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Simulation-optimization framework for train rescheduling in rapid rail transit Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-12-08 Erfan Hassannayebi; Arman Sajedinejad; Ali Kardannia; Masoud Shakibayifar; Hossein Jafari; Ehsan Mansouri
One of the primary challenges of re-planning in high-speed urban railways is the randomness of disruptive events. In this study, an integrated disturbance recovery model presented in which short-turn and stop-skip service operations are optimized together to minimize the average of passengers’ waiting times. This study develops a discrete-event simulation model that employs a variable neighborhood
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A discrete-time second-best dynamic road pricing scheme considering the existence of multiple equilibria Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-12-01 Linghui Han; Chengjuan Zhu; David Z. W. Wang; Jianjun Wu
When multiple equilibria exist, the desired traffic equilibrium, may not be reached through a day-to-day dynamic adjustment process. Han et al. [“Discrete-Time Day-to-Day Dynamic Congestion Pricing Scheme Considering Multiple Equilibria.” Transportation Research Part B: Methodological 104: 1–16.] proposed a day-to-day dynamic pricing scheme charged on all links to ensure the desired traffic equilibrium
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A day-to-day dynamic evolution model and pricing scheme with bi-objective user equilibrium Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-30 Xiaoyu Ma; Wei Xu; Caihua Chen
Travel time and monetary cost are the two important factors influencing travelers’ route choice behavior. Rather than combining them together as a single objective, a bi-objective user equilibrium (BUE) has been recently proposed in which travelers consider the two objectives separately. It has been shown that BUE can explain more possible route choice results in reality. Therefore, regarding the BUE
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Dynamic modelling and optimisation of transportation systems in the connected era Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-25 Andy H.F. Chow; Yong-Hong Kuo; Panagiotis Angeloudis; Michael G.H. Bell
(2020). Dynamic modelling and optimisation of transportation systems in the connected era. Transportmetrica B: Transport Dynamics. Ahead of Print.
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Joint estimation of paths and travel times from Bluetooth observations Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-23 Mehmet Yildirimoglu
Bluetooth data sets allow a direct estimation of travel times across sensor pairs; however, the resulting estimations contain noise because of missed detection rate and alternative paths between sensors. Additionally, although Bluetooth data sets allow tracking of vehicles across sensors, they do not provide an exact path (i.e. a sequence of traffic sections). Estimating vehicle paths from Bluetooth
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Exploration of pedestrian side preference behavior with circle antipode experiments: analysis, simulation and implication Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-23 Yao Xiao; Ziyou Gao; Rui Jiang; Qinxia Huang; Hai Yang
Conflicts between crowds are considered to be critical sources of safety incidents, and choosing a side is a common strategy for conflict resolution. Here, circle antipode experiments, which create significant conflicts and symmetric scenarios, were applied for the investigation of side preference behaviors. In the experiments, more participants (around 70%) preferred to reach the destination from
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Data-driven network loading Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-18 N. Tsanakas; J. Ekström; D. Gundlegård; J. Olstam; C. Rydergren
ABSTRACT Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the
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Cooperative CAVs optimal trajectory planning for collision avoidance and merging in the weaving section Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-11-18 Shoucai Jing; Xiangmo Zhao; Fei Hui; Asad J. Khattak; Lan Yang
Weaving sections may cause massive congestion and accident problems. Connected and automated vehicles (CAVs) are acknowledged to improve traffic safety and efficiency through effective communication and control. To this end, this study proposes a centralized cooperative vehicle trajectory planning framework for SAE Level 4 or 5 automation. Specifically, focusing on the complex movements at weaving
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Incorporating human factors into LCM using fuzzy TCI model Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-10-24 Linbo Li; Yang Li; Daiheng Ni
ABSTRACT Incorporation of Human Factors (HF) into the mathematical car-following (CF) models has always been the research hotspot. Ignorance of such inclusion would inevitably hinder us from acquiring a comprehensive understanding of traffic flow phenomena. This paper proposed a novel CF model in order to bridge three existing research gaps: the demand for more inclusion of HF into the Longitudinal
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W/CDM-MSFM-driven pedestrian path prediction at signalized crosswalk with mixed traffic flow Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-10-05 Hao Chen; Xi Zhang; Wenyan Yang; Wenqiang Jin; Wangwang Zhu; Baixuan Zhao
In this paper, pedestrian path prediction at a signalized crosswalk with pedestrian-electric bicycle-vehicle mixed flow is investigated. Firstly, a waiting/crossing decision model (W/CDM) is developed to predict pedestrians’ waiting/crossing intentions with approaching vehicles. Secondly, a Modified Social Force Model (MSFM) is developed by taking the evasion with conflicting road users, the reaction
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Performance of one-way carsharing systems under combined strategy of pricing and relocations Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-09-24 Rongqin Lu; Gonçalo Homem de Almeida Correia; Xiaomei Zhao; Xiao Liang; Ying Lv
A bilevel nonlinear mathematical programing model is formulated to determine the optimal pricing and operator-based relocations in a one-way station-based carsharing system in competition with private cars. In the upper level, the carsharing operator determines the vehicle fleet, prices, and relocation operations with the objective of maximizing profits, considering the potential reaction of travelers
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Graph attention temporal convolutional network for traffic speed forecasting on road networks Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-09-23 Ke Zhang; Fang He; Zhengchao Zhang; Xi Lin; Meng Li
Traffic speed forecasting plays an increasingly essential role in successful intelligent transportation systems. However, this still remains a challenging task when the accuracy requirement is demanding. To improve the prediction accuracy and achieve a timely performance, the capture of the intrinsically spatio-temporal dependencies and the creation of a parallel model architecture are required. Accordingly
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Day-to-day market evaluation of modular autonomous vehicle fleet operations with en-route transfers Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-08-21 Nicholas S. Caros; Joseph Y. J. Chow
This study extends the two-sided day-to-day learning framework to simulate the performance of a mobility service using modular autonomous vehicles (MAVs) capable of en-route passenger transfers. An insertion heuristic is used to assign trips to a fleet of vehicles and to determine whether engaging in an en-route transfer is advantageous. The operator acts as an endogenous decision maker, updating the
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Functional clustering and missing value imputation of traffic flow trajectories Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-21 Pai-Ling Li; Jeng-Min Chiou
Patterns of traffic flow trajectories play an essential role in analysing traffic monitoring data in transportation studies. This research presents a data-adaptive clustering approach to explore traffic flow patterns and a unified algorithm to impute missing values for incomplete traffic flow trajectories. We recommend using subspace-projected functional data clustering with the assumption that each
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Robust perimeter control design for two urban regions with sampled-data and input saturation Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Yuanxiang Fu; Shukai Li; Lixing Yang
This paper investigates the robust perimeter control for two urban regions with sampled-data and input saturation. Based on the macroscopic fundamental diagram, an uncertain network vehicle balance model is established for two urban regions. Instead of the continued feedback control, this paper designs a sampled-data feedback control law to stabilize the traffic accumulations at the desired state.
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A data-driven lane-changing behavior detection system based on sequence learning Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Jun Gao; Yi Lu Murphey; Jiangang Yi; Honghui Zhu
Lane-changing detection is one of the most challenging tasks in advanced driver assistance system (ADAS). However, modeling driver's lane-changing process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, a novel sequential model, data-driven lane change detection (DLCD) system is proposed using deep learning techniques. Firstly, DLCD system explores
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Modelling within-day ridehailing service provision with limited data Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Francisco Calderón; Eric J. Miller
This paper proposes a holistic, within-day ridehailing service provision modelling approach, focusing on large-scale services with human-driven fleets. The model is powered by a full, two-year record of ridehailing trips in Toronto. Canada. Despite the abundant data, operations and fleet-related data still lacks, and uncertainty still exists concerning actual service provision deployment. Hence, a
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Estimation of saturation flow for non-lane based mixed traffic streams Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Remya K. Padinjarapat; Tom V. Mathew
Saturation flow estimation is a challenge in non-lane based mixed traffic streams due to the presence of mixed vehicle-types, each having different static and dynamic characteristics. Such a mix gives way to traffic behaviours like weak lane discipline, multiple-leader following, etc. Due to these behaviours, queue discharge flow during green time fluctuates, which makes it difficult to identify a
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Vehicle trajectory reconstruction for signalized intersections: A hybrid approach integrating Kalman Filtering and variational theory Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Peng Chen; Lei Wei; Fangfang Meng; Nan Zheng
Trajectory data provide a rich source of information on spatial and temporal speed fluctuations of individual vehicles. To assemble a complete picture of traffic operations, obtaining vehicle trajectories of the entire traffic flow is essential. The current techniques cannot fulfill this need sufficiently. To this end, we developed a hybrid approach for reconstructing vehicle trajectories at signalized
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The short-run and long-run equilibria for commuting with autonomous vehicles Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-07-20 Fangni Zhang; Wei Liu; Gabriel Lodewijks; S. Travis Waller
Recent empirical studies indicated that using autonomous vehicles (AVs) can reduce commuters' value of time. In this context, this paper investigates how variation in value of time for AVs will reshape the commuting dynamics in the short-run and the implication on AV-related policies in the long run. We find that in the short run, the adoption of AV can create more congestion delays since delay becomes
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Reliable space–time prisms in the stochastic road networks under spatially correlated travel times Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-06-22 Alireza Sahebgharani; Hossein Haghshenas; Mahmoud Mohammadi
Conventional space–time prisms (STPs) represent deterministic travel times but ignore the stochastic nature of travel speeds. To this extent, reliable STPs were developed to take the effect of time uncertainty into account. Although empirical studies showed that link travel times are correlated in the urban road networks and obey non-normal distributions, existing reliable prisms assume that travel
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Collaborative passenger flow control on an oversaturated metro line: a path choice approach Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-06-22 Fanting Meng; Lixing Yang; Yun Wei; Shukai Li; Ziyou Gao; Jungang Shi
Focusing on reducing the traffic congestion on an oversaturated urban metro system, this study investigates the collaborative passenger flow control problem for a metro line. By introducing the timetable-oriented space-time network representation, the problem of interest is finally formulated as an integer programming model, in which the objective function aims to minimize the total weighted passenger
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Modeling sequences of discrete and continuous variables over time with an application to the vehicle ownership and usage problem Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-06-06 Yan Liu; Cinzia Cirillo
The problem of modeling individual decisions repeatedly over time is important to study dynamics in travel behavior, changes in preferences, and adoption of new services or technologies. Although different methods have been proposed to account for dynamics in pure discrete choice contexts, the case where both continuous and discrete decision variables evolve dynamically has not been fully solved. In
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Signal control method and performance evaluation of an improved displaced left-turn intersection design in unsaturated traffic conditions Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-06-01 Xiancai Jiang; Su Gao
This paper proposes an improved layout for the Displaced Left-turn (DLT) intersection by combining the conventional DLT intersection with protected left-turn phases, based on the safe-crossing requirements of pedestrians and non-motorized vehicles. The delay and stops are weighted to form an integrated performance index (PI) in a real-time vehicle-to-infrastructure communication environment. The PI
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Urban space consumption of cars and buses: an analytical approach Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-04-15 Mireia Roca-Riu; Monica Menendez; Igor Dakic; Samuel Buehler; Javier Ortigosa
Space is one of the most valuable assets in urban environments. Currently, many cities devote a significant amount of space to private, less sustainable modes of transport. Several attempts have been made to recover urban space for other purposes, e.g. pedestrians, low-speed residential areas, public modes of transport, or bike lanes. In this paper, we propose a new analytical methodology that quantifies
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Weather perception and its impact on out-of-home leisure activity participation decisions Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-04-07 Chengxi Liu; Yusak O. Susilo; Nursitihazlin Ahmad Termida
Weather is fundamentally a perception rather than an objective measure. This study uses data from a four-wave travel diary survey and aims to answer two research questions, i.e. 1. How individuals from different socio-demographic groups perceive weather. 2. How an individual’s weather perception affects his/her leisure activity participation decision. A thermal indicator, Universal Thermal Climate
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Bus driver scheduling enhancement: a derandomizing approach for uncertain bus trip times Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-26 Liujiang Kang; Qiang Meng; Chuanbei Zhou
The bus driver scheduling problems aim to optimally deploy drivers to fulfil published timetables for bus services subject to drivers’ contractual working rules. In this study, we first develop an integer linear programming model for a practical driver scheduling problem. We proceed to formulate another integer linear programming model for the driver scheduling enhancement to incorporate with uncertain
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A tensor-based K-nearest neighbors method for traffic speed prediction under data missing Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-26 Liang Zheng; Huimin Huang; Chuang Zhu; Kunpeng Zhang
This study proposes a tensor-based K-Nearest Neighbors (K-NN) method, in which traffic patterns involve multi-dimensional temporal information and bi-directional spatial information. Such multi-temporal information can not only capture the instantaneous fluctuation of short-term traffic but keep the general trend of long-term traffic. In numerical experiments, with taxis’ GPS data from an urban road
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Cooperative driving strategies of connected vehicles for stabilizing traffic flow Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-20 Dong-Fan Xie; Yong-Qi Wen; Xiao-Mei Zhao; Xin-Gang Li; Zhengbing He
It is foreseeable that connected vehicles (CVs) and regular vehicles (RVs) will be operated together on roads in the upcoming decades. The appearance of CVs provides us an opportunity to improve traffic efficiency by guiding drivers to properly steer their CVs. To take advantage of this opportunity, this paper proposes two cooperative driving strategies for CVs that move in heterogeneous RV and CV
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A car-following model to assess the impact of V2V messages on traffic dynamics Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-16 Tenglong Li; Dong Ngoduy; Fei Hui; Xiangmo Zhao
Connected vehicles (CVs) are considered to have the potential to significantly improve traffic flow stability. Although several studies have been devoted to modelling car-following behaviour in a connected environment, most model formulations are based on assumptions without empirical observations. Therefore, this paper utilizes data from field experiments to explore the dynamics of CVs. Data mining
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Dynamics of taxi-like logistics systems: theory and microscopic simulations Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-10 Bo Yang; Qianxiao Li
We study the dynamics of a class of bi-agent logistics systems consisting of two types of agents interacting on an arbitrary complex network. By approximating the system with simple microscopic models and solving them analytically, we reveal some universal dynamical features and propose applications of such features for system optimisations. Large-scale agent-based numerical simulations are also carried
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Accommodating correlation across days in multiple discrete-continuous models for time use Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-09 Chiara Calastri; Stephane Hess; Abdul Rawoof Pinjari; Andrew Daly
The MDCEV modelling framework has established itself as the preferred method for modelling time allocation, with data very often collected through travel or activity diaries. However, standard implementations fail to recognise the fact that many of these datasets contain information on multiple days for the same individual, with possible correlations and substitution between days. This paper discusses
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Multi-source data-driven prediction for the dynamic pickup demand of one-way carsharing systems Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-02-07 Ling Wang; Hao Zhong; Wanjing Ma; Yugao Zhong; Lei Wang
The one-way carsharing system has been widely used in the carsharing field due to its flexibility. However, one of its main disadvantages is the imbalance between supply and pickup demand. At present, multi-source data are available for the real-time prediction of pickup demand. The multi-source data that are used for this purpose include real-time user application log data, historical order data,
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A probability lane-changing model considering memory effect and driver heterogeneity Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-01-23 Meng-Yuan Pang; Bin Jia; Dong-Fan Xie; Xin-Gang Li
Lane changing is one of the basic driving behaviours, which may induce traffic oscillations and incidents. However, it is difficult to well model the lane-changing decision process due to the complex traffic status. To promote the prediction accuracy of lane-changing decisions, this paper presents a probability lane-changing model by taking into account the memory effect. That is, the lane-changing
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Development of a binary logistic lane change model and its validation using empirical freeway data Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-01-23 Christina Ng; Susilawati Susilawati; Md Abdus Samad Kamal; Irene Mei Leng Chew
An effective macroscopic lane change (LC) model is required to facilitate active and dynamic lane management to develop cell-based multilane macroscopic traffic models. Existing logistic regression LC models do not undertake model classification of lane change; do not consider performance measures in the validation of field data and ignore movement between lanes during time-varying traffic. Models
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Car-following characteristics of various vehicle types in respective driving phases Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2020-01-18 Akihito Nagahama; Daichi Yanagisawa; Katsuhiro Nishinari
The dynamics of mixed traffic were analysed by examining the driving features of various vehicles based on their car-following behaviours in a test-driving circuit. By applying decision tree analysis to the observed data, we successfully compared the acceleration, velocity difference and distance gap of different vehicles during driving trials and quantitatively extracted the features of these physical
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Modelling lane-changing mechanisms on motorway weaving sections Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2019-12-26 Andyka Kusuma; Ronghui Liu; Charisma Choudhury
A motorway weaving section connects a pair of closely spaced entry- and exit-ramps, where intensive lane-changings of merging and diverging vehicles take place over a relatively short space. A detailed trajectory data reveal that a significant proportion of the lane changing at the weaving section exhibits group lane-changing behaviour, in the forms of a lane-changing platoon and simultaneous weaving
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A dynamic macroscopic parking pricing and decision model Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2018-07-04 Manuel Jakob; Monica Menendez; Jin Cao
A dynamic macroscopic parking pricing model is developed to maximize the revenue for a city, while simultaneously minimizing the total cruising time on the network. The proposed responsive pricing scheme takes the parking search phenomenon into consideration. This means that the parking fee also changes in response to the number of searching vehicles, in addition to changes in response to the parking
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A macroscopic traffic flow model that includes driver sensitivity to the number of free spaces ahead Transportmetrica B Transp. Dyn. (IF 2.214) Pub Date : 2017-10-04 Ismael M. Pour; Habibollah Nassiri
This paper addresses the first-order extension of the Lighthill–Whitham– Richards (LWR) macroscopic traffic flow model. Although previous studies have focused on the fluid aspect of traffic flow, none have addressed the sensitivity of drivers to the number of free spaces within a certain distance ahead of the subject driver. To incorporate driver behavior, we used the number of free spaces ahead of
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