Sustainability starts with safer roads. How do we get there?
Cities globally are racing to zero; a campaign led by the C40 to rally leadership for a healthy, resilient, zero carbon recovery — one that prevents future threats, creates decent jobs, and unlocks equitable, sustainable growth. City-led initiatives like these reflect a shift in favour of green policies to eliminate congestion on the roads, and help pedestrians reclaim the streets. Many cities have set ambitious targets in favour of sustainable transportation solutions. In London, the Mayor’s Transport Strategy outlines that, by 2041, 80% of journeys will be made by walking, cycling and public transport. Choosing the sustainable option is consistently driven by how secure — how safe — people feel on the road. Is there trust in the automated systems that manage traffic on our streets? How safe do people feel cycling in the city centre? Sustainability starts with safer roads. Artificial intelligence supports this shift.
AI encourages sustainable transportation
Road safety is a known barrier to cyclist adoption. If people feel protected on the roads, they are more likely to use bicycles, eScooters, skateboards and other sustainable means of transport. Laws banning texting while driving and other unsafe driving practices, and building out cycling infrastructure are two effective but time consuming means of making roads safe for cyclists. Rather — cities should refocus on optimising existing infrastructure for safer roads now.
Camera based artificial intelligence provides a solution. Behaviour AI enables forward collision warning, blind spot detection and pedestrian crossing intent — significantly reducing the likelihood of fatal and serious accidents with cyclists. By integrating into public transportation, bus networks and truck fleets, Behaviour AI maps the road ahead. AI provides an added level of protection for cyclists, encourages sustainable transportation and rebuilds lost trust in unsafe intersections.
AI enables sustainable city planning
Many smart tech solutions for green cities require installation of additional hardware. Upgrading existing CCTV and public infrastructure can cost municipalities thousands in additional investment; draining resources and public funds for experimental technologies that do not provide immediate ROI. Some AI solutions seamlessly integrate into any camera-based infrastructure, analysing video footage for valuable insights to enable sustainable city planning.
In one case study, Transport for Greater Manchester deployed Humanising Autonomy’s hardware agnostic solution to test the effectiveness of different measures to improve social distancing. With Behaviour AI, TfGM was able to derive immediate insights for maximum ROI. The flexibility of the platform meant no additional investment was required on infrastructure, and provided assurance to interchange managers, transport authority and passengers as data driven solutions were implemented to improve accessibility, safety and level of comfort for all passengers, therefore making public transport more attractive to use.
Safety and sustainability are not mutually exclusive
Rather, they enable each other. When adopting smart technologies to meet carbon zero emissions, cities should consider Behaviour AI to optimise pre existing infrastructure. Artificial intelligence empowers safer driving at the vehicle level through forward collision warning, blind spot detection and pedestrian intent prediction. And, as evidenced by the work with Transport for Greater Manchester, cities are able to affordably deploy AI to ascertain how public infrastructure is used, and provide an additional level of safety and accessibility to the public. It’s clear that safety and sustainability are not mutually exclusive. With the help of AI, industry leaders can tackle them together.
