Wrong-way Driving Crashes Research Articles

Leveraging text mining approach to explore research roadmap and future direction of wrong-way driving crash studies

This study delves into the wrong-way driving (WWD) research performed in the United States over the past five decades. The study employs a text network to summarize and synthesize major themes, data sources, and collaboration efforts from 123 previously published WWD articles collected from various online databases. The analysis shows that the majority of WWD studies were conducted between 2014 and 2020. Throughout the entire period, the primary focuses have been on WWD countermeasures, freeways, exit ramps, contributing factors, driver behavior, and detection systems. Over time, there has been a noticeable shift in the key themes, whereby earlier studies focused on freeways and driver behaviors, while the latter delved into exit ramps, limited access, and contributing factors among others. Most studies were from Florida, Texas, Illinois, and Alabama, with little collaboration of researchers across the States, except for Alabama and Illinois. Further, across the four States, there observed variations in the interests. Studies from Texas and Florida were centered on WWD countermeasures, detection systems, and the use of connected vehicles, while Illinois and Alabama investigated WWD crashes on exit ramps and interchanges. Despite the development and deployment of various countermeasures, there is still a need to develop crash modification factors to examine the effectiveness of the countermeasures. Furthermore, as technology continues to advance, connected and autonomous technology is expected to play a significant role in mitigating the WWD problem. The findings are essential for transportation agencies to evaluate the mitigation efforts and direct resources toward the right course of action.

Identification of high-risk roadway segments for wrong-way driving crash using rare event modeling and data augmentation techniques

Wrong-Way Driving (WWD) crashes are relatively rare but more likely to produce fatalities and severe injuries than other crashes. WWD crash segment prediction task is challenging due to its rare nature, and very few roadway segments experience WWD events. WWD crashes involve complex interactions among roadway geometry, vehicle, environment, and drivers, and the effect of these complex interactions is not always observable and measurable. This study applied two advanced Machine Learning (ML) models to overcome the imbalanced dataset problem and identified local and global factors contributing to WWD crash segments. Five years (2015–2019) of WWD crash data from Florida state were used in this study for WWD model development. The first modeling approach applied four different hybrid data augmentation techniques to the training dataset before applying the XGBoost classification algorithm. In the second model, a rare event modeling approach using the Autoencoder-based anomaly detection method was applied to the original data to identify WWD roadway segments. A third model was applied based on the statistical method to compare the performance of ML models in predicting the WWD segments. The performance comparison of the adopted models showed that the XGBoost model with the Adaptive Synthetic Sampling (ADASYN) method performed best in terms of precision and recall values compared to the autoencoder-based anomaly detection method. The best-performing model was used for the feature analysis with an interpretable machine-learning technique. The SHapley Additive exPlanations (SHAP) values showed that high-intensity developed land use, length of roadway, log of Annual Average Daily traffic (AADT), and lane width were positively associated with WWD roadway segments. The results of this study can be used to deploy WWD countermeasures effectively.

Severity Analysis of Large-Truck Wrong-Way Driving Crashes in the State of Florida

Wrong-way driving (WWD) crashes lead to severe injuries and fatalities, especially when a large truck is involved. This study investigates the factors associated with crash-injury severity in large-truck WWD crashes in Florida. Various driver, roadway, weather, and traffic characteristics were explored as explanatory variables through a random parameter ordered logit model. The study also accounted for heterogeneity by identifying random parameters in the model and introducing interaction effects as potential sources of such heterogeneity. The findings indicate that not using a seatbelt, driving under the influence of drugs, and a driving speed of 50–74 mph were more likely to result in fatal crashes. On the contrary, female drivers, private roadways, and sideswipe collisions showed negative impacts on crash-injury severity. The model identified two random parameters, including a speed of 25–49 mph and early-morning crashes. The interaction effects showed that when driving at a speed of 25–49 mph, young drivers (under 20 years old) and middle-aged drivers (36–50 years old) were the sources of heterogeneity, decreasing crash-injury severity. Understanding the contributing factors of large-truck WWD crashes can help policymakers develop safety countermeasures to reduce the associated injury severity and improve truck safety.

Overview of Intelligent Transportation System Safety Countermeasures for Wrong-Way Driving

Wrong-way driving (WWD) crashes are rare but tend to cause severe injuries and fatalities. When they occur, WWD crashes are mostly head-on and tend to be more severe than any other crash type. Currently, most efforts to mitigate WWD crashes focus on the application of intelligent transportation systems (ITS) technologies. Since the mid-1960s, many agencies have proposed and tested a variety of countermeasures ranging from the conventional, including improvements in signage and pavement markings, to the more advanced, based mainly on ITS. The application of ITS in detecting and deterring WWD crashes involves a combination of several components, such as detection, warning, and action. The main objective of this paper is to provide a comprehensive overview of ITS technologies implemented by different transportation agencies in the mitigation and prevention of WWD crashes. This study proves the importance of ITS technologies that have seen widespread application in recent years. Moreover, according to the evaluation studies of different ITS-related countermeasures, it shows that the countermeasures deployed have been effective in detecting wrong-way drivers and reducing the rate of wrong-way incidents. The results will provide insights for policymakers, engineers, and researchers into the application of ITS for reducing the severity and frequency of WWD crashes and other incidents on highway facilities.

Wrong-way driving crash injury analysis on arterial road networks using non-parametric data mining techniques

Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Previous studies have used descriptive and parametric statistical models to identify factors that affect WWD crash severity on limited access facilities. This study adopted a combination of non-parametric data mining techniques aiming to recognize the pattern of contributing factors that affect the WWD crash severity on non-limited access facilities. These non-parametric methods can handle heterogeneity in crash datasets well. In this study, hierarchical clustering was used to divide the crash dataset into homogeneous clusters. A random forests analysis was used to select important variables, and decision trees and decision rules were generated to show the underlying pattern and interactions between different factors that affect WWD crash severity. The analysis was based on 1,475 WWD crashes that occurred on arterial streets from 2012-2016 in Florida. Results show that head-on collisions, weekend days, high-speed facilities, crashes involving vehicles entering from a driveway, dark-not lighted roadways, older drivers, and driver impairment are important factors that play a crucial role in WWD crash severity on non-limited access facilities.

Factors Affecting Driver Injury Severity in the Wrong-Way Crash: Accounting for Potential Heterogeneity in Means and Variances of Random Parameters

Because of the high percentage of fatalities and severe injuries in wrong-way driving (WWD) crashes, numerous studies have focused on identifying contributing factors to the occurrence of WWD crashes. However, a limited number of research effort has investigated the factors associated with driver injury-severity in WWD crashes. This study intends to bridge the gap using a random parameter logit model with heterogeneity in means and variances approach that can account for the unobserved heterogeneity in the data set. Police-reported crash data collected from 2014 to 2017 in North Carolina are used. Four injury-severity levels are defined: fatal injury, severe injury, possible injury, and no injury. Explanatory variables, including driver characteristics, roadway characteristics, environmental characteristics, and crash characteristics, are used. Estimation results demonstrate that factors, including the involvement of alcohol, rural area, principal arterial, high speed limit (>60 mph), dark-lighted conditions, run-off-road collision, and head-on collision, significantly increase the severity levels in WWD crashes. Several policy implications are designed and recommended based on findings.

Statewide Application of Wrong-Way Driving Crash Risk Modeling and Countermeasures Optimization Algorithm to Identify Optimal Locations for Countermeasure Deployment on Florida Limited Access Facilities

Wrong-way driving (WWD) crashes can have significant impacts on freeway safety and operations. Deploying intelligent transportation systems (ITS) WWD countermeasures at freeway exit ramps can effectively reduce WWD crash risk (WWCR), but these countermeasures are expensive. In this paper, a WWCR segment model and WWD countermeasures optimization algorithm are developed for all Florida limited access facilities (56 roadways with 1,375 exits) to identify the optimal locations for ITS countermeasure deployment. These were previously developed for specific toll-road networks within Florida, but never for a statewide network. Multiple WWCR models were investigated, with the final Poisson model using four-exit segments and 5 years of WWD event data. This model showed that more WWD events and higher crossing road traffic volumes increased WWCR, while certain interchange designs increased or decreased WWCR. Sixty-three segments containing 169 exit ramps without ITS WWD countermeasures were identified as WWD hotspots; these ramps were compared with the 169 ramps with the highest WWCR selected by the optimization algorithm. The algorithm selected 96 ramps not in the hotspots (improved resource utilization of 56.8%) and provided a 38.6% increase in WWCR reduction. Comparing WWD detection and turnaround data from 31 sites with rectangular flashing beacon ITS countermeasures to the optimization indicated a significant positive association between WWCR and turnaround percentage (higher WWCR at sites with lower turnaround percentage), verifying the accuracy of the optimization. By showing the transferability, scalability, accuracy, and benefits of this approach, this paper can help agencies reduce WWD and improve freeway safety and operations.

Estimating Fatality and Injury Savings Because of Deployment of Advanced Wrong-Way Driving Countermeasures on a Toll Road Network

Limited access facility wrong-way driving (WWD) crashes are typically more severe than other crashes. Deploying advanced WWD countermeasures, such as rectangular flashing beacon (RFB) and light-emitting diode (LED) technologies, at exit ramps can reduce WWD crashes, injuries, and fatalities. No previous research has developed a methodology to quantify the potential fatality and injury savings because of future countermeasure deployments. This paper developed such a methodology and applied it to Florida’s Turnpike Enterprise (FTE) toll road network. From 2011–2016, there were 53 FTE WWD crashes, resulting in 16 fatalities and annual injury costs of $37 million. The proportion of these crashes occurring during night-time was 87%. RFB and LED life-cycle injury savings and costs were determined for all 216 FTE exits. The total savings were $424 million for RFBs (benefit–cost [B/C] ratio of 23.20) and $144 million for LEDs (B/C ratio of 13.13). Deploying countermeasures at the 103 exits with the highest B/C ratios would provide 70% of the total possible savings by equipping 40% of the ramps. For the same capital investment, RFBs provide more savings than LEDs. Spending $1 million to deploy RFBs will provide similar savings as spending $3.4 million to deploy LEDs. Evaluating the existing FTE RFB and LED ramps shows that RFBs are more effective at night-time and can provide three times the savings of LEDs. The results of this paper show the improved performance of RFBs over LEDs and provide an example that other agencies could follow to identify savings and cost-effectively deploy advanced WWD countermeasures.

Modeling Wrong-way Driving (WWD) crash severity on arterials in Florida

Wrong-way Driving (WWD) is the movement of a vehicle in a direction opposite to the one designated for travel. WWD studies and mitigation strategies have exclusively been focused on limited-access facilities. However, it has been established that WWD crashes on arterial corridors are also severe and relatively more common. As such, this study focused on determining factors influencing the severity of WWD crashes on arterials. The analysis was based on five years of WWD crashes (2012–2016) that occurred on state-maintained arterial corridors in Florida. Police reports of 2,879 crashes flagged as “wrong-way” were downloaded and individually reviewed. The manual review of the police reports revealed that of the 2,879 flagged WWD crashes, only 1,890 (i.e., 65.6 %) occurred as a result of a vehicle traveling the wrong way. The Bayesian partial proportional odds (PPO) model was used to establish the relationship between the severity of these WWD crashes and different driver attributes, temporal factors, and roadway characteristics. The following variables were significant at the 90 % Bayesian Credible Interval (BCI): day of the week, lighting condition, presence of work zone, crash location, age and gender of the wrong-way driver, airbag deployment, alcohol use, posted speed limit, speed ratio (i.e., driver’s speed over the posted speed limit), and the manner of collision. Based on the model results, specific countermeasures on Education, Engineering, Enforcement, and Emergency response are discussed. Potential Transportation Systems Management and Operations (TSM&O) strategies for WWD detection systems on arterials to minimize WWD frequency and severity are also proposed.

Comparative Analysis of Freeway Exit Ramp Terminal Design Practices to Deter Wrong-Way Driving in Different States

Although wrong-way driving (WWD) crashes are rare compared with other crashes, the severe outcomes resulting from these crashes make them an important traffic safety issue, especially on freeways. The initial point of origin for the majority of WWD crashes is the exit ramp terminal. During 2009–2013, the exit ramp terminals of full diamond and partial cloverleaf interchanges in Alabama experienced considerably higher frequency of wrong-way entries compared with those in Illinois. In this study, a comparative analysis is conducted between these two states to compare the differences in exit ramp terminal design practices and determine the differences that might have caused the relatively higher frequency of wrong-way entries at the exit ramp terminals in Alabama. The comparative analysis revealed that there is relatively higher usage of certain geometric design features and traffic control devices in Illinois, which contributed to deterring WWD. The lessons learned from this study can potentially benefit the 4E community (i.e., enforcement, education, emergency response, and engineering) in further understanding the best practices on off-ramp terminal design and traffic control devices features that have the potential to reduce WWD crashes on freeways.

Benefit–Cost Analyses of Rectangular Flashing Beacon Wrong-Way Driving Countermeasures on Toll Road Exit Ramps in Florida

In recent years, rectangular flashing beacons (RFBs) and other technologies have been used as wrong-way driving (WWD) countermeasures on limited access facilities. Studies have shown that these devices effectively reduce WWD, but no research has compared the financial benefits and costs of these countermeasures. Three different methodologies were used to conduct benefit–cost analyses for RFB WWD countermeasures installed on Central Florida toll road exit ramps. The studied benefits included savings from reductions in WWD crashes, non-crash events, and injuries, whereas costs included equipment, installation, and maintenance costs. For the first two methodologies, the reduction in WWD crash risk (WWCR) at the RFB-equipped ramps was determined. This WWCR considered non-crash WWD events, interchange design, and traffic volumes. Different measures of effectiveness (turn-around percentage of detected wrong-way vehicles at the RFB ramps and reduction in WWD 911 calls and citations at the RFB interchanges compared with similar comparison interchanges without RFBs) were used in these two methodologies to estimate the WWCR reduction and associated savings. For the third methodology, the relationship between WWD crashes and non-crash events was used to determine the average savings for WWD 911 calls and citations. Before–after analyses were then conducted to determine the individual reductions in WWD 911 calls and citations. Applying these three methods resulted in life-cycle benefit–cost ratios ranging from 2.49 to 4.10 (crash savings) and from 4.77 to 7.20 (injury savings). Other agencies could use these methodologies to determine the benefits of WWD countermeasures or other technologies with limited crash data.

An optimization approach for deployment of intelligent transportation systems wrong-way driving countermeasures

The nature of wrong-way driving (WWD) crashes on limited access facilities makes it difficult for agencies to combat them effectively. WWD countermeasures equipped with Intelligent Transportation Systems (ITS) technologies, such as warning lights and detection devices, have been proven to reduce WWD. However, agencies often cannot deploy these ITS countermeasures at all exit ramps due to their expense. This paper discusses an innovative WWD countermeasure optimization approach to help agencies identify the optimal deployment locations based on available resources. The approach consists of a WWD crash risk (WWCR) model and a WWD countermeasures optimization algorithm. The WWCR model uses non-crash WWD events, interchange designs, and traffic volumes to predict the number of WWD crashes on multi-exit segments of limited access facilities. Then, the optimization algorithm uses the model results to identify the best exits for ITS countermeasure deployment based on WWCR reduction, available resources, and other applicable constraints. This approach was applied to the Florida’s Turnpike Enterprise (FTE) toll road network. Twenty-four segments were identified as WWD hotspots due to high WWCR. Three different optimization scenarios were tested to show how different constraints affect the results. These scenarios resulted in 38% to 41% of the maximum possible WWCR reduction by equipping only 39 of the 196 FTE ramps (20%) and could help FTE better utilize its investment by 36% compared to only equipping ramps in the identified 24 WWD hotspots. Other agencies could personalize this approach based on their available resources, and preferred WWD countermeasures to achieve similar benefits.

Comparison of two intelligent transportation systems Wrong-Way driving countermeasures currently deployed on Florida toll roads

Wrong way driving (WWD) crashes on high-speed limited access facilities often cause severe injuries and deaths. Conventional “Wrong Way” signs can reduce WWD events but can be insufficient in some cases. Intelligent Transportation Systems (ITS) WWD countermeasures can more effectively notify wrong-way drivers of their mistake. This paper compares the safety performance of two types of ITS WWD countermeasures implemented in Florida: Light-Emitting Diode (LED) signs in South Florida (which include one set of signs and one camera) and Rectangular Flashing Beacon (RFB) signs in Central Florida (which include two sets of signs and three cameras). The reduction in WWD events (911 calls and citations) and the percentage of wrong-way drivers who self-corrected their WWD behavior were used as surrogate safety performance measures instead of crashes, since WWD crashes are rare. Chi-squared tests revealed a significant reduction in WWD events at the LED and RFB treated sites compared to control sites without these countermeasures. Comparison group analyses indicated that the LED and RFB countermeasures reduced WWD events by 48.1% and 69.4%, respectively. Additionally, photographs taken by cameras on the countermeasures and/or closed-circuit television cameras monitored by the traffic management centers showed that over 16% of the 72 detected wrong-way vehicles self-corrected at the LED sites and 81% of the 353 detected wrong-way vehicles self-corrected at the RFB sites. The methods and results in this paper can help transportation agencies throughout the United States identify the most suitable WWD countermeasures and evaluate their performance.

Access Control Techniques to Mitigate Wrong-Way Driving Activities on Multilane Divided Highways: Case Studies in Alabama

This paper documents the results of a second phase statewide research project on wrong-way driving (WWD) crashes funded by the Alabama Department of Transportation. The purpose of this effort is to investigate why people drive in the wrong direction on the multilane divided highways in Alabama. The field data were collected at locations where there were WWD crashes or incidents over 5 years. Video cameras were used to monitor the WWD activities for 48 h from Friday to Sunday. The WWD activities were analyzed by the research team watching the video data. The study found that drivers tend to drive in the wrong direction as a result of driveways with a close median opening, poor front access control, lack of backage road connection, and limited sight distance because of large median widths or grade difference. The study also found that there is a high frequency of intentional WWD at some access points connecting gas stations, business, and residential areas on divided highways. It is recommended that access management techniques are applied to mitigate WWD activities on divided highways based on four case studies, including (1) providing closer exclusive U-turn median openings for indirect left turns; (2) improving poor front access control, for example installing a channelized island for right-in and right-out driveways; (3) providing backage road connections for close mixed land use; and (4) improving sight distance for minor-road traffic at unsignalized intersections with large grade difference or wide median widths.

Characteristics of Law Enforcement Response to Wrong-Way Driving Events in Florida

Wrong-way driving (WWD) can result in severe crashes. By responding quickly to WWD dispatch calls, law enforcement officers (LEOs) could stop the wrong-way vehicle before a crash occurs. This paper analyzed law enforcement (LE) response times to WWD dispatch calls in Florida between January 2003 and April 2018 to determine significant effects. The average LE response time was much lower for 2013 onward than before 2013. Average response time was lower during nighttime and in urban areas and was higher for county roads and toll roads. Two ordinal logit models were also developed. These models found that dispatch calls closer to regional traffic management centers or rest areas, in urban areas, or on state roads or local roads typically had lower response times than calls not in these locations. In addition, WWD dispatch calls on toll roads had lower response times than calls on non-toll limited access facilities. Intelligent transportation system (ITS) WWD countermeasures with flashing signs, detection devices, cameras, and direct communication with traffic management centers also help LEOs respond quickly to detected WWD events and more accurately identify the vehicle’s location. As of June 2018, these technologies located at 70 toll road exit ramps in Florida have prompted 307 wrong-way drivers to turn around, possibly preventing nine crashes and saving LEOs over 116 h. The results of this research can help identify locations where increasing LEO presence or installing ITS WWD countermeasure technologies could help reduce WWD response time and WWD crashes, potentially saving lives.

Modeling Wrong-Way Driving Entries at Limited Access Facility Exit Ramps in Florida

Wrong-way driving (WWD) is a dangerous behavior which poses a significant safety risk on limited access facilities. As WWD crashes are rare, it is difficult to build credible statistical models based solely on crashes. Modeling other WWD events, such as citations and 911 calls, can result in more reliable models. Even though these WWD events do not always result in a crash, they can be an effective surrogate for WWD crashes. Analysis of Florida limited access exit ramps found that ramps with multiple WWD crashes from 2011 to 2015 tended to have more WWD citations and 911 calls (WWD entries). Additionally, areas with high WWD crash densities also had high WWD entry densities and 68% of WWD crashes had an associated citation, 911 call, or both. These results show that modeling WWD entries can provide insights into WWD crashes. A model was developed for Florida limited access facilities to identify roadway factors and traffic characteristics of exit ramp terminals that influence WWD entries. This model indicated that interchange type, intersection angle of exit ramp terminals, presence of tolling at the entrance ramp, presence of a channelizing island between the exit ramp lanes, number of lanes on the exit ramp, area (rural or urban), and traffic volumes significantly affect the likelihood of WWD entries at exit ramps. With this model, transportation agencies can better predict WWD entries at exit ramps; identify suitable locations for possible countermeasures; and improve their current design, signing, and pavement marking practices while still following national and state standards.

Modeling the Risk of Wrong-Way Driving Entry at the Exit Ramp Terminals of Full Diamond Interchanges

Wrong-way driving (WWD) crashes are a critical safety issue on freeways. Although these crashes are rare and random in nature, they often result in severe injuries and/or fatalities. Typically, exit ramp terminals are the initial point of entry for wrong-way (WW) drivers on freeways. Therefore, it is important for transportation agencies to identify the exit ramp terminals with higher possibility of WW entries and apply safety countermeasures to reduce the chances of their occurrence. However, the random nature of WWD crashes and the difficulty in identifying the actual entry points makes it hard for transportation agencies to assess the risk of WWD at a particular exit ramp terminal and apply countermeasures accordingly. This study developed mathematical models for predicting the risk of WW entries at the exit ramp terminals of full diamond interchanges. The geometric design features, usage of traffic control devices, area type where the interchanges are located, and annual average daily traffic (AADT) at the exit ramp terminals with or without history of WWD were used as potential predictors of WW entry. Transportation agencies can use these models to assess the risk of WW entries at the exit ramp terminals within their jurisdictions and consider possible countermeasures. They also can be applied during the design phase to determine the combination of geometric design features and traffic control devices that ensures the least possibility of WW entry.

Wrong-Way Driving: A Regional Transportation Systems Management and Operations Approach to a Regional Problem

Wrong-way driving (WWD) has been problematic on United States highways for decades despite its rare occurrence. Since WWD crashes are rare, recent researchers have studied WWD non-crash events such as WWD 911 calls and WWD citations to understand the overall nature and trend of WWD. This paper demonstrates the regional nature of the WWD problem and proposes regional transportation systems management and operations (TSM&O) solutions to combat this problem. Specifically, it was found that 11% of all WWD multi-data events (e.g., multiple 911 calls for the same WWD event) involved travel from one county to another. Additionally, 30% of all WWD single-data and multi-data events occurred at or near interchanges between two limited access highways in counties with multiple operating agencies. This indicates that a significant proportion of WWD events could potentially travel from one limited access facility to another. Moreover, 28% of WWD events occurred on limited access facilities shared by multiple operating agencies. To emphasize the regional nature of WWD, this paper determined the vulnerable demographic groups in different regions of Florida by developing WWD crash and citation prediction models. The models’ findings indicate that certain demographic groups (e.g., elderly drivers) increase WWD risk. The models’ results can be used to improve driver education and increase law enforcement presence in high risk WWD locations. Regional TSM&O solutions, such as coordination and communication among agencies and traffic management centers (TMCs), law enforcement co-location with TMCs, and strengthening statewide TSM&O programs to manage WWD events are also proposed.

A Wrong-Way Driving Crash Risk Reduction Approach for Cost-Effective Installation of Advanced Technology Wrong-Way Driving Countermeasures

Wrong-way driving (WWD) is hazardous on high-speed limited access facilities. Traditional signage and pavement markings will not always prevent intoxicated or confused drivers from entering these facilities the wrong way. To better alert wrong-way drivers, agencies can consider WWD countermeasures equipped with advanced technologies (including warning lights and detection devices) on exit ramps. However, these countermeasures can be expensive for agencies to install on entire roadways or corridors. This paper develops an innovative WWD crash risk (WWCR) reduction approach consisting of a WWCR segment model and an optimization algorithm that can be used to help agencies decide where to install WWD countermeasures. The approach examines segments of limited access facilities to determine the interchanges where advanced technology WWD countermeasures will provide the greatest reduction in WWCR based on an agency’s available resources. A hypothetical example application of this approach is shown for the Central Florida Expressway Authority toll road network. This example shows how the WWCR reduction approach can help agencies identify the optimal investment level and high-risk locations. It also shows how the optimization algorithm can provide significant cost savings compared with equipping entire roadway segments (57% savings) or corridors (83% savings). Agencies can customize the algorithm by adding constraints to represent various scenarios and make the algorithm applicable for networks ranging from single roadways to statewide systems. This WWCR reduction approach could be utilized by agencies nationwide to help them save resources and prioritize investment.

Evaluating Wrong-Way Driving Characteristics, Countermeasures, and Alert Dissemination Methods through Driver and Law Enforcement Surveys

Wrong-way driving (WWD) on limited-access highways is a serious driver error that could be fatal for both the wrong-way driver and right-way drivers. Agencies and law enforcement officers (LEOs) can spend valuable time and resources responding to WWD events. A survey of 247 LEOs found that despite being dispatched multiple times per year in response to WWD, most issue fewer than one WWD citation per year. In the survey, LEOs also gave their perspectives on the characteristics of WWD events and the influences behind WWD. Agencies typically use dynamic message signs (DMS) for notifying right-way drivers of WWD events, but little research has considered solutions that are less costly and potentially farther-reaching. A survey of 900 Florida toll-road drivers found that drivers rely on navigation devices, apps, or both, significantly more than DMS for traveler information. Drivers were receptive to receiving WWD alerts through navigation services and indicated that they would react to WWD events in a way that is beneficial to highway safety. Crowdsourcing technologies were considered to generate WWD information and quickly disseminate alerts to drivers and officers. Additional survey questions answered by a combined group of 2,052 drivers, LEOs, and agency officials determined that among advanced WWD countermeasures, most preferred two sets of “Wrong Way” signs equipped with rectangular flashing beacons over one set of signs with light emitting diodes. Combining advanced countermeasures with innovative right-way driver notification methods could enhance law enforcement efficiency, reduce WWD crashes, and provide safer conditions for both drivers and officers.