## 3 Urban Road Intersection Traffic Spatiotemporal Collaborative Optimization Methods
Table 1 summarizes the technical characteristics, applicable scenarios, and performance improvements of different spatiotemporal collaborative optimization methods, providing a systematic framework for understanding current research achievements and future development directions. Despite the promising theoretical advances in spatiotemporal collaborative optimization, several critical implementation challenges persist. Penetration rate dependency represents a fundamental limitation, as most optimization methods require minimum CAV penetration rates (typically 20-30%) to achieve meaningful benefits, creating a \"chicken-and-egg\" problem during the transition period. Communication reliability poses another significant challenge, with V2X communication subject to latency, packet loss, and security vulnerabilities that can compromise control effectiveness. The computational complexity \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Optimization** & **Main Characteristics** & **Applicable Scenarios** & **Performance Improvement** & **References** \\ \hline \multirow{4}{*}{Signal Optimization-Based on Vehicle Trajectory Data} & Uses vehicle trajectory data for signal optimization; compensates for low penetration rates through statistical methods; establishes urban intersections & Low penetration rate probe vehicle environments; real urban intersections & Reduces delay by up to 20\%, decreases number of stops by 30\%; significant implementation results in Birmingham, Michigan & [PERSON] et al. (2011); [PERSON] et al. (2012) \\  & & & & \\  & queues with vehicle movements & & Birmingham, Michigan & \\ \hline \multirow{4}{*}{Spatiotemporal Collaborative Control in Connected Vehicle Environment} & Two-stage optimization (signal timing first, vehicle trajectories); single-layer joint optimization (simultaneously vehicle environments; simulated intersections) & High connected vehicle penetration rate & Vehicle delay reduction up to 24.0\%; CO\({}_{2}\) emissions reduction of 13.8\%; improved throughput; no level to presently terminal conditions & [PERSON] et al. (2013); [PERSON] et al. (2014) \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multirow{4}{*}{Collaborative Control Strategies in Heterogeneous Traffic Environment} & Traffic control based on & Mixed environment of connected automated vehicles & Average vehicle delay reduction of 54.32\%; emissions reduction of 54.32\%; vehicles & [PERSON] et al. (2015); \\  & & (SPDL); using CAVs as “catalys” & vehicles & 19.1\%; most significant & [PERSON] et al. (2015); \\  & to promote controllable platoon & and human-driven & benefits under medium benefits under medium & [PERSON] et al. (2016); \\  & formation; combining lane & vehicles; medium-low & traffic demand; low & [PERSON] et al. (2017) \\  & assignment with signal-vehicle & CAV penetration rate conditions (around 20\%) & sensitivity to CAV market adoption rate & \\ \hline \multirow{4}{*}{Routing Control and Behavior Prediction} & Multi-objective routing control based on deep Q-networks; hierarchical prediction framework considering traffic signals and interactive agents; combining detection and trajectory prediction and continuous trajectory prediction & Dynamic traffic environments; complex time, and waiting time; anonymous prediction accuracy; enhances decision-making safety & Reduces autonomous vehicles travel distance, time, and waiting time; & [PERSON] et al. (2018); \\  & & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\ \hline \multirow{4}{*}{Flexible Lane Assignment and Phase Swap Strategies through pre-signals; enabling all lanes to be used for discharging vehicles during green phases} & \multirow{4}{*}{Saturated or near-saturated intersections; urban intersections requiring intersections requiring fixed infrastructure environments} & Significantly increases increases increases increases synchronized & \multirow{4}{*}{[PERSON] and [PERSON] (2010); } \\  & & & & \\  & & & \\ \hline \hline \end{tabular}
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