[Nairobi city. Photo/courtesy]
Ma3Route, Kenya’s leading transport communication platform, has unveiled Nairobi’s first geo-coded accident dataset in a project which was carried out in 6 months from May – October 2015. Ma3Route had 500,000 + users at the time of the project.
The project was undertaken by 4 entities comprising of teams from Ma3Route, University of Nairobi, iHub Research and MIT Civic Data Design Lab.
During the period under review, the team studied 7,817 accident reports. There were 3,941 unique accidents that were reported, 1,900 verified accidents and 1,324 geo-coded verified accidents.
The data analysis involved linking individual reports, identifying road and landmark, reverse geo-coding and categorizing road users.
Despite the high concentration of Ma3Route users in Nairobi, the pilot also collected data far beyond the capital city. Nairobi, Kiambu and Machakos Counties had the highest cases of accident reported with 950, 111 and 56 cases having been reported respectively.
Nandi, Migori, Homabay, Busia and Bomet Counties had almost zero cases of accidents reported.
“Out of the 950 cases of accidents reported in Nairobi, we managed to map out 13 accident blackspots which are Cabanas, GM, Panari, Bellevue, T-Mall, Haile Selassie, Museum Hill, Kangemi, Waruku, Safaricom, Githurai, Pangani and Donholm,” Elizabeth Resor, the Data and Research Lead at Ma3Route said.
The team also studied the road user most responsible for accidents. It was found out that although private cars are the type of vehicle most often in an accident when taking into account the number of people affected by a single accident, PSV affect the most people because they carry the most people.
“For example, on June 18, at 6.38pm (period under review), there were 109 reports of two buses on a certain spot that had collided causing the death of two people and injuring scores others,” Resor noted.
The study also found out that 42.5% of accidents involving pedestrians happened within 500m of a pedestrian bridge.
“This shows a clear gap on the efficacy of footbridge in reducing pedestrian casualties or injuries without considering behavior change communication,” the Lead researcher pointed out.
She was speaking at a recent Nairobi BRT forum hosted by Institute for Transportation Development Policy (ITDP).
Majority of people find it time consuming climbing over a footbridge, hence end up being knocked down by fast-moving vehicles on the motorway as they run helter skelter past oncoming cars to cross to the other side of the road.
Trucks stood out at number 3 as the user most responsible for accidents after private cars and PSVs (the leading).
“To deal with the enormous traffic menace and to make people realize the benefits of daily commuting, we need to divert trucks out of the city using the bypasses,” added Resor.
The researchers observed that in terms of time of accidents, peak hours for traffic are –not surprisingly –also peak hours for accidents. Friday and Saturday have on average had the most accidents.
The National Transport and Safety Authority (NTSA) has in the past attributed the high number of casualty during the weekend to the high number of people travelling.
“From the data we collected, we found out most rush hour accidents tend to occur between 6-9am and 4-9pm,” said the Lead researcher.
The team also suggested other topics of interests for crowdsourcing which included Traffic, Weather & Road Conditions, Public Safety Concerns and Police Corruption.
As they call for collaboration with other like-minded individual and organizations, the Researchers noted that a mix of rich and diverse datasets will create a much more complete picture of a challenge such as road safety.