Integrated Connected Data for Safer More Efficient Traffic Management Operations

Regulating jaywalking behaviour in adaptive traffic signal control using a novel deep reinforcement learning approach

Lok Sang Chan, Xiaocai Zhang, Neema Nassir, Majid Sarvi

2026-06-01

This paper presents a deep reinforcement learning based adaptive traffic signal control framework that explicitly models jaywalkin..

Multi‐Objective Multi‐Step Adaptive Traffic Control (MOMSATC): Prioritising Pedestrians for a Safe and Sustainable Transport Development

Lok Sang Chan, Xiaocai Zhang, Neema Nassir, Majid Sarvi

2026-01-01

This paper introduces MOMSATC, an innovative multi-objective, multi-step adaptive traffic signal control framework grounded in the..

Preemptive crash risk reduction through a real-time cost-based safety prediction model (RECOSAM) for traffic signal control

LS Chan, N Nassir, X Zhang, M Yazdani, M Sarvi

2025-12-01

This paper proposes a novel real-time cost-based safety prediction model (RECOSAM) and incorporating it in intersection traffic si..

Intelligent vehicle pedestrian light (IVPL): A deep reinforcement learning approach for traffic signal control

M Yazdani, M Sarvi, S Asadi Bagloee, N Nassir, J Price, H Parineh

2023-04-01

Deep reinforcement learning (RL) has been widely studied in traffic signal control. Despite the promising results that indicate th..

Temporal pattern mining of urban traffic volume data: a pairwise hybrid clustering method

Iman Taheri Sarteshnizi, Majid Sarvi, Saeed Asadi Bagloee, Neema Nassir

2023-01-01

Multiple pattern analyses of traffic data have been conducted previously; however, it has yet to be explored with an awareness of ..