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EXAMINING ROUTE DIVERSION AND MULTIPLE RAMP METERING STRATEGIES FOR REDUCING REAL-TIME CRASH RISK ON URBAN FREEWAYS
Title
EXAMINING ROUTE DIVERSION AND MULTIPLE RAMP METERING STRATEGIES FOR REDUCING REAL-TIME CRASH RISK ON URBAN FREEWAYS.
Creator
Gayah, Vikash, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description
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....
Show moreRecent 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.
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Date Issued
2006
Identifier
CFE0001437, ucf:47054
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001437
EXAMINING DYNAMIC VARIABLE SPEED LIMIT STRATEGIES FOR THE REDUCTION OF REAL-TIME CRASH RISK ON FREEWAYS
Title
EXAMINING DYNAMIC VARIABLE SPEED LIMIT STRATEGIES FOR THE REDUCTION OF REAL-TIME CRASH RISK ON FREEWAYS.
Creator
Cunningham, Ryan, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description
Recent research at the University of Central Florida involving crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical models 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 the 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 the real-time traffic data...
Show moreRecent research at the University of Central Florida involving crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical models 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 the 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 the 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 variable speed limit implementation techniques for reducing the crash risk along the freeway. Variable speed limits is an ITS strategy that is typically used upstream of a queue in order to reduce the effects of congestion. By lowering the speeds of the vehicles approaching a queue, more time is given for the queue to dissipate from the front before it continues to grow from the back. This study uses variable speed limit strategies in a corridor-wide attempt to reduce rear-end and lane-change crash risks where speed differences between upstream and downstream vehicles are high. The idea of homogeneous speed zones was also introduced in this study to determine the distance over which variable speed limits should be implemented from a station of interest. This is unique since it is the first time a dynamic distance has been considered for variable speed limit implementation. Several VSL strategies were found to successfully reduce the rear-end and lane-change crash risks at low-volume traffic conditions (60% and 80% loading conditions). In every case, the most successful treatments involved the lowering of upstream speed limits by 5 mph and the raising of downstream speed limits by 5 mph. In the free-flow condition (60% loading), the best treatments involved the more liberal threshold for defining homogeneous speed zones (5 mph) and the more liberal implementation distance (entire speed zone), as well as a minimum time period of 10 minutes. This treatment was actually shown to significantly reduce the network travel time by 0.8%. It was also shown that this particular implementation strategy (lowering upstream, raising downstream) is wholly resistant to the effects of crash migration in the 60% loading scenario. In the condition approaching congestion (80% loading), the best treatment again involved the more liberal threshold for homogeneous speed zones (5 mph), yet the more conservative implementation distance (half the speed zone), along with a minimum time period of 5 minutes. This particular treatment arose as the best due to its unique capability to resist the increasing effects of crash migration in the 80% loading scenario. It was shown that the treatments implementing over half the speed zone were more robust against crash migration than other treatments. The best treatment exemplified the greatest benefit in reduced sections and the greatest resistance to crash migration in other sections. In the 80% loading scenario, the best treatment increased the network travel time by less than 0.4%, which is deemed acceptable. No treatment was found to successfully reduce the rear-end and lane-change crash risks in the congested traffic condition (90% loading). This is attributed to the fact that, in the congested state, the speed of vehicles is subject to the surrounding traffic conditions and not to the posted speed limit. Therefore, changing the posted speed limit does not affect the speed of vehicles in a desirable manner. These conclusions agree with Dilmore (2005).
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Date Issued
2007
Identifier
CFE0001723, ucf:47309
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001723
Microscopic Safety Evaluation and Prediction for Special Expressway Facilities
Title
Microscopic Safety Evaluation and Prediction for Special Expressway Facilities.
Creator
Wang, Ling, Abdel-Aty, Mohamed, Radwan, Essam, Eluru, Naveen, Lee, JaeYoung, Uddin, Nizam, University of Central Florida
Abstract / Description
Expressways are of great importance and serve as the backbone of a roadway system. One of the reasons why expressways increase travel speeds and provide high level of services is that limited access is provided to permit vehicles to enter or exit expressways. Entering and exiting of vehicles are accomplished through interchanges, which consist of several ramps, thus the spacing between ramps is important. A weaving segment might form when an on-ramp is closely followed by an off-ramp. The...
Show moreExpressways are of great importance and serve as the backbone of a roadway system. One of the reasons why expressways increase travel speeds and provide high level of services is that limited access is provided to permit vehicles to enter or exit expressways. Entering and exiting of vehicles are accomplished through interchanges, which consist of several ramps, thus the spacing between ramps is important. A weaving segment might form when an on-ramp is closely followed by an off-ramp. The geometric design of ramps and the traffic behavior of weaving segments are different from other expressway segments. These differences result in distinct safety mechanisms of these two expressway special facilities. Hence, the safety of these two facilities needs to be addressed.The majority of previous traffic safety studies on expressway special facilities are based on highly aggregated traffic data, e.g., Annual Average Daily Traffic (AADT). This highly aggregated traffic data cannot represent traffic conditions at the time of crashes and also cannot be used in the study of weather and temporal impact on crash occurrence. One way to solve this problem is microscopic safety evaluation and prediction through hourly crash prediction and real-time safety analysis. An hourly crash study averages one or several hours' traffic data in a year and also aggregates crash frequencies in the corresponding hour(s). Then it applies predictive models to determine the statistical relationship between crashes and hourly traffic flow characteristics, such as traffic volume. Real-time safety analysis enables us to predict crash risk and distinguish crashes from non-crashes in the next few minutes using the current traffic, weather, and other conditions.There are four types of crash contributing factors: traffic, geometry, weather, and driver. Among these, traffic parameters have been utilized in all previous microscopic safety studies. On the other hand, the other three factors' impact on microscopic safety has not been widely analyzed. The geometric factors' influence on safety are generally excluded by previous researchers using the matched-case-control method, because the majority of previous microscopic safety studies are on mainlines, where the geometric design of a segment does not change much and geometry does not have a significant effect on safety. Not enough studies have adopted weather factors in microscopic safety analysis because of the limited availability of weather data. The impact of drivers on safety has also not been widely considered since driver information is hard to be obtained. This study explores the relationship between crashes and the four contributing factors. Weather data are obtained from airport weather stations and crash reports which record weather and roadway surface conditions for crashes. Meanwhile, land-use and trip generation parameters serve as surrogates for drivers' behavior.Several methods are used to explore and quantify the impact of these factors. Random forests are used in discovering important and significant explanatory variables, which play significant roles in determining traffic safety, by ranking their importance. Meanwhile, in order to prevent high correlation between independent variables, Pearson correlation tests are carried out before model estimations. Only the variables which are not highly correlated are selected. Then, the selected variables are put in logistic regression models and Poisson-lognormal models to respectively estimate crash risk and crash frequency for special expressway facilities. Meanwhile, in case of correlation among observations in the same segment, a multilevel modeling structure has been implemented. Furthermore, a data mining technique(-)Support Vector Machine (SVM)(-)is used to distinguish crash from non-crash observations. Once the crash mechanisms for special expressway facilities are found, we are able to provide valuable information on how to manage roadway facilities to improve the traffic safety of special facilities. This study adopts Active Traffic Management (ATM) strategies, including Ramp Metering (RM) and Variable Speed Limit (VSL), in order to enhance the safety of a congested weaving segment. RM regulates the entering vehicle volume by adjusts metering rate, and VSL is able to provide smoother mainline traffic by changing the mainline speed limits. The ATM strategies are carried out in microscopic simulation VISSIM through the Component Object Model (COM) interface. The results shows that the crash risk and conflict count of the studies weaving segment have been significantly reduced because of ATM.Furthermore, the mechanisms of traffic conflicts, a surrogate safety measurement, are explored for weaving segments using microscopic simulation. The weaving segment conflict prediction model is compared with its crash prediction model. The results show that there are similarity and differences between conflict and crash mechanisms. Finally, potential relevant applications beyond the scope of this research but worth investigation in the future are also discussed in this dissertation.
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Date Issued
2016
Identifier
CFE0006414, ucf:51480
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006414
Arterial-level real-time safety evaluation in the context of proactive traffic management
Title
Arterial-level real-time safety evaluation in the context of proactive traffic management.
Creator
Yuan, Jinghui, Abdel-Aty, Mohamed, Eluru, Naveen, Hasan, Samiul, Cai, Qing, Wang, Liqiang, University of Central Florida
Abstract / Description
In the context of pro-active traffic management, real-time safety evaluation is one of the most important components. Previous studies on real-time safety analysis mainly focused on freeways, seldom on arterials. With the advancement of sensing technologies and smart city initiative, more and more real-time traffic data sources are available on arterials, which enables us to evaluate the real-time crash risk on arterials. However, there exist substantial differences between arterials and...
Show moreIn the context of pro-active traffic management, real-time safety evaluation is one of the most important components. Previous studies on real-time safety analysis mainly focused on freeways, seldom on arterials. With the advancement of sensing technologies and smart city initiative, more and more real-time traffic data sources are available on arterials, which enables us to evaluate the real-time crash risk on arterials. However, there exist substantial differences between arterials and freeways in terms of traffic flow characteristics, data availability, and even crash mechanism. Therefore, this study aims to deeply evaluate the real-time crash risk on arterials from multiple aspects by integrating all kinds of available data sources. First, Bayesian conditional logistic models (BCL) were developed to examine the relationship between crash occurrence on arterial segments and real-time traffic and signal timing characteristics by incorporating the Bluetooth, adaptive signal control, and weather data, which were extracted from four urban arterials in Central Florida. Second, real-time intersection-approach-level crash risk was investigated by considering the effects of real-time traffic, signal timing, and weather characteristics based on 23 signalized intersections in Orange County. Third, a deep learning algorithm for real-time crash risk prediction at signalized intersections was proposed based on Long Short-Term Memory (LSTM) and Synthetic Minority Over-Sampling Technique (SMOTE). Moreover, in-depth cycle-level real-time crash risk at signalized intersections was explored based on high-resolution event-based data (i.e., Automated Traffic Signal Performance Measures (ATSPM)). All the possible real-time cycle-level factors were considered, including traffic volume, signal timing, headway and occupancy, traffic variation between upstream and downstream detectors, shockwave characteristics, and weather conditions. Above all, comprehensive real-time safety evaluation algorithms were developed for arterials, which would be key components for future real-time safety applications (e.g., real-time crash risk prediction and visualization system) in the context of pro-active traffic management.
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Date Issued
2019
Identifier
CFE0007743, ucf:52398
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007743
Multi-Level Safety Performance Functions for High Speed Facilities
Title
Multi-Level Safety Performance Functions for High Speed Facilities.
Creator
Ahmed, Mohamed, Abdel-Aty, Mohamed, Radwan, Ahmed, Al-Deek, Haitham, Mackie, Kevin, Pande, Anurag, Uddin, Nizam, University of Central Florida
Abstract / Description
High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the...
Show moreHigh speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the crash risk on long and short term basis. Therefore, the main focus of the research in this dissertation is to provide a framework of risk assessment to promote safety and enhance mobility on freeways and expressways. Multi-level Safety Performance Functions (SPFs) were developed at the aggregate level using historical crash data and the corresponding exposure and risk factors to identify and rank sites with promise (hot-spots). Additionally, SPFs were developed at the disaggregate level utilizing real-time weather data collected from meteorological stations located at the freeway section as well as traffic flow parameters collected from different detection systems such as Automatic Vehicle Identification (AVI) and Remote Traffic Microwave Sensors (RTMS). These disaggregate SPFs can identify real-time risks due to turbulent traffic conditions and their interactions with other risk factors.In this study, two main datasets were obtained from two different regions. Those datasets comprise historical crash data, roadway geometrical characteristics, aggregate weather and traffic parameters as well as real-time weather and traffic data.At the aggregate level, Bayesian hierarchical models with spatial and random effects were compared to Poisson models to examine the safety effects of roadway geometrics on crash occurrence along freeway sections that feature mountainous terrain and adverse weather. At the disaggregate level; a main framework of a proactive safety management system using traffic data collected from AVI and RTMS, real-time weather and geometrical characteristics was provided. Different statistical techniques were implemented. These techniques ranged from classical frequentist classification approaches to explain the relationship between an event (crash) occurring at a given time and a set of risk factors in real time to other more advanced models. Bayesian statistics with updating approach to update beliefs about the behavior of the parameter with prior knowledge in order to achieve more reliable estimation was implemented. Also a relatively recent and promising Machine Learning technique (Stochastic Gradient Boosting) was utilized to calibrate several models utilizing different datasets collected from mixed detection systems as well as real-time meteorological stations. The results from this study suggest that both levels of analyses are important, the aggregate level helps in providing good understanding of different safety problems, and developing policies and countermeasures to reduce the number of crashes in total. At the disaggregate level, real-time safety functions help toward more proactive traffic management system that will not only enhance the performance of the high speed facilities and the whole traffic network but also provide safer mobility for people and goods. In general, the proposed multi-level analyses are useful in providing roadway authorities with detailed information on where countermeasures must be implemented and when resources should be devoted. The study also proves that traffic data collected from different detection systems could be a useful asset that should be utilized appropriately not only to alleviate traffic congestion but also to mitigate increased safety risks. The overall proposed framework can maximize the benefit of the existing archived data for freeway authorities as well as for road users.
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Date Issued
2012
Identifier
CFE0004508, ucf:49274
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004508