Optimized Speed Trajectories for Cyclists, Based on Personal Preferences and Traffic Light Information-A Stochastic Dynamic Programming Approach

The literature on green mobility and eco-driving in urban areas has burgeoned in recent years, with special attention to using infrastructure to vehicle (I2V) communications to obtain optimal speed trajectory which minimize the economic and environmental costs. This article shares the concept with these studies but turns the spotlight on...

Practical implementation of reinforcement learning algorithms for giving personalised speed advice to cyclists approaching intersections using function approximation and Dyna

<br/>Being a safe and healthy alternative for polluting and space-inefficient motorised vehicles, cycling can strongly improve living conditions in urban areas. Idling in front of traffic lights is seen as one of the major inconveniences of commuting by bicycle. By giving personalised speed advice, the probability of catching a green light can...

A traffic signal optimization method for balancing the interests of cyclists and motorized traffic

This thesis proposes a traffic signal optimization method for balancing the interests of cyclists and motorized traffic. Traditionally, in bicycle traffic has not been given the same priority as motorized traffic in the signalization system planning. As a consequence, cyclists have to stop many times during their journey, which leads to a waste...

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

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...

Improving moving jam detection performance with V2I communication