KLD has always invested in IR&D and sought out new areas. Our current areas of focus are:
- Crash Reconstruction
- Big Data: Management & Analysis
- Connected Vehicle & Safety
- Ped & Bike Safety
- Mobile Apps
KLD has performed analyses of individual motor vehicle crashes and of crash patterns for over 35 years. Our uniquely trained researchers and investigators perform thorough field investigations of individual crashes to reconstruct events, identify causative factors, and evaluate occupant protection and avoidance technologies. To further enhance the scope of our abilities, KLD has added staff with expertise in Total Station, Special Crash Investigations, technical/procedural document development/writing, and training. This development moves KLD into new areas of service to our clients.
Big Data: Management & Analysis
The era of big data is upon us in transportation and the potential vastness of the data becoming available can initially overwhelm traffic professionals and researchers, because the very magnitude seems to hold promises of untold levels of responsiveness and innovation. Therefore, there is a need to matching data with usage and develop a supporting set of robust tools. The management aspects (database design, data security, real time and offline systems, automated reports and health monitoring) and the analytics (dashboards, data summaries, etc.) are areas that we are currently looking to leverage our experience from work done to date.
Connected vehicles and safety
The rate of acceleration of technologies related to the autonomous/connected vehicles has been outpacing typical automotive innovation due to increased participation from a lot players outside the traditional automotive OEMs. We are soon entering the phase that will be referred to as the hybrid mode where the non-connected/semi-automated vehicle systems will co-exist with fully automated/connected systems. It is in our DNA to work on traffic safety, which is one the main driving forces/goals for this new technology. With the increased participation from the Federal government (USDOT, NHTSA, State and City DOTs) in the connected/autonomous vehicle technologies and the existing private sector involvement, this is an area that we are looking to leverage our experience to develop solutions.
Ped and Bike and Safety
The future of our planet is in our cities and urban centers. The urban migration is a trend that is expanding our cities geographically, and reshaping the urban planning paradigms. The increased reliance on non-motorized modes for transport (walking, biking, etc.) with the reduction in automobile ownership, increase in ride sharing (uber, lyft) have increased the design of ped and bike friendly areas (pedestrian malls in the large cities such as New York, Paris and London), and in turn require a different level of safety assessments for peds and bikes. The Vision Zero goals for government entities around the world have put the spotlight on ped and bike safety. We are looking to build off our strong background in safety to develop tools that work towards enhancing bike and ped safety, and to participate in large data programs related to this theme.
The mobile phone has revolutionized the way we interact with devices and ushered in an era of enhanced productivity for transportation professionals in the field. The mobile devices (phones, tablets, computers) have seen explosive growth in computational power and capabilities in terms of sensors on these devices. Leveraging these to support transportation professionals is something we have done successfully in projects such as TPMS. The ability to collect data efficiently with high quality, to monitor the data sets in real time, and to refine the experimental designs on the fly offers improved ROIs on large scale data collection efforts. Also, the need to ensure data security and privacy for both data at rest and in transit, requires special attention as well. We see the need to be involved in the areas of cyber security and transportation, with a special focus on mobile apps to support large scale data collection efforts.