Analysis of Advanced Driver-Assistance Systems in Police Vehicles

69A3551747115/[TTI-05-02]Motor vehicle crashes are the leading cause of death for police officers. Advanced driver assistance systems (ADAS) have the potential to improve officer safety by removing some of the driver\u2019s vehicle control responsibilities. This project included two phases: (1) an ADAS needs and implementation analysis in police vehicles; and (2) an evaluation of police ADAS in a driving simulation study. The first phase included a systematic review of literature and an online survey with officers to understand their ADAS needs and current systems in police vehicles. The second phase evaluated ADAS in high-demand situations using a high-fidelity driving simulator. Results indicated that officer behaviors and opinions on ADAS features were influenced by the trust officers had in the available ADAS, as well as other key factors such as ADAS training and perceived usefulness. ADAS features, including forward collision warning, automatic emergency braking, and blind spot monitoring had a positive effect on police officers' driving performance and in reducing workload. The outcomes of this project provide guidelines regarding effective ADAS features/types to automotive companies supplying police vehicles and can improve officer safety in police operations

Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving

Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving

Driving into the sunset: Supporting cognitive functioning in older drivers

Copyright @ 2011 Mark S. Young and David Bunce - This article has been made available through the Brunel Open Access Publishing Fund.The rise in the aging driver population presents society with a significant challenge-how to maintain safety and mobility on the roads. On the one hand, older drivers pose a higher risk of an at-fault accident on a mile-for-mile basis; on the other hand, independent mobility is a significant marker of quality of life in aging. In this paper, we review the respective literatures on cognitive neuropsychology and ergonomics to suggest a previously unexplored synergy between these two fields. We argue that this conceptual overlap can form the basis for future solutions to what has been called "the older driver problem." Such solutions could be found in a range of emerging driver assistance technologies offered by vehicle manufacturers, which have the potential to compensate for the specific cognitive decrements associated with aging that are related to driving.Support was received from the Leverhulme Trust, UK

Vibrotactile pedals : provision of haptic feedback to support economical driving

The use of haptic feedback is currently an underused modality in the driving environment, especially with respect to vehicle manufacturers. This exploratory study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. A stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive for economical driving. Results showed significant decreases in mean acceleration values, and maximum and excess throttle use when the haptic pedal was active as compared to a baseline condition. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal as compared to when drivers were simply asked to drive economically. The literature suggests that the haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving

Analysis of Disengagements in Semi-Autonomous Vehicles: Drivers’ Takeover Performance and Operational Implications

This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the simulation experiment. Independent variables considered for the study were the age of the driver, the speed at the time of disengagement, and the time at which the disengagement occurred (i.e., how long automation was engaged for). The study shows that changes in the vehicle speed significantly affect all the variables investigated, pointing to the importance of setting up thresholds for maximum operational speed of vehicles driven in autonomous mode when the human driver serves as back-up. The results shows that the establishment of an operational threshold could reduce the maximum drift and lead to better control during takeover, perhaps warranting a lower speed limit than conventional vehicles. With regards to the age variable, neither the response times analysis nor the drift analysis provide support for any claim to limit the age of drivers of semi-autonomous vehicles

Identifying Modes of Intent from Driver Behaviors in Dynamic Environments

In light of growing attention of intelligent vehicle systems, we propose developing a driver model that uses a hybrid system formulation to capture the intent of the driver. This model hopes to capture human driving behavior in a way that can be utilized by semi- and fully autonomous systems in heterogeneous environments. We consider a discrete set of high level goals or intent modes, that is designed to encompass the decision making process of the human. A driver model is derived using a dataset of lane changes collected in a realistic driving simulator, in which the driver actively labels data to give us insight into her intent. By building the labeled dataset, we are able to utilize classification tools to build the driver model using features of based on her perception of the environment, and achieve high accuracy in identifying driver intent. Multiple algorithms are presented and compared on the dataset, and a comparison of the varying behaviors between drivers is drawn. Using this modeling methodology, we present a model that can be used to assess driver behaviors and to develop human-inspired safety metrics that can be utilized in intelligent vehicular systems.Comment: Submitted to ITSC 201