Statistical models of accidents on interchange ramps and speed-change lanes.

Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

An evaluation of the 1979 Texas law (V.C.S., Sec. 73.A.) which requires frontage road traffic to yield at freeway ramps. Interim report.

Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

Improving the traffic operations and safety of ramps and speed change lanes - a review of state design practices. Interim report.

Federal Highway Administration, Environmental Division, Washington, D.C.

Evaluation of freeway high occupancy vehicle lanes and ramp metering. Volume I. Final report.

Transportation Department, Office of the Assistant Secretary for Policy and International Affairs, Washington, D.C.

Evaluation of freeway high occupancy vehicle lanes and ramp metering. Volume II: bibliography and abstracts.

Transportation Department, Office of the Assistant Secretary for Policy and International Affairs, Washington, D.C.

Distance requirements for ramp metering.

Texas Department of Transportation, Austin

Case studies and annotated bibliography of truck accident countermeasures on urban freeways. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

Feasibility of an automatic truck warning system. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

Conceptual plan for an interactive highway safety design model. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean Va.

Side impact crash testing of roadside structures. Final report.

Federal Highway Administration, Washington, D.C.

Truck accident countermeasures on urban freeways. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

FRELANE: an analysis model for major freeway segments: user's guide. Final report.

Federal Highway Administration, Washington, D.C.

Algorithm for queue estimation with loop detector of time occupancy in off-ramps on signalized motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.