We propose a fully automated, vision-based traffic light for pedestrians. Traditional industrial solutions only report people standing in a constrained waiting zone near the crosswalk. However, reporting only people below the traffic light does not allow for efficient traffic scheduling. For example, some pedestrians do not want to cross the street and walk past the traffic light, or just wait for another person to arrive. In contrast, our system leverages intent prediction to estimate which pedestrians are actually going to cross the road by analyzing both short-term and long-term trajectory cues. In this way, we can decrease the waiting times and pave the road for optimal and adaptive traffic light scheduling. We conduct a long-term evaluation in a European capital that proves the applicability and reliability of our system and demonstrates that it is not only able to replace existing push-button solutions but also yields additional information that can be used to further optimize traffic light scheduling.
|Title of host publication||IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)|
|Number of pages||6|
|Publication status||Published - 2018|
|Event||15th IEEE International Conference on Advanced Video and Signal-based Surveillance: AVSS 2018 - Auckland, New Zealand|
Duration: 27 Nov 2018 → 30 Dec 2018
|Conference||15th IEEE International Conference on Advanced Video and Signal-based Surveillance|
|Period||27/11/18 → 30/12/18|