# Smart Intersections and Connected Autonomous Vehicles for Sustainable Smart Cities: A Brief Review
## 6 Case Studies of Smart Roads and Intersections  
There is a high degree of heterogeneity globally in deploying smart roads and smart intersections, reflecting differing policy priorities, tech capabilities, and mobility challenges in urban areas. Some cities have achieved measurable improvements in traffic congestion, safety, and sustainability, yet many infrastructural, economic, and societal factors shape their success. Some case studies are briefly considered here: Amsterdam, Toronto, London, Korea, and Barcelona are critically appraised based on their strategies for smart transportation systems; in addition, C-Road Platforms are considered. Amsterdam has implemented and tested the so-called Shockwave jam services on the A58, the Netherlands' first cooperative vehicle-roadside system for the motorway between the cities of Eindhoven and Tilburg [155]. Shockwave Traffic Jams A58 was the first in Europe to implement the prescribed data security measures for WiFi-P and immediately raised them to a higher level [156, 157, 158]. Toronto has implemented AI-driven traffic optimization systems [159, 160, 161]. SCOOT has been the lifeline for real-time traffic optimization in London for quite some time; the new kid on the block FUSION comes with machine learning and digital twin modeling. Even with FUSION, with its 15% improvement in travel time reliability, the deployment is a testament to AI-powered urban traffic control problem-solving when presented on such a large scale. Public perception is still off, with a certain level of mistrust in the transparency of AI decision-making. Because adaptive traffic models need constant recalibrations, the long-term financial sustainability of FUSION is possible in cities with less constrained budgets [162, 163]. Pyeongtaek City (South Korea) is implementing edge AI-powered intelligent intersections in South Korea, which is a pioneering effort at AI data centralization for real-time decision-making and traffic signal coordination. Unlike cloud-based models, the edge AI conducts in-device (local) data processing and lowers latency for faster response times. The model resulted in quantifiable benefits such as a 25% reduction in congestion and an increase in pedestrian safety by an average of 30% [164]. Barcelona has hyper-optimized pedestrian areas and eliminated vehicle traffic in most city center streets with the \"Superblock model\" project. This model tends to favor central urban districts at the expense of neighboring road congestion. Instead, congestion is relocated by routing traffic away from the intended destination places, even in the case of AVs [165]. The case studies show that although we believe smart road and intersection solutions are game changers for traffic efficiency and safety, many things work together for successful deployment. The Amsterdam C-ITS model illustrates the difficulty in building connected vehicle systems in mixed-traffic environments. The AI signals in Toronto show what happens when the efficiency vs. equity tradeoffs come to vulnerable road users. London's FUSION model presents the conundrum between the optimization of algorithms and transparency; South Korea's edge AI approach introduces security and scalability concerns. Finally, Barcelona's Superblock initiative illustrates the socio-political aspects of moving towards Western-oriented urban mobility. In Europe, with the C-Roads Platform, various road operators join together to harmonize cooperative intelligent transport system (C-ITS) deployment activities in European countries. The main objective is the deployment of interoperable cross-border C-ITS services for road users, especially the so-called \"Day 1--C-ITS service\" and \"Day 1.5--C-ITS service\". The core C-Roads Platform members (Figure 1a) are Austria, Belgium/Flanders, Belgium/Wallonia, the Czech Republic, Denmark, Finland, France, Germany, Hungary, Italy, the Netherlands, Norway, Portugal, Slovenia, Spain, Sweden, and the United Kingdom.