A biographical note about me (Laurence Howe)

I left school at the end of 1962 with few qualifications and spent a short period of time in the Royal Signals where I worked in the fields of digital electronics and cryptography.  Following that, I worked in various environments, including retail, office and engineering.   I then became an analogue electronics technician repairing mainly televisions and audio equipment.   Later, I transferred into a career as a training professional, where I began teaching electronics and microprocessor applications before specialising in team building and leadership.

In 1987, I gained a first class honours degree in maths and physics before undertaking post-graduate studies in neutron scattering and computer modelling.  After obtaining my PhD in 1990, I worked as a computational physicist with the Atomic Energy Authority.   Later, I branched out into risk-based studies as a consultant, where my work encompassed areas such as project risk management and failure analysis.  During this time, I developed my VEDENS traffic simulation, which was published in 1997.   In 2000, I completed an MBA with the Open Business School, which enabled my to undertake more strategic work in the area of risk.

As a result of my experience in the field of traffic modelling I was summoned to the National Traffic Control Centre (NTCC) in 2004 to help improve the accuracy of the traffic flow data.  By using the VEDENS traffic simulation, I was able to demonstrate the limiting parameters for calculated traffic flows. The following year, I was appointed Chief Scientist at NTCC, a post which I held until my retirement from full-time employment in May 2010.  The first formal output was the Long-Term Integration Process (LIP), a self-consistent method for detecting inaccurate traffic counts from inductive loop counting sites.   LIP was eventually developed as the CAVEMAN process for the automatic recording of counting site accuracy, which became the benchmark for classifying traffic count accuracy.   Later, I used the VEDENS model to demonstrate the feasibility of estimating delays for en route drivers by using traffic counting data.  This was developed as EDDEE (Event Detection and Delay Estimation Engine), but more work remains to be done before EDDEE can become a useful tool.