Simulation Exploration of the Potential of Connected Vehicles in Mitigating Secondary Crashes

Secondary crashes (SCs) on freeways are a major concern for traffic incident management systems. Studies have shown that their occurrence is significant and can lead to deterioration of traffic flow conditions on freeways in addition to injury and fatalities, albeit their magnitudes are relatively low when compared to primary crashes. Due to the limited nature of crash data in analyzing freeway SCs, surrogate measures provide an alternative for safety analysis for freeway analysis using conflict analysis. Connected Vehicles (CVs) have seen compelling technological advancements since the concept was introduced in the 1990s. In recent years, CVs have emerged as a feasible application with many safety benefits especially in the urban areas, that can be deployed in masses imminently. This study used a freeway model of a road segment in Florida’s Turnpike system in VISSIM microscopic simulation software to generate trajectory files for conflict analysis in SSAM software, to analyze potential benefits of CVs in mitigating SCs. The results showed how SCs could potentially be reduced with traffic conflicts being decreased by up to 90% at full 100% composition of CVs in the traffic stream. The results also portrayed how at only 25% CV composition, there was a significant reduction of conflicts up to 70% in low traffic volumes and up to 50% in higher traffic volumes. The statistical analysis showed that the difference in average time-to-collision surrogate measure used in deriving conflicts was significant at all levels of CV composition

Examining Route Diversion And Multiple Ramp Metering Strategies For Reducing Real-time Crash Risk On Urban Freeways

Recent research at the University of Central Florida addressing crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical models capable of calculating the crash risk on the freeway (Abdel-Aty et al., 2004; 2005, Pande and Abdel-Aty, 2006). These models yield the rear-end and lane-change crash risk along the freeway in real-time by using static information at various locations along the freeway as well as real-time traffic data that is obtained from the roadway. Because these models use the real-time traffic data, they are capable of calculating the respective crash risk values as the traffic flow changes along the freeway. The purpose of this study is to examine the potential of two Intelligent Transportation System strategies for reducing the crash risk along the freeway by changing the traffic flow parameters. The two ITS measures that are examined in this research are route diversion and ramp metering. Route diversion serves to change the traffic flow by keeping some vehicles from entering the freeway at one location and diverting them to another location where they may be more efficiently inserted into the freeway traffic stream. Ramp metering alters the traffic flow by delaying vehicles at the freeway on-ramps and only allowing a certain number of vehicles to enter at a time. The two strategies were tested by simulating a 36.25 mile section of the Interstate-4 network in the PARAMICS micro-simulation software. Various implementations of route diversion and ramp metering were then tested to determine not only the effects of each strategy but also how to best apply them to an urban freeway. Route diversion was found to decrease the overall rear-end and lane-change crash risk along the network at free-flow conditions to low levels of congestion. On average, the two crash risk measures were found to be reduced between the location where vehicles were diverted and the location where they were reinserted back into the network. However, a crash migration phenomenon was observed at higher levels of congestion as the crash risk would be greatly increased at the location where vehicles were reinserted back onto the network. Ramp metering in the downtown area was found to be beneficial during heavy congestion. Both coordinated and uncoordinated metering algorithms showed the potential to significantly decrease the crash risk at a network wide level. When the network is loaded with 100 percent of the vehicles the uncoordinated strategy performed the best at reducing the rear-end and lane-change crash risk values. The coordinated strategy was found to perform the best from a safety and operational perspective at moderate levels of congestion. Ramp metering also showed the potential for crash migration so care must be taken when implementing this strategy to ensure that drivers at certain locations are not put at unnecessary risk. When ramp metering is applied to the entire freeway network both the rear-end and lane-change crash risk is decreased further. ALINEA is found to be the best network-wide strategy at the 100 percent loading case while a combination of Zone and ALINEA provides the best safety results at the 90 percent loading case. It should also be noted that both route diversion and ramp metering were found to increase the overall network travel time. However, the best route diversion and ramp metering strategies were selected to ensure that the operational capabilities of the network were not sacrificed in order to increase the safety along the freeway. This was done by setting the maximum allowable travel time increase at 5% for any of the ITS strategies considered

A Framework for Developing and Integrating Effective Routing Strategies Within the Emergency Management Decision-Support System, Research Report 11-12

This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San José, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would be effective in the event of a no-notice disaster. The modeled network required a large amount of data on network geometry, signal timings, signal coordination schemes, and turning-movement volumes. Turning-movement counts at intersections were used to validate the network with the empirical formula-based measure known as the GEH statistic. Once the base network was tested and validated, various scenarios were modeled to estimate evacuation and emergency vehicle arrival times. Based on these scenarios, a variety of emergency plans for San José’s downtown traffic circulation were tested and validated. The model could be used to evaluate scenarios in other communities by entering their community-specific data

Analyzing Benefits of Connected Vehicle Technologies During Incidents on Freeways and Diversion Strategies Implementation: A Microsimulation-Based Case Study of Florida\u27s Turnpike

The full utilization of connected vehicles (CVs) is highly anticipated to become a reality soon. As CVs become increasingly prevalent in our roadway network, connected technologies have enormous potential to improve safety. This study conducted a microscopic simulation to quantify the benefits of CVs in improving freeway safety along a 7.8-mile section on Florida’s Turnpike (SR-91) system. The simulation incorporated driver compliance behavior in a CV environment. The simulation was implemented via an existing VISSIM network model partially developed by the Florida Department of Transportation (FDOT). In addition, the study analyzed how CVs would assist in detour operations as a strategy for congestion management during traffic incidents on freeways. The Surrogate Safety Assessment Model (SSAM) software was used to evaluate the benefits of CVs based on time-to-collision (TTC) as the performance measure. The TTC was evaluated at various CV market penetration rates (MPRs) of 0%, 25%, 50%, 75%, and 100%. The results showed a decreasing trend of conflicts for morning and evening peak hours, especially from 25% to 100% CV MPRs. The benefits were statistically significant at a 95% confidence level for high CV MPR (above 25%). Upon an incident on the freeway, at higher CV MPRs simulations, the detour strategy seemed to reduce travel time on the freeway. Besides, the detour strategy was more helpful when the incident clearance duration lasted more than 30 minutes. Findings from this study may help the incident management process prepare for detour strategies based on the severity of the incident at hand and could explain the importance of CVs in supporting warning and management strategies for drivers to improve safety on freeways. Keywords: Conflicts, Connected Vehicles, Driver Compliance Rate, Detour, Incident Modeling, Safety Surrogate Measure

Evaluating the Performance of Cooperative Merging Assistance System for Aging Drivers

Freeway merging maneuvers demand considerable attention by drivers and are among the more complex operations drivers must perform on freeways. Aging drivers, a growing population in the United States, face added challenges when merging. This study utilized Vissim models created in a previous study that modeled the behavior of aging drivers during freeway merging. An algorithm for Cooperative Merging Assistance System (CMAS) that utilizes Connected Vehicle (CV) technology was developed in this study. The Vissim models were created for two interchanges on I-75 in Fort Myers, Florida, each with different geometric characteristics. Acceleration lane lengths of 1000ft and 1500ft were analyzed in this study, and the CV environment was created in Vissim through the Component Object Model (COM) Interface. A sensitivity analysis was conducted by varying CV penetration rates, composition of aging on-ramp drivers, and mainline and on-ramp traffic flows to analyze the effects of CV technology under different levels of service (LOSs). Merging location, merging speed and vehicle interaction states (braking for lane change, emergency stop and cooperative braking) together with deceleration rate were the measures of effectiveness (MOEs) considered. Findings showed the number of aging drivers merging late onto the freeway can be decreased by up to 60.0% when CMAS was employed, while there was no significant change in merging speed at 95% confidence level when CMAS was employed. Furthermore, the results showed that CMAS reduced the percentages of aging drivers braking for lane change or emergency stop and also hard braking by up to 100% for low traffic conditions (LOS A and B). A maximum reduction of 82.2% was observed for cooperative braking of mainline vehicles when CMAS was employed. The reductions in interaction states were significant at 95% confidence level according to Mann-Kendall trend test

Exploring The Potential Of Combining Ramp Metering And Variable Speed Limit Strategies For Alleviating Real-time Crash Risk On Urban Freeways

Research recently conducted at the University of Central Florida involving crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical and neural networks models that are capable of determining the crash risk on the freeway (Abdel-Aty et al., 2004; 2005, Pande and Abdel-Aty, 2006). These models are able to calculate rear-end and lane-change crash risks along the freeway in real-time through the use of static information at various locations along the freeway as well as real-time traffic data obtained by loop detectors. Since these models use real-time traffic data, they are capable of calculating rear-end and lane-change crash risk values as the traffic flow conditions are changing on the freeway. The objective of this study is to examine the potential benefits of combining two ITS strategies (Ramp Metering and Variable Speed Limits strategies) for reducing the crash risk (both rear-end and lane-change crash risks) along the I-4 freeway. Following this aspect, a 36.25-mile section of I-4 running though Orlando, FL was simulated using the PARAMICS micro-simulation program. Gayah (2006) used the same network to examine the potential benefits of two ITS strategies separately (Route Diversion and Ramp Metering) for reducing the crash risk along the freeway by changing traffic flow parameters. Cunningham (2007) also used the same network to examine the potential benefits of implementing Variable Speed Limits strategy for reducing the crash risk along the freeway. Since the same network is used, the calibration and validation procedures used in this study are the same as these previous two studies. This study simulates three volume loading scenarios on the I-4 freeway. These are 60, 80 and 90 percent loading scenarios. From the final experimental design for the 60 % loading, it was concluded that implementing VSL strategy only was more beneficial to the network than either implementing Ramp Metering everywhere (through the whole network) in conjunction with VSL everywhere or implementing Ramp Metering downtown (in downtown areas only) in conjunction with VSL everywhere. This was concluded from the comparison of the results of this study with the results from Cunningham (2007). However, either implementing Ramp Metering everywhere or downtown in conjunction with VSL everywhere showed safety benefits across the simulated network as well as a reduction in the total travel time. The best case for implementing Ramp Metering everywhere in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of half speed zone and a speed change time of 5 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. And the best case for implementing Ramp Metering downtown in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of half speed zone and a speed change time of 10 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. For the 80 % loading, it was concluded that either implementing Ramp Metering everywhere in conjunction with VSL everywhere or implementing Ramp Metering downtown in conjunction with VSL everywhere was more beneficial to the network than implementing VSL strategy only. This was also concluded from the comparison of the results of this study with the results from Cunningham (2007). Moreover, it was concluded that implementing Ramp Metering everywhere in conjunction with VSL everywhere showed higher safety benefits across the simulated network than implementing Ramp Metering downtown in conjunction with VSL everywhere. Also, both of them increased the total travel time a bit, but this was deemed acceptable. Additionally, both of them had successive fluctuations and variations in the average lane-change crash risk vs. time step. The best case for implementing Ramp Metering everywhere in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 5 mph, a speed change distance of half speed zone and a speed change time of 30 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. And the best case for implementing Ramp Metering downtown in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 5 mph, a speed change distance of half speed zone and a speed change time of 30 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. Searching for the best way to implement both Ramp Metering and VSL strategies in conjunction with each other, an indepth investigation was conducted in order to remove the fluctuations and variations in the crash risk with time step (through the entire simulation period). The entire simulation period is 3 hours, and each time step is 5 minutes, so there are 36 time steps representing the entire simulation period. This indepth investigation led to the idea of not implementing VSL at consecutive zones (using either a gap of one zone or more). Then this idea was applied for the best case of implementing Ramp Metering and VSL everywhere at the 80 % loading, and the successive fluctuations and variations in the crash risk with time step were removed. Moreover, much better safety benefits were found. So, this confirms that this idea was very beneficial to the network. For the 90 % loading, it was concluded that implementing Ramp Metering strategy only (Zone algorithm in downtown areas, and ALINEA algorithm in non downtown areas) was more beneficial to the network than implementing Ramp Metering everywhere in conjunction with VSL everywhere. This was concluded from the comparison of the results of this study with the results from Gayah (2006). However, implementing Ramp Metering everywhere in conjunction with VSL everywhere showed safety benefits across the simulated network as well as a reduction in the total travel time. The best case was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of the entire speed zone and a speed change time of 20 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. In summary, Ramp Metering was more beneficial at congested situations, while Variable Speed Limits were more beneficial at free-flow conditions. At conditions approaching congestion, the combination of Ramp Metering and Variable Speed Limits produced the best benefits. These results illustrate the significant potential of ITS strategies to improve the safety and efficiency of urban freeways

Developing and Simulating a Communication Plan for Mitigation of Secondary Crashes: Leveraging Connected Vehicle Technologies

The Federal Highway Administration (FHWA) has identified secondary crashes (SCs) on United States (US) highways as one of the core transportation issues that needs to be addressed. These crashes contribute to increased property damage, injuries, and fatalities and a decline in traffic flow conditions on freeways and adjacent arterials. The purpose of this study was to 1) propose a communication plan that leverages connected vehicle (CV) technologies to increase awareness to road users to target the mitigation of SCs, and 2) to evaluate the potential benefits of the proposed communication plan with CV technologies in alleviating SCs. This study used VISSIM microscopic software to model a freeway road segment on Florida’s Turnpike system and Lyons Road, a parallel arterial. The software was used to replicate the proposed communication plan and CV applications to issue advisories, such as speed, lane-change, or detour advisory to drivers during an incident. A safety evaluation was performed using the Surrogate Safety Assessment Model (SSAM) software by importing trajectory files from VISSIM to analyze generated traffic conflicts. The change in the number of simulated conflicts was used to evaluate the mitigation of SCs. The results showed significant safety benefits using the proposed communication plan with CV technologies. A conflict reduction of up to 98% was observed with full penetration of CVs at low traffic volume. Statistical analysis indicated that different penetration rates of CVs were required to achieve significant safety benefits depending on the analyzed scenario, i.e., traffic volume, number of lanes closed, side of the road the lane is closed, and dissemination of detour advisory

Advanced Quantitative Methods for Imminent Detection of Crash Prone Conditions and Safety Evaluation

Crashes can be accurately predicted through reliable data sources and rigorous statistical models; and prevented through data-driven, evidence-based traffic control strategies. Both predictive analysis and analysis to estimate the causal effect of traffic variables of real-time crashes are instrumental to crash prediction and a better understanding of the mechanism of crash occurrence. However, the research on the second analysis type is very limited for real-time crash prediction; and the conventional predictive analysis using inductive loop detector data has accuracy issues related to inconsistently and distantly spaced loop detectors. The effectiveness of traffic control strategies for improving safety performance cannot be measured and compared without an appropriate traffic simulation application. This dissertation is an attempt to address these research gaps. First, it conducts the propensity score based analysis to assess the causal effect of speed variation on crash occurrence using the crash data and ILD data. As a casual analysis method, the propensity score based model is applied to generate samples with similar covariate distributions in both high- and low-speed variation groups of all cases. Under this setting, the confounding effects are removed and the causal effect of speed variation can be obtained. Second, it conducts a predictive analysis on lane-change related crashes using lane-specific traffic data collected from three ILD stations near a crash location. The real-time traffic data for the two lanes – the vehicle’s lane (subject lane) and the lane to which that a vehicle intends to change (target lane) – are more closely related with lane-change related crashes, as opposed to congregated traffic data for all lanes. It is found that lane-specific variables are appropriate to study the lane-change frequency and the resulting lane-change related crashes. Third, it conducts a predictive analysis on real-time crashes using simulated traffic data. The purpose of using simulated traffic data rather than real data is to mitigate the temporal and spatial issues of detector data. The cell transmission model (CTM), a macroscopic simulation model, is employed to instrument the corridor with a uniform and close layout of virtual detector stations that measure traffic data when physical stations are not available. Traffic flow characteristics at the crash site are simulated by CTM 0-5 minutes prior to a crash. It shows that the simulated traffic data can improve the prediction performance by accounting for the spatial-tempo issue of ILD data. Fourth, it presents a novel approach to modeling freeway crashes using lane-specific simulated traffic data. The new model can not only account for the spatial-tempo issues of detector data but also account for heterogeneous traffic conditions across lanes using a lane-specific cell transmission model (LSCTM). The LSCTM illustrates both discretionary lane-changing (DLC) and mandatory lane-changing (MLC) activities. This new approach presents a viable alternative for utilizing traffic simulation models for safety analysis and evaluation. Last, it develops a crash prediction and prevention application (CPPA) based on simulated traffic data to detect crash-prone conditions and to help select the desirable traffic control strategies for crash prevention. The proposed application is tested in a case study with VSL strategies, and results show that the proposed crash prediction and prevention method could effectively detect crash-prone conditions and evaluate the safety and mobility impacts of various VSL alternatives before their deployment. In the future, the application will be more user-friendly and can provide both online traffic operations support as well as offline evaluation of various traffic control operations and methods

Safety analysis of interchange functional areas

Limited access facilities, such as freeways and expressways, are generally designed to the highest standards among public roads. Consequently, these facilities demonstrate crash, injury, and fatality rates that are significantly lower than other road facility types. However, these rates are generally elevated in the immediate vicinity of interchanges due to increases in traffic conflicts precipitated by weaving, merging, and diverging traffic. Given the extensive costs involved in interchange construction, it is important to discern the expected operational and safety impacts of various design alternatives. To this end, the objective of this study was to analyze the safety performance within the functional areas of interchanges. The study involves the integration of traffic crash, volume, and roadway geometric information using data from 2010 to 2014 from the state of Iowa in order to assess the relationships between these factors and frequency of crashes within the interchange functional area. Separate analyses were conducted for the freeway mainline and ramp connections. Safety performance functions (SPFs) were estimated for the interchange mainline and ramps using negative binomial regression models, and random effects models were estimated to account correlation in crash counts at the same location over time. The results from this study suggest that speed limit and interchange configuration have a significant impact on crash rates. Lower ramp advisory speeds (10 mph to 35 mph) were associated with fewer crashes on-ramps. Off-ramps were also associated with elevated crash risk in comparison to on-ramps and freeway-to-freeway ramps. Comparison SPF models were also developed using Iowa-specific data to relate the outcomes of these simple SPFs with Florida-specific SPFs and the national default SafetyAnalyst SPFs with varying results