This work contributes to the field of agricultural vehicle dynamics by assessing the dimensional sensitivity of over-arch differential drive vehicle performance. The findings from this work are important for vehicle optimisation with regards to drive forces, energy consumption, chassis loading, and vehicle stability. Dimensional optimisation of the vehicles has been ignored, which is a problem if efficient and environmentally friendly autonomous over-arch agricultural vehicles are to be built. Worldwide, one in nine people do not have enough food to eat. The World Food Program has a goal to end hunger and improve the quality of available food by 2030. In New Zealand, the agricultural industry contributes $13.8 billion dollars to annual GDP and is growing, making agriculture’s contribution valuable to the New Zealand economy. However, there is a labour shortage in agriculture. This shortage of labour negatively effects food production. One potential solution to the labour shortage is automation. Differential drive mobile robots (DDMRs) are often used in agricultural automation research because they are simple and cheap to build, and the drive system is ideal for an over-arch chassis design. Over-arch vehicles are often required in vineyards and apple orchards. Research into DDMRs is largely limited to optimisation of control and path tracking, but optimisation of the physical vehicle has been ignored. In order to optimise vehicle dimensions before manufacturing starts, the influence of dimensions on drive forces, energy consumption, chassis loading, and vehicle stability needs to be assessed. In this study, a dynamic model of a large scale agricultural over-arch DDMR is constructed and the dimensional sensitivity of peak drive/braking force, energy consumption, chassis shear force and lateral chassis splay/compression force is assessed. The effects of caster trail and the lateral position of the center of mass on stability are also assessed. Results show that peak drive/braking force, energy consumption, stability and chassis loading are all sensitive to vehicle dimensions to different degrees. Energy consumption showed the least sensitivity, while forces were found to be significantly influenced. For a large scale DDMR traversing common agricultural trajectories, increasing caster trail by 0.2 m, decreasing longitudinal position of the center of mass by 0.2 m, and increasing track width by 0.2 m provides a decrease in peak drive force of 56.4 %, 13.9 % and 9.37 % respectively. These sample results illustrate the importance of understanding dimensional sensitivity, because they are not insignificant. The dimensional sensitivities were also found to be a good guide for vehicles of smaller scale. A case study was conducted on a Simulink model of a large scale over-arch DDMR designed for operating in vineyards. Dimensional optimisation was successfully performed such that the vehicle was able to operate adequately in the simulated vineyard environment. The case study illustrates that dimensional sensitivity is useful for the optimisation of a vehicle for its intended working environment. This works shows that physical optimisation of these vehicles is extremely important. If optimised, savings could be found in energy consumption, cost, and materials. As automation becomes more important, accurate vehicle control is essential for performance and safety, and the work in this thesis helps to achieve this. The products of dimensional optimisation benefit the overall effort to fill the labour gap and supply enough food for the worlds growing population.