# Monitoring Technologies for Truck Drivers: A Systematic Review of Safety and Driving Behavior
## 3 Results
### Monitoring Technologies
#### 3.3.6 Connectivity and Communication Systems  
Connectivity and communication systems, such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies, have revolutionized the monitoring and management of truck drivers' safety by enabling real-time data exchange and communication. These systems enhance situational awareness, facilitate decision-making, and reduce the likelihood of accidents.  
[PERSON] et al. [43] analyzed the implementation of connected vehicle (CV) technology in Wyoming under the Wyoming Department of Transportation pilot program. The program aimed to improve safety along the Interstate 80 corridor through vehicle-to-everything (V2X) communication technologies, offering applications such as forward collision warnings, traveler information messages, and distress notifications. Results highlighted the effectiveness of CV training programs for professional truck drivers, with participants demonstrating increased understanding and usage of CV warnings. The study also underscored the role of V2X technology in mitigating risks under adverse weather conditions, such as low visibility and icy roads.  
[PERSON] et al. [44] explored the use of a human-machine interface (HMI) for cooperative truck overtaking maneuvers enabled by V2X communication. The system facilitated the negotiation of overtaking requests between drivers, improving coordination and reducing traffic conflicts. However, the study noted limitations in the success rate of automated cooperation requests, primarily due to suboptimal HMI design. Furthermore, system failures, such as communication disruptions, were not perceived as safety-critical by drivers, but effective information delivery was crucial to maintain trust and system acceptance.  
[PERSON], [PERSON], and [PERSON] [45] assessed the use of Basic Safety Messages (BSMs) transmitted in connected vehicle environments to detect crash-prone conditions. By leveraging trajectory-level data, the study demonstrated the potential for detecting and mitigating rear-end and run-off-road crashes. The introduction of kinematic-based surrogate measures of safety, such as steering and acceleration variability, allowed for the precise identification of crash-prone scenarios. The findings highlighted how real-time data sharing in CV environments can significantly enhance predictive safety measures.  
[PERSON] et al. [46] investigated the impact of a connected vehicle-based variable speed limit (CV-VSL) application on truck driver behavior under adverse weather conditions. Utilizing a high-fidelity driving simulator, the study found that CV-VSL systems significantly reduced speed variability and improved compliance with speed limits. This reduction in speed inconsistencies directly correlated with a decreased likelihood of crashes, especially in hazardous weather conditions. The study emphasized that such systems provide proactive warnings to drivers, enabling better decision-making and safer driving.  
Despite the numerous advantages, connectivity and communication systems face challenges such as high implementation costs, infrastructure requirements, and varying driver acceptance rates. Furthermore, system failures or partial adoption in mixed-trafficenvironments may undermine the full potential of these technologies. Addressing these limitations through comprehensive training programs, infrastructure investments, and system reliability improvements can ensure wider adoption and enhanced safety outcomes for truck drivers.