Meng Wang

Coordination between tram rescheduling and signal control is critical for urban traffic systems recovering from tram disturbances. This paper develops a Multimodal Coordinated Optimization framework for tram Rescheduling and Signal control (M-CORS) benefiting both road and tramway traffic. With the objective of minimizing tramway total delay and waiting time at intersections, and maximizing road traffic throughput, the model captures tramway and road traffic dynamics with their interactions by the disjunctive graph and improved Link Transmission Model (LTM) to derive the optimal tram timetable and signal green ratio. The M-CORS is formulated as a Mixed Integer Programming (MIP) and solved using a Benders Decomposition (BD) algorithm to ensure computational tractability and solution optimality. Two case studies are conducted on a synthetic grid network and the Dresden network. Numerical results on a synthetic grid network demonstrate that the proposed M-CORS reduces average road traffic delay by over 20\% under different degrees of Right-Of-Way (ROW), while the total tramway delay decreases by 37.9\% in the fully shared ROW scenario. The real-world case study in Dresden, Germany, verifies the model applicability on large urban multimodal network by recovering the network within one hour. These findings highlight the effectiveness of M-CORS in improving multimodal stability and reliability after tram disturbances.

Intersections account for a significant proportion of bicycle-to-vehicle accidents, where early recognition of a cyclist’s turning intention is essential for collision avoidance and trustworthy warnings. We present a model-based framework that combines map-derived routes with sensor data to estimate maneuver probabilities from position, heading, speed, and yaw rate. Focusing on left/right turns versus going straight, we evaluate how detection accuracy evolves under different temporal horizons and reference points. Results show that incorporating trajectory prediction improves early detection, enabling detection of right-turn intentions up to 3 s before the conflict point. Position provides the most reliable late-stage confirmation within the final 2 s (more than 80% accuracy), while speed provides earlier but less stable cues. These findings reveal the variable-wise, stage-dependent reliability of kinematic variables, providing interpretable guidance for intelligent transportation systems safety systems, including advanced driver assistance systems and vehicle-to-everything applications to protect cyclists at intersections.

Modeling multimodal traffic dynamics and their interactions in a unified framework is critical for urban traffic planning and coordinated management. Nevertheless, continuous road traffic and discrete tramway traffic were often studied separately with distinct modeling paradigms, overlooking inter-modal interactions. We propose a continuum multimodal traffic dynamic model based on kinematic wave theory to capture the evolution of both traffic modes and their interactions within a consistent framework. The Lighthill–Whitham–Richards (LWR) model is adapted to tramway traffic and solved semi-analytically using the variational theory, consistent with road traffic modeling. Building on this, multimodal traffic dynamics are formulated for both separated and shared right-of-way (ROW) conditions. Numerical experiments are conducted to verify the effectiveness of the proposed model, evaluate the delay sensitivity to traffic demands, and assess the tramway traffic resilience to disturbances. Results indicate that the model accurately captures multimodal traffic dynamics under diverse conditions and demonstrates strong potential for urban traffic analysis and coordinated control.

Vehicle platoons employing Cooperative Adaptive Cruise Control (CACC) exhibit outstanding performance. However, communication interruptions can destroy string stability and jeopardize driving safety of the platooning systems. To address this issue, this paper proposes a controller switching strategy and derives an analytical model to determine the boundary of communication delays. When the communication delay exceeds this theoretical boundary, the system seamlessly transitions from the primary CACC controller to a backup Adaptive Cruise Control (ACC) controller. The cost function and co-states are continuously adjusted during this transition using a Gaussian membership function. Analytical derivations demonstrate that the proposed switching strategy theoretically guarantees string stability. Comprehensive simulations further validate its effectiveness through both standardized scenario-based evaluations and real-world tests using the NGSIM dataset. Compared with existing methods, the proposed approach improves the string stability by 16.87% and enhances the safety index by 68.28%.