspects of traffic flow and queuing patterns during work zone operations on selected urban freeways. Findings from field observations were significant traffic volume changes on exit and entrance terminals upstream of work zones and the stabilization of vehicle queue after initial queue development. A demand-adjust factor was developed and applied to WZCAT-R for effectiveness and efficiency. WZCAT-R produces effective results for queue prediction. It can be an effective and reliable tool in predicting work zone delay and queue development. The tool can also help engineers proactively plan work phasing, lane restrictions, and potential detour routes to move traffic more efficiently.

Aggressive Driving and Safety Campaigns: Lessons Learned from Better Driver Campaign in Florida

Aggressive driving is a growing concern in the United States. Often such driving results in crashes that harm both drivers and others. In NCHRP Report 500, “aggressive driving” is defined as “operating a motor vehicle in a selfish, pushy, or impatient manner, often unsafely, that directly affects other drivers.” In other words, aggressive driving includes many unsafe driving behaviors by ordinary drivers. Most previous safety campaigns have used enforcement interventions as the primary means of reducing aggressive driving. Enforcement clearly plays a crucial role in reducing aggressive driving. Limited efforts have been made, however, to enhance awareness of aggressive driving by providing proper education to the public. The Better Driver Campaign plan was developed and executed to address aggressive driving in Florida. The campaign was geared toward promoting awareness of aggressive driving. The education-oriented safety campaign was effective in addressing aggressive driving and was appreciated by the public.

Development of New Performance Measure for Winter Maintenance by Using Vehicle Speed Data

The study investigated vehicle speed changes during winter weather events. A total of 954 winter maintenance logs in 24 counties over three winter seasons were analyzed. Several variables of interest were developed, such as storm duration, maintenance operation hour, crew delayed, maximum speed reduction, and the storm start and end times. Also, t1, which represents the start of vehicle speed reduction, and t3, the time at which vehicle speeds recover to normal winter driving speeds, were measured from automatic traffic recorder data. The study confirms that vehicle speed seems to be a good measure of representing driving conditions during winter weather events and winter maintenance performance alike. Speed recovery duration was found to be a dependent variable, defined as a possible evaluation of winter maintenance operations using vehicle speed data.

Pilot Study of Speed-Recovery Duration as a Measure of Winter Maintenance Performance

Many state and local governments in the United States are seeking improved methods of providing winter highway maintenance to meet the increasing demands of todays drivers. Winter maintenance activity can improve road conditions for travel in terms of mobility, safety, and economic benefit. The benefits and costs of winter maintenance make it very important that these activities be completed effectively and efficiently. To improve the effectiveness and the efficiency of winter maintenance activities, the performance of the approach taken must be measured. Winter maintenance performance measures were developed on the basis of speed data from automatic traffic recorders (ATRs) and winter storm report data. An attempt was made to combine the ATR speed data and the storm report data to determine both the average vehicle speed reduction during a snow event relative to normal vehicle speeds at a location and the time needed from the minimum value to regain normal or average vehicle speeds. A determination was made related to whether this speed-recovery duration might be an appropriate performance measure for winter maintenance.

Rapid scene perception with tragic consequences: observers miss perceiving vulnerable road users, especially in crowded traffic scenes

How does scene complexity influence the detection of expected and appropriate objects within the scene? Traffic research has indicated that vulnerable road users (VRUs: pedestrians, bicyclists, and motorcyclists) are sometimes not perceived, despite being expected. Models of scene perception emphasize competition for limited neural resources in early perception, predicting that an object can be missed during quick glances because other objects win the competition to be individuated and consciously perceived. We used pictures of traffic scenes and manipulated complexity by inserting or removing vehicles near a to-be-detected VRU (crowding). The observers’ sole task was to detect a VRU in the laterally presented pictures. Strong bias effects occurred, especially when the VRU was crowded by other nearby vehicles: Observers failed to detect the VRU (high miss rates), while making relatively few false alarm errors. Miss rates were as high as 65% for pedestrians. The results indicated that scene context can interfere with the perception of expected objects when scene complexity is high. Because urbanization has greatly increased scene complexity, these results have important implications for public safety.

Rearview Video System as Countermeasure for Trucks’ Backing Crashes: Evaluating the System’s Effectiveness by Controlled Test

In general, the operation of large trucks involves many different types of maneuvers. The backing maneuver, in particular, requires a higher level of driver attention because of the limited rear view. A growing number of trucks in the United States are equipped with a rearview video system (RVS) that can help the driver see much of the area behind the vehicle. An RVS consists of one or more cameras and one monitor. It is expected that an RVS can help drivers reduce potential backing crashes. To evaluate the effectiveness of the system, this study performed a controlled driver test with 45 truck drivers. The test used three backing maneuvers and a pedestrian dummy for observation of potential crashes. The results showed that the use of an RVS increased the stop rate of the drivers during the straight-line backing maneuver by 46.7%, which could be interpreted as an increase in the odds of avoiding potential backing crashes during the backing maneuver. The stop rate increased 4.4% and 17.8% for the offset right backing and alley dock backing maneuvers, respectively. Driver age, commercial driving experience, and experience with an RVS showed no statistical association with the increased stop rate, which means an RVS can be adopted by drivers quickly. In general, drivers showed positive attitudes toward using an RVS, and more than 90% of respondents agreed that an RVS could reduce the rear blind spot for large trucks.

Interactive Process of Microsimulation and Logistic Regression for Short-Term Work Zone Traffic Diversion

The rapidly growing number of work zones on national highways is having significant operational impacts due to the temporary loss of capacity. Work zone impact on safety and mobility creates a strong need to alleviate work zone congestion and protect road users and workers, which requires a sufficient understanding of work zone impact on traffic flow. Previous studies and field observations demonstrated the importance of considering diversion phenomena when performing work zone impact analysis. To overcome the limitations of deterministic queuing approaches applied in most work zone impact analysis tools, an interactive process combining microsimulation and logistic regression was developed to imitate diversion behavior dynamically in the upstream of work zones with a number of entrance and exit ramps. Specifically, the logistic regression model based on the field observations was incorporated into a well-calibrated VISSIM model to simulate traffic flow in work zones with diversion behavior. The integration of the two models was achieved via the development of diversion calculation module using a COM interface provided by VISSIM. The comparison between simulated results and field observations suggested that the diversion calculation module using logistic regression can simulate the queue propagation process due to lane closure in an efficient and effective manner. It was demonstrated that the interactive process can improve work zone impact analysis by using real-time traffic feedback information to emulate the diversion phenomenon upstream of work zones.