A new lateral impact warning system with grey prediction

Abstract

Vehicle lateral impact is one of the major traffic collision accidents. Usually, this collision accident is caused when the target vehicle appears in the driver's blind spot during lane change or crowded urban travelling and the driver has not carefully observed the approaching vehicle from the rear and side mirrors. Hence, additional sensors need to be installed to measure the relative distance between two closing vehicles for active collision warning purpose. Generally, the lateral distance between two neighbouring vehicles is small compared with longitudinal distance: for crowded city traffic it is less than 1.5m. It is difficult to estimate accurately or assess the time-to-collision (TTC) based on a single relative distance index between two cars. Here, a novel two-indices TTC decision algorithm is proposed, which can distinguish the safe passing of neighbouring lanes from the essential dangerous lateral collision situation. In addition, the grey prediction theory is introduced to estimate the relative distance of two approaching vehicles one step ahead for TTC estimation to gain additional driver reaction time. The simulation results show that this strategy can create 0.5s extra time for the driver to take collision avoidance action.

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

“…Specifically, when the TTC threshold was set at 1 s, there were 137 rear-end collisions, whereas for the other two TTC thresholds combined, there were only 12 collisions. This illustrates that a stringent TTC threshold provides minimal temporal and spatial margin for AEB system control, consequently resulting in collisions [ 27 ]. Furthermore, when the TTC thresholds were set at 2 s and 3 s, there was no significant difference in the number of rear-end collisions, collision probability, or collision severity between the two threshold conditions.…”

“…Time-to-collision (TTC) is a crucial measure in different warning systems and is commonly used to trigger warnings. Huang and Chao [ 27 ] proposed a lateral impact warning system-based two-indices TTC decision algorithm and introduced the grey prediction theory to estimate TTC to ensure drivers gain additional reaction time. Sun et al [ 28 ] adopted the TTC and the relative distance as the warning indicators in the lane change warning system and gave warning thresholds in different stages.…”

Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

“…Thomas et al [10] reviewed the safety aspects involved in the use of rear-view mirrors and discussed the research directions. Moreover, major accidents were caused when the target vehicle appeared in the driver's blind spot during lane change or crowded urban travelling and the driver did not carefully observe the approaching vehicle from the rear and side mirrors [11]. Jan and Pieter [12] studied the use of cameras to support drivers under low visibility conditions or/and in the blind spot area.…”

“…Step 2 -Determination of normalized decision matrix: The data of influencing criteria are normalized using equation (11). …”

An Earlier Predictive Rollover Index Designed for Bus Rollover Detection and Prevention

“…The grey model was applied to predict the vehicle's wheel slip, and then the predicted slip was transferred to a sliding mode controller, which strengthened the controller's robustness [11]. The grey model has also been used to predict the lateral distance between approaching vehicles to provide drivers with extra time to react to an impending collision [12]. In terms of real-time LTR simulation, Chou et al [13] combined a grey model and a rollover index to detect the rollover of a 14-degree-of-freedom tractor-trailer.…”