Search

Advanced driver-assistance systems such as Honda’s collision mitigation brake system (CMBS) can help achieve traffic safety. In this paper, the naturalistic driving study and a series of simulations are combined to better evaluate the performance of the CMBS in the Chinese traffic environment. First, because safety-critical situations can be diverse especially in the Chinese environment, the Chinese traffic-accident characteristics are analyzed according to accident statistics over the past 17 years. Next, 10 Chinese traffic-accident scenarios accounting for more than 80% of traffic accidents are selected. For each typical scenario, 353 representative cases are collected from the traffic-management department of Beijing. These real-world accident cases are then reconstructed by the traffic-accident-reconstruction software PC-Crash on the basis of accident-scene diagrams. This study also proposes a systematic analytical process for estimating the effectiveness of the technology using the co-simulation platform of PC-Crash and rateEFFECT, in which 176 simulations are analyzed in detail to assess the accident-avoidance performance of the CMBS. The overall collision-avoidance effectiveness reaches 82.4%, showing that the proposed approach is efficient for avoiding collisions, thereby enhancing traffic safety and improving traffic management.

Crash probability estimation is an important method to predict the potential reduction of crash probability contributed by forward collision avoidance technologies (FCATs). In this study, we propose a practical approach to estimate crash probability, which combines a field operational test and numerical simulations of a typical rear-end crash model. To consider driver hazard perception characteristics, we define a novel hazard perception measure, called as driver risk response time, by considering both time-to-collision (TTC) and driver braking response to impending collision risk in a near-crash scenario. Also, we establish a driving database under mixed Chinese traffic conditions based on a CMBS (Collision Mitigation Braking Systems)-equipped vehicle. Applying the crash probability estimation in this database, we estimate the potential decrease in crash probability owing to use of CMBS. A comparison of the results with CMBS on and off shows a 13.7% reduction of crash probability in a typical rear-end near-crash scenario with a one-second delay of driver's braking response. These results indicate that CMBS is positive in collision prevention, especially in the case of inattentive drivers or ole drivers. The proposed crash probability estimation offers a practical way for evaluating the safety benefits in the design and testing of FCATs.

This paper considers a comprehensive naturalistic driving experiment to collect driving data under potential threats on actual Chinese roads. Using acquired real-world naturalistic driving data, a near-crash database is built, which contains vehicle status, potential crash objects, driving environment and road types, weather condition, and driver information and actions. The aims of this study are summarized into two aspects: (1) to cluster different driving-risk levels involved in near-crashes, and (2) to unveil the factors that greatly influence the driving-risk level. A novel method to quantify the driving-risk level of a near-crash scenario is proposed by clustering the braking process characteristics, namely maximum deceleration, average deceleration, and percentage reduction in vehicle kinetic energy. A classification and regression tree (CART) is employed to unveil the relationship among driving risk, driver/vehicle characteristics, and road environment. The results indicate that the velocity when braking, triggering factors, potential object type, and potential crash type exerted the greatest influence on the driving-risk levels in near-crashes.

Evaluating the performance of Forward Collision Avoidance Technologies (FCATs) is essential in the early stage of the system testing. Drivers are the key interaction parts between the FCATs and vehicles, which play an important role in the performance evaluation. This paper proposes a practical method to evaluate the performance of FCATs by using a novel driver hazard perception measure, namely driver's risk response time. This measure describes the driver's awareness of potential collision risk, which is defined based on the Time-to-collision (TTC) and driver's brake response in a near-crash scenario. A two-month naturalistic driving experiment has been conducted using a vehicle equipped with one FCAT, i.e., Collision Mitigation Brake System (CMBS). An interval-based cumulative frequency data pretreatment method is used to extract near-crashes. Then, the hazard perception measure is computed in near-crashes with CMBS on and off, which can show the effectiveness of CMBS. The results demonstrate that CMBS is highly-positive in improving driver's hazard perception, especially in speed range between 45 km/h and 60 km/h. This fact is consistent with the expected effect of CMBS, which shows the proposed measure for hazard perception is capable of describing drivers' awareness of collision risk. In addition, this measure is applicable to assess the performance of FCATs during the function designing stage.

In addition to the real traffic accident data, naturalistic driving data can allow researchers gain insights into the factors that cause risk/hazard situations. This paper considers a comprehensive naturalistic driving experiment to collect detailed driving data on actual Chinese roads. Using acquired real-world driving data, a near-crash database is built, which contains vehicle status, potential crash object, driving environment and road type, and weather condition. K-means cluster analysis is applied to classify the near-crash cases into different driving risk levels using braking process features, namely maximum deceleration, average deceleration and percentage reduction in the vehicle kinetic energy. The results indicate that the velocity when braking and triggering factors have strong relationship with the driving risk level involved in near-crash cases.

Japan has a higher rate of rear-end collisions than any other kind of traffic accident and the causes of rear-end collisions were investigated. Accident statistics were used to conduct a statistical traffic accident analysis while a questionnaire was used to conduct a detailed traffic accident analysis and simulation was then used to perform traffic accident analysis. The results of the traffic accident analysis suggested that many of these accidents were caused by lack of attention during daily driving. Research was conducted to determine what kind of collision avoidance systems would be effective. A system was developed that is effective in reducing the collision velocity during rear-end collisions by making up for driver delays in recognition, judgment and operation by means of brake control and external sensing technology using millmeter wave radar sensor. This paper will discuss the testing and development of this new system.