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This paper proposed a collision avoidance strategy that take over the control of ego vehicle when faced with urgent collision risk. To improve the applicability of collision avoidance strategy in complex scenarios, the theory of ICS (Inevitable Collision State) is introduced to evaluate the collision risk and compute the trigger flag of the system, and vehicle dynamic is taken into account when modeling ego vehicle to predict ego vehicle’s following moving. Vehicle specific characteristics including reaction time of the braking system and the braking force increasing process are taken into account. In order to reduce injury caused by collision accidents and minimize disruption to drivers, slight steering is added on top of emergency braking. The direction of the steering angle is determined according to IM (Imitating Maneuvers) The flow chart of the strategy is presented in the paper.

Advanced driver assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This paper presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modeled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models.

One of the key technologies of automotive active safety systems is to calculate the wheel speed and wheel angular acceleration or deceleration. Obtaining an accurate control quantity is the prerequisite for active safety systems no matter what control logics are used to realize the control function. This paper puts forward a new wheel speed processing algorithm. This method was simulated in MATLAB \ Simulink. Then it was tested in a certain type of vehicle of FAW by applying dSPACE RCP. It proves that this algorithm assures the precision at high and low speed and the real-time performance at low speed.

The overall technology trend of Active Safety and Driver Assistance systems is relatively clear: increasing capability to avoid crashes as well as convenience on a path toward autonomous driving. What's less obvious, though, is the selection of features/technologies will make sense at each step along the path. Specific vehicle contenting decisions get made early in the vehicle planning process and rely on forecasting factors such as technology readiness, consumer interest, the economics in the supply base, and projected government regulations and consumer metrics. Additionally, for these technologies to be effective, often they need to be introduced in conjunction with other features and grouped in ways that are intuitive and relevant to current consumer needs.

Vehicle manufacturers conduct tests to develop crash sensing system calibrations. Ditch fall-over is one of a suite of laboratory tests used to develop rollover sensing calibrations that can trigger deployment of safety devices like roof rail airbags and seat belt pretensioners. The ditch fall-over test simulates a flat road followed by a ditch on one side of the road. The vehicle heads into the ditch and the driver applies swift steer input once the ditch slope is sensed. Typically, the steer input is applied when the two down-slope wheels on the ditch side enter the ditch. Multi-Body Dynamics (MBD) software can be used for virtual simulation of these test events. Conventionally in simulations, the vehicle-model is run without steer input and the marking line crossing time is observed/manually recorded from observation of simulation video. This recorded time is used to apply the steer input and the full event is then re-simulated.

Active collision avoidance can assist drivers to avoid longitudinal collision through active brake. Regenerative braking can improve the driving range and braking response speed. At this stage, conventional hydraulic braking system limits the implements of above technologies because of its poor performance of response speed and coordinated control. While the brake-by-wire system is a better actuator that can fulfill requirements of automotive electric and intelligent development due to its rapid response and flexible adjustment. However, the system control algorithm becomes more complicated with introduction of regenerative braking and active collision avoidance function, which is also the main problem solved in this paper.

Studying traffic accidents by using naturalistic driving data has become increasingly appealing for its potential benefits in improving road safety. This paper presents findings from a field test which has been conducted on 50 taxis in the urban areas of Beijing for 10 months using Video Drive Recorders (VDRs). The VDR used in this study could record the information of vehicle front view video, vehicle states, as well as driver operations immediately before and after an event. The drivers were given no specific instructions during the test, and the instrumentation for data collection was unobtrusive. Important safety-relevant parameters, such as vehicle speed, pre-event maneuver, time headway, time-to-collision, and driver reaction time, were calculated with precision. Based on these parameters, an analysis into features and causes of rear-end conflicts is performed.

Intelligent driving, aimed for collision avoidance and self-navigation, is mainly based on environmental sensing via radar, lidar and/or camera. While each of the sensors has its own unique pros and cons, camera is especially good at object detection, recognition and tracking. However, unpredictable environmental illumination can potentially cause misdetection or false detection. To investigate the influence of illumination conditions on detection algorithms, we reproduced various illumination intensities in a photo-realistic virtual world, which leverages recent progress in computer graphics, and verified vehicle detection effect there. In the virtual world, the environmental illumination is controlled precisely from low to high to simulate different illumination conditions in the driving scenarios (with relative luminous intensity from 0.01 to 400). Sedan cars with different colors are modelled in the virtual world and used for detection task.

Steering movement is the most basic movement of the vehicle, in the car driving process, the driver through the steering wheel has always been to control the direction of the car, in order to achieve their own driving intention. Four Wheel Steering (4WS) is an advanced vehicle control technique which can markedly improve vehicle steering characteristics. Compared with traditional front wheel steering vehicles, 4WS vehicles can steer the front wheels and the rear wheels individually for cornering, according to the vehicle motion states such as the information of vehicle speed, yaw velocity and lateral acceleration. Therefore, 4WS can enhance the handling stability and improve the active safety for vehicles.

The Advanced Driver Assistance System (ADAS) is a comprehensive feature set designed to aid a driver in avoiding or reducing the severity of collisions while operating the vehicle within specified conditions. In General Motors (GM) vehicles, the primary controller for the ADAS is the Active Safety Control Module (ASCM). In the 2013 model year, GM introduced an ASCM utilizing the GM internal nomenclature of External Object Calculation Module (EOCM) in some of their vehicles produced for the North American market. Similar to the Sensing and Diagnostic Module (SDM) utilized in the restraints system, the EOCM3 LC contains an Event Data Recorder (EDR) function to capture and record information surrounding certain ADAS or Supplemental Inflatable Restraint (SIR) events. The ASCM EDR contains information from external object sensors, various chassis and powertrain control modules, and internally calculated data.

Highway traffic safety has been the most serious problem in current society, statistics show that about 70% to 90% of accidents are caused by driver operational errors. The autonomous emergency braking (AEB) is one of important vehicle intelligent safety technologies to avoid or mitigate collision. The AEB system applies the vehicle brakes when a collision is eminent in spite of any reaction by the driver. In some technologies, the system forewarns the driver with an acoustic signal when a collision is still avoidable, but subsequently applies the brakes automatically if the driver fails to respond. This paper presents the development and implementation of a rear-end collision avoidance system based on hierarchical control framework which consists of threat assessment layer, wheel slip ratio control layer and integrated-electro-hydraulic brake (IEHB) actuator control layer.

A program of integrated electro-hydraulic braking system is proposed, and its structural composition and working principle are analyzed. According to the structural and mechanical characteristics of all key components, through some reasonable assumptions and simplifications, a motor, a brake master cylinder, four brake wheel cylinders, solenoid valves and an ESP (Electronic Stability Program) algorithm model is set up and simulations of typical braking conditions are carried out based on the Matlab/Simulink. Finally, after the assembly of each sub-model is complete and combining a vehicle which is set up in CarSim software environment, simulation tests and comprehensive performance analysis of the active safety stability control for a vehicle in double lane change and single lane change situations are carried out respectively. According to the dynamic characteristic curves of system, the effects of different structural and control parameters on braking performance are analyzed.

Lane-changing systems have been developed and applied to improve environmental adaptability of advanced driver assistant system (ADAS) and driver comfort. Lane-changing control consists of three steps: decision making, trajectory planning and trajectory tracking. Current methods are not perfect due to weaknesses such as high computation cost, low robustness to uncertainties, etc. In this paper, a novel lane changing control method is proposed, where lane-changing behavior is analogized to parallel parking behavior. In the perspective of host vehicle with lane-changing intention, the space between vehicles in the target adjacent lane can be regarded as dynamic parking space. A decision making and path planning algorithm of parallel parking is adapted to deal with lane change condition. The adopted algorithm based on rules checks lane-changing feasibility and generates desired path in the moving reference system at the same speed of vehicles in target lane.

According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This article focuses on the research of control algorithm and control logic for the pneumatic EBS (Electronic Braking System) of commercial vehicle. An overall technical program was proposed which develops conventional braking and emergency braking for commercial vehicle EBS. According to the overall scheme, the methods of vehicle state estimation and driver's braking intention were determined, modeling and simulation for key components of commercial vehicle EBS were then carried out. This lead to the development of deceleration control, braking force distribution, brake assist and ABS control. Simulation models for key components of EBS and control strategy were validated through hardware-in-the-loop simulation tests. Simulation results show that the control strategy improves vehicle braking stability and vehicle active safety.

Adaptive cruise control is one of the key technologies in advanced driver assistance systems. However, improving the performance of autonomous driving systems requires addressing various challenges, such as maintaining the dynamic stability of the vehicle during the cruise process, accurately controlling the distance between the ego vehicle and the preceding vehicle, resisting the effects of nonlinear changes in longitudinal speed on system performance. To overcome these challenges, an adaptive cruise control strategy based on the Takagi-Sugeno fuzzy model with a focus on ensuring vehicle lateral stability is proposed. Firstly, a collaborative control model of adaptive cruise and lateral stability is established with desired acceleration and additional yaw moment as control inputs. Then, considering the effect of the nonlinear change of the longitudinal speed on the performance of the vehicle system.

Vehicle to Everything (V2X) communication is a prominent solution for active safety collision avoidance and for providing autonomous vehicles Non-Line of Sight (NLOS) capabilities. For safety purposes, it is essential the V2X technology would support communication between all road users, e.g., Vehicles (V2V), pedestrians (V2P) and road infrastructure (V2I). Hence, the efficiency of a V2V communication solution should be evaluated through system level performance. In addition, the examined performance metrics need to reflect safety related properties. Metrics as Packet Reception Ratio (PRR) and transmission latencies, which are commonly used to assess V2X system’s functionality, aren’t enough since reception latencies are overlooked. The latter is crucial in ensuring messages would reach their destination on time to avoid hazardous incidents. The reception cadence may be much lower than this of the transmission due to various phenomenon (e.g. channel congestion).

Universal Connectivity in the vehicle is no longer a nice-to-have function, but a critical tool to support every other function of the car - infotainment, active safety, autonomous driving, diagnostics, driving comfort etc. Although CASE (Connectivity, Autonomous, Services, Electrification) is now a commonly accepted foundation of new technology, it should perhaps be more accurately described as “C + ASE”, since Connectivity is an important enabler for the other three. Typically, connectivity in a vehicle implies primarily cellular (terrestrial) communication along with several other wireless protocols such as WiFi, Bluetooth, NFC etc. In addition, emerging vehicular technologies such as autonomous driving would potentially require ubiquitous and highly reliable connectivity.

With rapid development of the automobile industry and the growing maturity of the automotive electronic technologies, the distributed-traction electric vehicle with four-wheel-distributed steering/braking/traction systems is regarded as an important development direction. With its unique chassis structure, it is the ideal benchmark platform used to evaluate active safety systems. The distributed-traction electric vehicle with four-wheel-distributed steering system is essentially full drive-by-wire vehicle. With its flexible chassis layout and high control degrees-of-freedom, the full drive-by-wire electric vehicle acted as a kind of redundant system is an ideal platform for the research of integrated control. In this treatise, the longitudinal dynamics of the electric vehicle as well as its lateral and yaw motions are controlled simultaneously.