A Review of Game Theory Models of Lane Changing

Recently published:

Driver lane-changing behaviours have a significant impact on the safety and the capacity of the vehicle-based traffic system. Therefore, modeling lane-changing ma- neuvers has become an essential component of driving behaviour analysis. Among microscopic LC models, game theory-based lane-changing models highlight the inter- action of drivers, which reveal a more realistic image of driving behaviours compared to other classic models. However, the potential of game theory to describe the hu- man driver’s lane-changing strategies is currently under-estimated. This paper aims to review the recent development of game-theoretic models that are classified ac- cording to their different methodologies and features. They are designed for both human-driven and autonomous vehicles, and we hope they can find applications in future AV industries.

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Estimating the Social Gap with a Game Theory Model of Lane Changing

Recent paper:

Changing lanes is a commonly-used technique for drivers to either overtake slow-moving cars or enter/exit highway ramps. Optional lane changes may save drivers travel time but increase the risk of collision with others. Drivers make such decisions based on experience and emotion rather than analysis, and thus may fail to select the best solution while in a dynamic state of flux. Unlike human drivers, autonomous vehicles can systematically analyze their surroundings and make real-time decisions accordingly. This paper develops a game theory-based lane-changing model by comparing two types of optimization methods. To realize our expectations, we need to first investigate the payoff function of drivers in discretionary lane-changing maneuvers and then quantify it in an equation of costs that trades-off safety and time-saving. After the evaluation for each alternative strategy combination, the results show that there exists a social gap in the discretionary lane-changing game. To deal with that problem, we provide some suggestions for future policy as well as autonomous vehicle controller designs, offering solutions to reduce the impact of disturbances and crashes caused by inappropriate lane changes, and also, inspire further research about more complex cases.

 

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Walking and Talking: The Effect of Smartphone Use and Group Conversation on Pedestrian Speed

Recently published:

Walking speed, walking in group, and phone use
Walking speed, walking in group, and phone use

Distracted walking due to smartphone use is on the rise resulting in growing concern over pedestrian safety and well-being. Our study measured the walking speeds of pedestrian groups differentiated by their smartphone use in two different environments – a wide pedestrian bridge at a university, and a narrow footpath on a busy commercial street. The results show that groups of people, phone users, and often followers of phone users, walk significantly slower than solo walkers uninfluenced by phone. Especially on the narrow street, people in groups and phone users are seen to not only slow themselves down but also slow the people walking behind them.

Temporal Variations in Daily Activity Networks Using Smartcard Data

This study explores temporal variations in activity networks for four million passengers, differentiated as workers and non-workers, using public transport based on a large-scale smart card dataset generated over 105 days in Beijing. We aim to capture their day-to-day transition and cumulative temporal expansion in activity network using transit over days, weeks, and months. Particularly, workers and non-workers are automatically identified based on their different daily routines, whose activity networks are characterized by six features concerning space coverage, distance coverage, and frequency coverage in two ways, namely, on a per-day transition and with an accumulation of days. The transition features of the networks are statistically analyzed and compared by time, while how the expansion features evolve with time are modeled. Results show that, on weekdays, workers are more likely to travel longer (have larger distance coverage), but cover less area (have smaller space coverage) than non- workers. While opposite patterns occur on weekends. Traveling in the ‘North-South’ direction is weakly correlated with traveling in the ‘East-West’ direction. Workers on weekdays, as well as non-workers on weekends, make longer ‘North-South’ trips. Manhattan distance, trip count, and perimeter present a ∩ shape in their probability density functions, while the remaining features decline dramatically, with probability density functions fit by the exponential distribution. The distance coverage expands faster than that of space coverage. Most passengers increase coverage of space and distance when time expands (obviously no one decreases coverage over time, but some don’t change). The research enables findings on temporal load-balancing, long-term cumulative expansion in travel demands of workers and non-workers, re-balancing the distribution of existing workplace and residential location opportunities, and constructing transit-oriented developments with mixed functions over time.

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A Review of Game Theory Models of Lane Changing

Recent working paper:

Driver lane-changing behaviours have a significant impact on the safety and the capacity of the vehicle-based traffic system, therefore, modeling lane-changing maneuvers has become an essential component of driving behaviour analysis. Among microscopic LC models, game theory based lane-changing models highlight the interaction or competition of drivers, which reveal a more realistic image of driving behaviours compared to other classic models. However, the potential of game theory to describe the human driver’s lane-changing strategies is currently under-estimated. This paper aims to review the recent development of game theoretic models that are classified according to their different methodologies and features. They are designed for both human-driven (User-optimal) and autonomous vehicles (User and system-optimal), and we hope they can find applications in future AV industries.

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Trains, trams, and terraces: population growth and network expansion in Sydney: 1861-1931

Recent working paper:

This paper examines the changes that occurred in the tram and train networks and density of population in Sydney between the early 1860s and 1930s when both trains and trams were developing. A set of statistical analysis has been conducted using panel data representing 593 districts of Greater Sydney at suburb (neighborhood) level over each decade from 1861 to 1931. We find that trams and population density are positively associated in a positive feedback process, tram deployment leads population growth and population growth leads tram deployment, both satisfying a Granger causality test.

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Commute Mode Share and Access to Jobs across US Metropolitan Areas

Recently published:

How much of the variation in transit mode share is attributable to accessibility is not well understood, despite its significant policy implications. It is hypothesized that better transit accessibility leads to higher transit mode share. This paper explains block-group level transit mode share using transit accessibility in a logistic model for 48 major US metropolitan areas. Transit accessibility alone explains much of the variation in transit mode share for all 48 regions despite their geographical differences (adjusted R2 0.61, potential accessibility); models for individual cities have stable and interpretable parameters for transit accessibility. The models better explain mode share in cities with higher person weighted transit accessibility and larger populations; an adjusted R2 of 0.76 is achieved for New York City with transit accessibility as the only explanatory variable. Additional automobile accessibility and income variables modestly improve model fit. Time-decay functions fitted to accessibility measures better explain mode choice than the isochrone accessibility, and suggest the catchment area affecting transit mode choice to be within 35 minutes. This work contributes to the understanding of transit mode share by solidifying its link with accessibility, which is determined by the structure of the transport network and land development.

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Shortest paths, travel costs, and traffic

Recent working paper:

This study focuses on path flow for road network, as the sum of individual route choices from individual travelers, associated with specific path type for each cost fac- tor of auto travel that finds the optimal route with the minimum cumulative cost from the perspective of the corresponding cost analyst interest. The considered cost factors include time, safety, emission, and monetary costs, as well as their composite, internal and full cost of travel. We further explore the extent to which each cost factor explains the observed link traffic flows given an estimated home-to-work demand pattern. The results of the Minneapolis – St. Paul metropolitan area indicate that flows from multiple path types, associated with internal cost components, additionally to the factor of distance, provides the best fit.

 

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Moving Array Traffic Probes

Recent working paper:

  • Davis, Blake, Ji, Ang,  Liu, Bichen, and Levinson, D. (2020) Moving Array Traffic Probes. To be presented at the Transportation Research Board Annual Meeting, January 2020.

This paper explores the potential of moving array `probes’ to collect traffic data. This application simulates the prospect of mining environmental data on traffic conditions to present a cheap and potentially widespread source of traffic conditions. Based on three different simulations, we measure the magnitude and trends of probe error (comparing the probe’s `subjective’ or time-weighted perception with an `objective’ observer) in density, speed, and flow in order to validate the proposed model and compare the results with loop detectors. From these simulations, several conclusions were reached. A single probe’s error follows a double hump trend due to an interplay between the factors of traffic heterogeneity and shockwaves. Reduced visibility of the single probe does not proportionately increase the error. Multiple probes do not tend to increase accuracy significantly, which suggests that the data will be still useful even if probes are sparsely distributed. Finally, probes can measure the conditions of oncoming traffic more accurately than concurrent traffic. Further research is expected to consider more complex road networks and develop methods to improve the accuracy of moving array samples.

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