Exploring The Potential Of Combining Ramp Metering And Variable Speed Limit Strategies For Alleviating Real-time Crash Risk On Urban Freeways

Research recently conducted at the University of Central Florida involving crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical and neural networks models that are capable of determining the crash risk on the freeway (Abdel-Aty et al., 2004; 2005, Pande and Abdel-Aty, 2006). These models are able to calculate rear-end and lane-change crash risks along the freeway in real-time through the use of static information at various locations along the freeway as well as real-time traffic data obtained by loop detectors. Since these models use real-time traffic data, they are capable of calculating rear-end and lane-change crash risk values as the traffic flow conditions are changing on the freeway. The objective of this study is to examine the potential benefits of combining two ITS strategies (Ramp Metering and Variable Speed Limits strategies) for reducing the crash risk (both rear-end and lane-change crash risks) along the I-4 freeway. Following this aspect, a 36.25-mile section of I-4 running though Orlando, FL was simulated using the PARAMICS micro-simulation program. Gayah (2006) used the same network to examine the potential benefits of two ITS strategies separately (Route Diversion and Ramp Metering) for reducing the crash risk along the freeway by changing traffic flow parameters. Cunningham (2007) also used the same network to examine the potential benefits of implementing Variable Speed Limits strategy for reducing the crash risk along the freeway. Since the same network is used, the calibration and validation procedures used in this study are the same as these previous two studies. This study simulates three volume loading scenarios on the I-4 freeway. These are 60, 80 and 90 percent loading scenarios. From the final experimental design for the 60 % loading, it was concluded that implementing VSL strategy only was more beneficial to the network than either implementing Ramp Metering everywhere (through the whole network) in conjunction with VSL everywhere or implementing Ramp Metering downtown (in downtown areas only) in conjunction with VSL everywhere. This was concluded from the comparison of the results of this study with the results from Cunningham (2007). However, either implementing Ramp Metering everywhere or downtown in conjunction with VSL everywhere showed safety benefits across the simulated network as well as a reduction in the total travel time. The best case for implementing Ramp Metering everywhere in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of half speed zone and a speed change time of 5 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. And the best case for implementing Ramp Metering downtown in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of half speed zone and a speed change time of 10 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. For the 80 % loading, it was concluded that either implementing Ramp Metering everywhere in conjunction with VSL everywhere or implementing Ramp Metering downtown in conjunction with VSL everywhere was more beneficial to the network than implementing VSL strategy only. This was also concluded from the comparison of the results of this study with the results from Cunningham (2007). Moreover, it was concluded that implementing Ramp Metering everywhere in conjunction with VSL everywhere showed higher safety benefits across the simulated network than implementing Ramp Metering downtown in conjunction with VSL everywhere. Also, both of them increased the total travel time a bit, but this was deemed acceptable. Additionally, both of them had successive fluctuations and variations in the average lane-change crash risk vs. time step. The best case for implementing Ramp Metering everywhere in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 5 mph, a speed change distance of half speed zone and a speed change time of 30 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. And the best case for implementing Ramp Metering downtown in conjunction with VSL everywhere was using a homogeneous speed zone threshold of 5 mph, a speed change distance of half speed zone and a speed change time of 30 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. Searching for the best way to implement both Ramp Metering and VSL strategies in conjunction with each other, an indepth investigation was conducted in order to remove the fluctuations and variations in the crash risk with time step (through the entire simulation period). The entire simulation period is 3 hours, and each time step is 5 minutes, so there are 36 time steps representing the entire simulation period. This indepth investigation led to the idea of not implementing VSL at consecutive zones (using either a gap of one zone or more). Then this idea was applied for the best case of implementing Ramp Metering and VSL everywhere at the 80 % loading, and the successive fluctuations and variations in the crash risk with time step were removed. Moreover, much better safety benefits were found. So, this confirms that this idea was very beneficial to the network. For the 90 % loading, it was concluded that implementing Ramp Metering strategy only (Zone algorithm in downtown areas, and ALINEA algorithm in non downtown areas) was more beneficial to the network than implementing Ramp Metering everywhere in conjunction with VSL everywhere. This was concluded from the comparison of the results of this study with the results from Gayah (2006). However, implementing Ramp Metering everywhere in conjunction with VSL everywhere showed safety benefits across the simulated network as well as a reduction in the total travel time. The best case was using a homogeneous speed zone threshold of 2.5 mph, a speed change distance of the entire speed zone and a speed change time of 20 minutes in conjunction with a 60 seconds cycle length for the Zone algorithm, a critical occupancy of 0.17 and a 30 seconds cycle length for the ALINEA algorithm. In summary, Ramp Metering was more beneficial at congested situations, while Variable Speed Limits were more beneficial at free-flow conditions. At conditions approaching congestion, the combination of Ramp Metering and Variable Speed Limits produced the best benefits. These results illustrate the significant potential of ITS strategies to improve the safety and efficiency of urban freeways

Quantum search on structured problems

This paper shows how a basic property of unitary transformations can be used for meaningful computations. This approach immediately leads to search-type applications, where it improves the number of steps by a square-root - a simple minded search that takes N steps, can be improved to O(sqrt(N)) steps. The quantum search algorithm is one of several immediate consequences of this framework. Several novel search-related applications are presented.Comment: To be presented at the 1st NASA QCQC conference in Palm Springs, California, Feb. 17-20, '98. 12 pages, postscrip

Pushdown Compression

The pressing need for eficient compression schemes for XML documents has recently been focused on stack computation [6, 9], and in particular calls for a formulation of information-lossless stack or pushdown compressors that allows a formal analysis of their performance and a more ambitious use of the stack in XML compression, where so far it is mainly connected to parsing mechanisms. In this paper we introduce the model of pushdown compressor, based on pushdown transducers that compute a single injective function while keeping the widest generality regarding stack computation. The celebrated Lempel-Ziv algorithm LZ78 [10] was introduced as a general purpose compression algorithm that outperforms finite-state compressors on all sequences. We compare the performance of the Lempel-Ziv algorithm with that of the pushdown compressors, or compression algorithms that can be implemented with a pushdown transducer. This comparison is made without any a priori assumption on the data's source and considering the asymptotic compression ratio for infinite sequences. We prove that Lempel-Ziv is incomparable with pushdown compressors