Proof read my answers to job competency questions (Native English speakers only)

As part of a job application, I have some competency questions which I have answered (attached to this project description). Considering that this is just a draft, I need a native english speaker to professionally proofread this piece, ensuring that:- 1. The sentences are gramatically punctuated correctly and are very coherent, and engaging. 2. The overall style of writing is consistent and the write up is coincised. 3. Clumsy sentences are replaced with ones that are highly engaging with alot of punch/action words, and are straight to the point. This is a relatively simple project and so would be expecting to entertain bids from proven and engaging writers with a native command of english. **To help me decide if you are best suited for this job, please include as part of your bid, a proofread version of the answer to the first competency question which is detailed below:- Draft version of answer to first competency question -------------------------------------------------------------------------------------- I have a PhD in Mechanical Engineering from the University of Bath. In the Chapter 6 of my PhD thesis titled: ROBUST REAL-TIME CONTROL OF A PARALLEL HYBRID ELECTRIC VEHICLE, I undertook a related study to investigate the potential for reduction of fuel savings through vehicle speed control, using driving information. Here, easily available partial route preview driving information like: Route speed limit, average driving speed on route (obtained using GPS), minimum driving speed on route, was used to compute using the dynamic programming algorithm, an optimal speed-distance profile for a hilly driving route. Simulation results show that, using the proposed optimal vehicle speed control method, as much as 54.45% fuel savings on conventional vehicles and 64.81% on Hybrid Electric Vehicles could be achieved, with only a 12.69% penalty in driving time. Building on my already established interest and background in the use of driving information for optimisation of vehicular fuel economy, I intend to contribute in the following ways:- 1. Develop quantitative metrics for measuring driver reactions to different driving scenarios and quantify the the fuel and emissions cost of each reaction. 2. Develop a detailed human-traffic reaction model that is generic and representative of most driving reactions to different scenarios, with provision for future updates to the behavioural database. 3. Validate the human-traffic reaction model using experimental testing in form of blind trails with various drivers. 4. Compute a database of global optimal reactions to different driving scenarios (using this database as a representation of the best possible fuel savings). 5. Re-compute the optimal reactions taking in to consideration constraints like driver reaction time, driver intentions and driveability. 6. Compare and validate the resulting quasi-optimal optimisation model with the global optimal model, using experimental testing on actual vehicles. 7. Analyse results, Explain observed trend and publish research findings.