Table 8.

Summary of the possible impact of network performance on cooperative perception.

Authors, Year	Key Research Points	Remarks
Liu et al. 2020 [99]	Analyzed the impact of the analysis of factors affecting DSRC performance.	Communication distance and shelter are the main factors that cause the degradation of DSRC communication performance, and selective deployment of roadside equipment can effectively improve DSRC communication performance.
Bae et al. 2021 [100]	Analyzed the impact of communication distance on packet reception rates in LoS and NLoS test scenarios.	Communication distance has a great influence on the reception rate of data packets. The greater the communication distance, the more serious the loss of packet reception rate.
Lee et al. 2020 [102]	Analyzed the impact of PLR and delay on V2X data fusion.	By predicting data changes and using historical data, the accuracy of data fusion can be improved, and the detection accuracy is nearly 50% higher than that of lossy networks.
Xiong et al. 2018 [104]	Evaluated the impact of latency and packet loss on the security of Internet of vehicles applications.	The higher the PLR, the lower the security. The smaller the initial speed, the lower the limit latency.
Thandavarayan et al. 2020 [109]	The study investigated the impact of congestion control on cooperative perception using the DCC framework.	The combination of congestion control functions at the access and facility layers can improve the perception achieved with cooperative perception, ensure the timely transmission of the information, and significantly improve the object perception rate.
Günther et al. 2016 [110]	Selected the best DCC variant and format of messages to maximize vehicle awareness.	The amount of data generated by cooperative perception can easily lead to channel congestion, resulting in too much old sensing information and reducing the accuracy of sensing information.
Furukawa et al. 2019 [111]	Improved the vehicle position relationship and road structure to dynamically adjust the sensor data transmission rate method to improve the transmission rate of useful information.	Selecting high-probability vehicles to broadcast data and prioritizing data from other vehicles’ blind spots reduces radio traffic and enhances the real-time situational awareness of other vehicles.
Sepulcre et al. 2020 [113]	Selected high-probability vehicles to broadcast and prioritize data from other vehicles’ blind spots, reducing radio traffic and enhancing real-time situational awareness of other vehicles.	Controlling the way the vehicle drops packets can reduce the flow of packets transmitted to the wireless channel, but the dropped packets are not transmitted, resulting in the lower performance of the application.