Design of Signal Timing Plan for Urban Signalized Networks including Left Turn Prohibition

Urban road networks may benefit from left turn prohibition at signalized intersections regarding capacity, for particular traffic demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. With the flows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length, and the green durations using a stage-based method which can handle the case that stages are sharing movements. The final output is a list of the prohibited left turns in the network and a new signal timing plan for every intersection. The optimal list of prohibited left turns was found using a genetic algorithm, and a combination of several algorithms was employed for the signal timing plan. The results show that left turn prohibition may lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered on a par with other left turn treatment options. Document type: Articl

Minimierung von Reisezeiten im Straßennetz durch das Verbot des Linksabbiegens an signalisierten Kreuzungen

Left turns have potential efficiency problems. The prohibition of left turns is explored as means of shortening total travel time and improving overall efficiency performance. The objective of this thesis is to explore whether prohibiting left turns can improve the efficiency of urban road networks using existing infrastructure. Improving the efficiency refers to reducing the travel time of all vehicles in the network. A model is proposed to determine the effects of left turn prohibition with the objective to minimize the total travel time. The first task is to forecast the distribution of demands as vehicles are redistributed in the network after left turns are prohibited. Prohibiting left turns not only affects the route choices of the affected vehicles, but also influences the vehicles' other movements because the prohibited turns may increase traffic flows on some links and cause delays. A stochastic user equilibrium model is applied to forecast the distribution of demands. Optimizing signal settings is another important task in the absence of left turns. The whole signal timing plan of the affected intersection has to be changed because the prohibited left turn is removed from the signal group. The corresponding signal timing is adjusted according to the redistributed traffic flow. Further, the lanes for prohibited left turn should be reassigned to make use of their capacities at intersections. This thesis presents two methods of signal setting optimization: the stage-based method and the lane-based method. Both methods consider the influences of left turn phasing types and left turn prohibition. Using the proposed method, it is determined that prohibiting left turns may reduce the total travel time in the network, though this reduction has not been observed for every origin-destination path. The proposed method can handle various traffic demands. Protected left turns with small flows, left turns with large opposing flows, and permitted left turns at intersections with high saturations have a higher probability of being prohibited. This research provides insight into network design and congestion management in urban road networks. Using the proposed model, the left turn prohibition problem can be solved analytically. Signal setting optimization methods are improved, and can handle the absence of left turns. The findings from the numerical solution could contribute to the usage of left turn prohibitions in practice.Linksabbiegen an Kreuzungen birgt potentielle Effizienzprobleme. Das Verbot wird von Linksabbiegen untersucht, um die Passierdauer zu verkürzen und die Effizienz von Kreuzungen insgesamt zu verbessern. Das Ziel dieser Arbeit ist es zu untersuchen, ob ein Verbot von Linksabbiegen die Effizienz städtischer Straßennetze unter Verwendung der vorhandenen Infrastruktur verbessern kann. Es wird ein Modell vorgeschlagen, um die Auswirkungen des Verbots von Linksabbiegen zu bestimmen, um die Gesamtfahrzeit zu minimieren. Die erste Aufgabe besteht darin, die Verteilung der Anforderungen vorherzusagen, da Fahrzeuge nach Einführen des Linksabbiegeverbots im Netz umverteilt werden. Das Verbot des Linksabbiegens wirkt sich nicht nur auf die Routenwahl der betroffenen Fahrzeuge aus, sondern beeinflusst auch die Routen der anderen Fahrzeuge, da die verbotenen Abzweigungen den Verkehrsfluss auf einigen Verbindungen erhöhen und Verzögerungen verursachen können. Ein stochastisches Benutzergleichgewichtsmodell wird verwendet, um die Verteilung der Anforderungen vorherzusagen. Die Optimierung der Signalsteuerung ist eine weitere wichtige Aufgabe, unter der Voraussetzung, dass Linksabbiegen nicht möglich ist. Der gesamte Signalzeitplan der betroffenen Kreuzung muss geändert werden, da das verbotene Linksabbiegen aus der Signalgruppe entfernt wird. Das entsprechende Signal-Timing wird entsprechend dem umverteilten Verkehrsfluss angepasst. Außerdem sollten die Fahrstreifen für das verbotene Linksabbiegen neu belegt werden, um ihre Kapazitäten an Kreuzungen zu nutzen. Zwei Methoden zur Optimierung der Signalpläne werden vorgestellt: die phasenbasierte Methode und die spurbasierte Methode. Beide Methoden berücksichtigen die Einflüsse von Linksabbieger-Phasen und das Linksabbiegeverbot. Unter Verwendung des vorgeschlagenen Verfahrens wird bestimmt, dass ein Verbot des Linksabbiegens die Gesamtfahrzeit im Netzwerk reduzieren kann. Geschütztes Linksabbiegen mit kleinen Verkehrsflüssen, Linksabbiegen mit großem entgegengesetztem Verkehrsfluss und erlaubtes Linksabbiegen an Kreuzungen mit hohen Sättigungen haben eine höhere Wahrscheinlichkeit, dass hier ein Linksabbiegeverbot sinnvoll ist. Diese Forschungsarbeit bietet Einblicke in das Netzwerkdesign und das Staumanagement in städtischen Straßennetzen. Die Methoden zur Optimierung der Signalsteuerung wurden verbessert. Die Erkenntnisse aus der numerischen Lösung könnten dazu beitragen, Linksabbiegeverbote in der Praxis zu verwenden

Research on Warnings with New Thought of Neuro-IE

AbstractSafety production is a seriously stubborn problem in modern industry engineering. Warnings, as the most fundamental and important measure used in safety management, especially in Mine Exploitation, have played a vital role in risk cognition, behaviors guide and accidents prevention. However, traditional researches are so subjective that it's hard to deeply explore the inner mechanism and process, which has been hidden behind the outer behaviors. As a result, the effectiveness of Warnings is much discounted. In this paper, we make use of neuroscience methods to study Warnings from the basically cognitive levels and have acquired preliminary achievements, which provide new evidence, discussion and introductions for former researches

Deep CNN-BiLSTM Model for Transportation Mode Detection Using Smartphone Accelerometer and Magnetometer

Transportation mode detection from smartphone data is investigated as a relevant problem in the multi-modal transportation systems context. Neural networks are chosen as a timely and viable solution. The goal of this paper is to solve such a problem with a combination model of Convolutional Neural Network (CNN) and Bidirectional-Long short-term memory (BiLSTM) only processing accelerometer and magnetometer data. The performance in terms of accuracy and F1 score on the Sussex-Huawei Locomotion-Transportation (SHL) challenge 2018 dataset is comparable to methods that require the processing of a wider range of sensors. The uniqueness of our work is the light architecture requiring less computational resources for training and consequently a shorter inference time

Simulation-based method of a dynamical on-demand transportation problem

Demand-oriented public transportation is a new way to provide mobility in both urban area and rural area. This paper aims to simulate an on-demand transportation system which will be implemented in Elde region, Germany. The work flows of sending a trip request and driving are first simulated using Java. The involved data models are explained and implemented. An ant colony algorithm is developed for the routing optimization. By applying the measures, request acceptance rate, average waiting time, vehicle occupancy and vehicle capacity occupancy, in different request arrival rate, the number of vehicles, vehicle capacities and the maximum acceptable riding time, it is found that the vehicles with four seats are most suitable for this system. Also in order to maintain a high acceptance rate more than 80%, the vehicle occupancy rate should be more than 70%. The analysis and evaluation results provide suggestions for vehicle resource assignment and system management

Left turn phasing type determination at isolated intersections solved by a genetic algorithm

A left turn could be treated as a permitted or protected left turn. Good left turn treatment could improve the efficiency at intersections. This paper aims to solve the left turn phasing type problem with the goal of minimizing the total delay. The determination of left turn phasing types extends the lane-based signal optimization method by introducing the decision variables of left turn phasing type indicators. This problem is solved with a genetic algorithm with Penalty functions. It is found that permitted left turns contribute to total delay reduction

Exit lane allocation with the lane-based signal optimization method at isolated intersections

In signal optimization problems, incompatible movements usually are in either of two states: predecessor or successor. However, if the exit lane is well allocated, the incompatible movements merging at the same destination arm can exist in parallel. The corresponding longer green duration is expected to increase the capacity of intersection. This paper aims to solve the exit lane allocation problem with the lane-based method by applying the three states among incompatible movements at conventional signalized intersections. After introducing auxiliary variables, the problem is formulated as a mixed integer programming and can be solved using a standard branch-and-cut algorithm. In addition to the exit lane allocation results, this proposed method can also determine the cycle length, green duration, start of green and signal sequence. The results show that the proposed method can obtain a higher capacity than that without the exit lane allocation. The pavement markings are further suggested for safety

Design of signal timing plan for urban signalized networks including left turn prohibition

Urban road networks may bene�t from left turn prohibition at signalized intersections in terms of safety and capacity, for particular tra�c demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. The �nal output is a list of the prohibited left turns in the network, and a new signal timing plan for every intersection. Using the ows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length and the green duration of each stage. The optimal list of prohibited left turns was found using the genetic algorithm, and a combination of several algorithms was employed for the signal timing plan using a stage-based method. The results show that left turn prohibition may sometimes lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered just as any other left turn treatment

An ant colony algorithm with penalties for the dial-a-ride problem with time windows and capacity restriction

This paper proposes a metaheuristic algorithm to solve the dial-a-ride problem (DARP) with time windows and capacity restrictions. The algorithm was developed for the project "HubChain", which proposes an on demand system being integrated with local public transport in the Elde rural region, in northern Germany. Users can request their trips via an online platform by providing the origin and destination as well as the desired arrival or departure time. To solve the problem, ant colony optimization with penalties (ACOP) is developed based on the algorithm of Dorigo, in which the ants communicate pheromones both locally and globally and meanwhile the constraints are handled by setting penalties. To validate the results, the proposed algorithm and an exact algorithm were run for multiple test scenarios using the simulation SUMO as a framework. The routes obtained with the proposed algorithm show travel times comparable to the optimal routes, yet obtained in low computation times. This allows therefore the implementation of the proposed ACOP algorithm in a dynamic booking system