A staggering $23 billion annually—that’s the societal cost attributed to sitting at red lights and the ensuing traffic congestion, as revealed by the 2019 Traffic Signal Benchmarking and State of the Practice Report.
Not only does this result in wasted time and vehicle wear and tear, but it also significantly increases emissions, with pollutants like carbon monoxide, carbon dioxide, nitrogen oxides, and particulates soaring up to four times higher in typical high-congestion scenarios.
The traditional approach to optimizing traffic light timing relies on outdated traffic studies, with costs for gathering data at a single intersection reaching over $5,000.
Considering there are more than 330,000 traffic light-controlled intersections in the US alone, the financial burden becomes alarmingly evident. Moreover, conventional traffic studies merely offer snapshots of specific intersections rather than providing a comprehensive citywide traffic flow overview.
To address this issue, engineers at the University of Michigan have devised a groundbreaking method leveraging data from connected cars to develop dynamic traffic models.
Unlike traditional methods, which require timing adjustments every few years at significant expense, this innovative approach enables frequent optimization of traffic light timing at a fraction of the cost.
While adaptive traffic lights using vehicle detection technology have been available for decades, their implementation costs range from $15,000 to $100,000, posing a significant financial barrier.
From in-road sensors to complex camera systems, the expense and maintenance requirements remain substantial, especially for retrofitting existing intersections.
In a recent study conducted in Birmingham, Michigan, Professor Henry Liu and his team demonstrated the effectiveness of utilizing data from connected cars to improve traffic flow.
By analyzing information supplied by a small fleet of GM-connected vehicles, new timing plans were developed and implemented, resulting in a remarkable 20% reduction in travel times and a 30% decrease in the need to stop at traffic lights.
This groundbreaking approach not only offers significant cost savings but also delivers tangible improvements in traffic efficiency and environmental impact.
By harnessing the wealth of data already available from connected vehicles, cities can pave the way for smarter, more adaptive traffic management systems, ultimately enhancing the quality of urban mobility for all.
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