Advance Active Safety Systems play a preventive role in mitigating crashes and accidents by providing warning, additional assistance to the driver and maneuverability of vehicle by itself. Some of the features include forward collision warning system and lane departure warning system activate a warning alert when potentially dangerous situations are detected. These active safety features present in developed markets work with Fusion based algorithm combining Radar, Lidar, Camera, Ultrasonic sensor’s input. Application of these algorithms are Intelligent Cruise Control, Collision avoidance, parking assistance, identify pedestrian etc. The complexity of the algorithm, cost of the control unit and road infrastructure are hindrance to emerging market. The solution presented in this paper is towards camera-based solution, describing the method to determine the predictive path, that is obstacle free space and use the predictive space to navigate or steer. This paper focuses on vehicle maneuverability in poor road infrastructure (lane irregularities or no lane marking) by using only cameras.

More than 90% of new vehicles include Advanced Driving Assistance Systems that offer features such as Lane Keep Assist and Adaptive Cruise Control [1]. These ever-improving vehicle systems present a great opportunity to increase driving safety and reduce the number of roadway deaths and injuries. Indeed, they are already having a positive effect. However, the wide variety of features offered in the marketplace can be confusing to consumers, who may not clearly understand their vehicles’ true capabilities and limitations, or have an easy way of comparing system performance between vehicle models. This lack of information has the potential to reduce the safety gains of ADAS features by increasing the risk of improper use. To encourage transparency in the marketplace and thus engender the maximum positive effect of ADAS technologies, this paper proposes a five-level rating system, which utilizes diamonds to denote significant milestone achievements in vehicle system performance. The rating charts resulting from this system describe gradients of performance within criteria addressed by certain foundational ADAS features. Presented here in its initial stage of development,…

This SAE Standard describes standardized medium-independent messages needed by information service providers for Advanced Traveler Information Systems (ATIS). The messages contained herein address all stages of travel (informational, pre-trip and en route), all types of travelers (drivers, passengers, personal devices, computers, other servers), all categories of information, and all platforms for delivery of information (in-vehicle, portable devices, kiosks, etc.).

The current study presents the results of an experiment on driver performance including reaction time, eye-attention movement, mental workload, and subjective preference when different features of Advanced Driver Assistance Systems (ADAS) warnings (Forward Collision Warning) are displayed, including different locations (HDD (Head-Down Display) vs HUD (Head-Up Display)), modality of warning (text vs. pictographic), and a new concept that provides a dynamic bird’s eye view for warnings.Sixteen drivers drove a high-fidelity driving simulator integrated with display prototypes of the features. Independent variables were displayed as modality, location, and dynamics of the warnings with driver performance as the dependent variable including driver reaction time to the warning, EORT (Eyes-Off-Road-Time) during braking after receiving the warning, workload and subject preference. The primary results were in line with previous research, validating previous claims of the superiority of HUD over HDD in warning delivery. It was also found that the text format of the warning yielded higher response rates along with lower workload, while most participants preferred the dynamic bird’s eye view layout.

Current Advanced Driver Assistance Systems (ADAS) often interact with the driver; aiding with either warnings or direct intervention. This work explores the development of an ADAS system to provide lane departure warning, forward collision warning, and a recommended following distance for a custom plug-in hybrid-electric vehicle. The system utilizes off-the-shelf hardware with in-house computer vision and sensor fusion algorithms to create a low-cost SAE Level 0 driver assistance system. The system utilizes a radar sensor as well as a camera to detect, classify, and track target vehicles. This work will illustrate the systems engineering methods used for outlining customer requirements, technical requirements, component selection, software development, simulation, vehicle fitment, and validation. Similar system engineering processes could be implemented for higher level SAE systems.

Autonomous vehicles perform various functions with their own control strategies. Functions like Lane Departure Warning (LDW), Lane Keeping system (LKS) and Forward Collision Warning System (FCWS) requires special test tracks for their verification and validation. These test track requirements change with region to region according to available infrastructure.This paper deals with the design and development of test tracks for different ADAS functions verification and validation of Indian specific scenarios and its simulation in IPG CarMaker. The test track conceptualization has been done through the understanding and study of different international standards and geometry of test tracks for Indian conditions have been developed. IPG CarMaker software tool is used for creation of test track, and same track is used for simulation of above ADAS functions in IPG CarMaker. It is used as a scenario editor which can also simulate ECU and respond to sensor inputs dynamically which is not possible with other simulation environments. It creates a repeatable test scenario for particular function. IPG CarMaker is used to generate the required test track conditions in animated…

Vehicle emissions and fuel consumption are significantly affected by driving behavior. Many studies of eco-driving technology such as eco-driving training, driving simulators and on-board eco-driving devices have reported potential reductions in emissions and fuel consumption. Use of on-board safety devices is mainly for safety, but also affects vehicle emissions and fuel consumption. In this study, an on-board safety device was installed to alert the driver and provide several types of warning to the driver (e.g. headway monitoring warning, lane collision warning, speed limit warning, etc.) to improve driving behavior. A portable emissions measurement system (PEMS) was used to measure vehicle exhaust concentrations, including hydrocarbons (HC), carbon monoxide (CO), carbon dioxide (CO2) and nitrogen oxides (NOx). The driving parameters including vehicle speed, acceleration and position were also recorded. A specific test route was designed for the experiment to investigate both urban and highway conditions. The driving parameters and emissions data were compared before and after the installation of the on-board safety device with the same driver. The Vehicle Specific Power (VSP) methodology was applied to evaluate…

This SAE Recommended Practice establishes a uniform, powered vehicle test procedure and minimum performance requirement for lane departure warning systems used in highway trucks and buses greater than 4546 kg (10000 pounds) GVW. Systems similar in function but different in scope and complexity, including Lane Keeping/Lane Assist and Merge Assist, are not included in this document. This document does not apply to trailers, dollies, etc. This document does not intend to exclude any particular system or sensor technology. The specification will test the functionality of the LDWS (e.g., ability to detect lane presence, and ability to detect an unintended lane departure), its ability to indicate LDWS engagement, its ability to indicate LDWS disengagement, and determine the point at which the LDWS notifies the Human Machine Interface (HMI) or vehicle control system that a lane departure event is detected. Moreover, the specification determines whether a system performs at a minimally acceptable level. The HMI is not addressed herein but is considered in SAE Standard J2808.