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

[1]  Albinder Dhindsa.  Evaluating Ramp Metering And Variable Speed Limits To Reduce Crash Potential On Congested Freeways Using Micro-simulation , 2005 .

[2]  Mohamed Abdel-Aty,et al.  Modeling drivers' diversion from normal routes under ATIS using generalized estimating equations and binomial probit link function , 2004 .

[3]  Mohamed Abdel-Aty,et al.  Linking Crash Patterns to ITS-Related Archived Data: Phase IIVolume II: Evaluations of ITS Strategies , 2004 .

[4]  Mohamed Abdel-Aty,et al.  Evaluation of variable speed limits for real-time freeway safety improvement. , 2006, Accident; analysis and prevention.

[5]  Markos Papageorgiou,et al.  ALINEA: A LOCAL FEEDBACK CONTROL LAW FOR ON-RAMP METERING , 1990 .

[6]  Vaishali P. Shah,et al.  Potential of Advanced Traveler Information System to Reduce Travel Disutility: Assessment in Washington, D.C., Region , 2003 .

[7]  R. Jayakrishnan,et al.  Emergence of Private Advanced Traveler Information System Providers and Their Effect on Traffic Network Performance , 2002 .

[8]  Ryuichi Kitamura,et al.  Impact Of ATIS On Drivers' Decisions And Route Choice: A Literature Review , 1993 .

[9]  Harilaos N. Koutsopoulos,et al.  A microscopic traffic simulator for evaluation of dynamic traffic management systems , 1996 .

[10]  Klaus Bogenberger,et al.  Advanced Coordinated Traffic Responsive Ramp Metering Strategies , 1999 .

[11]  Mohamed Abdel-Aty,et al.  Predicting Freeway Crashes from Loop Detector Data by Matched Case-Control Logistic Regression , 2004 .

[12]  Lester A Hoel,et al.  Using Simulation to Predict Safety and Operational Impacts of Increasing Traffic Signal Density , 2002 .

[13]  P. Casey,et al.  Federal Highway Administration , 2020, Federal Regulatory Guide.

[14]  P J Wong,et al.  GUIDELINES FOR DESIGN AND OPERATION OF RAMP CONTROL SYSTEMS , 1975 .

[15]  Mohamed Abdel-Aty,et al.  Comprehensive Analysis of the Relationship between Real-Time Traffic Surveillance Data and Rear-End Crashes on Freeways , 2006 .

[16]  Yorgos J. Stephanedes,et al.  Implementation of on-line zone control strategies for optimal ramp metering in the Minneapolis Ring Road , 1994 .

[17]  Mohamed Abdel-Aty,et al.  Linking Crash Patterns to ITS-Related Archived Data: Phase IIVolume I: Real-time Crash Risk Assessment Models , 2007 .

[18]  Henry X. Liu,et al.  A calibration procedure for microscopic traffic simulation , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[19]  Kaan Ozbay,et al.  Quantifying effects of ramp metering on freeway safety. , 2006, Accident; analysis and prevention.

[20]  Baher Abdulhai,et al.  MICROSIMULATION MODELLING AND IMPACT ASSESSMENT OF STREETCAR TRANSIT PRIORITY OPTIONS : THE TORONTO EXPERIENCE , 2002 .

[21]  Markos Papageorgiou,et al.  ALINEA Local Ramp Metering: Summary of Field Results , 1997 .

[22]  Randolph W. Hall,et al.  Traveler route choice: Travel time implications of improved information and adaptive decisions , 1983 .

[23]  Mohamed Abdel-Aty,et al.  Assessment of freeway traffic parameters leading to lane-change related collisions. , 2006, Accident; analysis and prevention.

[24]  Lei Yu,et al.  AN EVALUATION OF TRAFFIC SIMULATION MODELS FOR SUPPORTING ITS DEVELOPMENT , 2000 .

[25]  Markos Papageorgiou,et al.  SERIES OF NEW LOCAL RAMP METERING STRATEGIES , 2003 .

[26]  Robert L. Bertini,et al.  D R A F T Application of PARAMICS Simulation At a Diamond Interchange , 2002 .

[27]  Mohamed Abdel-Aty,et al.  Coordinated Use of Variable Speed Limits and Ramp Metering for Improving Safety on Congested Freeways , 2007 .

[28]  Fedel Frank Saccomanno,et al.  Assessing Safety Benefits of Variable Speed Limits , 2004 .

[29]  Mohamed Abdel-Aty,et al.  Split Models for Predicting Multivehicle Crashes during High-Speed and Low-Speed Operating Conditions on Freeways , 2005 .

[30]  Michael Zhang,et al.  Evaluation of On-ramp Control Algorithms , 2001 .

[31]  Hani S. Mahmassani,et al.  System performance and user response under real-time information in a congested traffic corridor , 1991 .

[32]  Yorgos J. Stephanedes,et al.  Optimal control of freeway corridors , 1993 .

[33]  Moshe Ben-Akiva,et al.  Evaluation of ramp control algorithms using microscopic traffic simulation , 2002 .

[34]  William R. McShane,et al.  A review of pedestrian safety models for urban areas in Low and Middle Income Countries , 2016 .

[35]  Virginia P Sisiopiku,et al.  A MODIFIED ALINEA RAMP METERING MODEL , 2001 .

[36]  Markos Papageorgiou,et al.  Freeway ramp metering: an overview , 2002, IEEE Trans. Intell. Transp. Syst..

[37]  H M Koble,et al.  CONTROL STRATEGIES IN RESPONSE TO FREEWAY INCIDENTS. FINAL REPORT. VOLUME 1: EXECUTIVE SUMMARY , 1980 .

[38]  Jeremy Harvey Dilmore,et al.  Implementation Strategies For Real-time Traffic Safety Improvements On Urban Freeways , 2005 .

[39]  Arnoud Visser,et al.  Traffic simulation , 2001, Future Gener. Comput. Syst..

[40]  Will Recker,et al.  Using Microscopic Simulation to Evaluate Potential Intelligent Transportation System Strategies Under Nonrecurrent Congestion , 2004 .

[41]  Baher Abdulhai,et al.  Simulation of ITS on the Irvine FOT Area Using "Paramics 1.5" Scalable Microscopic Traffic Simulator: Phase I: Model Calibration and Validation , 1999 .

[42]  Jonathan P Masinick,et al.  An analysis on the impact of rubbernecking on urban freeway traffic. , 2004 .

[43]  Chris Lee,et al.  Real-Time Crash Prediction Model for Application to Crash Prevention in Freeway Traffic , 2002 .

[44]  Mohamed Abdel-Aty,et al.  Evaluating Route Diversion as a Strategy for Reduction of Real-Time Crash Risk on Freeways Using Microscopic Simulation , 2008 .

[45]  S. Spraggs,et al.  Traffic Engineering , 2000 .