Design of emergency braking algorithm for pedestrian protection based on multi-sensor fusion

Globally, safety has become an increasingly important issue in the automotive industry. In an attempt to reduce traffic fatalities, UNECE launched a new EU Road Safety Program which aims to decrease the number of road deaths by half by 2020. AEB (Autonomous Emergency Braking) is a very effective active safety system intended to reduce fatalities. This study involves the design of a multi-sensor data fusion strategy and decision-making algorithm for AEB pedestrian. Possible collision avoidance scenarios according to the EuroNCAP protocol are analyzed and a robust pedestrian tracking strategy is proposed. The performance of the AEB system is enhanced by using a braking model to predict the collision avoidance time and by designing the system activation zone according to the relative speed and possible distance required to stop for pedestrians. The AEB activation threshold requires careful consideration. The test results confirm the advantages of the proposed algorithm, the performance of which is described in this paper.     

Tire Lateral Force Estimation Using Kalman Filter

As for the tire analysis, lateral tire force is a fundamental factor that describes the stability of vehicle handling. Attempts to analyze the vehicle stability have been made based on various objective test methods and some specific factors such as yaw, lateral acceleration and roll angle. However, the problem to identify which axle is lack of the tire grip at a certain situation still remains. Since indoor tire force measurement system cannot represent a real road and vehicle conditions, tire force measurement through a real vehicle test is inevitable. Due to the high price of the tire force measurement device, tire force estimator can be an alternative toward cost reduction and device failure. In this paper, nonlinear planar full car model combined with tire model is proposed. Then, using discrete-time extended Kalman-Bucy filter (EKBF), individual tire lateral force are estimated with modified relaxation length model.     

Innovative Public Transport Oriented Policies in Seoul

The objective of this paper is to introduce the innovative transport policies of Seoul that have recently been planned and implemented. In this paper, the various transport policies of Seoul are classified and explained according to two important paradoxes that are highlighted by Downs and Thomson, and Edgeworth. These paradoxes describe how to break the vicious circle of car and public transport use by restraining car use and encouraging the use of public transport, and thus indicate how traffic congestion problems might be solved.     

A study of the bi-directional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities

This paper investigates the bi-directional flow characteristics at signalized crosswalk facilities in Hong Kong. Pedestrian flow measurements were conducted at selected signalized crosswalks in Hong Kong urban area with and without the Light Rail Transit (LRT) railway tracks in the median of the carriageway. The pedestrian speed-flow functions for these crosswalk facilities were calibrated. The relationships between the walking speed at capacity and directional distribution of pedestrian flow (or flow ratio) are determined. The effects of different flow ratio on the effective capacity are also investigated. The bi-directional pedestrian flow effects on signalized crosswalk facilities with LRT tracks are found more significant than those without LRT tracks. The result could be used as a basis to improve the assessment of the crosswalk's capacity and to determine the design walking speeds under different flow ratios at signalized crosswalks in Hong Kong and in other Asian cities with similar environments.     

我在澳洲的八辆车

在十几岁时,我随着家人移民到澳大利亚——一个主要靠汽车代步的国家。那时的我对汽车并没多少兴趣,更喜欢在国内一直开的摩托。但澳洲这边路况好车速快,最安全还是开汽车,所以到达后,我就开始读考驾照的书籍,很快就拿到了驾照。     

Development of a self-driving car that can handle the adverse weather

Lane and road recognition are essential for self-driving where GPS solution is inaccurate due to the signal block or multipath in an urban environment. Vision based lane or road recognition algorithms have been studied extensively, but they are not robust to changes in weather or illumination due to the characteristic of the sensor. Lidar is a sensor for measuring distance, but it also contains intensity information. The road mark on the road is made to look good with headlight at night by using a special paint with good reflection on the light. With this feature, road marking can be detected with lidar even in the case of changes in illumination due to the rain or shadow. In this paper, we propose equipping autonomous cars with sensor fusion algorithms intended to operate in a different weather conditions. The proposed algorithm was applied to the self-driving car EureCar (KAIST) in order to test its feasibility for real-time use.     

Structural Optimization for Roof Crush Test Using an Enforced Displacement Method

A roof crush test has been utilized to reduce passengers’ injuries from a vehicle rollover. The Federal Motor Vehicle Safety Standards (FMVSS) 216 and the Insurance Institute for Highway Safety (IIHS) perform actual vehicle tests and evaluate the vehicle’s ratings. Nonlinear dynamic response structural optimization can be employed not only for achievement of a high rating but also minimization of the weight. However, the technique needs a huge computation time and cost because many nonlinear dynamic response analyses are required in the time domain. A novel method is proposed for nonlinear dynamic response structural optimization regarding the roof crush test. The process of the proposed method repeats the analysis domain and the design domain until the convergence criteria are satisfied. In the analysis domain, the roof crush test is simulated using a high fidelity model of nonlinear dynamic finite element analysis. In the design domain, a low fidelity model of linear static response structural optimization is utilized with enforced displacements that come from the analysis domain. Correction factors are employed to compensate the differences between a nonlinear dynamic analysis response and a linear static analysis response with enforced displacement. A full-scale vehicle problem is optimized with a constraint on the rigid wall force from the analysis in the design domain.     

Development of a Driving Behavior-Based Collision Warning System Using a Neural Network

An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation.     

Optimal Design for the Rear-Glass Joint of an Automobile for Squeak and Rattle Noise Reduction

Ever since vehicle noise, vibration, and harshness (NVH) reduction technology made dramatic improvements, vehicle interior noises represented by Squeak and Rattle (S/R) becomes an ever more important factor to improve the emotional quality of vehicles. Generally, people detect S/R noises on automotive interior parts, brake system, suspension, Body in White (BIW), etc. Among them, the rear-glass joint is a major source for vehicle interior noise, and can cause S/R noises under a variety of environmental and driving conditions. This study uses, two approaches, experimental and numerical approaches, to define the cause of S/R noise at the rear-glass section. Based on these two approaches, this study confirms that S/R noises generate through the contact between bottom side of molding and BIW. The sealant penetration length, panelmolding distance, and sealant width are the parameters affecting noise generation. In addition, this study created an optimal design with Design of Experiments (DOE) of the rear-glass joint. The design maximized the sealant penetration length, which is a parameter that majorly affects noise. The optimal design comprises of two steps: sealant injections shape optimization and rear-glass joint parameter optimization. Each step is carried out with FEA and validated by sealant penetration experiments. Through these optimizations, this study obtained an optimum combination of design parameters and fignificantly reduced the noise generated by rear-glass section.     

Effects of FTP-75 mode vehicle fuel economy improvement due to types of power steering system

This paper focuses on fuel economy improvement according to the type of power steering system. Usually, a conventional power steering system is directly driven by the crankshaft of the engine with a belt, known as HPS (hydraulic power steering). However, there is some inefficiency with this system at high engine speeds. To improve this inefficiency, automobile makers have developed two power steering systems: EHPS (electro-hydraulic power steering) and MDPS (motor-driven power steering) or EPS (electric powered steering). However, there has been insufficient study of effects of the type of power steering system on fuel economy. In this paper, the effect of the type of power steering system on fuel economy is studied experimentally, and calculations of the effect on vehicle fuel economy are presenting using computer simulation with AVL cruise software. The results demonstrate that a 1% vehicle fuel economy improvement can be achieved in a vehicle with an electro-hydraulic power steering system compared to a vehicle with a hydraulic power steering system. In addition, a 1.7% vehicle fuel economy improvement can be achieved using a full electric power steering system in a FTP-75 driving cycle. These results could be used to choose a power steering system.