A novel traffic conflict risk measure considering the effect of vehicle weight

Bifurcation analysis and control of improved traffic flow model considering the effect of strong winds

In recent years, the problem of traffic congestion has become increasingly serious, and research on traffic system control has become a new hotspot. Studying the bifurcation characteristics of traffic flow systems and designing control schemes for unstable support points can alleviate traffic congestion from a new perspective. This article improves the full speed differential model considering strong wind models from the perspective of bifurcation control to adjust traffic flow. This article theoretically proves the existence conditions of Hopf bifurcation and saddle node bifurcation in the model and finds the stability mutation point of the transportation system stability. A nonlinear system feedback controller was designed for unstable bifurcation points using Chebyshev polynomial approximation and random feedback control methods. Without changing the system equilibrium point, the advance, delay, and elimination of Hopf bifurcation were achieved, and the abrupt behavior of the transportation system was controlled, thereby alleviating traffic congestion. This article explains the changes in the stability of complex transportation systems from the perspective of bifurcation analysis, which can better capture the characteristics of traffic flow. By adjusting the control parameters in the feedback controller, the influence of boundary conditions on the stability of the transportation system is fully described, and the influence of unstable focal points and saddle points on the system is suppressed, thereby slowing down the traffic flow. In addition, unstable bifurcation points can be eliminated, and the Hopf bifurcation can be controlled to advance, delay, and disappear, thereby achieving control over the stable behavior of the transportation system. This helps alleviate traffic congestion and also helps describe actual traffic phenomena.

Frontal NCAP performance and field injury over 40 years

OBJECTIVES

Vehicle and occupant responses in 35 mph NCAP tests were determined for small-midsize passenger cars grouped around model year (MY) 1980, 1990, 2000, 2010 and 2020. A baseline was established with 1980 vehicles not designed for NCAP. The results of four decades of vehicles designed for NCAP were compared to the baseline. The study also determined the risk for serious injury (MAIS 3 + F) by vehicle model year (MY) using 1989-2015 NASS and 2017-2020 CISS. It explored safety trends in frontal crashes over 50 MYs of vehicles.

METHODS

The 1980 baseline group was established with 10 1979-1983 MY passenger cars weighing <1,500 kg. Four decades of vehicle crash tests from five manufacturers established trends in vehicle dynamics and dummy responses over four decades of vehicles designed for NCAP. Triaxial acceleration of the head and chest were reanalyzed for each test to have a consistent set of responses over five decades. The risk for serious injury (MAIS 3 + F) to the driver and front passenger was determined by vehicle MY using 1989-2015 NASS and 2017-2020 CISS with belted and unbelted drivers and right-front passengers. The data was sorted in four MY groups 1961-1989 MY, 1990-1999 MY, 2000-2009 MY and 2010 MY-2021 MY. The risk for MAIS 3 + F injury was determined with standard errors using weighted data.

RESULTS

The 1980 NCAP tests brought about changes in vehicle structures and occupant restraints by 1990; however, HIC15 and 3 ms chest acceleration have not changed much the past 20 years since the use of advanced airbags and seatbelts with pretensioner and load-limiters. For the driver, HIC15 dropped 40 ± 19% from the 1980 to 1990 NCAP tests and dropped further to 76 ± 32% in 2020. The percentage drops after 1990 were not statistically significant. The driver 3 ms chest acceleration dropped 18 ± 5% from 1980 to 1990 and plateaued with 22 ± 6% in 2020. For the front passenger, HIC15 dropped 68 ± 52% from the 1980 to 1990 NCAP tests and plateaued at 71 ± 49% in 2020. The passenger 3 ms chest acceleration dropped 13 ± 5% from 1980 to 1990 and has fluctuated with minimal change. Injury risks based on responses show the same initial drop in 1990 and have remained essentially constant. Nothing meaningful has changed in dummy responses in the past 20 years of NCAP testing. The field data found the belted driver MAIS 3 + F risk was 1.66 ± 0.37% in 1961-1989 MY vehicles and 1.39 ± 0.33% in 2010-2021 MY vehicles. For belted right-front passengers, the risk was 1.52 ± 0.39% in 1961-1989 MY vehicles and 1.42 ± 0.46% in 2010-2021 MY vehicles. The field data shows no meaningful change in injury risk in 50 MYs of vehicles. NCAP involves 35-40 mph delta-V, which represents a small fraction, 0.33%, of belted occupant exposure and only 8.6% of severe injury based on 1994-2015 NASS.

CONCLUSIONS

The NCAP test lacks field relevance. Manufacturers are merely "tuning" the restraint systems for star ratings without meaningful changes in field injury risks the past 20 years. There are disbenefits of "tuning" safety for a single, high-severity crash when most of the severe injury occurs in lower severity crashes. NHTSA should reevaluate plans to change the dummy to Thor and add BrIC injury criteria to assess NCAP responses. These changes would cause manufacturers to further "tune" structures, restraints and interiors without meaningful effects in real-world crashes.

Numerical Analysis of an Autonomous Emergency Braking System for Rear-End Collisions of Electric Bicycles

The rapid growth in the number of electric bicycles (e-bicycles) has greatly improved daily commuting for residents, but it has also increased traffic collisions involving e-bicycles. This study aims to develop an autonomous emergency braking (AEB) system for e-bicycles to reduce rear-end collisions. A framework for the AEB system composed of the risk recognition function and collision avoidance function was designed, and an e-bicycle following model was established. Then, numerical simulations were conducted in multiple scenarios to evaluate the effectiveness of the AEB system under different riding conditions. The results showed that the probability and severity of rear-end collisions involving e-bicycles significantly decreased with the application of the AEB system, and the number of rear-end collisions resulted in a 68.0% reduction. To more effectively prevent rear-end collisions, a low control delay (delay time) and suitable risk judgment criteria (TTC threshold) for the AEB system were required. The study findings suggested that when a delay time was less than or equal to 0.1 s and the TTC threshold was set at 2 s, rear-end collisions could be more effectively prevented while minimizing false alarms in the AEB system. Additionally, as the deceleration rate increased from 1.5 m/s2 to 4.5 m/s2, the probability and average severity of rear-end collisions also increased by 196.5% and 42.9%, respectively. This study can provide theoretical implications for the design of the AEB system for e-bicycles. The established e-bicycle following model serves as a reference for the microscopic simulation of e-bicycles.