Heavy Goods Vehicles (HGVs) are overrepresented in cyclist fatality statistics in the UK relative to their proportion of total traffic volume. In particular, the statistics highlight a problem for vehicles turning left across the path of a cyclist on their inside. In this paper we present a camera-based system to detect and track cyclists in the blind spot. The system uses boosted classifiers and geometric constraints to detect cyclist wheels, and Canny edge detection to locate the ground contact point. The locations of these points are mapped into physical coordinates using a calibration system based on the ground plane. A Kalman Filter is used to track and predict the future motion of the cyclist. Full-scale tests were conducted using a construction vehicle fitted with two cameras, and the results compared with measurements from an ultrasonic-sensor system. Errors were comparable to the ultrasonic system, with average error standard deviation of 4.3 cm when the cyclist was 1.5 m from the HGV, and 7.1 cm at a distance of 1 m. When results were compared to manually extracted cyclist position data, errors were less than 4 cm at separations of 1.5 m and 1 m. Compared to the ultrasonic system, the camera system requires simpler hardware and can easily differentiate cyclists from stationary or moving background objects such as parked cars or roadside furniture. However, the cameras suffer from reduced robustness and accuracy at close range, and cannot operate in low-light conditions.
Controlling greenhouse gas emissions is becoming increasingly more important. With road freight contributing to a significant amount of energy usage, finding ways to improve this sector will, in turn, lead to large reductions in carbon dioxide emissions, with one method to achieve this being to use larger vehicles. Currently, prescriptive legislation dictates the dimensions a vehicle can take. An alternative to this is to use 'Performance-Based Standards (PBS)'. This involves determining a set of manoeuvres and performance metrics that a vehicle must perform and pass in order to be roadworthy, instead of saying a vehicle can be a certain size or a certain weight. Through innovation and optimisation, using this method will then allow larger vehicles that are safe for driving on the road to be built. The research conducted here involved creating a PBS framework based on low-speed manoeuvrability for rigid delivery vehicles as well as assessing the high-speed stability of articulated vehicles to determine whether they would be safe for use on urban roads. Additionally, design changes such as incorporating rear axle steering were considered to determine whether vehicles that had failed the proposed PBS framework could be made to pass.
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