Identification of different vehicle-following manoeuvres for heterogeneous weak-lane disciplined traffic condition from vehicle trajectory data
01 Jun 2020-Vol. 491, Iss: 1, pp 012052
About: The article was published on 2020-06-01 and is currently open access. It has received 7 citations till now. The article focuses on the topics: Trajectory.
Citations
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TL;DR: Empirical evidence of qualitative and quantitative differences among following behaviors that can help in developing better microscopic traffic flow models for mixed traffic conditions is provided.
Abstract: In mixed traffic streams without lane discipline, driving behaviors are complex and difficult to model. However, limited attempts have been made to study the characteristics of these maneuvers usin...
4 citations
Cites background from "Identification of different vehicle..."
...Previously the following behavior was identified based on the percentage of lateral overlap (34) and lateral gap (35) between the leader and the follower....
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08 Oct 2022
TL;DR: In this paper , the authors provide an overview of the available literature on the current non-lane based driving and future LFT strategies, as well as the taxonomy used in literature to clearly distinguish the two traffic modes.
Abstract: Connected and automated vehicles (CAVs), with the capability to exchange information with other CAVs and the infrastructure, open up new opportunities in road traffic systems including the recently introduced concept of lane-free traffic (LFT). In an LFT environment, vehicles move without the need for traditional fixed lanes. It is an emerging research area where many forms of LFT strategies are being investigated that can benefit road capacity optimization, thus reducing traffic congestion and increasing traffic efficiency. LFT strategies can also benefit from current research on non-lane based driving behavior observed in some countries. Thus, this paper overviews the available literature on the current non-lane based driving and future LFT. It also studies the taxonomy used in literature to clearly distinguish the two traffic modes. It details the current developments in LFT research and the underlying technologies. From these developments, the paper provides an overview of currently available approaches for realizing LFT. Finally, it discusses the policy considerations needed for the seamless integration of LFT into the current infrastructure once CAVs become mainstream.
3 citations
TL;DR: In this article , a comprehensive model consisting of a real-time lane identification model and a realtime queue length estimation model is developed based on the traffic shockwave theory using GPS data.
Abstract: Nowadays more private car trips have caused worse congestion due to the Covid-19 pandemic in many cities. Congestion charging is one of the taxes that is levied on vehicle owners to reduce urban traffic congestion. One of the most important reasons congestion charging is not accepted by the public is the high cost. Monitoring the state of traffic congestion in real time requires a lot of expensive installations. The purpose of this paper is to make congestion charging more accurate and acceptable using artificial intelligent algorithm. Massive real-time Global Positioning System (GPS) data provides new data for road congestion charging. The queuing length at intersections is an important measurement for the degree of traffic congestion, and it is also the basis for road congestion pricing. GPS positioning cannot provide sufficient position accuracy for lane identification of vehicles. In this study, a comprehensive model consisting of a real-time lane identification model and a real-time queue length estimation model is developed based on the traffic shockwave theory using GPS data. The comprehensive model can identify the lane where the queuing vehicle is located and estimate the real-time queue length of the lane. The proposed models were evaluated using field-collected data in Guangzhou, China. The testing results show that the proposed comprehensive model can identify lanes and estimate queue lengths with satisfactory accuracy. The model proposed in this paper provides real-time data for road dynamic pricing in a cost-effective way, which can promote the implementation of congestion charging in cities.
3 citations
08 Oct 2022
TL;DR: In this article , the authors provide an overview of the available literature on the current non-lane based driving and future LFT strategies, as well as the taxonomy used in literature to clearly distinguish the two traffic modes.
Abstract: Connected and automated vehicles (CAVs), with the capability to exchange information with other CAVs and the infrastructure, open up new opportunities in road traffic systems including the recently introduced concept of lane-free traffic (LFT). In an LFT environment, vehicles move without the need for traditional fixed lanes. It is an emerging research area where many forms of LFT strategies are being investigated that can benefit road capacity optimization, thus reducing traffic congestion and increasing traffic efficiency. LFT strategies can also benefit from current research on non-lane based driving behavior observed in some countries. Thus, this paper overviews the available literature on the current non-lane based driving and future LFT. It also studies the taxonomy used in literature to clearly distinguish the two traffic modes. It details the current developments in LFT research and the underlying technologies. From these developments, the paper provides an overview of currently available approaches for realizing LFT. Finally, it discusses the policy considerations needed for the seamless integration of LFT into the current infrastructure once CAVs become mainstream.
2 citations
TL;DR: In this paper , a comprehensive model consisting of a real-time lane identification model and a realtime queue length estimation model is developed based on the traffic shockwave theory using GPS data.
Abstract: Nowadays more private car trips have caused worse congestion due to the Covid-19 pandemic in many cities. Congestion charging is one of the taxes that is levied on vehicle owners to reduce urban traffic congestion. One of the most important reasons congestion charging is not accepted by the public is the high cost. Monitoring the state of traffic congestion in real time requires a lot of expensive installations. The purpose of this paper is to make congestion charging more accurate and acceptable using artificial intelligent algorithm. Massive real-time Global Positioning System (GPS) data provides new data for road congestion charging. The queuing length at intersections is an important measurement for the degree of traffic congestion, and it is also the basis for road congestion pricing. GPS positioning cannot provide sufficient position accuracy for lane identification of vehicles. In this study, a comprehensive model consisting of a real-time lane identification model and a real-time queue length estimation model is developed based on the traffic shockwave theory using GPS data. The comprehensive model can identify the lane where the queuing vehicle is located and estimate the real-time queue length of the lane. The proposed models were evaluated using field-collected data in Guangzhou, China. The testing results show that the proposed comprehensive model can identify lanes and estimate queue lengths with satisfactory accuracy. The model proposed in this paper provides real-time data for road dynamic pricing in a cost-effective way, which can promote the implementation of congestion charging in cities.
2 citations
References
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TL;DR: A logistic regression model is created that predicts the acceptance or rejection of a given gap, depending on the gap value and the speed difference between the merging vehicle and the putative follower, both in the Netherlands and in France.
Abstract: This paper presents two empirical trajectory data sets focusing on the merging behaviour on a motorway, both in the Netherlands and in France. A careful review of the literature shows that the main theories explaining this behaviour rely on the hypothesis of gap acceptance, i.e. the fact that each driver has a certain threshold value depending on among other things the distance to the end of the acceleration lane, and when the offered gap is larger than this threshold the driver decides to merge. We conducted a detailed comparative analysis of the two data sets examining the main variables identified in our conceptual model of merging behaviour. The contribution of this paper is that the analysis does not only focus on the accepted gaps, but it also takes into account the rejected gaps. The comparison of our observations with the critical gap formula in literature showed that this formula does not take into account the strong probability of rejecting a gap, even larger than the gap finally accepted. Moreover, we created a logistic regression model that predicts the acceptance or rejection of a given gap, depending on the gap value and the speed difference between the merging vehicle and the putative follower. We have shown that two other factors impact the probability of rejecting or accepting a given gap, but these are significant for just one of the data sets: the distance to the end of the acceleration lane and the speed difference between the putative follower and the putative leader. This shows the impact of the local situation on the merging behaviour (e.g. traffic composition, road geometry, and traffic conditions).
60 citations
TL;DR: It was found that area-occupancy can be a substitute for occupancy and a relationship was developed between area- Occupancy and traffic stream speed that was found to be logical indicating the appropriateness of the area-Occupancy concept for heterogeneous traffic conditions.
22 citations
TL;DR: In this article, a series of acceleration-deceleration models were developed for the merging vehicle, its putative leader (PL), and their putative follower (PF), and visual angle data were used as the stimuli to reflect the influence of longitudinal and lateral vehicle movements.
Abstract: One major limitation of existing microscopic traffic simulation models is the lack of data about vehicle interactions during the lane-changing process in congested merging areas. The interactions between vehicles during lane changing in the congested weaving sections are quantified. A series of acceleration-deceleration models was developed for the merging vehicle, its putative leader (PL), and its putative follower (PF). After US-101 data were analyzed, the yielding behavior of the merging vehicle's PL for merging cooperation and the lateral separation between vehicles in the weaving section (features largely ignored in previous research) were introduced into the proposed acceleration-deceleration models, and visual angle data were used as the stimuli to reflect the influence of longitudinal and lateral vehicle movements. Car-following behavior was incorporated into the model (e.g., the PF gradually changed its car-following leader from the PL to the merging vehicle, dependent on relative vehicle locatio...
19 citations
Journal Article•
TL;DR: In this article, the authors used a detailed vehicle trajectory data analysis to investigate the effects of microscopic characteristics of the surrounding traffic on lane changing decision of heavy vehicle drivers, which can be divided into two stages: the motivation to change lanes and the selection of the target lane.
Abstract: Lane changing manoeuvres have major impacts on traffic flows. Despite the increasing number of heavy vehicles on freeways, previous lane changing studies are predominantly associated with passenger cars. This study uses a detailed vehicle trajectory data analysis to investigate the effects of microscopic characteristics of the surrounding traffic on lane changing decision of heavy vehicle drivers. Lane changing decision can be divided into two stages: the motivation to change lanes and the selection of the target lane. To investigate the factors which influence heavy vehicle drivers' lane changing decision, 42 heavy vehicle lane changes are analysed. Heavy vehicles are classified into heavy trucks and light trucks based on their length. The results show that the speeds of the front and the rear vehicles in the current lane may motivate the heavy vehicle drivers to change lanes. Furthermore, the speed difference between the lead and the lag vehicles in both adjacent lanes has an impact on selection of the target lane. In general, different influencing traffic characteristics are observed in lane changing decision of heavy truck and light truck drivers.
9 citations