This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

Stakeholders and transportation planners often use users' feedback to assess transit
services including ride hailing platforms and reflect them for future plans. Interestingly, social …

Traffic anomaly detection (TAD) in driving videos is critical for ensuring the safety of
autonomous driving and advanced driver assistance systems. Previous single-stage TAD …

Emergency management systems' performance relies on effective utilisation of available
resources and timely delivery of designated services. Intelligent transportation systems are …

Understanding speed and travel-time dynamics in response to various city related events is
an important and challenging problem. Sensor data (numerical) containing average speed …

Citizens in various locations can report local infrastructure issues to the government by
posting reports on certain websites, such as Chiba Report and FixMyStreet. Recently, these …

Enhancing road safety remains a critical concern, encompassing the well-being of drivers,
pedestrians, and cyclists alike. A promising approach to elevate road safety involves the …

Traffic flow analysis is essential for intelligent transportation systems. In this paper, we
introduce our Intelligent Traffic Analysis Software Kit (iTASK) to tackle three challenging …

Timely detection of traffic events is of upmost importance in contributing towards traffic safety
and ease of commute. A spatial mobile crowdsourcing framework is proposed, enabling …

This paper focuses on the migratable traffic risk estimation problem in intelligent
transportation systems using the social sensing. The goal is to accurately estimate the traffic …