For the purpose of this work, both primary and secondary data was collected to cover every aspect of the study. Secondary data, considered as one of the first stages of our research, was collected from previous works related to our topic. Thus, we consulted documents of the works of best scholars all over the world we could lay hands on. This armed us with a better understanding of the literature drawn from the theories, concepts, principal ideas and results of these scholars. This was sourced from the internet and University libraries in Cameroon. Government Ministries and Agencies including the Ministry of Public works, Ministry of Transport, Ministry of Urban Development and Housing and Central Bureau of Census and Population Studies (BUCREP) for census results and other vital records for this study. The National Institute of Cartography provided the village dictionary and topographic maps of 1:50,000 scale of Cameroon. Meanwhile data on road network of the study area was gotten from the Ministry of Public works and from respective councils.

The primary data was collected via qualitative or quantitative investigation. As part of primary data collection, direct observation, questionnaires and interviews constituted part of the investigation. The target population of this study are the vulnerable population who live in Mbankomo, Mfou and Soa who commute to Yaounde. Amongst this targeted population, 125 questionnaires were distributed in all three communities ( Table 2 ) and 4 interviews conducted with the stakeholders in charge through which important data and information were gathered. Amongst the other information we gathered was the role they play in the transport system development and the difficulties they face in making the transport system more inclusive so that no one is left behind. The distributed questionnaire was centred on transport infrastructural and modal system which characterises inclusivity grouped under availability, accessibility, affordability, security/safety and Comfort/adaptability for the vulnerable commuter’s appraisal. For a proper and facilitated data collection process, snowball sampling was employed where a commuter was used to locate another commuter particularly for people with physical impairment. For the other segments, random sampling was employed. GPS was also used in the field to collect spatial data of minibus and clando-taxi stations. A buffer zone of 500 m wide was applied to major road networks and stations as described by the SDGs goals target 11.2 regarding access to a light duty transport stop or road network. SPSS was exploited for statistical data analysis and Arc GIS 10.8 for spatial analysis.

Source: Fieldwork (July 2025).

Availability presents to be one of the most important elements in evaluating transport inclusiveness as it sets the baseline in demonstrating if the transport infrastructure, modes and services are sufficiently provided in the first place as well as the provision of alternative options.

Multiple commuting routes which create viable mobility options are necessary as it ensures that commuters can have access to varied destinations or places of interest. It also promotes the use of public transport, provides alternatives during road closures, allows for speedy evacuations and access for emergency services and at times reduces congestion. In this regard, an evaluation of the current state of the transport system shows that the routes or lines leading to the Yaounde CBD are generally inadequate from all the three corners of the satellite towns. As seen in Figure 4 the commuters who uses shared transport system, which is of interest in this study, depends solely on one commuting route from their respective satellite towns to get to Yaounde. Whereas splitting distance especially for the vulnerable is quite challenging.

As evidenced from Table 4 , a majority of the respondents are of the fact that transport infrastructure is poor and fair. Out of 125 participants who answered this question, 59.2% in Mbankomo, 82.1% in Mfou and 64.6% in Soa rated availability of transport infrastructure, mode and services as fair. In a whole, only 26.5% respondents in Mbankomo and 10.4% in Soa mentioned that it is good.

Source: Authors, 2025.

For the transport network or modes to efficiently serve the community at all times, its infrastructure has to be adapted and comfortable if it portrays any form of degradation, safety and environmental concerns as failure to do this will obviously lead to negative consequences. This makes adaptation a key element much needed in either restoring the transport system the way it was or shaping it into a better one in meeting its users’ needs. This goes beyond availability and takes a step deeper from what’s available to how adaptable and comfortable the transport system in our case study is in relation to inclusiveness.

Most of the roads within our study area are not in good condition. Many African countries pay less interest and attention in repairing and maintaining roads [29] . These roads particularly along the Soa and Mfou lines are degraded characterised by potholes and cracks which are not adapted nor comfortable for the commuting vulnerable population. Figure 5(b) shows a clear view of this where along the Soa Yaounde road axis there exist about 34 potholes with sizes ranging from 0 to 2 m. Mfou also has a similar situation where before reaching Yaounde a commuting vehicle has to bounce in and out of about 46 potholes which is a huge challenge for the commuters ( Figure 5(a) and Figure 6 ). These potholes of varied sizes which renders commuting quite stressful. However, the Mbankomo axis presents a better case though there is the absence of potholes, it only has multiple cracks which can be related to its function as a national road as more attention is paid to keeping the road in a better state.

For the case of Soa the potholes are highly concentrated immediately before the minibus station in Soa and within Yaounde particularly along the Total Ngoussou and Fouda stretches. The case of Mfou is different and more deplorable as the cracks and potholes are sparingly distributed within the community itself with a dense and high concentration along Awae and Yaounde 4 area.

Source: Authors, 2025.

Concerning the respondent’s opinion on adaptability and comfortability, 69.4% of Mbankomo respondents mentioned that comfort is poor. This is followed with 64.3% for Mfou with a slight drop in Soa represented by 58.3% ( Table 5 ).

The globally accepted SDGs in its goa1 11.2 stipulates that a road network or station can be classified accessible, when it’s within a 500m walk to a light duty vehicle which is what was used in this study due to the absence of heavy-duty public transport like the rail. Unfortunately, in this assessment SDG 11 did not specify any particular accessibility indicator or exact distances to be covered for people with special needs regarding access to road networks or stations as it would have been necessary to evaluate this group using a different metric. As people with any physical limitation, it will normally take longer duration to access any point of interest when compared to the general or physically upright population.

So, accessibility challenges were accessed using a performance-based approach as stipulated by SDG target 11.2.4 combined with that of the commuter’s perception since this study is a people’s centric with focus on the vulnerable population.

In classifying accessibility into three categories: accessible, fairly accessible and not accessible, in Mbankomo, only 17.7% resides within the 500 m proximity threshold, 47.3% in Mfou and 31.8% in Soa. That of Mfou is higher because of linear settlement along the road and also because of a less dense population settlement which is not the case for Mbankomo and Soa which is more densely populated. As a whole, a minor portion of commuters (29.9%) is covered within 500m, with 16.8% between 500 - 100 m (fairly accessible) and a significant portion of 53.3% covered above 1000 m radius (Not accessible) ( Table 6 and Figure 7 ).

Source: Authors, 2025.

Regarding the commuter’s opinion, amongst 125 vulnerable respondents who answered this question from all three satellite towns, only 15.2% stated that accessibility is fair. They fall under the group of those who explain that they have overtime adapt to the system. Whereas a majority rated accessibility as poor represented by a total of 84.8% as seen in Table 7 . Meanwhile a greater share of the population in Mfou mentioned its poor (92.9%) followed by those of Soa (87.5%) then last by Mbankomo respondents (77.6%).

Source: Authors, 2025.

The commuting time to reach destination in most developing countries and Cameroon in particular is not a matter of choice and it’s impossible to know the exact commuting time because real time traffic flows are not available. Research from the SAMSET project (2017) engaged in supporting Sub-Saharan Africa’s municipalities with sustainable energy transition noted that many commuters in African cities experience very long travel times, often due to heavy congestion and urban sprawl [30] - [32] . This shares a similar context that is prevalent in our study area as data collected from survey revealed that it takes a long travelling time for the commuters to reach their destination. Worst is that overtime this has augmented due to population increase without corresponding modification in infrastructures and modes as necessary measures have not been undertaken to ease congestion over the years nor efficient mass public transport and other inclusive modes made available.

With respect to data collected, the mean travel time to Yaounde varies across the different towns which are intricately linked to fluctuating congestion levels especially in Mbankomo and Soa ( Figure 8 ). The long time taken to travers to Mbankomo is attributed to the frequent travelling along the NR3 linking Douala and Yaounde and the narrow road network (3 * 3). Same applies for Soa which is principally related to frequent traffic congestion and due to the merging of bigger roads into smaller ones which cannot carry the heightened number of vehicles. Another reason is due to the location of the Soa station in the heart of Yaounde city though an advantage to the commuters is not supported by the limited design put in place.

Another aspect that causes a huge barrier to transport inclusiveness is the usage of prevalent modes that do not embrace inclusive design. These modes are characterised by design deficiencies that are not convenient particularly for people with special needs. This was depicted through observation as one of the methods used in this work which revealed that the transport mode is not adapted to the slightest degree of the population. To verify if this observation was true, questionnaires from commuters were used for more clarity and certainty.

As observed in Figure 9 , most of the vehicles like the minibuses in Soa poses a real challenge for boarding and alighting as the steps and gabs are very high (25 cm) and also because the old buses being used were not designed for lowering. In addition, they do not have spacious and comfortable seating arrangements with limited space as they throw preference on carrying more passengers over comfort and there is also a complete absence of designated (priority) seats for people with special needs. As if this is not enough, they are usually poorly ventilated as most of the windows of these buses are defective. This makes commuting for the general commuters and extremely difficult for persons with mobility limitations especially the aged, pregnant women and physically handicapped. These issues are common traits of almost 65% of the 350 minibuses which run along the Soa-Yaounde stretch. There is even a more absurd practice were in Soa some of the buses are readapted to increase the number of seats rendering it more uncomfortable and inaccessible for the vulnerable groups.

These were all confirmed during the survey as both the general population and the vulnerable commuters in particular expressed the fact that none of the modes are suitable for them as the vehicles in general are not comfortable in any way.

In Mbankomo and Mfou, with similar commuting modes, the major problem expressed by the population is that of very tight and uncomfortable seats which makes commuting quite challenging as overloading is a common practice along these routes. The normal carrying capacity of four passengers is usually exceeded by up to six or seven passengers. The clando-taxis also have their own practice of which they carry two passengers in the front seat and four behind which at times pushes some of the vulnerable people to pay for two seats, which in turn affects their overall cost.

It was also noticed that, in all three areas the modes are not suitable for wheelchair users, which will normally incur extra expenses for commuting though we did not come across any within these settlements who frequently commute to Yaounde. Nevertheless, this case is important for consideration in making provisions for a complete inclusive design.

The survey responds from the vulnerable population, revealed that most of this portion of the population do not find it easy to commute due to the challenges mentioned in accessing the minibuses and clando taxis. Whereas 25% made it clear that they have adapted overtime to the modes and find it fairly accessible.

There is also Information and communication inaccessibility, due to the paucity of digital information and absence of digital payment system.

In many towns, around the world, special attention is being paid on transport cost through different incentivised methods [33] in other to encourage the usage of public transportation. This approach demonstrates the importance of such actions for the utilisation of public transport mode. Conversely in most urban milieus of Cameroon, due to the lack of public transport options commuters are forced to rely on the prevailing options owned and ran by individuals which is certainly not inclusive in terms of transport cost [34] .

The cost of transportation has increased over time due to the increase in fuel hikes and because of Covid 19 as drivers were demanded to respect social distancing. The rise in fuel prices occurred twice in 2010 and 2024 and covid 19 in 2019 which both affected transports as shown in Table 8 . Currently, transportation varies between 350 and 500 FCFA. Mfou has the highest fare at 500 followed by Mbankomo with 400 FCFA and Soa has the lowest fare at 350. Mfou is more expensive due to the distance which separates this satellite town from the Yaounde as compared to Soa and Mbankomo.

Source: SYNTRAPUIRCAM (2025), Business in Cameroon (2024).

On a general assessment, the commuters had a variety of viewports regarding transport affordability but with a general opinion who rated it as poor with a total of 95.2% as seen in Table 9 with a very insignificant population (4.8%) who rated it as fair. Most of the vulnerable population explained they spend more on transport because most often they only feel comfortable when sitting either in front of the vehicle or if they pay for two seats, which generally becomes very expensive for them as they are not covered by any special pricing scheme.

Whereas during the days of the failed Le BUS and STECY all public transportation which were operational in 2005 and 2016, transport fare was affordable only at 200 fcfa, which drops to 180 fcfa for a commuter who could purchase five (05) tickets at once. This underpins the challenge that the population are currently facing due to the absence of a public transportation system.

Source: Authors, 2025.

Most OECD countries have improved road safety through the adoption of policies that take into consideration the need of different road users embedded in the universal design principles, most especially the vulnerable. Conversely, this is not the case in most developing countries as only very few have begun to follow a similar path.

In Sub-Saharan African countries like Cameroon, safety is a real challenge for its commuters. This is related to the poor state of the transport infrastructure and the increasing use of old and road unworthy vehicles. In addition, there is the situation where all sorts of modes compete in limited road space with different speeds coupled with unsafe driving practices with vehicles that do not have the slightest degree of safety measures.

As already seen with our satellite towns, from road infrastructure and modes, none provides safety measures for its users, especially the vulnerable. Most of the limited roads and pedestrian paths are also degraded with no clear demarcations. What worsens this is the high usage of second handed aged vehicles which are prone to frequent breakdowns.

Regarding safety and security, an average of the population shared the view that the transportation system is fair (50.4%). Meanwhile 49.6% mentioned that it is poor. Nevertheless, the responds from Mbankomo shows they are facing higher safety challenges than those of Mfou and Soa as a majority the respondents mentioned that safety and security is poor (73.5%) as illustrated in Table 10 .

Averaging the means per dimension within all the three towns taking into consideration they all carry equal weights portrays that though they all face mobility challenges, Mfou commuters faces even greater challenges with a lowest mean of 1.68 followed by Mbankomo with 1.69 and then Soa with 1.75 as shown in Table 11 .

Source: Authors, 2025.

Source: Authors, 2025.

Fusing the three satellite towns, an overall assessment indicates that affordability stands as the lowest rated dimension (1.2 mean score). It is followed by accessibility with 1.5, then comfort/adaptability with 1.67 and safety/security 1.9. Availability scored the highest (2.2) though it still falls only under the fair category.

A deep dive into the indicators illustrates with clarity the areas where stakeholders’ efforts are much needed to provide an inclusive transport system for the vulnerable segment of the population. Subsidised transport fare, accommodation of modes and onboard safety reveals as areas where severe challenges lie amongst all the other elements rated as poor with the lowest means of 1, 1.02 and 1.03 respectively. Provision of information is also rated as poor with a 1.2 mean. Meanwhile, operational hours are rated good with a 3.2 mean. Onboard security and distance between stops are also fairly rated. Table 12 shows a detail ratings of all the 25 indicators.

Source: Authors, 2025.