## 2 IoT-Based Shared Bus Lane System (IoT-SBL)  
The IoT-SBL system proposed in this paper, as illustrated in Figure 1, aims to enhance the throughput efficiency of signal intersections, reduce vehicle queues and delays, and minimize fuel consumption. This system is designed to operate on both bus lanes and general-purpose lanes, utilizing loop detectors or cameras positioned near or above the lanes to monitor real-time traffic conditions.  
Buses are equipped with GPS and wireless communication technologies to obtain real-time spatial-temporal data. This information is collected by roadside units and transmitted to a central server for analysis and processing, enabling informed planning and decision-making. The decision-making process is activated under two specific conditions: (1) when the queue length of private vehicles exceeds a predetermined threshold, indicating congestion; and (2) when all private vehicles within the IoT-SBL area must be cleared prior to the arrival of a bus.  
Once these conditions are met, a command is issued to private vehicles, instructing them to yield access to the bus lane. The expectation is that drivers may utilize the bus lane when no bus is present; however, as a bus approaches, private vehicles will be cleared from the lane and prohibited from entering to ensure smooth transit for public transport.  
The comprehensive architecture of the IoT-based intelligent bus lane, illustrated in Figure 2, consists of three distinct layers: the perception layer, the network transmission layer, and the application layer.  
Figure 1: Overall system operation diagram.  
In the perception layer, real-time traffic conditions are monitored through intersection cameras or pre-installed loop detectors. The current position of buses is transmitted in real time via GPS or the bus's integrated Wi-Fi module, while the intersection's signal status is communicated to the edge processing unit through IoT protocols. The network transmission layer serves as a conduit for relaying the collected traffic signal statuses, bus position data, and intersection signal light statuses to the roadside unit for processing. At the application layer, the roadside unit makes decisions based on the processed information, allocating signals to vehicles equipped with Vehicle-to-Everything (V2X) capabilities. This effectively guides connected vehicles into the bus lane. For the specific case of isolated intersections considered in this study, it is advisable to avoid uploading data to a centralized server for processing. Instead, edge processing significantly reduces the volume of data that requires analysis and facilitates rapid real-time decision-making. The core of the entire system architecture consists of three modules:  
1. Traffic Data Collection Module: Responsible for receiving real-time traffic queuing information detected by loop detectors or cameras, as well as spatial and temporal information of buses, and transmitting it to the server via roadside units.
2. Lane Change Information Decision-Making Strategy: By integrating the collected traffic information, the server makes lane change decisions for private vehicles, ensuring compliance with traffic rules and constraints.
3. Private Vehicles Driver Lane Change Information Acceptance Module: Processed information from the server can be transmitted through the roadside unit to relevant signs, including vertical signal indicators, or displayed in real time on the onboard monitor using more intelligent I2V and V2V communication.