No name, 1935

[With thumbs in his work pants pockets, a man stands at the rear end of a car, tents can be seen in the background with a figure seated at a bench]

Brake system performance requirements of a lightweight electric/hybrid rear wheel drive vehicle

Investigates the braking performance requirements of the UltraCommuter, a lightweight series hybrid electric vehicle currently under development at the University of Queensland. With a predicted vehicle mass of 600 kg and two in-wheel motors each capable of 500 Nm of peak torque, decelerations up to 0.46 g are theoretically possible using purely regenerative braking. With 99% of braking demands less than 0.35 g, essentially all braking can be regenerative. The wheel motors have sufficient peak torque capability to lock the rear wheels in combination with front axle braking, eliminating the need for friction braking at the rear. Emergency braking levels approaching 1 g are achieved by supplementation with front disk brakes. This paper presents equations describing the peak front and rear axle braking forces which occur under straight line braking, including gradients. Conventionally, to guarantee stability, mechanical front/rear proportioning of braking effort ensures that the front axle locks first. In this application, all braking is initially regenerative at the rear, and an adaptive ''by-wire'' proportioning system presented ensures this stability requirement is still satisfied. Front wheel drive and all wheel drive systems are also discussed. Finally, peak and continuous performance measures, not commonly provided for friction brakes, are derived for the UltraCommuter's motor capability and range of operation.

Lap belt angle measurement in adjustable rear seats: procedure development and vehicle survey. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Statistical evaluation of the effectiveness of Federal Motor Vehicle Safety Standard 207: Seat Back Locks (Only). Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Motor vehicle safety - a review of the NTSB report on rear seat lap belt effectiveness.

Mode of access: Internet.

Hand receipt covering contents of Components of End Item (COEI), Basic Issue Items (BII), and Additional Authorization List (AAL) for vehicle, combat engineer, full-tracked, M728, (2350-00-795-1797).

"April 1987."

Hand receipt covering content of Components of End Item (COEI), Basic Issue Items (BII), and Additional Authorization List (AAL) for fighting vehicle, infantry, M2, (2350-01-048-5920) and fighting vehicle, cavalry, M3, (2350-01-049-2695).

"August 1984."

Hand receipt covering contents of components of end item (COEI), basic issue items (BII), and additional authorization list (AAL) for vehicle, combat engineer, full-tracked, M728 (2350-00-795-1797).

"April 1987."

Hand receipt covering contents of Components of End Item (COEI), Basic Issued Items (BII), and Additional Authorization List (AAL) for combat vehicle, anti-tank : improved tow vehicle, M901 (2350-01-045-1123).

"April 1983."

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.