Identifying Wrong-Way Driving Hotspots by Modeling Crash Risk and Assessing Duration of Wrong-Way Driving Events

Because wrong-way driving (WWD) crashes are often severe, it is important for transportation agencies to identify WWD hotspot segments appropriate for potential implementation of advanced WWD countermeasures. Two approaches to identify these hotspot segments were developed and applied to a case study of limited-access highways in Central Florida. The first approach used a Poisson regression model that predicted the number of WWD crashes in a roadway segment based on WWD citations, 911 calls, traffic volumes, and interchange designs. Combining this predicted crash value with the actual number of WWD crashes in the segment gave the WWD crash risk of the segment. Ranking roadway segments by WWD crash risk provided agencies with an understanding of which segments had high WWD crash frequencies and high potential for future WWD crashes. This approach was previously applied to South Florida; the research presented here extended this approach to Central Florida. The second approach was based on operational data collected in traffic management centers and could be used if accurate WWD 911 and citation data with GPS location were not available or as a supplement to the first approach. The approach identified and ranked WWD hotspots on the basis of the reported duration of WWD events. In Central Florida, the results of the two approaches agreed with each other and were used by agencies to decide where to implement advanced WWD countermeasures. Together, these approaches can help transportation agencies determine regional WWD hotspots and cooperate to implement advanced WWD countermeasures at these locations

Framework For Atis Safety

Advanced Traveler Information Systems utilize advance techniques to acquire, process, and disseminate information to motorists. The main purpose of ATIS is to provide motorists with information prior to and during a trip. This process may improve the System performance and route traffic around congested sections of the street network, however, there is no assurance that the potential trip time savings gained by ATIS will not be compromised by safety issues

Framework For Evaluating Level Of Service At Electronic Toll Collection Plazas

The objective of this paper is to develop a framework for evaluating level of service (LOS) at toll plazas with and without Electronic Toll Collection (ETC) systems. Quantifying the level of service at toll plazas will provide a standard tool for comparing between performance of traffic operations strategies and evaluating the true potential of ETC systems in traffic management at toll plazas. Three methods are proposed to evaluate LOS. In the first method, the plaza will be treated as a traffic signal, and the average delay per vehicle at the plaza is used to assess the LOS. In the second method, the plaza is treated as a freeway section, and the average density at the plaza is used to assess the LOS. In the third method, a combination of both average delay and average density is applied to LOS. The three methods will be validated with data collected by the University of Central Florida (UCF) at three toll plaza sites in Orlando

A simple model for route guidance benefits

This paper concerns the benefits from vehicle route guidance in urban networks. We suppose that routes can be altered in such a way as to achieve system optimal assignment. Benefits are measured by the savings in total travel time when comparing this assignment with the user equilibrium, which is assumed to occur in the absence of route guidance. A continuum approach is used to analyze an idealized corridor in which a freeway is superimposed over a dense grid of surface streets. The main role of route guidance is to divert traffic from the freeway whenever its marginal cost exceeds that of the street system. It is found that saving in total system travel time of the order of 3-4% can be achieved from route guidance. Benefits are quite sensitive to city street speed. At low speed more users would choose the freeway resulting in congestion, and the potential benefits of route guidance are relatively high. However, as street speed increases and approaches that of the freeway, route guidance would be of less value as more of the motorists would be choosing the city street on their own. Benefits can be enhanced if information is customized to motorists on the basis of their origins and destinations. Finally, it is shown that benefits are reduced when the freeway network is dense. This paper does not consider important aspects of the evaluation of route guidance, such as the equity issue stemming from increasing some trip times in order to achieve system optimum, or the local impact of diverted traffic.

Freeway incident detection using Fuzzy ART

Pattern recognition techniques such as artificial neural networks continue to offer potential solutions to many of the existing problems associated with freeway incident detection algorithms. This study focuses on the application of Fuzzy ART neural networks to incident detection on freeways. Unlike backpropagation models, Fuzzy ART is capable of fast stable learning of recognition categories. It is an incremental approach that has the potential for online implementation. Fuzzy ART is trained with traffic patterns that are represented by 30-second loop detector data of occupancy, speed, or a combination of both. To reduce the false alarm rate that results from occasional misclassification of traffic patterns, a persistence time period of 3 minutes was arbitrarily selected. The algorithm performance improves when the temporal size of traffic patterns increases from one to two 30-second periods for all traffic parameters. An interesting finding is that the speed patterns produced better results than occupancy patterns. However, when combined in one pattern, occupancy and speed patterns yield the best results with 100% detection rate and 0.07% false alarm rate

Potential Impact Of Advanced Traveler Information Systems (Atis) On Accident Rates In An Urban Transportation Network

Advanced Traveler Information Systems (ATIS) have the potential to improve the travel experience of individuals and, consequently, enhance the transportation system performance. ATIS will provide information that assists the traveler in selecting his destination, departure time, pre-trip route, enroute diversion, and trip chaining. One of the direct benefits of ATIS is to provide warnings on incident blockages which may encourage drivers to divert from incident routes, leading to shorter queues, fewer abrupt deceleration and safer travel conditions. ATIS may have various safety implications on the transportation network. On one side, there exists the possible distracting effect of the on-board gadget on the driver. This research is still under investigation. On the other side, congestion avoidance may improve traffic safety on the network. Thus, reducing congestion on freeways by diverting traffic to alternative arterials is expected to reduce the accident risk on freeways. However, safety on these arterials may be reduced as they become more congested. Moreover, travel conditions on arterials are not as safe as on freeways because of the higher level of traffic flow interruptions caused by side streets and traffic signals. In essence, when traffic is diverted from congested freeways to less congested arterials, the switch from higher to lower roadway hierarchy may offset the safety benefits anticipated on freeways. This paper presents a methodology for predicting changes in accident rates as a result of traffic diversion by ATIS in Orlando\u27s Transportation Network

Wrong-Way Driving Incidents On Central Florida Toll Road Network, Phase-1 Study: An Investigation Into The Extent Of This Problem?

The focus of this research project was to understand the extent of wrong-way driving (WWD) incidents on Central Florida toll roads by analyzing WWD data. The universe of WWD data contains many sources on both reported and unreported WWD events. Various WWD data sources were analyzed, including crash reports, citation data, and 911 call data to determine WWD trends and areas of high occurrence. A Computer Assisted Telephone Instrument survey was conducted on 400 randomly selected toll road customers that either personally witnessed WWD or knew someone who had witnessed WWD on Central Florida highways. These customers were asked about the details of this WWD incident, if it affected how they drive, and if they reported it by calling 911. The intent of this survey was to capture information about unreported WWD events to determine the full extent of the WWD problem and understand how toll road users react to WWD and want to be alerted about it. The analysis results were used to create a systematic ranking of Central Florida toll roads with respect to WWD. The rankings indicated that SR 408 and SR 528 (in this order) are the worst roads with respect to WWD. The results indicated that WWD is a problem in Central Florida that requires attention. In addition, the survey showed that many people do not report WWD, so it is important to detect and warn drivers about WWD. In order to improve detection and reduce WWD incidents, a Phase-2 study will evaluate various WWD countermeasures to determine which are most effective for Central Florida toll roads. These countermeasures will include low-cost and medium-cost improvements and technologie

Truck Trip Generation Models For Seaports With Container And Trailer Operation

Freight movement throughout the United States continues to evolve as a significant challenge to the transportation industry. Seaport operations dominated by container and trailer movements will require operational and infrastructure changes to maintain the growth of international cargo operations. Transportation planning models can be used to determine the needs of port and street network modifications. Described is the research and initial development process of models for predicting the levels of cargo truck traffic moving inbound and outbound at the Port of Miami. The models were restricted to container and trailer truck configurations that transport virtually all of the Port of Miami\u27s freight. Consequently, this associated truck traffic moves through the nearby street network within downtown Miami. The purpose of the trip generation models is to predict volumes of large inbound and outbound trucks for specified time frames. The concern is to know how many large cargo vehicles are traveling on the only road leading to the port. Primary factors affecting truck volume were found to be the amount and direction of cargo vessel freight and the particular weekday of operation. Time series models for predicting seasonal variations in freight movements were developed as part of the study. These models are useful for long-term forecasts of the input variables used in the trip generation models. Truck trip generation models will provide transportation planners and public agencies with valuable information when making transportation management decisions and infrastructure modifications. This information also is necessary for prioritizing funds for roadway upgrade projects