efforts. In the development of today’s truly smart cities, the infrastructure is at the core of all things pedestrian. This is being seen up and down the West coast of the U.S., in cities like Seattle; Portland, Ore.; and San Jose, Calif., where officials are reshaping busy corridor strategies leveraging AI and data technology to move urban transit, pedestrians, bikers, commuters, and first responder vehicles in a more concerted effort. These reshaped urban transit strategies, centered on prescriptive efforts in reducing congestion, have resulted in less stop-and-go traffic, where pedestrians can be more in tune where they co-exist better with traffic systems. The design of modern vehicles also plays a role. Today’s cars are equipped with numerous in-dash technologies that,while convenient, can also be distracting. Infotainment systems, navigation aids, and even advanced driver assistance systems can divert attention away from the road. Furthermore, larger vehicles like SUVs and trucks, which are more popular today than ever, pose a greater threat to pedestrians due to their size and weight. As one example, Tesla’s Cybertruck is measured at 6,843 pounds, and can accelerate from 0-60 mph in 2.6 seconds. For comparison, the 2023 Ford F-150 starts at slightly more than 4,000 pounds and can go from 0-60 mph in about 5.5 seconds. The Cybertruck’s extreme acceleration capabilities, combined with its weight, means that drivers will have less time to react to pedestrians, and collisions with them will be deadlier. THE ROLE OF AI IN ENHANCING PEDESTRIAN SAFETY AT INTERSECTIONS AI offers promising solutions to improve pedestrian safety at intersections. AI transit prioritization systems can enhance the management of traffic flow, reduce accidents, and save lives. Here’s how: • Adaptive traffic signals: AI-driven adaptive traffic signals can adjust signal timing based on real-time traffic conditions and pedestrian activity. Traditional traffic signals operate on fixed schedules that do not account for variations in traffic flow or pedestrian presence. AI systems can analyze data from cameras, sensors, and other inputs to dynamically adjust signal timings, ensuring pedestrians have sufficient time to cross safely. This will result in resetting roads not just to the demands of vehicles and constantly changing vehicle traffic patterns, but also resetting to pedestrian and bicyclist demands. Imagine a day when walkers and runners can enjoy a series of green lights, in addition to cars and buses. • Predictive analytics: AI can use historical data and real-time inputs to predict potential pedestrian-vehicle conflicts. By identifying patterns and high-risk times or conditions, city planners and traffic managers can implement targeted measures to enhance safety. For instance, predictive models can inform the placement of additional signage, speed bumps or pedestrian crossings in areas with high pedestrian traffic. • Enhanced data collection and analysis: AI can improve the collection and analysis of data related to pedestrian safety. By continuously monitoring traffic patterns, pedestrian movements and accident data, AI systems can provide valuable insights for improving intersection design and traffic management strategies.This data-driven approach enables more informed decisionmaking and better resource allocation. As we continue to embrace technological advancements, it is imperative that city planners, policymakers, and technology developers collaborate to implement AI-driven solutions that are more predictive and prescriptive. The future of pedestrian safety depends on our ability to leverage these innovations to create smarter, safer and more efficient urban environments. 12 BUSINESS VIEW MAGAZINE VOLUME 11, ISSUE 06
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