Little Rock, AR

AARP Community Challenge Grant Year: 2018

Project Category: Engaging people in transportation options/safety

Description: When state transportation officials asked Arkansans why they don't bicycle more, the answer was clear: Because they did not feel safe. To address this, the City of Little Rock worked to educate drivers about road safety best practices. The City developed a two-hour training -- the Friendly Driver Certification Program -- modeled after a similar program in Fort Collins, Colorado. "Twenty years ago, we didn't have any bike lanes, pedestrian hybrid beacons or other new types of facilities to keep pedestrians and cyclists safe," program coordinator John Landosky told Little Rock Soiree. "That infrastructure is only useful if drivers know what to do around it." Since its launch, the class has educated more than 500 participants, with nearly six in ten saying it made them more confident in walking or biking. The City says the training also helped lay a foundation for its Complete Streets bike plan.

North Little Rock, AR

AARP Community Challenge Grant Year: 2025

Project Category: Bike Audits

Description: Older adults in North Little Rock often navigate streets that feel unsafe to walk or cross, yet their experiences were not reflected in local planning. Womens Own Worth addressed this gap by recruiting volunteers, including many age 50-plus, to complete structured, seated bike and walk audits along a key corridor. Participants documented issues such as unclear signage, poor surface quality and limited lighting, creating a clearer picture of conditions that affect mobility and safety. One retired volunteer said the audit helped her see and describe hazards she had long sensed, noting it gave her the ability to "really see what needs improvement...and to feel like my perspective matters." The findings are being compiled into a report that will inform future planning and funding proposals, helping ensure older adults have a stronger voice in shaping safer public spaces.

Project description was created using generative AI and then reviewed for accuracy.