Jorge R. Ramos

Tool with Road-Level Crash Prediction for Transportation Safety Planning

The growing use of packages based on geographic information systems (GISs) in transportation planning is assisting in the development and implementation of methods that facilitate consideration of safety. This paper presents a method of predicting safety for planning alternatives. Although applicable to large road networks, the method predicts crashes at the road facility level (intersections and segments). Thus it is suitable for joint evaluation of modifications of the road network, changes in network traffic flows, and improvements in road geometry considered by planners. A complete set of crash prediction models was developed by the authors for seven types of road segments and four types of road nodes on the basis of crashes reported on Indiana highways from 2003 to 2005. A mainstream research method has been used: negative binomial regression with a stepwise method for variable selection and the Akaike information criterion. The obtained equations are transparent to transportation planners and allow efficient computations for large road networks. The crash prediction equations have been implemented in the GIS-based planning package TransCAD as an add-on tool. The calibration procedure included in the tool allows a planner to search for optimal values of calibration factors if calibration of crash prediction models is needed.

A fast computational algorithm for simulating round-robin service

An efficient computation-based algorithm for effecting round-robin (RR) service in discrete-event simulation systems is presented. The new algorithm improves upon an older computational algorithm which itself is an improvement over naive RR scheduling currently in use in process-oriented simulation systems. The naive approach can be prohibitively expensive due to process context switch overhead. The original computational algorithm avoids much of this context switching but offers a run-time complexity of only O(n2), where n is the size of the job pool. This is because the processing of each arrival and departure event requires a traversal of the entire pool. In this paper, we propose an improved algorithm which reduces run-time complexity to O(n log n) by using tree-based data structures. The expected computation to process each arrival or departure event is proportional to O(log n). Empirical evidence suggests that, except for very small size of job pool, this algorithm is considerably faster than other methods.

Efficient implementation of multiprocessor scheduling algorithms on a simulation testbed

A layered and modular approach to implementing a process‐oriented simulator testbed is described. The simulation kernel is supported by a threads library and is, in turn, capable of supporting distinct domains or application areas for various applications. The testbed offers an implementation methodology for testing novel simulation algorithms at the domain level, without interfacing with the kernel. To demonstrate its utility, a novel algorithm for simulating multiprocessing with round‐robin scheduling is presented. The algorithm is more complex than the naïve round‐robin implementation in use, but offers significant performance improvement. Copyright

Updating RoadHAT: Collision Diagram Builder and HSM Elements

were compared and their performance evaluated using Indiana data. The HSM models also were checked as to whether they would perform better in Indiana by calibrating them with Indiana data. A second major component of the study was to improve the current Indiana safety management tool, RoadHAT2, by developing a computer application facilitating preparation of a so-called collision diagram. These diagrams are an important component of safety audits. However, they are not used frequently due to the considerable time required to build collision diagrams.

A framework for synthetic stego

We present a technique for hiding information in stochastic settings via data-synthesizing schemes based on transform-expand-sample (Tes) processes. The technique is applicable whenever data generated by an application or process is sufficiently complex to exhibit random but structured behavior (such as in collective data transforms), and data trajectories have viable alternatives that are unverifiable or simply hard to verify. In such cases, a synthesizing procedure generates novel data that either actually replaces, or is generated instead of, application or process data. When information can be hidden in such data at levels higher than typical levels of noise, message-neutralizing attacks will fail; and if synthetic data, stego data and application/process data cannot be distinguished, secure stego transmissions can be launched. An information-theoretic model shows that such hiding techniques are arbitrarily secure. We present some experimental results.

Knowledge-Based System to Support Site Investigation for Safety Improvement

Specialists in transportation and other areas of engineering are trying to improve road safety. The most difficult part is determining the road features, driver behaviors, and vehicular failures that unduly increase the risk of crash. To help INDOT safety investigation teams, a previous research project developed a prototype Road Safety Investigation Tool (RSIT) for two-way stop-controlled intersections. The research summarized here has evaluated the prototype RSIT and has developed a new version RSIT2 that has incorporated the findings of the evaluation. The evaluation of the RSIT prototype confirmed usefulness of the proposed methodology. The tool has been applied to two two-way stop-controlled intersections by a team of non-experts. The two sites have been previously investigated by experts using the standard approach. The safety investigation outcomes obtained by both the teams indicate strong similarities. The proposed RSIT method helped non-experts identify additional road hazards confirmed later by the experts’ team. RSIT has been found decreasing the required investigation team size and time as well as being useful as a training tool. RSIT presents the logical connections between driver behaviors, road elements and environment conditions. RSIT2 is the next version of the RSIT method. The knowledge base developed for RSIT 2 includes all the major types of roads in Indiana: a) all-way stop-controlled intersection, b) road segment, c) railroad crossing, and d) signalized intersection, and e) improved two-way stop-controlled intersections. The RSIT 2 method uses the rule-based structure converted to a dynamic checklist that adjusts in real-time to the investigation progress. A friendly graphic-user interface has been developed together with a knowledge base editor to allow updating the knowledge base by the user. Finally, a novel technique of ranking safety countermeasures was developed and applied.

Feature-based generators for time series data

A variety of interesting domains, such as financial markets, weather systems, herding phenomena, etc., are characterized by highly complex time series datasets which defy simple description and prediction. The generation of input data for simulators operating in these domains is challenging because process description usually involves high-dimensional joint distributions that are either too complex or simply unavailable. In such applications, a standard approach is to drive simulators with (historical) trace-data, along with facilities for real-time interaction and synchronization. But, limited input data, or conversely, abundant but low-fidelity random data, limits the usefulness and quality of the results. With a view to generating high-fidelity, random input for such applications, we propose a methodology which uses the original data, as a template, to generate candidate datasets, to finally accept only those datasets which resemble the template, based upon parameterized features. We demonstrate the methodology with some early experimental results.