SPECIALIST: A dynamic speed limit control algorithm based on shock wave theory

Hegyi, Andreas; Schreuder, Marco; Stoelhorst, Henk; Viti, Francesco

doi:10.1109/itsc.2008.4732611

Cited by 141 publications

(111 citation statements)

References 8 publications

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“…The reason was that (the measured) v [1] was lower than v [5] or that the ρ [1] was higher than ρ [5] . These cases were due to the random fluctuations in the downstream state.…”

Section: B Algorithmic Resultsmentioning

confidence: 97%

“…The average flow q [6] and q [1] (veh/h/lane) and average density ρ [6] and ρ [1] (veh/km/lane) respectively upstream and downstream are determined by q [6] = (1/N ) i∈I [6] q i , and ρ [6] = (1/N ) i∈I [6] (q i /v i ), (and similarly for state 1) where q i (veh/h/lane) and v i (km/h) are respectively the flow and speed measurements of segment i, and I [6] and I [1] is the set segment indexes of the segments in free flow respectively upstream and downstream from the jam, and N the number of segments considered. This determines states 1 and 6.…”

Section: B Control Scheme Generationmentioning

confidence: 99%

“…The density of state 2 is determined by using the density and flow of state 1, the flow of state 2, and solving v [1,2] = (q [1] −q [2] )/(ρ [1] −ρ [2] ), for ρ [2] , where v [1,2] denotes the propagation speed of the head of the shock wave. The propagation speed of the head of the shock wave can be taken from off-line data, since it is well-known to be fairly constant (around -18 km/h).…”

Section: B Control Scheme Generationmentioning

confidence: 99%

“…In earlier publications we presented an approach to dynamic speed limit control to eliminate shock waves on freeways that is based on shock wave theory, the so-called SPECIALIST algorithm (SPEed ControllIng ALgorIthm using Shock wave Theory) [1], [2]. It was shown by simulation that the algorithm is capable of resolving shock waves, and that the improvement of the total time was that the vehicles spend on the freeway is comparable with approaches using other control techniques [3], [4].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic speed limit control to resolve shock waves on freeways - Field test results of the SPECIALIST algorithm

Hegyi

Hoogendoorn

2010

13th International IEEE Conference on Intelligent Transportation Systems

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Abstract-We present the real-world test of the SPECIALIST algorithm in which dynamic speed limits were used to resolve shock waves on freeways. The real-world test was performed in the period September 2009-February 2010 on a 14 km long stretch on the Dutch A12 freeway.For the evaluation of the algorithm various performance measures were determined for each activation of the speed limits. The results show that the SPECIALIST algorithm can resolve shock waves in nearly 80% of the cases when the algorithm activated for shock waves. However, in approximately 50% of the activations the algorithm activated for jam types other than shock waves, in which case the effectivity was 40-50%. Due to the tuning the stability of the traffic flow could be significantly improved, and the number of average activations per day was increased from 1.5 to 2.9 activations per day.The SPECIALIST algorithm was not only evaluated for traffic performance, but also for the correctness of the algorithm for real traffic in terms of expected qualitative behavior. Although the general operation of the algorithm is according to the theoretical expectations, some points for further improvements are identified during the test.

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“…The reason was that (the measured) v [1] was lower than v [5] or that the ρ [1] was higher than ρ [5] . These cases were due to the random fluctuations in the downstream state.…”

Section: B Algorithmic Resultsmentioning

confidence: 97%

Section: B Control Scheme Generationmentioning

confidence: 99%

Section: B Control Scheme Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic speed limit control to resolve shock waves on freeways - Field test results of the SPECIALIST algorithm

Hegyi

Hoogendoorn

2010

13th International IEEE Conference on Intelligent Transportation Systems

Self Cite

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“…jams produced by traffic instabilities) [12,13]. The algorithm takes advantage of the fact that when the speed limit is instantaneously reduced on a freeway stretch, the flow reduces proportionally with the speed reduction, while the density remains the same.…”

Section: Introductionmentioning

confidence: 99%

Effects of Dynamic Speed Limits on a Dutch Freeway

Plana

Soriguera

Hegyi

2016

Transportation Research Record: Journal of the Transportation R

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The paper presents the effects of Dynamic Speed Limit control (DSL) in a 3 lane section on the A13 freeway, in Rotterdam. The main objective is to contrast the latest empirical findings in Barcelona [1], where the mainline metering capability (i.e. gating, meaning mainline flow restriction) due to sub-critical speed limits (e.g. down to 40 km/h) was questioned. Moreover, according to the Barcelona results, the validity of the current fundamental diagram models accounting for DSL could be strongly compromised.This investigation takes advantage of the huge empirical traffic database recorded by the Dutch government and of DSL strategies being present on most of their freeways. Data is treated in order to identify stationary periods of traffic. A method, reproducible elsewhere, and computerized into an algorithm has been developed to this end. The fundamental diagram is used as a graphical tool to assess the results.The main findings do not contradict the Barcelona observations. Flows of 1850 veh/h per lane were steadily observed for the sub-critical speed limit of 50 km/h. The reactive nature of the DSL-control implemented in the Netherlands, implies that very low speed limits do not affect a wide range of traffic states. This hampered the possibility of extending this conclusion. Further research with less limiting DSL control strategies would be necessary to clarify the extent of the phenomenon considered.

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Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Othman

Nunzio

Sciarretta

et al. 2021

Handbook of Climate Change Mitigation and Adaptation

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In the member countries of the Organization for Economic Cooperation and Development (OECD), projections show that the improved energy efficiency in transportation may lead to a net decline of about 2% in energy use until 2040, thus outpacing the predicted increase of vehicle-miles traveled (VMT). However, in OECD-Europe, transportation still represents the biggest source of carbon emissions, contributing by about 25% to the total CO2 emissions, with cars and vans representing more than two thirds of this share. The situation is even more alarming in non-OECD countries, where the transportation energy demand is expected to rise by 64% until 2040. The shift that we are witnessing toward the adoption of connected and automated vehicles (CAVs) is going to be perhaps, the most disruptive since the early days of automobiles and could revolutionize movement of people and goods. This level of connectivity and autonomy will transform transportation in several dimensions with important societal and economic impacts: improved safety, increased comfort, time saving potential, and more efficient road utilization are among the most widely discussed positive impacts of CAVs. However, the potential energy efficiency benefits of these technologies remain uncertain. From a single-vehicle efficiency perspective, research suggests that lightweight, low-speed, autonomous vehicles have the potential to achieve fuel economy an order of magnitude higher than current cars. Yet, at system-wide level, current estimates suggest that the total energy consumption impacts can range from a 90% decrease to a 200% increase in fuel consumption as compared to a projected 2050 baseline energy consumption. The paradigm that traffic congestion mitigation should reduce CO2 emissions is yet to be proved. Therefore, interest in transportation regulation problems with explicit environmental considerations is growing. This work takes a more in-depth look at increased opportunities for energy-efficient driving with energy-oriented traffic management and CAVs deployment. In particular, the focus will be put on the road traffic control strategies in urban networks using connectivity to enable variable speed limits and traffic light adaptive control, as well as the energy-saving opportunities that arise for individual CAVs by anticipating future road geometry, traffic conditions, and interactions with neighboring vehicles.

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SPECIALIST: A dynamic speed limit control algorithm based on shock wave theory

Cited by 141 publications

References 8 publications

Dynamic speed limit control to resolve shock waves on freeways - Field test results of the SPECIALIST algorithm

Dynamic speed limit control to resolve shock waves on freeways - Field test results of the SPECIALIST algorithm

Effects of Dynamic Speed Limits on a Dutch Freeway

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

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