Maertens, Tom

Walraevens, Joris

Wittevrongel, Sabine

English

Ghent University Academic Bibliography

Giving Priority Access to Freight Vehicles atSignalized IntersectionsJoris WalraevensGhent University - UGent, Department of Telecommunications and Information Processinge-mail: Joris.Walraevens@UGent.beTom MaertensGhent University - UGent, Department of Telecommunications and Information Processinge-mail: Tom.Maertens@UGent.beSabine WittevrongelGhent University - UGent, Department of Telecommunications and Information Processinge-mail: Sabine.Wittevrongel@UGent.beDeceleration and acceleration of vehicles have a large impact on pollution andon waiting times. This is even more outspoken for freight vehicles, as they havemuch longer acceleration times and higher pollution levels than regular vehicles.Therefore, it makes sense to avoid, as much as possible, that freight vehicleshave to stop at intersections. Note that this can also be beneficial for regularvehicles, as they have a lesser chance of getting stuck behind a freight vehicle atan intersection.We concentrate on signalized intersections in this abstract. The aim is togive freight vehicles a high probability of green-light passage. This can be doneby extending standard actuated control signals. First, freight vehicles should bedetected. This can be done through sensing traffic and distinguishing freightvehicles from regular vehicles (by means of height, weight, . . . ). A future andpromising alternative is active identification of freight vehicles by means of V2I(Vehicle-to-Infrastructure) communication. Second, an algorithm is required todecide whether the freight vehicle can be given a green light or not. This algo-rithm should be based on efficiency of passage, fairness for all intersecting trafficstreams and vehicle types, safety, . . .We analyze the effect of increasing the green-light probability for freight vehi-cles on the mean waiting times of freight and regular vehicles. We concentrate ona fairly simple algorithm and intersection configuration. We assume that withina complete green/red cycle of the intersection, one of the green periods can beextended for a fixed period if freight vehicles are approaching. Obviously, theconcurrent red periods are extended as well. We model separately each streampassing the intersection, where we assume that all vehicles that use the same lanemake up one stream. So for a regular four-way intersection with separate turnlanes, we have 12 streams (4 origins and 3 destinations per origin). We furtherassume that a stream that is given a green light can pass the intersection withoutinterference of other streams.1To model the streams, we group them in two categories: streams that benefit(category 1) and streams that suffer (category 2) from the extended green timefor freight vehicles. As a first model, we assume independent Poisson arrivals forregular vehicles and freight vehicles in each stream. A generic stream of category1 is modeled as follows: freight vehicles arrive at rate λf , regular vehicles at rateλr. Without the extension of the green period, the stream sees cycles of freeflow (green light; duration tg seconds) and blocked access (red or yellow light;duration tr seconds). The green light is extended for a period of teg seconds if atleast one freight vehicle of the streams of category 1 arrives during this period. Ageneric stream of category 2 has similar parameters; the main difference is thatthe red period of these streams is extended when the green period of the streamsof category 1 is extended.We analyze the mean waiting times of regular vehicles and freight vehicles ingeneric streams of both categories (i.e., 4 different analyses and end formulas).Since we expect that the algorithm will have the biggest effect in a light-trafficscenario, we assume that no waiting time is added by the intersection when avehicle arrives during a green period. When arriving in a red period, the waitingtime of a vehicle consists of the time until the traffic sign turns green and the timeuntil the vehicle passes the traffic light after it turns green. The latter dependson the number of vehicles in front of the vehicle when the traffic light turns greenand the speed with which the vehicle can leave the intersection. Since we assumeslower discharge speeds for freight vehicles than for regular vehicles, the latter,in turn, depends on whether the vehicle itself is a freight vehicle and/or whetherat least one freight vehicle is in front of the vehicle.The analyses exist of conditioning and calculating conditioned mean waitingtimes, but is in essence rather straightforward. We are in particular interested inthe difference between mean waiting times in this scenario with extended greenperiods and mean waiting times when traffic control is static. Although the lattercould be analyzed more accurately (for instance by using results from pollingmodels), we propose to calculate the latter simply by substituting the green periodextension teg by 0 in the expressions of the former scenario. The advantage ofthis approach is that both results suffer from the same approximation error.The obtained formulas are explicit in the parameters of the model and cantherefore easily be used to assess the impact of the extension length teg (andother parameters) on the mean waiting times of different streams. Furthermore,they can also be used in an optimization function to find the optimal teg.In future, we will concentrate on extending the analysis to also deal withoverflow during a red/green cycle. Relaxing the independent Poisson arrivalprocesses to dependent platooning arrival processes is another interesting researchdirection.

Giving priority access to freight vehicles at signalized intersections

https://biblio.ugent.be/publication/8621482/file/8621486

Giving priority access to freight vehicles at signalized intersections

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Ghent University Academic Bibliography