#Rear end accident simulation driver#
#Rear end accident simulation verification#
#Rear end accident simulation software#
#Rear end accident simulation mac#

Vehicle acceleration modeling in PC-CRASH (64) SAE Rose et al (2014).

Field effectiveness calculation of integrated safety systems (01) SAE Ressle et al (2011).

A comparison study on head injury risk in care to pedestrian collisions in Changsha and Hannover (67) SAE Chen et al (2010).

#Rear end accident simulation verification#

Verification of ABS models applied in programs for road accident simulation (70) SEA ZД™bala et al (2010).

Analysis of a dolly rollover with PC-CRASH (22) SAE Rose and Beauchamp (2009).

Soil trip rollover simulation and occupant kinematics in real world accidents (80) SAE Ootani and Pai (2007).

Effective numerical simulation tool for real world rollover accidents by combing PC-CRASH and FEA (73) Ootani and Pai (2007).

Yaw testing of an instrumented vehicle with and without braking (87) SAE Cliff et al (2004).

Simulation of rollover crashes using PC-CRASH (41) SAE Steffan and Moser (2004).

Simulation and testing of a suite of field relevant rollovers (35) SAE Gopal et al (2004).

Reconstruction of twenty staged collisions with PC-CRASHвЂ™s optimizer (07) SAE Cliff and Moser (2001).

Tire friction during locked wheel braking (14) SAE Goudie et al (2000).

Data from five staged car to car collisions and comparison with simulations (49) SAE Bailey et al (2000).

Validation of the coupled PC-CRASH вЂ“ MADYMO occupant simulation model (71) SAE Steffan et al (2000).

The pedestrian model in PC-CRASH вЂ“ The introduction of a multi body system and its validation (45) SAE Moser et al (1999).

A new approach to occupant simulation through the coupling of PC-CRASH and MADYMO (44) SAE Steffan et al (1999).

#Rear end accident simulation software#

Applications of the monte carlo methods of stability analysis within the accident reconstruction software PC-Crash (03B-24) SAE Moser and Spek (2003).

Accident reconstruction: Crash analysis (SP-1572), pp.

Reconstruction of twenty staged collisions with PC-CrashвЂ™s optimizer Cliff WE, Moser, A (07).

Warrendale, PA: Society of Automotive Engineers. In: Accident reconstruction (SP-1873), pp.

Yaw testing of an instrumented vehicle with and without braking Cliff WE, Lawrence JM, Heinrichs BE, Fricker TR (87).

#Rear end accident simulation mac#

Sensitivity of Collision Simulation Results to Initial Assumptions Heinrichs BE, Mac Giolla Ri B, Hunter RC (04).

Lastly, it was found that the CPI-based crash prediction model can correctly identify the crash and non-crash cases at higher accuracy than the other crash prediction models based on detectors.

#Rear end accident simulation driver#

Thus, it is important to reflect the differences in driver behavior and vehicle performance characteristics between cars and heavy vehicles in estimating surrogate safety measures. The result also shows that rear-end collision risk is lower for heavy vehicles than cars in the crash case due to their shorter reaction time and lower speed when spacing is shorter. This demonstrates that the CPI can be used to capture rear-end collision risk during car-following maneuver on freeways. The result shows that the values of CPI were consistently higher during the traffic conditions immediately before the crash time (crash case) than the normal traffic conditions (non-crash case). The observed data were obtained from crash records and loop detectors on a section of the Gardiner Expressway in Toronto, Canada. This study also validates the CPI using the simulated traffic data which replicate the observed traffic conditions a few minutes before the crash time upstream and downstream of the crash locations. It was found that the CPI was generally higher for the following heavy vehicle than the following car due to heavy vehicleвЂ™s lower braking capability. CPIs were estimated using the individual vehicle trajectory data from a segment of the US-101 freeway in Los Angeles, U.S.A. The crash potential index (CPI) was modified to reflect driverвЂ™s reaction time and estimated by types of lead and following vehicles (car or heavy vehicle). This study analyzes rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure.