Crowding Effects in Vehicular Traffic
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{"title"=>"Crowding Effects in Vehicular Traffic", "type"=>"journal", "authors"=>[{"first_name"=>"Jay Samuel L.", "last_name"=>"Combinido", "scopus_author_id"=>"36008347400"}, {"first_name"=>"May T.", "last_name"=>"Lim", "scopus_author_id"=>"7201473102"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"23139762", "doi"=>"10.1371/journal.pone.0048151", "sgr"=>"84868382850", "arxiv"=>"1209.6203", "isbn"=>"1932-6203 (Electronic)\\n1932-6203 (Linking)", "scopus"=>"2-s2.0-84868382850", "issn"=>"19326203", "pui"=>"365988320"}, "id"=>"29d8e0c6-956e-3a47-9cd1-54654d09e063", "abstract"=>"While the impact of crowding on the diffusive transport of molecules within a cell is widely studied in biology, it has thus far been neglected in traffic systems where bulk behavior is the main concern. Here, we study the effects of crowding due to car density and driving fluctuations on the transport of vehicles. Using a microscopic model for traffic, we found that crowding can push car movement from a superballistic down to a subdiffusive state. The transition is also associated with a change in the shape of the probability distribution of positions from a negatively-skewed normal to an exponential distribution. Moreover, crowding broadens the distribution of cars' trap times and cluster sizes. At steady state, the subdiffusive state persists only when there is a large variability in car speeds. We further relate our work to prior findings from random walk models of transport in cellular systems.", "link"=>"http://www.mendeley.com/research/crowding-effects-vehicular-traffic", "reader_count"=>14, "reader_count_by_academic_status"=>{"Librarian"=>2, "Researcher"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3}, "reader_count_by_user_role"=>{"Librarian"=>2, "Researcher"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Environmental Science"=>1, "Medicine and Dentistry"=>1, "Arts and Humanities"=>1, "Physics and Astronomy"=>6, "Psychology"=>1, "Computer Science"=>2, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Psychology"=>{"Psychology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Computer Science"=>{"Computer Science"=>2}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Luxembourg"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/548892"], "description"=>"<p>Values of the cluster size distribution rate parameter plotted against and .</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>219387, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g008", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cluster_size_distribution_rate_parameter_/219387", "title"=>"Cluster size distribution rate parameter.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:51:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/548420"], "description"=>"<p>(a) Mean-square displacement (MSD) as function of time for car densities at . All curves are superdiffusive with at long times but the behavior at short times changes with . (b) Plot of the scaled MSD, , reveals that during the transient period, cars can be at subdiffusive states () at high .</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>218919, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g002", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MSD_plots_/218919", "title"=>"MSD plots.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:48:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/548482"], "description"=>"<p>Colormap of the (a) transient and (b) steady state values of the scaling exponent and as a function of car density and the mean randomization probability . Dashed lines show the approximate super diffusion () and normal diffusion () boundaries. Region I (a) is always superdiffusive () indicating a good region for traffic. Region II generally starts with a superdiffusive transient behavior () then approach . Lastly, Region III is subdiffusive. The scaling exponent is independent of .</p>", "links"=>[], "tags"=>["scaling"], "article_id"=>218984, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Transient_and_steady_state_scaling_exponents_/218984", "title"=>"Transient and steady state scaling exponents.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:49:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/549005"], "description"=>"<p>Values of the trap time distribution rate parameter plotted against and .</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>219502, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g010", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Trap_time_distribution_rate_parameter_/219502", "title"=>"Trap time distribution rate parameter.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:51:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/549050"], "description"=>"<p>The variance of the probability density for increases with time.</p>", "links"=>[], "tags"=>["probability"], "article_id"=>219548, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g011", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spread_in_the_probability_density_/219548", "title"=>"Spread in the probability density.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:52:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/548945"], "description"=>"<p>Trap time distributions for (a) constant and and (b) constant and taken from 400 tracer trajectories. Both distributions are exponential. An increase in either parameters broadens the distributions indicating an increased probability of tracers being trapped for longer periods.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>219449, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g009", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Trap_time_distribution_/219449", "title"=>"Trap time distribution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:51:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/548595"], "description"=>"<p>Time evolution of for different car transient behaviors (from superdiffusion [a] to subdiffusion [f]) for <i>t</i> = 10, 50, 100, 300, 900 (dark red to blue). The dotted (black) line is the CCDF of a standard normal distribution. Superballistic cars in (a) have a CCDF of a negatively skewed normal distribution which can be attributed to the initial acceleration of the cars. Ballistic cars as in (b) fits the standard normal CCDF. Cars with an initial sub-ballistic motion as in (c-f) begin with an exponential distribution then slowly approach standard normal as the movement of cars become ballistic. <i>Inset</i>: Plots for the vs. time <i>t</i>. A slope > 0 indicates superdiffusion;  =  0 is diffusion; and <0 is subdiffusion. Ballistic movement is superdiffusive with vs. <i>t</i> slope = 1.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>219094, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g004", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Time_evolution_of_/219094", "title"=>"Time evolution of .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:49:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/548659"], "description"=>"<p>The Q-Q plots were calculated from the probability density for all times for to test for normality: (a) values were calculated to quantify the closeness of the probability densities to that of a normal distribution; (b) skewness of the probability densities as a function of time. Values of skewness falling within are within the accepted values for a normal distribution. High and close to zero indicate a normal distribution.</p>", "links"=>[], "tags"=>["q-q", "plots"], "article_id"=>219160, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g005", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_values_from_Q_Q_plots_and_skewness_/219160", "title"=>"values from Q-Q plots and skewness.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:49:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/548380"], "description"=>"<p>The road is represented by a periodic boundary 1D lattice divided into L = 200 cells. Each cell is either empty or occupied by a single car.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>218876, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Road_setup_/218876", "title"=>"Road setup.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:48:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/548752"], "description"=>"<p>Spatiotemporal diagrams for a constant at (from left to right) . The increase in produces fewer but larger clusters (black regions) as well as larger unoccupied space.</p>", "links"=>[], "tags"=>["diagrams", "varying"], "article_id"=>219254, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g006", "stats"=>{"downloads"=>3, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spatiotemporal_diagrams_for_varying_/219254", "title"=>"Spatiotemporal diagrams for varying .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:50:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/548824"], "description"=>"<p>Cluster size distributions for (a) constant and and (b) constant and taken from 400 tracer trajectories. Both distributions are exponential. An increase in either parameters broadens the distributions indicating an increased probability to form large clusters.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>219329, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.g007", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cluster_size_distribution_/219329", "title"=>"Cluster size distribution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 20:50:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/549115"], "description"=>"<p>Correspondence of the NaSch model rules to the dynamics of other systems.</p>", "links"=>[], "tags"=>["nasch", "rules"], "article_id"=>219615, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Jay Samuel L. Combinido", "May T. Lim"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0048151.t001", "stats"=>{"downloads"=>5, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correspondence_of_the_NaSch_model_rules_to_the_dynamics_of_other_systems_/219615", "title"=>"Correspondence of the NaSch model rules to the dynamics of other systems.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-19 20:52:19"}

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Relative Metric

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