4 research outputs found
Measuring traffic lane-changing by converting video into space–time still images
Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accuracy achieved is usually not enough to improve traffic flow models. In contrast “visual” data extraction by watching the recordings requires extensive human intervention. A semiautomatic video processing methodology to count lane-changing in freeways is proposed. The method allows counting lane changes faster than with the visual procedure without falling into the complexities and errors of full automation. The method is based on converting the video into a set of space–time still images, from where to visually count. This methodology has been tested at several freeway locations near Barcelona (Spain) with good results. A user-friendly implementation of the method is available on http://bit.ly/2yUi08M.Peer ReviewedPostprint (published version
Modeling present and future freeway management strategies : variable speed limits, lane-changing and platooning of connected autonomous vehicles
Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit d’Enginyeria Civil i AmbientalFreeway traffic management is necessary to improve capacity and reduce congestion, especially in metropolitan freeways where the rush period lasts several hours per day. Traffic congestion implies delays and an increase in air pollutant emissions, both with harmful effects to society. Active management strategies imply regulating traffic demand and improving freeway capacity. While both aspects are necessary, the present thesis only addresses the supply side.
Part of the research in traffic flow theory is grounded on empirical data. Today, in order to extend our knowledge on traffic dynamics, detailed and high-quality data is needed. To that end, the thesis presents a pioneering data collection campaign, which was developed in a freeway accessing Barcelona. In a Variable Speed Limits (VSL) environment, different speed limits where posted, in order to observe their real and detailed effects on traffic. All the installed surveillance instruments were set to capture data in the highest possible level of detail, including video recordings, from where to count lane-changing maneuvers. With this objective, a semi-automatic method to reliably count lane changes form video recordings was developed and is presented in the thesis.
Data analysis proved that the speed limit fulfillment was only relevant in sections with enforcement devices. In these sections, it is confirmed that, the lower the speed limit, the higher the occupancy to achieve a given flow. In contrast, the usually assumed mainline metering effect of low speed limits was not relevant. This might be different in case of stretch enforcement. These findings mean that, on the one hand, VSL strategies aiming to restrict the mainline flow on a freeway by using low speed limits will need to be applied carefully, avoiding conditions as the ones presented here. On the other hand, VSL strategies trying to get the most from the increased vehicle storage capacity of freeways under low speed limits might be rather promising.
Results also show that low speed limits increase the speed differences across lanes for moderate demands. This, in turn, also increases the lane changing rates. In contrast, lower speed limits widen the range of flows under uniform lane flow distributions, so that, even for moderate to low demands, the under-utilization of any lane can be avoided. Further analysis of lane-changing activity allowed unveiling that high lane-changing rates prevent achieving the highest flows. This inverse relationship is modeled in the thesis using a stochastic model based on Bayesian inference. This model could be used as a control tool, in order to determine which level of lane-changing activity can be allowed to achieve a desired capacity with some level of reliability.
Previous results identify drivers' fulfillment of traffic regulations as a weak point in order to maximize the benefits of current management strategies, like VSL or lane-changing control. This is likely to change in the near future with the irruption of Autonomous Vehicles (AV) in freeways. V2X communications will allow directly actuating on individual vehicles with high accuracy. This will open the door to new management strategies based on simultaneous communication to groups of AVs and extremely short reaction times, like platooning, which stands out as a strategy with a huge potential to improve freeway traffic. Strings of AVs traveling at extremely short gaps (i.e. platoons) allow achieving higher capacities and lower energy consumption rates. In this context, the thesis presents a parsimonious macroscopic model for AVs platooning in mixed traffic (i.e. platoons of AVs travelling together with human driven vehicles). The model allows determining the average platoon length and reproducing the overall traffic dynamics leading to higher capacities. Results prove that with a 50% penetration rate of AVs in the lane, capacity could reach 3400 veh/h/lane under a cooperative platooning strategy.Per tal de millorar la capacitat i reduir la congestiĂł a les autopistes cal gestionar el trĂ nsit de manera activa. Les estratègies de gestiĂł activa del trĂ nsit sĂłn d’especial importĂ ncia en autopistes metropolitanes. La congestiĂł provoca retards i un increment del consum de combustible que va lligat a unes majors emissions de gasos contaminants, tots amb efectes perniciosos per la societat. La gestiĂł activa del transit requereix regular la demanda i millorar la capacitat de la via. Encara que tots dos aspectes son necessaris, la present tesis nomĂ©s analitza la gestiĂł de l’oferta. Part de la recerca en l’anĂ lisi i la teoria del trĂ nsit es basa en dades empĂriques. Per satisfer el requeriment de dades detallades i d’alta qualitat, aquesta tesis presenta una campanya pionera de recol·lecciĂł de dades. Les dades es van recollir a l’autopista B-23 d’accĂ©s a Barcelona. Tots els instruments de mesura es van configurar per tal de registrar les dades amb el major nivell de detall possible, incloent les cĂ meres de videovigilĂ ncia, d’on es varen extreure els comptatges de canvi de carril. Amb aquest objectiu, es va desenvolupar una metodologia semiautomĂ tica per comptar canvis de carril a partir de gravacions de trĂ nsit, que es presenta en el cos de la tesi. L’anĂ lisi de les dades obtingudes ha demostrat que el compliment dels lĂmits de velocitat nomĂ©s resulta rellevant en aquelles seccions que compten amb un radar. És en aquestes seccions on s’ha confirmat que com menor Ă©s el lĂmit de velocitat, major es l’ocupaciĂł per a un flux donat. Per contra, la hipòtesi habitual de que uns lĂmits de velocitat baixos produeixen una restricciĂł del flux no es va observar de forma rellevant. Aquest comportament podria esser diferent en el cas d’implantar un radar de tram. Els resultats obtinguts tambĂ© mostren com les diferències de velocitats entre carrils s’incrementen per a lĂmits de velocitat baixos i en condicions de demanda moderada. Això, alhora, incrementa el nombre de canvis de carril. Per contra, els lĂmits de velocitat baixos contribueixen a una distribuciĂł de flux mĂ©s uniforme entre carrils, de forma que es pot evitar la infrautilitzaciĂł de carrils. L’anĂ lisi mĂ©s detallat de l’activitat de canvi de carril demostra que una taxa elevada de canvis de carril impedeix assolir fluxos grans de circulaciĂł. En la tesi, aquesta relaciĂł inversa entre la taxa de canvis de carril i el flux mĂ xim de trĂ nsit a l’autopista s’ha modelat de forma estocĂ stica utilitzant un model basat en la inferència Bayesiana. Aquest model es pot utilitzar com una eina de control, per tal de determinar quina taxa de canvi de carril es pot permetre si es vol assolir una capacitat determinada amb una determinada probabilitat de compliment. En vista dels resultats previs, la falta de compliment de les normes de trĂ nsit per part dels conductors s’identifica com un punt dèbil a l’hora de maximitzar els beneficis de les actuals estratègies de gestiĂł del transit. Això probablement canviarĂ en el futur pròxim amb la irrupciĂł dels Vehicles Autònoms (VA) a les autopistes. Els sistemes de comunicaciĂł V2X permetran actuar individualment sobre cada vehicle amb una gran precisiĂł. Això obrirĂ la porta a noves estratègies de gestiĂł, basades en la comunicaciĂł simultĂ nia entre diferents grups de VA i en temps de reacciĂł extremadament curts, com per exemple Ă©s el “platooning”, que destaca pel seu gran potencial per millorar el trĂ nsit en autopista. Els “platons” son cadenes de VA viatjant amb uns espaiaments extremadament curts que permeten assolir capacitats mes elevades i un menor consum energètic. En aquest context, la tesi presenta un model macroscòpic parsimoniĂłs per a “platons” de VA en condicions de transit mixt, Ă©s a dir, compartint la infraestructura amb vehicles tradicionals.
El model permet determinar la longitud mitjana del “platons” i reproduir el trà nsit global
dinĂ miques que condueixen a majors capacitats. Els resultats demostren que amb un 50%
la velocitat de penetració dels AV al carril, la capacitat podria arribar als 3.400 vehicles / h / carril sota una estratègia cooperativa de “platooning”Award-winningPostprint (published version
Modeling present and future freeway management strategies : variable speed limits, lane-changing and platooning of connected autonomous vehicles
Freeway traffic management is necessary to improve capacity and reduce congestion, especially in metropolitan freeways where the rush period lasts several hours per day. Traffic congestion implies delays and an increase in air pollutant emissions, both with harmful effects to society. Active management strategies imply regulating traffic demand and improving freeway capacity. While both aspects are necessary, the present thesis only addresses the supply side.
Part of the research in traffic flow theory is grounded on empirical data. Today, in order to extend our knowledge on traffic dynamics, detailed and high-quality data is needed. To that end, the thesis presents a pioneering data collection campaign, which was developed in a freeway accessing Barcelona. In a Variable Speed Limits (VSL) environment, different speed limits where posted, in order to observe their real and detailed effects on traffic. All the installed surveillance instruments were set to capture data in the highest possible level of detail, including video recordings, from where to count lane-changing maneuvers. With this objective, a semi-automatic method to reliably count lane changes form video recordings was developed and is presented in the thesis.
Data analysis proved that the speed limit fulfillment was only relevant in sections with enforcement devices. In these sections, it is confirmed that, the lower the speed limit, the higher the occupancy to achieve a given flow. In contrast, the usually assumed mainline metering effect of low speed limits was not relevant. This might be different in case of stretch enforcement. These findings mean that, on the one hand, VSL strategies aiming to restrict the mainline flow on a freeway by using low speed limits will need to be applied carefully, avoiding conditions as the ones presented here. On the other hand, VSL strategies trying to get the most from the increased vehicle storage capacity of freeways under low speed limits might be rather promising.
Results also show that low speed limits increase the speed differences across lanes for moderate demands. This, in turn, also increases the lane changing rates. In contrast, lower speed limits widen the range of flows under uniform lane flow distributions, so that, even for moderate to low demands, the under-utilization of any lane can be avoided. Further analysis of lane-changing activity allowed unveiling that high lane-changing rates prevent achieving the highest flows. This inverse relationship is modeled in the thesis using a stochastic model based on Bayesian inference. This model could be used as a control tool, in order to determine which level of lane-changing activity can be allowed to achieve a desired capacity with some level of reliability.
Previous results identify drivers' fulfillment of traffic regulations as a weak point in order to maximize the benefits of current management strategies, like VSL or lane-changing control. This is likely to change in the near future with the irruption of Autonomous Vehicles (AV) in freeways. V2X communications will allow directly actuating on individual vehicles with high accuracy. This will open the door to new management strategies based on simultaneous communication to groups of AVs and extremely short reaction times, like platooning, which stands out as a strategy with a huge potential to improve freeway traffic. Strings of AVs traveling at extremely short gaps (i.e. platoons) allow achieving higher capacities and lower energy consumption rates. In this context, the thesis presents a parsimonious macroscopic model for AVs platooning in mixed traffic (i.e. platoons of AVs travelling together with human driven vehicles). The model allows determining the average platoon length and reproducing the overall traffic dynamics leading to higher capacities. Results prove that with a 50% penetration rate of AVs in the lane, capacity could reach 3400 veh/h/lane under a cooperative platooning strategy.Per tal de millorar la capacitat i reduir la congestiĂł a les autopistes cal gestionar el trĂ nsit de manera activa. Les estratègies de gestiĂł activa del trĂ nsit sĂłn d’especial importĂ ncia en autopistes metropolitanes. La congestiĂł provoca retards i un increment del consum de combustible que va lligat a unes majors emissions de gasos contaminants, tots amb efectes perniciosos per la societat. La gestiĂł activa del transit requereix regular la demanda i millorar la capacitat de la via. Encara que tots dos aspectes son necessaris, la present tesis nomĂ©s analitza la gestiĂł de l’oferta. Part de la recerca en l’anĂ lisi i la teoria del trĂ nsit es basa en dades empĂriques. Per satisfer el requeriment de dades detallades i d’alta qualitat, aquesta tesis presenta una campanya pionera de recol·lecciĂł de dades. Les dades es van recollir a l’autopista B-23 d’accĂ©s a Barcelona. Tots els instruments de mesura es van configurar per tal de registrar les dades amb el major nivell de detall possible, incloent les cĂ meres de videovigilĂ ncia, d’on es varen extreure els comptatges de canvi de carril. Amb aquest objectiu, es va desenvolupar una metodologia semiautomĂ tica per comptar canvis de carril a partir de gravacions de trĂ nsit, que es presenta en el cos de la tesi. L’anĂ lisi de les dades obtingudes ha demostrat que el compliment dels lĂmits de velocitat nomĂ©s resulta rellevant en aquelles seccions que compten amb un radar. És en aquestes seccions on s’ha confirmat que com menor Ă©s el lĂmit de velocitat, major es l’ocupaciĂł per a un flux donat. Per contra, la hipòtesi habitual de que uns lĂmits de velocitat baixos produeixen una restricciĂł del flux no es va observar de forma rellevant. Aquest comportament podria esser diferent en el cas d’implantar un radar de tram. Els resultats obtinguts tambĂ© mostren com les diferències de velocitats entre carrils s’incrementen per a lĂmits de velocitat baixos i en condicions de demanda moderada. Això, alhora, incrementa el nombre de canvis de carril. Per contra, els lĂmits de velocitat baixos contribueixen a una distribuciĂł de flux mĂ©s uniforme entre carrils, de forma que es pot evitar la infrautilitzaciĂł de carrils. L’anĂ lisi mĂ©s detallat de l’activitat de canvi de carril demostra que una taxa elevada de canvis de carril impedeix assolir fluxos grans de circulaciĂł. En la tesi, aquesta relaciĂł inversa entre la taxa de canvis de carril i el flux mĂ xim de trĂ nsit a l’autopista s’ha modelat de forma estocĂ stica utilitzant un model basat en la inferència Bayesiana. Aquest model es pot utilitzar com una eina de control, per tal de determinar quina taxa de canvi de carril es pot permetre si es vol assolir una capacitat determinada amb una determinada probabilitat de compliment. En vista dels resultats previs, la falta de compliment de les normes de trĂ nsit per part dels conductors s’identifica com un punt dèbil a l’hora de maximitzar els beneficis de les actuals estratègies de gestiĂł del transit. Això probablement canviarĂ en el futur pròxim amb la irrupciĂł dels Vehicles Autònoms (VA) a les autopistes. Els sistemes de comunicaciĂł V2X permetran actuar individualment sobre cada vehicle amb una gran precisiĂł. Això obrirĂ la porta a noves estratègies de gestiĂł, basades en la comunicaciĂł simultĂ nia entre diferents grups de VA i en temps de reacciĂł extremadament curts, com per exemple Ă©s el “platooning”, que destaca pel seu gran potencial per millorar el trĂ nsit en autopista. Els “platons” son cadenes de VA viatjant amb uns espaiaments extremadament curts que permeten assolir capacitats mes elevades i un menor consum energètic. En aquest context, la tesi presenta un model macroscòpic parsimoniĂłs per a “platons” de VA en condicions de transit mixt, Ă©s a dir, compartint la infraestructura amb vehicles tradicionals.
El model permet determinar la longitud mitjana del “platons” i reproduir el trà nsit global
dinĂ miques que condueixen a majors capacitats. Els resultats demostren que amb un 50%
la velocitat de penetració dels AV al carril, la capacitat podria arribar als 3.400 vehicles / h / carril sota una estratègia cooperativa de “platooning
Measuring traffic lane-changing by converting video into space–time still images
Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accuracy achieved is usually not enough to improve traffic flow models. In contrast “visual” data extraction by watching the recordings requires extensive human intervention. A semiautomatic video processing methodology to count lane-changing in freeways is proposed. The method allows counting lane changes faster than with the visual procedure without falling into the complexities and errors of full automation. The method is based on converting the video into a set of space–time still images, from where to visually count. This methodology has been tested at several freeway locations near Barcelona (Spain) with good results. A user-friendly implementation of the method is available on http://bit.ly/2yUi08M.Peer Reviewe