Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Extraction of descriptive driving patterns from driving data using unsupervised algorithms

Being one of the most promising applications enabled by connected and automated vehicles (CAV) technology, Cooperative Adaptive Cruise Control (CACC) is expected to be deployed in the near term on public roads. Thus far, the majority of the CACC studies have been focusing on the overall network performance with limited insights on the potential impacts of CAVs on human-driven vehicles (HVs). This paper aims to quantify such impacts by studying the high-resolution vehicle trajectory data that are obtained from microscopic simulation. Two platoon clustering strategies for CACC- an ad hoc coordination strategy and a local coordination strategy-are implemented. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. According to the two-sample Kolmogorov-Smirnov test, however, the distributions of the hard braking events (as a potential safety impact) for HVs change significantly under local coordination strategy. For both of the clustering strategy, CAVs increase the average lane change frequency for HVs. The break-even point for average lane change frequency between the two strategies is observed at 30% MPR, which decreases from 5.42 to 5.38 per vehicle. The average lane change frequency following a monotonically increasing pattern in response to MPR, and it reaches the highest 5.48 per vehicle at 40% MPR. Lastly, the interaction state of the car-following model for HVs is analyzed. It is revealed that the composition of the interaction state could be influenced by CAVs as well. One of the apparent trends is that the time spent on approaching state declines with the increasing presence of CAVs.

Influence of CAV clustering strategies on mixed traffic flow characteristics: An analysis of vehicle trajectory data

The article presents the calculation of roundabout entry capacity as a case study based on roundabouts located in Tokyo, Japan, and Tokyo surroundings. The analysis was conducted as part of the project entitled “Analysis of the applicability of the author’s method of roundabouts entry capacity calculation developed for the conditions prevailing in Poland to the conditions prevailing at roundabouts in Tokyo (Japan) and in the Tokyo surroundings”. The main aim and the research question was whether the author’s model of roundabouts entry capacity calculation constructed for the conditions prevailing in Poland after calibration is suitable to calculate roundabout entry capacity of roundabouts located in Tokyo and in the Tokyo surroundings. In order to perform the calibration in 2019, measurements were taken at the single-lane roundabouts located in Tokyo and Tokyo surroundings. The model calibration revealed that it is possible to evaluate the entry capacity of roundabouts located in Tokyo and in Tokyo surroundings using the author’s model.

Roundabout Entry Capacity Calculation—A Case Study Based on Roundabouts in Tokyo, Japan, and Tokyo Surroundings

The time headway of vehicles is of fundamental importance in traffic engineering applications like capacity, level-of-service and safety studies. Further, the performance of traffic simulation depends on inputs into the simulation process and ‘accurate vehicle generation’ is critical in this context. Thus, it is important to define headway distribution pattern for the purpose of analyzing traffic and subsequently, taking infrastructure related decisions. In so far, majority of the researches on this subject are based on homogeneous traffic and effects of mixed traffic especially on two-lane roads are yet to be culminated. The present study, thus, aimed at investigating headway distributions on such roads under mixed traffic situation. Field study was conducted on two-lane highways in India that exhibits heterogeneity in its traffic composition. Contestant headway distribution models were evaluated and four distribution functions namely, log-logistic, lognormal, Pearson 5 and Pearson 6 were considered while modeling the headway data. The appropriate models were selected using a methodology based on K-S test and subsequent field validation. Log-logistic distribution was found appropriate at moderate flow whereas, at congested state of flow it was Pearson 5. However, at unstable flow nearing capacity, both, following and non-following components of headways were observed to follow different distributional characteristics. Nomographs are developed for calculating the headway probabilities at different flow levels considering the appropriate distribution models. ‘Probability of headway less than‘t’s’ increases with the flow rate and rate of such increase is considerably high for headways 7.5 s or more. This attributes to the fact that at heavy flow more vehicles are entrapped inside platoons and they move in following with shorter headways. Further, a comparison was made between the headway probabilities obtained in the current study and road segments that exhibit more or less homogeneous traffic. It was found that at moderate flow level proportion of shorter headways are considerably high under mixed traffic. The present paper demonstrates the effect of mixed traffic on distribution of time headways of two-lane roads. Presence of slower vehicles in such traffic leads to frequent formation of platoons, thereby, increases the risk taking behavior of drivers’ while overtaking. As a result, proportion of shorter headways increases resulting in highly skewed observations. Thus, the study proposed Log-logistic distribution under medium flow since it can model events which have ‘increased initial rate’ and Pearson 5 under heavy flow to model ‘highly skewed data’. The model outputs were accordingly compared with other studies and were found to explain the mixed traffic characteristics satisfactorily. The present study, thus, creates a starting point of further initiatives aimed at establishing a robust method of modeling headways on two-lane roads with mixed traffic.

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Headway distribution models of two-lane roads under mixed traffic conditions: a case study from India

This paper presents an investigation on the adequacy of one of the major performance indicators for two-lane highways, the percent-time-spent-following (PTSF) under changing driver’s behavior in ch...

Preferred time headway of drivers on two-lane highways with heterogeneous traffic

Effect of Mixed Traffic on Capacity of Two-Lane Roads: Case Study on Indian Highways

Time headway is an important microscopic traffic flow parameter, which affects safety, level-of-service, capacity and traffic simulation. It is, therefore, important to know the specific distribution for a particular roadway and traffic condition. Further, headway between two vehicles depends on the type of lead vehicle and is influenced by its size and dynamics. Such impact is considerably high on two-lane roads with mixed traffic composed of a wide variety of vehicle types. This paper identified sixteen combinations of vehicle pairs and analysed vehicle-type-specific headways using field data. Appropriate distribution functions were fitted to field data and predictive models were used in understanding carfollowing behaviour. Observations indicate that quite often bike riders become reluctant in obeying lane discipline. However, car drivers show conservative attitude and usually, keep safe distance from the lead vehicle except the case when they follow another car. In addition, while following Non-Motorized Vehicles (NMV), most of the drivers keep reasonably safe distances. In this paper, a comparison of computed headway probabilities was also made with those obtained from more or less homogeneous traffic. It was found that values obtained in current study are high in most of the instances. This indicates risk-taking behaviour of driver population, which eventually affects safety of such roads. The present study, thus, demonstrates the need of investigating vehicle-type-specific headways under mixed traffic based on comprehensive field data.

/pdf/analysis-of-vehicle-type-specific-headways-on-two-lane-roads-1i87mly45i.pdf

Rupali Roy

Papers

Headway distribution models of two-lane roads under mixed traffic conditions: a case study from India

Preferred time headway of drivers on two-lane highways with heterogeneous traffic

Effect of Mixed Traffic on Capacity of Two-Lane Roads: Case Study on Indian Highways

Analysis of vehicle-type-specific headways on two-lane roads with mixed traffic

Speed Distributional Trends on Two-lane Roads with Mixed Traffic under Heavy Flow