Sensor-Friendly Vehicle and Roadway Cooperative Safety Systems: Benefits Estimation

An analysis was performed to estimate the potential national costs and benefits of cooperative vehicle and roadway measures to enhance the effectiveness of driver assistance systems. These cooperative measures—query-response communication systems, light-emitting-diode brake light messaging, radar cross-section paint-striping modifications, fluorescent paint for lane and other marking applications, passive amplifiers on license plates, spatial tetrahedral arrays of reflectors, and in-vehicle corner cubes—are briefly described, along with assumptions that were made regarding performance. For the example lane departure case, the incremental nationwide effectiveness over an autonomous collision-avoidance system is estimated and monetized. This was generally determined with respect to annual crash-reduction savings, although the technique used allows other mobility benefits to be considered. The marginal benefits of providing each sensor-friendly technology were then calculated and aggregated across the various Intelligent Vehicle Initiative services so that a total marginal benefit was determined for each technology. Complementing this, a method has been established to estimate the magnitude of at- and near-intersection lead-vehicle-not-moving crashes for these technologies. Together, these methods illustrate national benefits across all crash types (the three-step process) and a more focused means to estimate benefits for a particular crash type (rear-end collisions at or near intersections)—and provide a composite approach to the problem.

[1]  G Reichart,et al.  DRIVER ASSISTANCE: BMW SOLUTIONS FOR THE FUTURE OF INDIVIDUAL MOBILITY , 1996 .

[2]  Ronald R Knipling,et al.  THE DIMENSIONS OF MOTOR VEHICLE CRASH RISK , 1999 .

[3]  John Lygeros,et al.  Longitudinal control of the lead car of a platoon , 1993 .

[4]  James Bret Michael,et al.  Benefit Evaluation of Crash Avoidance Systems , 1998 .

[5]  Thomas A. Dingus,et al.  Forward-Looking Collision Warning System Performance Guidelines , 1997 .

[6]  L Tijerina RECOMMENDED PERFORMANCE OF A LANE CHANGE CRASH AVOIDANCE SYSTEM (CAS) DRIVER INTERFACE, WITH SPECIAL REFERENCE TO SYSTEM RELIABILITY , 1997 .

[7]  Petros A. Ioannou,et al.  Autonomous intelligent cruise control , 1993 .

[8]  Bongsob Song,et al.  Emergence of a Cognitive Car-Following Driver Model: Application to Rear-End Crashes with a Stopped Lead Vehicle , 2000 .

[9]  Charles E. Thorpe,et al.  ENHANCING DRIVER-ASSIST SENSORS: BACKGROUND AND CONCEPTS FOR SENSOR-FRIENDLY VEHICLES AND ROADWAYS , 1999 .

[10]  Wassim G. Najm,et al.  DRIVER/VEHICLE CHARACTERISTICS IN REAR-END PRECRASH SCENARIOS BASED ON THE GENERAL ESTIMATES SYSTEM (GES) , 1999 .

[11]  Steven E Schladover Review of the State of Development of Advanced Vehicle Control Systems (AVCS) , 1995 .

[12]  W G Najm,et al.  BENEFITS ESTIMATION FOR SELECTED COLLISION AVOIDANCE SYSTEMS , 1997 .

[13]  Jerry D. Woll,et al.  Radar Based Adaptive Cruise Control for Truck Applications , 1997 .

[14]  Seungchul Kim,et al.  Development of intelligent cruise control system , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[15]  Charles E. Thorpe,et al.  PERFORMANCE SPECIFICATION DEVELOPMENT FOR ROADWAY DEPARTURE COLLISION AVOIDANCE SYSTEMS , 1997 .