Framework and Algorithms for Data Analytics, Semantic Querying and Realistic Modelling of Traffic

Sagar Pathrudkar, Guido Schroeer, Vijaya Indla, Saikat Mukherjee

2023

Abstract

Infrastructure elements would be crucial in enabling autonomous mobility at scale to provide centrally shared insights and possibly planning and control. Infrastructure mounted multi-sensor perception systems observe traffic and generate data in object list format which typically consists of timestamped vehicle trajectories and metadata about the vehicles, ie, their type, dimensions, etc. Such data is huge in volume and its analysis is difficult due to the spatiotemporal sequential nature of the data. In this work, we present framework and algorithms to semantically model and analyze this data in the context of map geometry to gain statistics and insights at an actionable level of abstraction. We start with algorithms to process common 2D-HDmap formats to extract map features - roads, lanes, junctions, etc. We then present meaningful traffic KPIs and statistics that describe traffic patterns. We finally describe methods to abstract the traffic patterns and driving behaviors into parametrized functions for various applications.

Paper Citation

in Harvard Style

Pathrudkar S., Schroeer G., Indla V. and Mukherjee S. (2023). Framework and Algorithms for Data Analytics, Semantic Querying and Realistic Modelling of Traffic. In Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-652-1, SciTePress, pages 240-247. DOI: 10.5220/0011838900003479

in Bibtex Style

@conference{vehits23,
author={Sagar Pathrudkar and Guido Schroeer and Vijaya Indla and Saikat Mukherjee},
title={Framework and Algorithms for Data Analytics, Semantic Querying and Realistic Modelling of Traffic},
booktitle={Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2023},
pages={240-247},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011838900003479},
isbn={978-989-758-652-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Framework and Algorithms for Data Analytics, Semantic Querying and Realistic Modelling of Traffic
SN - 978-989-758-652-1
AU - Pathrudkar S.
AU - Schroeer G.
AU - Indla V.
AU - Mukherjee S.
PY - 2023
SP - 240
EP - 247
DO - 10.5220/0011838900003479
PB - SciTePress