Speed advice for cyclists; design task to reduce the stops at traffic lights

Abstract

Stops en route are a main concern for cyclists as they want to travel in the most comfortable fashion possible. The braking and acceleration at traffic lights cause losses of kinetic energy and make the trips of cyclists more strenuous than they would have been without stops. By reducing the number of stops for cyclists, the attraction of the bicycle as transport mode could be increased. This research will focus on the reduction of stops by implementing a speed advice for cyclists that will help the cyclist to arrive at intersections when the traffic light is green. The design of a system that can reduce the number of stops is presented for the situation with a fixed time controller and an vehicle actuated controller. The design for the fixed time controller consists of a speed advice that is given once to the cyclist approaching the traffic light. The cyclist can approach the traffic light with this speed to arrive at the intersection with a green light. The advice is given by a road side sign that can be read by the cyclist. Reductions in the fraction of stopped cyclists are in the order of 10-20%. The actuated controller asks for a more flexible structure of the speed advice in which the cyclist should adjust its speed dependent on the state of the traffic light controller. The speed advice system must be implemented in a way that the consequence of the state of the controller for the advice of the cyclist can be distributed to the cyclist at the moment this change of state occurs. The flexible appearance of the system allows it to adjust its speed advice to the preferences of the user. This is done by a score function that takes into account the probability to catch the green light and the sacrifice the cyclist has to make in his desired speed to end up at the green traffic light. The reductions in fraction of stopped cyclists are largely dependent on the chosen values for the attributes in the speed advice system. The tested scenarios indicate a maximum reduction of stopped cyclists of 45%.