Issues and challenges for pedestrian active safety systems based on real world accidents

The purpose of this study was to analyze real crashes involving pedestrians in order to evaluate the potential effectiveness of autonomous emergency braking systems (AEB) in pedestrian protection. A sample of 100 real accident cases were reconstructed providing a comprehensive set of data describing the interaction between the vehicle, the environment and the pedestrian all along the scenario of the accident. A generic AEB system based on a camera sensor for pedestrian detection was modelled in order to identify the functionality of its different attributes in the timeline of each crash scenario. These attributes were assessed to determine their impact on pedestrian safety. The influence of the detection and the activation of the AEB system were explored by varying the field of view (FOV) of the sensor and the level of deceleration. A FOV of 35 was estimated to be required to detect and react to the majority of crash scenarios. For the reaction of a system (from hazard detection to triggering the brakes), between 0.5 and 1 s appears necessary

Modified hamiltonian algorithm for optimal lane change with application to collision avoidance

This paper deals with collision avoidance for road vehicles when operating at the limits of available friction. For collision avoidance, a typical control approach is to: (a) define a reference geometric path that avoids collision; (b) apply low-level control to perform path following. However, there are a number of limitations in this approach, which are addressed in the current paper. First, it is typically unknown whether a predefined reference path is feasible or over-conservative. Secondly, the control scheme is not well suited to avoiding a moving object, e.g. another vehicle. Further: incorrect choice of reference path may degrade performance, fast adaptation to friction change is not easy to implement and the associated low-level control allocation may be computationally intensive. In this paper we use the general nonlinear optimal control formulation, include some simplifying assumptions and base optimal control on the minimization of an underlying Hamiltonian function. A particle model is used to define an initial reference in the form of a desired global mass-center acceleration vector. Beyond that, yaw moment is taken into account for the purpose of enhancing the stability of the vehicle. The Hamiltonian function is adapted as a linear function of tyre forces and can be minimized locally for individual wheels; this significantly reduces computational workload compared to the conventional approach of forcemoment allocation. Several combinations of actuators are studied to show the general applicability of the control algorithm based on a linear Hamiltonian function. The method has the potential to be used in future vehicle control systems across a wide range of safety applications and hence improve overall vehicle agility and improve safety

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.

Reset to zero and specify active safety systems according to real world needs

Emergency Brake Assist (EBA), Adaptive Cruise Control (ACC) and alternative instantiations of intelligent vehicle control systems aspire to support the driver in controlling the vehicle and alleviate the incidents that would lead to collisions and injury. This paper resets to zero and based on data from the On-The-Spot (OTS) accident study challenges the capability of active safety systems to aim at the sources of longitudinal control failures. The road user interactions file from 3024 road accidents in Thames Valley and Nottinghamshire in UK was analysed. Interactions where “failure to stop” or “sudden braking” is the precipitating factor are analysed and the main contributory factors are identified. Some of those factors are addressed by current and coming technologies – like low road friction, excessive speed and close following, but other common ones are significantly neglected – like distraction, failure to judge other person’s path, failure to look, and “look but did not see” instances